Papers
2024
- Multi-Agent Clarity-Aware Dynamic Coverage with Gaussian ProcessesThis paper presents two algorithms for multi-agent dynamic coverage in spatiotemporal environments, where the coverage algorithms are informed by the method of data assimilation. In particular, we show that by explicitly modeling the environment using a Gaussian Process (GP) model, and considering the sensing capabilities and the dynamics of a team of robots, we can design an estimation algorithm and multi-agent coverage controller that explores and estimates the state of the spatiotemporal environment. The uncertainty of the estimate is quantified using clarity, an information-theoretic metric, where higher clarity corresponds to lower uncertainty. By exploiting the relationship between GPs and Stochastic Differential Equations (SDEs) we quantify the increase in clarity of the estimated state at any position due to a measurement taken from any other position. We use this relationship to design two new coverage controllers, both of which scale well with the number of agents exploring the domain, assuming the robots can share the map of the clarity over the spatial domain via communication. We demonstrate the algorithms through a realistic simulation of a team of robots collecting wind data over a region in Austria.
- Learning to Refine Input Constrained Control Barrier Functions via Uncertainty-Aware Online Parameter AdaptationAvailable on arXiv
abstract / project page / video / code / arxiv /Control Barrier Functions (CBFs) have become powerful tools for ensuring safety in nonlinear systems. However, finding valid CBFs that guarantee persistent safety and feasibility remains an open challenge, especially in systems with input constraints. Traditional approaches often rely on manually tuning the parameters of the class K functions of the CBF conditions a priori. The performance of CBF-based controllers is highly sensitive to these fixed parameters, potentially leading to overly conservative behavior or safety violations. To overcome these issues, this paper introduces a learning-based optimal control framework for online adaptation of Input Constrained CBF (ICCBF) parameters in discrete-time nonlinear systems. Our method employs a probabilistic ensemble neural network to predict the performance and risk metrics, as defined in this work, for candidate parameters, accounting for both epistemic and aleatoric uncertainties. We propose a two-step verification process using Jensen-Renyi Divergence and distributionally-robust Conditional Value at Risk to identify valid parameters. This enables dynamic refinement of ICCBF parameters based on current state and nearby environments, optimizing performance while ensuring safety within the verified parameter set. Experimental results demonstrate that our method outperforms both fixed-parameter and existing adaptive methods in robot navigation scenarios across safety and performance metrics. - Visibility-Aware RRT* for Safety-Critical Navigation of Perception-Limited Robots in Unknown EnvironmentsAvailable on arXiv
abstract / project page / video / code / arxiv /Safe autonomous navigation in unknown environments remains a critical challenge for robots with limited sensing capabilities. While safety-critical control techniques, such as Control Barrier Functions (CBFs), have been proposed to ensure safety, their effectiveness relies on the assumption that the robot has complete knowledge of its surroundings. In reality, robots often operate with restricted field-of-view and finite sensing range, which can lead to collisions with unknown obstacles if the planning algorithm is agnostic to these limitations. To address this issue, we introduce the visibility-aware RRT* algorithm that combines sampling-based planning with CBFs to generate safe and efficient global reference paths in partially unknown environments. The algorithm incorporates a collision avoidance CBF and a novel visibility CBF, which guarantees that the robot remains within locally collision-free regions, enabling timely detection and avoidance of unknown obstacles. We conduct extensive experiments interfacing the path planners with two different safety-critical controllers, wherein our method outperforms all other compared baselines across both safety and efficiency aspects. - Eclares: Energy-Aware Clarity-Driven Ergodic SearchPlanning informative trajectories while considering the spatial distribution of the information over the environment, as well as constraints such as the robot’s limited battery capacity, makes the long-time horizon persistent coverage problem complex. Ergodic search methods consider the spatial distribution of environmental information while optimizing robot trajectories; however, current methods lack the ability to construct the target information spatial distribution for environments that vary stochastically across space and time. Moreover, current coverage methods dealing with battery capacity constraints either assume simple robot and battery models or are computationally expensive. To address these problems, we propose a framework called Eclares, in which our contribution is two-fold. 1) First, we propose a method to construct the target information spatial distribution for ergodic trajectory optimization using clarity, an information measure bounded between [0, 1]. The clarity dynamics allow us to capture information decay due to a lack of measurements and to quantify the maximum attainable information in stochastic spatiotemporal environments. 2) Second, instead of directly tracking the ergodic trajectory, we introduce the energy-aware (eware) filter, which iteratively validates the ergodic trajectory to ensure that the robot has enough energy to return to the charging station when needed. The proposed eware filter is applicable to nonlinear robot models and is computationally lightweight. We demonstrate the working of the framework through a simulation case study.
@inproceedings{naveed2024eclares, title={Eclares: Energy-aware clarity-driven ergodic search}, author={Naveed, Kaleb Ben and Agrawal, Devansh and Vermillion, Christopher and Panagou, Dimitra}, booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)}, pages={14326--14332}, year={2024}, organization={IEEE} } - Advances in the Theory of Control Barrier Functions: Addressing practical challenges in safe control synthesis for autonomous and robotic systemsThis tutorial paper presents recent work of the authors that extends the theory of Control Barrier Functions (CBFs) to address practical challenges in the synthesis of safe controllers for autonomous systems and robots. We present novel CBFs and methods that handle safety constraints (i) with time and input constraints under disturbances, (ii) with high-relative degree under disturbances and input constraints, and (iii) that are affected by adversarial inputs and sampled-data effects. We then present novel CBFs and adaptation methods that prevent loss of validity of the CBF, as well as methods to tune the parameters of the CBF online to reduce conservatism in the system response. We also address the pointwise-only optimal character of CBF-induced control inputs by introducing a CBF formulation that accounts for future trajectories, as well as implementation challenges such as how to preserve safety when using output feedback control and zero-order-hold control. Finally we consider how to synthesize non-smooth CBFs when discontinuous inputs and multiple constraints are present.
@article{garg2024advances, title={Advances in the Theory of Control Barrier Functions: Addressing practical challenges in safe control synthesis for autonomous and robotic systems}, author={Garg, Kunal and Usevitch, James and Breeden, Joseph and Black, Mitchell and Agrawal, Devansh and Parwana, Hardik and Panagou, Dimitra}, journal={Annual Reviews in Control}, volume={57}, pages={100945}, year={2024}, publisher={Elsevier} } - Construction of the Sparsest Maximally r-Robust GraphsIn recent years, the notion of r-robustness for the communication graph of the network has been introduced to address the challenge of achieving consensus in the presence of misbehaving agents. Higher r-robustness typically implies higher tolerance to malicious information towards achieving resilient consensus, but it also implies more edges for the communication graph. This in turn conflicts with the need to minimize communication due to limited resources in real-world applications (e.g., multi-robot networks). In this paper, our contributions are twofold. (a) We provide the subgraph structures and tight lower bounds on the number of edges required for graphs with a given number of nodes to reach the maximum robustness. (b) We then use the results of (a) to introduce two classes of graphs that utilize the least number of edges to maintain maximum robustness. Our work is validated through a series of simulations.
- Algorithms for Finding Compatible Constraints in Receding-Horizon Control of Dynamical Systems.This paper addresses synthesizing receding-horizon controllers for nonlinear, control-affine dynamical systems under multiple incompatible hard and soft constraints. Handling incompatibility of constraints has mostly been addressed in literature by relaxing the soft constraints via slack variables. However, this may lead to trajectories that are far from the optimal solution and may compromise satisfaction of the hard constraints over time. In that regard, permanently dropping incompatible soft constraints may be beneficial for the satisfaction over time of the hard constraints (under the assumption that hard constraints are compatible with each other at initial time). To this end, motivated by approximate methods on the maximal feasible subset (maxFS) selection problem, we propose heuristics that depend on the Lagrange multipliers of the constraints. The main observation for using heuristics based on the Lagrange multipliers instead of slack variables (which is the standard approach in the related literature of finding maxFS) is that when the optimization is feasible, the Lagrange multiplier of a given constraint is non-zero, in contrast to the slack variable which is zero. This observation is particularly useful in the case of a dynamical nonlinear system where its control input is computed recursively as the optimization of a cost functional subject to the system dynamics and constraints, in the sense that the Lagrange multipliers of the constraints over a prediction horizon can indicate the constraints to be dropped so that the resulting constraints are compatible. The method is evaluated empirically in a case study with a robot navigating under multiple time and state constraints, and compared to a greedy method based on the Lagrange multiplier.
@inproceedings{DBLP:conf/amcc/ParwanaWP24, author = {Hardik Parwana and Ruiyang Wang and Dimitra Panagou}, title = {Algorithms for Finding Compatible Constraints in Receding-Horizon Control of Dynamical Systems}, booktitle = {American Control Conference, {ACC} 2024, Toronto, ON, Canada, July 10-12, 2024}, pages = {2074--2081}, publisher = {{IEEE}}, year = {2024}, url = {https://doi.org/10.23919/ACC60939.2024.10644243}, doi = {10.23919/ACC60939.2024.10644243}, timestamp = {Sat, 21 Sep 2024 12:19:37 +0200}, biburl = {https://dblp.org/rec/conf/amcc/ParwanaWP24.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Formally verified asymptotic consensus in robust networks.
@inproceedings{DBLP:conf/tacas/TekriwalTJKP24, author = {Mohit Tekriwal and Avi Tachna{-}Frame and Jean{-}Baptiste Jeannin and Manos Kapritsos and Dimitra Panagou}, editor = {Bernd Finkbeiner and Laura Kov{\'{a}}cs}, title = {Formally verified asymptotic consensus in robust networks}, booktitle = {Tools and Algorithms for the Construction and Analysis of Systems - 30th International Conference, {TACAS} 2024, Held as Part of the European Joint Conferences on Theory and Practice of Software, {ETAPS} 2024, Luxembourg City, Luxembourg, April 6-11, 2024, Proceedings, Part {I}}, series = {Lecture Notes in Computer Science}, volume = {14570}, pages = {248--267}, publisher = {Springer}, year = {2024}, url = {https://doi.org/10.1007/978-3-031-57246-3\_14}, doi = {10.1007/978-3-031-57246-3\_14}, timestamp = {Sun, 06 Oct 2024 21:15:24 +0200}, biburl = {https://dblp.org/rec/conf/tacas/TekriwalTJKP24.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Risk-Aware Fixed-Time Stabilization of Stochastic Systems Under Measurement Uncertainty.This paper addresses the problem of risk-aware fixed-time stabilization of a class of uncertain, output-feedback nonlinear systems modeled via stochastic differential equations. First, novel classes of certificate functions, namely risk-aware fixed-time- and risk-aware path-integral-control Lyapunov functions, are introduced. Then, it is shown how the use of either for control design certifies that a system is both stable in probability and probabilistically fixed-time convergent (for a given probability) to a goal set. That is, the system trajectories probabilistically reach the set within a finite time, independent of the initial condition, despite the additional presence of measurement noise. These methods represent an improvement over the state-of-the-art in stochastic fixed-time stabilization, which presently offers bounds on the settling-time function in expectation only. The theoretical results are verified by an empirical study on an illustrative, stochastic, nonlinear system and the proposed controllers are evaluated against an existing method. Finally, the methods are demonstrated via a simulated fixed-wing aerial robot on a reach-avoid scenario to highlight their ability to certify the probability that a system safely reaches its goal.
@inproceedings{DBLP:conf/amcc/BlackFHP24, author = {Mitchell Black and Georgios Fainekos and Bardh Hoxha and Dimitra Panagou}, title = {Risk-Aware Fixed-Time Stabilization of Stochastic Systems Under Measurement Uncertainty}, booktitle = {American Control Conference, {ACC} 2024, Toronto, ON, Canada, July 10-12, 2024}, pages = {3276--3283}, publisher = {{IEEE}}, year = {2024}, url = {https://doi.org/10.23919/ACC60939.2024.10644792}, doi = {10.23919/ACC60939.2024.10644792}, timestamp = {Sat, 21 Sep 2024 12:19:37 +0200}, biburl = {https://dblp.org/rec/conf/amcc/BlackFHP24.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Robust Safety-Critical Control for Systems With Sporadic Measurements and Dwell-Time Constraints.This letter presents extensions of control barrier function (CBF) theory to systems with disturbances wherein a controller only receives measurements infrequently and operates open-loop between measurements, while still satisfying state constraints. This letter considers both impulsive and continuous actuators, and models the actuators, measurements, disturbances, and timing constraints as a hybrid dynamical system. We then design an open-loop observer that bounds the worst-case uncertainty between measurements. We develop definitions of CBFs for both actuation cases, and corresponding conditions on the control input to guarantee satisfaction of the state constraints. We apply these conditions to simulations of a satellite rendezvous in an elliptical orbit and autonomous orbit stationkeeping.
@article{DBLP:journals/csysl/BreedenZP24, author = {Joseph Breeden and Luca Zaccarian and Dimitra Panagou}, title = {Robust Safety-Critical Control for Systems With Sporadic Measurements and Dwell-Time Constraints}, journal = {{IEEE} Control. Syst. Lett.}, volume = {8}, pages = {1415--1420}, year = {2024}, url = {https://doi.org/10.1109/LCSYS.2024.3410631}, doi = {10.1109/LCSYS.2024.3410631}, timestamp = {Fri, 19 Jul 2024 23:16:25 +0200}, biburl = {https://dblp.org/rec/journals/csysl/BreedenZP24.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2023
- gatekeeper: Online safety verification and control for nonlinear systems in dynamic environmentsThis paper presents the gatekeeper algorithm, a real-time and computationally-lightweight method to ensure that nonlinear systems can operate safely in dynamic environments despite limited perception. gatekeeper integrates with existing path planners and feedback controllers by introducing an additional verification step that ensures that proposed trajectories can be executed safely, despite nonlinear dynamics subject to bounded disturbances, input constraints and partial knowledge of the environment. Our key contribution is that (A) we propose an algorithm to recursively construct committed trajectories, and (B) we prove that tracking the committed trajectory ensures the system is safe for all time into the future. The method is demonstrated on a complicated firefighting mission in a dynamic environment, and compares against the state-of-the-art techniques for similar problems.
@inproceedings{agrawal2023gatekeeper, title={gatekeeper: Online safety verification and control for nonlinear systems in dynamic environments}, author={Agrawal, Devansh and Chen, Ruichang and Panagou, Dimitra}, booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={259--266}, year={2023}, organization={IEEE} } - Predictive Velocity Trajectory Control for a Persistently Operating Solar-Powered Autonomous Surface VesselThe Gulf Stream represents a major potential resource for renewable energy but is presently only sparsely characterized via radar, buoys, gliders, and intermittently op- erating human-operated research vessels. Dramatically greater resolution is possible through the use of persistently operating autonomous surface vessels (ASVs), which can be powered by wind, wave, or solar resources. Optimizing the control of these ASVs, taking into account the device and environmental properties, is crucial to obtaining good data. An ASV’s path and velocity profile along that path both significantly influence the amount of a mission domain that can be covered and, ultimately, the scientific quality of the mission. While our previous work focused on optimizing the path of a solar-powered ASV with fixed speed, the present work represents the complement: optimizing the speed for a given path, accounting for the ASV dynamics, flow resource, and solar resource. We perform this optimization through a model predictive controller that maxi- mizes the projected distance traversed, with a terminal incentive that captures the estimated additional long-duration range that is achievable from a given terminal battery state of charge. We present simulation results based on the SeaTrac SP-48 ASV, Mid-Atlantic Bight/South-Atlantic Bight Regional Ocean Model, and European Centre for Medium-Range Weather Forecasts solar model. Our results show improved performance relative to simpler heuristic controllers that aim to maintain constant speed or constant state of charge. However, we also show that the design of the MPC terminal incentive and design of the heuristic comparison controller can significantly impact the achieved performance; by examining underlying simulation results for different designs, we are able to identify likely causes of performance discrepancies.
- Sensor-based Planning and Control for Robotic Systems: Introducing Clarity and PerceivabilityIn this letter, we first introduce an information measure, termed clarity , motivated by information entropy, and show that it has intuitive properties relevant to dynamic coverage control and informative path planning. Clarity defines on a scale of [0,1] the quality of the information that we have about a variable of interest in an environment. Clarity lower bounds the expected estimation error of any estimator, and is used as the information metric in the notion of perceivability , which is defined later on and is the primary contribution of this letter. Perceivability captures whether a given robotic (or more generally, sensing and control) system has sufficient sensing and actuation capabilities to gather desired information about an environment. We show that perceivability relates to the reachability of an augmented system, which encompasses the robot dynamics and the clarity about the environment, and we derive the corresponding Hamilton-Jacobi-Bellman equations. Thus, we provide an algorithm to measure an environment’s perceivability, and obtain optimal controllers that maximize information gain. In simulations, we demonstrate how clarity is a useful concept for planning trajectories, how perceivability can be determined using reachability analysis, and how a Control Barrier Function controller can be used to design controllers to maintain a desired level of information.
@article{agrawal2023sensor, title={Sensor-based planning and control for robotic systems: Introducing clarity and perceivability}, author={Agrawal, Devansh R and Panagou, Dimitra}, journal={IEEE Control Systems Letters}, year={2023}, publisher={IEEE} } - Adaptation for Validation of Consolidated Control Barrier Functions.We develop a novel adaptation-based technique for safe control design in the presence of multiple state constraints. Specifically, we introduce an approach for synthesizing any number of candidate control barrier functions (CBFs), each encoding a different state constraint, into one consolidated CBF (C-CBF) candidate. We then propose a parameter adaptation law for the weights of the C-CBF's constituent functions such that its controllable dynamics are non-vanishing. We prove that the adaptation law certifies the consolidated CBF candidate as valid for a class of nonlinear, control-affine, multi-agent systems, which permits its use in a quadratic program based control law. We highlight the success of our approach in simulation on a multi-robot goal-reaching problem in a warehouse environment, and further demonstrate its efficacy via a laboratory study with an AION ground rover operating amongst other vehicles behaving both aggressively and conservatively.
@inproceedings{DBLP:conf/cdc/BlackP23, author = {Mitchell Black and Dimitra Panagou}, title = {Adaptation for Validation of Consolidated Control Barrier Functions}, booktitle = {62nd {IEEE} Conference on Decision and Control, {CDC} 2023, Singapore, December 13-15, 2023}, pages = {751--757}, publisher = {{IEEE}}, year = {2023}, url = {https://doi.org/10.1109/CDC49753.2023.10383597}, doi = {10.1109/CDC49753.2023.10383597}, timestamp = {Mon, 29 Jan 2024 17:31:54 +0100}, biburl = {https://dblp.org/rec/conf/cdc/BlackP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Adversarial Resilience for Sampled-Data Systems Under High-Relative-Degree Safety Constraints.Control barrier functions (CBFs) have recently become a powerful method for rendering desired safe sets forward invariant in single-agent and multiagent systems. In the multiagent case, prior literature has considered scenarios where all agents cooperate to ensure that the corresponding set remains invariant. However, these works do not consider scenarios where a subset of the agents are behaving adversarially with the intent to violate safety bounds. In addition, prior results on multiagent CBFs typically assume that control inputs are continuous and do not consider sampled-data dynamics. This article presents a framework for normally behaving agents in a multiagent system with heterogeneous control-affine, sampled-data dynamics to render a safe set forward invariant in the presence of adversarial agents. The proposed approach considers several aspects of practical control systems including input constraints, clock asynchrony and disturbances, and distributed calculation of control inputs. Our approach also considers functions describing safe sets having high relative degree with respect to system dynamics. The efficacy of these results are demonstrated through simulations.
@article{DBLP:journals/tac/UsevitchP23, author = {James Usevitch and Dimitra Panagou}, title = {Adversarial Resilience for Sampled-Data Systems Under High-Relative-Degree Safety Constraints}, journal = {{IEEE} Trans. Autom. Control.}, volume = {68}, number = {3}, pages = {1537--1552}, year = {2023}, url = {https://doi.org/10.1109/TAC.2022.3157791}, doi = {10.1109/TAC.2022.3157791}, timestamp = {Sat, 11 Mar 2023 00:13:06 +0100}, biburl = {https://dblp.org/rec/journals/tac/UsevitchP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Adversary Detection and Resilient Control for Multiagent Systems.This article presents an adversary detection mechanism and a resilient control framework for multiagent systems under spatiotemporal constraints. Safety in multiagent systems is typically addressed under the assumption that all agents collaborate to ensure the forward invariance of a desired safe set. This work analyzes agent behaviors based on certain behavior metrics, and designs a proactive adversary detection mechanism based on the notion of the critical region for the system operation. In particular, the presented detection mechanism not only identifies adversarial agents, but also ensures all-time safety for intact agents. Then, based on the analysis and detection results, a resilient quadratic programming-based controller is presented to ensure safety and liveness constraints for intact agents. Simulation results validate the efficacy of the presented theoretical contributions.
@article{DBLP:journals/tcns/MustafaP23, author = {Aquib Mustafa and Dimitra Panagou}, title = {Adversary Detection and Resilient Control for Multiagent Systems}, journal = {{IEEE} Trans. Control. Netw. Syst.}, volume = {10}, number = {1}, pages = {355--367}, year = {2023}, url = {https://doi.org/10.1109/TCNS.2022.3203350}, doi = {10.1109/TCNS.2022.3203350}, timestamp = {Tue, 28 Mar 2023 19:51:22 +0200}, biburl = {https://dblp.org/rec/journals/tcns/MustafaP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Aerial Swarm Defense Using Interception and Herding Strategies.This article presents a multimode solution to the problem of defending a circular protected area (target) from a wide range of attacks by swarms of risk-taking and/or risk-averse attacking agents (attackers). The proposed multimode solution combines two defense strategies, namely: 1) an interception strategy for a team of defenders to intercept multiple risk-taking attackers while ensuring that the defenders do not collide with each other; 2) a herding strategy to herd a swarm of risk-averse attackers to a safe area. In particular, we develop mixed integer programs (MIPs) and geometry-inspired heuristics to distribute and assign and/or reassign the defenders to interception and herding tasks under different spatiotemporal behaviors by the attackers such as splitting into smaller swarms to evade defenders easily or high-speed maneuvers by some risk-taking attackers to maximize damage to the protected area. We provide theoretical as well as numerical comparison of the computational costs of these MIPs and the heuristics, and demonstrate the overall approach in simulations.
@article{DBLP:journals/trob/ChipadeP23, author = {Vishnu S. Chipade and Dimitra Panagou}, title = {Aerial Swarm Defense Using Interception and Herding Strategies}, journal = {{IEEE} Trans. Robotics}, volume = {39}, number = {5}, pages = {3821--3837}, year = {2023}, url = {https://doi.org/10.1109/TRO.2023.3292514}, doi = {10.1109/TRO.2023.3292514}, timestamp = {Sat, 14 Oct 2023 20:13:20 +0200}, biburl = {https://dblp.org/rec/journals/trob/ChipadeP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Collaborative Control of Aerial Robots for Inferring Human Intent from Gaze Following.In an ideal human-robot collaboration, autonomous robots work side-by-side with humans in a joint workspace, often performing complementary tasks to the humans. A robotic ability to infer human intention and goals directly from human behavior will facilitate the collaboration and maximize its efficiency. In this paper, we focus on inferring which object the human wants picked up next, based on what the human is looking at, by visually following the human gaze and head orientation. We develop a coordination protocol for a team of aerial robots to extract effective human head and gaze cues. The aerial robots are controlled to navigate around the human and collect data that improves the detection of the human's gaze and hence the intended object to be picked up. The effectiveness of the approach is shown using simulations in AirSim, a photo-realistic simulator.
@inproceedings{DBLP:conf/ccta/ChipadeGHP23, author = {Vishnu S. Chipade and Alia Gilbert and Daniel Harari and Dimitra Panagou}, title = {Collaborative Control of Aerial Robots for Inferring Human Intent from Gaze Following}, booktitle = {{IEEE} Conference on Control Technology and Applications, {CCTA} 2023, Bridgetown, Barbados, August 16-18, 2023}, pages = {255--262}, publisher = {{IEEE}}, year = {2023}, url = {https://doi.org/10.1109/CCTA54093.2023.10252647}, doi = {10.1109/CCTA54093.2023.10252647}, timestamp = {Thu, 28 Sep 2023 09:28:41 +0200}, biburl = {https://dblp.org/rec/conf/ccta/ChipadeGHP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Compositions of Multiple Control Barrier Functions Under Input Constraints.This paper presents a methodology for ensuring that the composition of multiple Control Barrier Functions (CBFs) always leads to feasible conditions on the control input, even in the presence of input constraints. In the case of a system subject to a single constraint function, there exist many methods to generate a CBF that ensures constraint satisfaction. However, when there are multiple constraint functions, the problem of finding and tuning one or more CBFs becomes more challenging, especially in the presence of input constraints. This paper addresses this challenge by providing tools to 1) decouple the design of multiple CBFs, so that a CBF can be designed for each constraint function independently of other constraints, and 2) ensure that the set composed from all the CBFs together is a viability domain. Thus, a quadratic program subject to all the CBFs simultaneously is always feasible. The utility of this methodology is then demonstrated in simulation for a nonlinear orientation control system.
@inproceedings{DBLP:conf/amcc/BreedenP23, author = {Joseph Breeden and Dimitra Panagou}, title = {Compositions of Multiple Control Barrier Functions Under Input Constraints}, booktitle = {American Control Conference, {ACC} 2023, San Diego, CA, USA, May 31 - June 2, 2023}, pages = {3688--3695}, publisher = {{IEEE}}, year = {2023}, url = {https://doi.org/10.23919/ACC55779.2023.10156625}, doi = {10.23919/ACC55779.2023.10156625}, timestamp = {Tue, 11 Jul 2023 16:44:32 +0200}, biburl = {https://dblp.org/rec/conf/amcc/BreedenP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Future-Focused Control Barrier Functions for Autonomous Vehicle Control.In this paper, we introduce a class of future-focused control barrier functions (ff-CBF) aimed at improving traditionally myopic CBF based control design and study their efficacy in the context of an unsignaled four-way intersection crossing problem for collections of both communicating and non-communicating autonomous vehicles. Our novel ff-CBF encodes that vehicles take control actions that avoid collisions predicted under a zero-acceleration policy over an arbitrarily long future time interval. In this sense the ff-CBF defines a virtual barrier, a loosening of which we propose in the form of a relaxed future-focused CBF (rff-CBF) that allows a relaxation of the virtual ff-CBF barrier far from the physical barrier between vehicles. We study the performance of ff-CBF and rff-CBF based controllers on communicating vehicles via a series of simulated trials of the intersection scenario, and in particular highlight how the rff-CBF based controller empirically outperforms a benchmark controller from the literature by improving intersection throughput while preserving safety and feasibility. Finally, we demonstrate our proposed ff-CBF control law on an intersection scenario in the laboratory environment with a collection of 5 non-communicating AION ground rovers.
@inproceedings{DBLP:conf/amcc/BlackJSP23, author = {Mitchell Black and Mrdjan Jankovic and Abhishek Sharma and Dimitra Panagou}, title = {Future-Focused Control Barrier Functions for Autonomous Vehicle Control}, booktitle = {American Control Conference, {ACC} 2023, San Diego, CA, USA, May 31 - June 2, 2023}, pages = {3324--3331}, publisher = {{IEEE}}, year = {2023}, url = {https://doi.org/10.23919/ACC55779.2023.10156163}, doi = {10.23919/ACC55779.2023.10156163}, timestamp = {Tue, 11 Jul 2023 16:44:32 +0200}, biburl = {https://dblp.org/rec/conf/amcc/BlackJSP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Robust Control Barrier Functions under high relative degree and input constraints for satellite trajectories.
@article{DBLP:journals/automatica/BreedenP23, author = {Joseph Breeden and Dimitra Panagou}, title = {Robust Control Barrier Functions under high relative degree and input constraints for satellite trajectories}, journal = {Autom.}, volume = {155}, pages = {111109}, year = {2023}, url = {https://doi.org/10.1016/j.automatica.2023.111109}, doi = {10.1016/J.AUTOMATICA.2023.111109}, timestamp = {Wed, 16 Aug 2023 16:57:32 +0200}, biburl = {https://dblp.org/rec/journals/automatica/BreedenP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Safety Under Uncertainty: Tight Bounds with Risk-Aware Control Barrier Functions.We propose a novel class of risk-aware control barrier functions (RA-CBFs) for the control of stochastic safety-critical systems. Leveraging a result from the stochastic level-crossing literature, we deviate from the martingale theory that is currently used in stochastic CBF techniques and prove that a RA-CBF based control synthesis confers a tighter upper bound on the probability of the system becoming unsafe within a finite time interval than existing approaches. We highlight the advantages of our proposed approach over the state-of-the-art via a comparative study on an mobile-robot example, and further demonstrate its viability on an autonomous vehicle highway merging problem in dense traffic.
@inproceedings{DBLP:conf/icra/BlackFHPP23, author = {Mitchell Black and Georgios Fainekos and Bardh Hoxha and Danil V. Prokhorov and Dimitra Panagou}, title = {Safety Under Uncertainty: Tight Bounds with Risk-Aware Control Barrier Functions}, booktitle = {{IEEE} International Conference on Robotics and Automation, {ICRA} 2023, London, UK, May 29 - June 2, 2023}, pages = {12686--12692}, publisher = {{IEEE}}, year = {2023}, url = {https://doi.org/10.1109/ICRA48891.2023.10161379}, doi = {10.1109/ICRA48891.2023.10161379}, timestamp = {Sun, 06 Oct 2024 21:06:22 +0200}, biburl = {https://dblp.org/rec/conf/icra/BlackFHPP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Safety-Critical Control for Systems With Impulsive Actuators and Dwell Time Constraints.This letter presents extensions of control barrier function (CBF) and control Lyapunov function (CLF) theory to systems wherein all actuators cause impulsive changes to the state trajectory, and can only be used again after a minimum dwell time has elapsed. These rules define a hybrid system, wherein the controller must at each control cycle choose whether to remain on the current state flow or to jump to a new trajectory. We first derive a sufficient condition to render a specified set forward invariant using extensions of CBF theory. We then derive related conditions to ensure asymptotic stability in such systems, and apply both conditions online in an optimization-based control law with aperiodic impulses. We simulate both results on a spacecraft docking problem with multiple obstacles.
@article{DBLP:journals/csysl/BreedenP23, author = {Joseph Breeden and Dimitra Panagou}, title = {Safety-Critical Control for Systems With Impulsive Actuators and Dwell Time Constraints}, journal = {{IEEE} Control. Syst. Lett.}, volume = {7}, pages = {2119--2124}, year = {2023}, url = {https://doi.org/10.1109/LCSYS.2023.3285141}, doi = {10.1109/LCSYS.2023.3285141}, timestamp = {Fri, 07 Jul 2023 23:32:29 +0200}, biburl = {https://dblp.org/rec/journals/csysl/BreedenP23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2022
- A Constructive Method for Designing Safe Multirate Controllers for Differentially-Flat SystemsThis paper introduces the notion of an Input Constrained Control Barrier Function (ICCBF), as a method to synthesize safety-critical controllers for nonlinear control-affine systems with input constraints. The method identifies a subset of the safe set of states, and constructs a controller to render the subset forward invariant. The feedback controller is represented as the solution to a quadratic program, which can be solved efficiently for real-time implementation. Furthermore, we show that ICCBFs are a generalization of Higher Order Control Barrier Functions, and thus are applicable to systems of non- uniform relative degree. Simulation results are presented for the adaptive cruise control problem, and a spacecraft rendezvous problem.
@ARTICLE{9655322, author={Agrawal, Devansh R. and Parwana, Hardik and Cosner, Ryan K. and Rosolia, Ugo and Ames, Aaron D. and Panagou, Dimitra}, journal={IEEE Control Systems Letters}, title={A Constructive Method for Designing Safe Multirate Controllers for Differentially-Flat Systems}, year={2022}, volume={6}, number={}, pages={2138-2143}, doi={10.1109/LCSYS.2021.3136465} } - Safe and robust observer-controller synthesis using control barrier functionsThis letter addresses the synthesis of safety-critical controllers using estimate feedback. We propose an observer-controller interconnection to ensure that the nonlinear system remains safe despite bounded disturbances on the system dynamics and measurements that correspond to partial state information. The co-design of observers and controllers is critical, since even in undisturbed cases, observers and controllers designed independently may not render the system safe. We propose two approaches to synthesize observer-controller interconnections. The first approach utilizes Input-to-State Stable observers, and the second uses Bounded Error observers. Using these stability and boundedness properties of the observation error, we construct novel Control Barrier Functions that impose inequality constraints on the control inputs which, when satisfied, certifies safety. We propose quadratic program-based controllers to satisfy these constraints, and prove Lipschitz continuity of the derived controllers. Simulations and experiments on a quadrotor demonstrate the efficacy of the proposed methods.
@article{agrawal2022safe, title={Safe and robust observer-controller synthesis using control barrier functions}, author={Agrawal, Devansh R and Panagou, Dimitra}, journal={IEEE Control Systems Letters}, volume={7}, pages={127--132}, year={2022}, publisher={IEEE} } - Coverage-Maximizing Solar-Powered Autonomous Surface Vehicle Control for Persistent Gulf Stream ObservationThe Gulf Stream, which comes within 100 km of the United States coastline in both the Florida Straits and the vicinity of Cape Hatteras, is estimated to possess over 160 TWh/year of technical energy capacity. To better understand the behavior of the Gulf Stream, whose flow resource varies in both space and time, a relatively sparse network of fixed acoustic Doppler current profilers (ADCPs) and shore-mounted high-frequency radar units have been supplemented by more granular but infrequent boat transect runs and undersea glider deployments. Collectively, these measurements provide highly granular data with respect to either time or space, but not both. This work represents part of a comprehensive effort to evaluate use of a solar-powered autonomous surface vehicle (ASV) fleet to supplement existing observational capabilities. The proposed solar-powered ASV can provide data with high spatial and temporal granularity, but comes with the challenge of optimally planning its mission in an adaptive manner. To address this challenge in this work, we propose a multilevel controller that fuses the A* search algorithm with an upper level waypoint selector and lower level heading control. Focusing on a critically important mission domain adjacent to Cape Hatteras, and relying on a Mid-Atlantic Bight, South Atlantic Bight Regional Ocean Model (MAB-SAB-ROM), we compare the performance of our proposed algorithm against several competing strategies. We demonstrate a significant performance improvement in terms of a dynamic coverage metric, both in comparison to competing strategies and to the existing observational network.
- Adaptive Control of Second-Order Safety-Critical Multiagent Systems With Nonlinear Dynamics.In this article, we propose a distributed adaptive control architecture for leader-following consensus of uncertain multiagent systems with second-order nonlinear dynamics. A nonlinear reference model system captures an ideal behavior of the agents for the leader-following consensus problem. We design a modified nonlinear reference model system and propose a distributed model reference adaptive control architecture to suppress the effects of system uncertainties without a strict knowledge of their magnitude and rate upper bounds. Consequently, each agent evolves within a (possibly different) prescribed distance from the corresponding modified reference system trajectories. Based on an input-to-state stability analysis, it is shown that the trajectories of the modified reference model system can get arbitrarily close to the trajectories of the ideal reference model system. As a result, the trajectories of the agents evolve within a user-specified prescribed distance from their ideal system trajectories, satisfying the safety constraints. The key feature of the presented control architecture in this article is the elimination of the ad hoc tuning process for the adaptation rate that is conventionally required in model reference adaptive control systems to ensure safety. An illustrative numerical example finally demonstrates the efficacy of the proposed distributed adaptive control architecture.
@article{DBLP:journals/tcns/ArabiP22, author = {Ehsan Arabi and Dimitra Panagou}, title = {Adaptive Control of Second-Order Safety-Critical Multiagent Systems With Nonlinear Dynamics}, journal = {{IEEE} Trans. Control. Netw. Syst.}, volume = {9}, number = {4}, pages = {1911--1922}, year = {2022}, url = {https://doi.org/10.1109/TCNS.2022.3181547}, doi = {10.1109/TCNS.2022.3181547}, timestamp = {Sun, 15 Jan 2023 18:31:15 +0100}, biburl = {https://dblp.org/rec/journals/tcns/ArabiP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Control Barrier Functions in Sampled-Data Systems.This letter presents conditions for ensuring forward invariance of safe sets under sampled-data system dynamics with piecewise-constant controllers and fixed time-steps. First, we introduce two different metrics to compare the conservativeness of sufficient conditions on forward invariance under piecewise-constant controllers. Then, we propose three approaches for guaranteeing forward invariance, two motivated by continuous-time barrier functions, and one motivated by discrete-time barrier functions. All proposed conditions are control affine, and thus can be incorporated into quadratic programs for control synthesis. We show that the proposed conditions are less conservative than those in earlier studies, and show via simulation how this enables the use of barrier functions that are impossible to implement with the desired time-step using existing methods.
@article{DBLP:journals/csysl/BreedenGP22, author = {Joseph Breeden and Kunal Garg and Dimitra Panagou}, title = {Control Barrier Functions in Sampled-Data Systems}, journal = {{IEEE} Control. Syst. Lett.}, volume = {6}, pages = {367--372}, year = {2022}, url = {https://doi.org/10.1109/LCSYS.2021.3076127}, doi = {10.1109/LCSYS.2021.3076127}, timestamp = {Tue, 13 Jul 2021 13:26:13 +0200}, biburl = {https://dblp.org/rec/journals/csysl/BreedenGP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Expanding human visual field: online learning of assistive camera views by an aerial co-robot.
@article{DBLP:journals/arobots/BentzQP22, author = {William Bentz and Long Qian and Dimitra Panagou}, title = {Expanding human visual field: online learning of assistive camera views by an aerial co-robot}, journal = {Auton. Robots}, volume = {46}, number = {8}, pages = {949--970}, year = {2022}, url = {https://doi.org/10.1007/s10514-022-10059-4}, doi = {10.1007/S10514-022-10059-4}, timestamp = {Sun, 13 Nov 2022 17:53:19 +0100}, biburl = {https://dblp.org/rec/journals/arobots/BentzQP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Fixed-time control under spatiotemporal and input constraints: A Quadratic Programming based approach.
@article{DBLP:journals/automatica/GargAP22, author = {Kunal Garg and Ehsan Arabi and Dimitra Panagou}, title = {Fixed-time control under spatiotemporal and input constraints: {A} Quadratic Programming based approach}, journal = {Autom.}, volume = {141}, pages = {110314}, year = {2022}, url = {https://doi.org/10.1016/j.automatica.2022.110314}, doi = {10.1016/J.AUTOMATICA.2022.110314}, timestamp = {Wed, 07 Dec 2022 23:03:25 +0100}, biburl = {https://dblp.org/rec/journals/automatica/GargAP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Guaranteed Safe Spacecraft Docking With Control Barrier Functions.This letter presents a strategy for control of a spacecraft docking with a non-maneuvering target in the presence of safety constraints and bounded disturbances. The presence of disturbances prevents convergence to a unique docking state, so in our formulation, docking is defined as occurring within a set constructed using prescribed tolerances. Safety is ensured via application of Robust Control Barrier Functions to render a designated safe set forward invariant for any allowable disturbance. However, this safety strategy necessarily presumes a worst-case disturbance, and thus restricts trajectories to a subset of the safe set when a worst-case disturbance is not present. The presented controller accounts for this restriction, and guarantees that the spacecraft both remains safe and achieves docking in finite time for any allowable disturbance. The controller is then validated in simulation for a spacecraft landing on an asteroid, and two spacecraft docking in low Earth orbit.
@article{DBLP:journals/csysl/BreedenP22, author = {Joseph Breeden and Dimitra Panagou}, title = {Guaranteed Safe Spacecraft Docking With Control Barrier Functions}, journal = {{IEEE} Control. Syst. Lett.}, volume = {6}, pages = {2000--2005}, year = {2022}, url = {https://doi.org/10.1109/LCSYS.2021.3136813}, doi = {10.1109/LCSYS.2021.3136813}, timestamp = {Sat, 08 Jan 2022 02:23:17 +0100}, biburl = {https://dblp.org/rec/journals/csysl/BreedenP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Multi-Rate Control Design Under Input Constraints via Fixed-Time Barrier Functions.In this letter, we introduce the notion of periodic safety, which requires that the system trajectories periodically visit a subset of a forward-invariant safe set, and utilize it in a multi-rate framework where a high-level planner generates a reference trajectory that is tracked by a low-level controller under input constraints. We introduce the notion of fixed-time barrier functions which is leveraged by the proposed low-level controller in a quadratic programming framework. Then, we design a model predictive control policy for high-level planning with a bound on the rate of change for the reference trajectory to guarantee that periodic safety is achieved. We demonstrate the effectiveness of the proposed strategy on a simulation example, where the proposed fixed-time stabilizing low-level controller shows successful satisfaction of control objectives, whereas an exponentially stabilizing low-level controller fails.
@article{DBLP:journals/csysl/GargCRAP22, author = {Kunal Garg and Ryan K. Cosner and Ugo Rosolia and Aaron D. Ames and Dimitra Panagou}, title = {Multi-Rate Control Design Under Input Constraints via Fixed-Time Barrier Functions}, journal = {{IEEE} Control. Syst. Lett.}, volume = {6}, pages = {608--613}, year = {2022}, url = {https://doi.org/10.1109/LCSYS.2021.3084322}, doi = {10.1109/LCSYS.2021.3084322}, timestamp = {Thu, 16 Sep 2021 18:02:01 +0200}, biburl = {https://dblp.org/rec/journals/csysl/GargCRAP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Predictive Control Barrier Functions for Online Safety Critical Control.This paper presents a methodology for constructing Control Barrier Functions (CBFs) that proactively consider the future safety of a system along a nominal trajectory, and effect corrective action before the trajectory leaves a designated safe set. Specifically, this paper presents a systematic approach for propagating a nominal trajectory on a receding horizon, and then encoding the future safety of this trajectory into a CBF. If the propagated trajectory is unsafe, then a controller satisfying the CBF condition will modify the nominal trajectory before the trajectory becomes unsafe. Compared to existing CBF techniques, this strategy is proactive rather than reactive and thus potentially results in smaller modifications to the nominal trajectory. The proposed strategy is shown to be provably safe, and then is demonstrated in simulated scenarios where it would otherwise be difficult to construct a traditional CBF. In simulation, the predictive CBF results in less modification to the nominal trajectory and smaller control inputs than a traditional CBF, and faster computations than a nonlinear model predictive control approach.
@inproceedings{DBLP:conf/cdc/BreedenP22, author = {Joseph Breeden and Dimitra Panagou}, title = {Predictive Control Barrier Functions for Online Safety Critical Control}, booktitle = {61st {IEEE} Conference on Decision and Control, {CDC} 2022, Cancun, Mexico, December 6-9, 2022}, pages = {924--931}, publisher = {{IEEE}}, year = {2022}, url = {https://doi.org/10.1109/CDC51059.2022.9992926}, doi = {10.1109/CDC51059.2022.9992926}, timestamp = {Wed, 18 Jan 2023 15:37:50 +0100}, biburl = {https://dblp.org/rec/conf/cdc/BreedenP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Recursive Feasibility Guided Optimal Parameter Adaptation of Differential Convex Optimization Policies for Safety-Critical Systems.Quadratic Program(QP) based state-feedback controllers, whose inequality constraints bound the rate of change of control barrier (CBFs) and lyapunov function with a class-$\mathcal{K}$ function of their values, are sensitive to the parameters of these class-$\mathcal{K}$ functions. The construction of valid CBFs, however, is not straightforward, and for arbitrarily chosen parameters of the QP, the system trajectories may enter states at which the QP either eventually becomes infeasible, or may not achieve desired performance. In this work, we pose the control synthesis problem as a differential policy whose parameters are optimized for performance over a time horizon at high level, thus resulting in a bi-level optimization routine. In the absence of knowledge of the set of feasible parameters, we develop a Recursive Feasibility Guided Gradient Descent approach for updating the parameters of QP so that the new solution performs at least as well as previous solution. By considering the dynamical system as a directed graph over time, this work presents a novel way of optimizing performance of a QP controller over a time horizon for multiple CBFs by (1) using the gradient of its solution with respect to its parameters by employing sensitivity analysis, and (2) backpropagating these as well as system dynamics gradients to update parameters while maintaining feasibility of QPs.
@inproceedings{DBLP:conf/icra/ParwanaP22, author = {Hardik Parwana and Dimitra Panagou}, title = {Recursive Feasibility Guided Optimal Parameter Adaptation of Differential Convex Optimization Policies for Safety-Critical Systems}, booktitle = {2022 International Conference on Robotics and Automation, {ICRA} 2022, Philadelphia, PA, USA, May 23-27, 2022}, pages = {6807--6813}, publisher = {{IEEE}}, year = {2022}, url = {https://doi.org/10.1109/ICRA46639.2022.9812398}, doi = {10.1109/ICRA46639.2022.9812398}, timestamp = {Wed, 20 Jul 2022 18:22:50 +0200}, biburl = {https://dblp.org/rec/conf/icra/ParwanaP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Resilient Trajectory Propagation in Multirobot Networks.This article presents a novel method for a class of multirobot networks to resiliently propagate vector messages from a set of leaders to all followers within the network in the presence of faulty or adversarially behaving robots. It is shown that the proposed method can operate under heterogeneous communication rates between robots and perturbations of the leaders’ propagated information. As a case study, the proposed method is applied to the problem of time-varying trajectory tracking; more specifically, time-varying reference trajectories in the form of Bezier curves are encoded into vectors of static parameters, which, in turn, are resiliently propagated from the leaders to the followers.
@article{DBLP:journals/trob/UsevitchP22, author = {James Usevitch and Dimitra Panagou}, title = {Resilient Trajectory Propagation in Multirobot Networks}, journal = {{IEEE} Trans. Robotics}, volume = {38}, number = {1}, pages = {42--56}, year = {2022}, url = {https://doi.org/10.1109/TRO.2021.3127076}, doi = {10.1109/TRO.2021.3127076}, timestamp = {Wed, 23 Feb 2022 11:15:29 +0100}, biburl = {https://dblp.org/rec/journals/trob/UsevitchP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Robust Leader-Follower Formation Control for Human-Robot Scenarios.This paper presents a robust formation control problem for multiple robots surrounding a human leader in the presence of measurement uncertainties. Utilizing previous work on adaptive estimation and Lyapunov-like barrier functions, an architecture is designed for the formation control of follower robots around a human leader in the presence of uncertainties in the leader’s and follower robots’ state information. Convergence and safety of the follower robots is proved formally. The proposed architecture is demonstrated in simulations and experiments.
@inproceedings{DBLP:conf/amcc/GilbertCP22, author = {Alia Gilbert and Vishnu S. Chipade and Dimitra Panagou}, title = {Robust Leader-Follower Formation Control for Human-Robot Scenarios}, booktitle = {American Control Conference, {ACC} 2022, Atlanta, GA, USA, June 8-10, 2022}, pages = {641--646}, publisher = {{IEEE}}, year = {2022}, url = {https://doi.org/10.23919/ACC53348.2022.9867709}, doi = {10.23919/ACC53348.2022.9867709}, timestamp = {Mon, 06 Nov 2023 12:57:51 +0100}, biburl = {https://dblp.org/rec/conf/amcc/GilbertCP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Trust-based Rate-Tunable Control Barrier Functions for Non-Cooperative Multi-Agent Systems.For efficient and robust task accomplishment in multi-agent systems, an agent must be able to distinguish cooperative agents from non-cooperative (i.e., uncooperative and adversarial) agents. In this paper, we first develop a trust metric based on which each agent forms its own belief of how cooperative the other agents are, i.e., of how much the other agents contribute to maintaining safety. With safety encoded as Control Barrier Functions (CBFs), the trust metric is in turn used to adjust the rate at which the CBFs allow the system trajectories to approach the boundary of the safe set. This is achieved via a novel Rate-Tunable CBF, which yields less conservative performance compared to an identity-agnostic implementation, where cooperative and non-cooperative agents are treated similarly. The proposed adaptation and control method is evaluated via simulations on heterogeneous multi-agent systems including non-cooperative agents.
@inproceedings{DBLP:conf/cdc/ParwanaMP22, author = {Hardik Parwana and Aquib Mustafa and Dimitra Panagou}, title = {Trust-based Rate-Tunable Control Barrier Functions for Non-Cooperative Multi-Agent Systems}, booktitle = {61st {IEEE} Conference on Decision and Control, {CDC} 2022, Cancun, Mexico, December 6-9, 2022}, pages = {2222--2229}, publisher = {{IEEE}}, year = {2022}, url = {https://doi.org/10.1109/CDC51059.2022.9992744}, doi = {10.1109/CDC51059.2022.9992744}, timestamp = {Wed, 18 Jan 2023 15:37:50 +0100}, biburl = {https://dblp.org/rec/conf/cdc/ParwanaMP22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2021
- Safe Control Synthesis via Input Constrained Control Barrier FunctionsThis paper introduces the notion of an Input Constrained Control Barrier Function (ICCBF), as a method to synthesize safety-critical controllers for nonlinear control-affine systems with input constraints. The method identifies a subset of the safe set of states, and constructs a controller to render the subset forward invariant. The feedback controller is represented as the solution to a quadratic program, which can be solved efficiently for real-time implementation. Furthermore, we show that ICCBFs are a generalization of Higher Order Control Barrier Functions, and thus are applicable to systems of non- uniform relative degree. Simulation results are presented for the adaptive cruise control problem, and a spacecraft rendezvous problem.
@INPROCEEDINGS{9682938, author={Agrawal, Devansh R. and Panagou, Dimitra}, booktitle={2021 60th IEEE Conference on Decision and Control (CDC)}, title={Safe Control Synthesis via Input Constrained Control Barrier Functions}, year={2021}, volume={}, number={}, pages={6113-6118}, doi={10.1109/CDC45484.2021.9682938} } - A Fixed-Time Stable Adaptation Law for Safety-Critical Control under Parametric Uncertainty.We present a novel technique for solving the problem of safe control for a class of nonlinear, control-affine systems subject to parametric model uncertainty. Invoking Lyapunov analysis and the notion of fixed-time stability (FxTS), we introduce a parameter adaptation law which guarantees convergence of the estimates of unknown parameters in the system dynamics to their true values within a fixed-time independent of the initial error. We then synthesize this law with a robust, adaptive control barrier function (RaCBF)-based quadratic program to compute safe control inputs despite the considered uncertainty. To corroborate our results, we undertake a comparative case study on the efficacy of this result versus other recent approaches in the literature to safe control under uncertainty, and close by highlighting the value of our method in the context of an automobile overtake scenario.
@inproceedings{DBLP:conf/eucc/BlackAP21, author = {Mitchell Black and Ehsan Arabi and Dimitra Panagou}, title = {A Fixed-Time Stable Adaptation Law for Safety-Critical Control under Parametric Uncertainty}, booktitle = {2021 European Control Conference, {ECC} 2021, Virtual Event / Delft, The Netherlands, June 29 - July 2, 2021}, pages = {1328--1333}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.23919/ECC54610.2021.9655080}, doi = {10.23919/ECC54610.2021.9655080}, timestamp = {Thu, 31 Mar 2022 11:10:43 +0200}, biburl = {https://dblp.org/rec/conf/eucc/BlackAP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Adaptive Active-Passive Networked Multiagent Systems.Active-passive multiagent systems consist of agents subject to inputs (active agents) and agents with no inputs (passive agents), where active and passive agent roles are considered to be interchangeable in order to capture a wide array of applications. A challenge in the control of active-passive multiagent systems is the presence of information exchange uncertainties that can yield to undesirable closed-loop system performance. Motivated by this standpoint, this paper proposes an adaptive control algorithm for this class of multiagent systems to suppress the negative effects of information exchange uncertainties. Specifically, by estimating these uncertainties, the proposed adaptive control architecture has the ability to recover the active-passive multiagent system performance in a distributed manner. As a result, the agents converge to a user-adjustable neighborhood of the average of the applied inputs to the active agents. The efficacy of the proposed control architecture is also validated from a human-robot collaboration perspective, where a human is visiting several task locations, and the multiagent system identifies these locations and move toward them as a coverage control problem.
@inproceedings{DBLP:conf/amcc/ArabiPY21, author = {Ehsan Arabi and Dimitra Panagou and Tansel Yucelen}, title = {Adaptive Active-Passive Networked Multiagent Systems}, booktitle = {2021 American Control Conference, {ACC} 2021, New Orleans, LA, USA, May 25-28, 2021}, pages = {1113--1118}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.23919/ACC50511.2021.9483258}, doi = {10.23919/ACC50511.2021.9483258}, timestamp = {Fri, 30 Jul 2021 11:11:53 +0200}, biburl = {https://dblp.org/rec/conf/amcc/ArabiPY21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Adversarial Resilience for Sampled-Data Systems using Control Barrier Function Methods.Control barrier functions (CBFs) have recently become a powerful method for rendering a desired safe set forward invariant in single- and multi-agent systems. In the multiagent case, prior literature has considered scenarios where all agents cooperate to ensure that the corresponding set remains invariant. However, these works do not consider scenarios where a subset of the agents are behaving adversarially with the intent to violate safety bounds. In addition, prior results on multi-agent CBFs assume that control inputs are continuous and do not explicitly consider sampled-data dynamics. This paper presents a method for normally behaving agents in a multi-agent system with heterogeneous control-affine sampled-data dynamics to render a safe set forward invariant in the presence of adversarial agents. The efficacy of these results are demonstrated through simulations.
@inproceedings{DBLP:conf/amcc/UsevitchP21, author = {James Usevitch and Dimitra Panagou}, title = {Adversarial Resilience for Sampled-Data Systems using Control Barrier Function Methods}, booktitle = {2021 American Control Conference, {ACC} 2021, New Orleans, LA, USA, May 25-28, 2021}, pages = {758--763}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.23919/ACC50511.2021.9482659}, doi = {10.23919/ACC50511.2021.9482659}, timestamp = {Fri, 30 Jul 2021 11:11:53 +0200}, biburl = {https://dblp.org/rec/conf/amcc/UsevitchP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Aerial Swarm Defense by StringNet Herding: Theory and Experiments.This paper studies a defense approach against one or more swarms of adversarial agents. In our earlier work, we employed a closed formation (“StringNet”) of defending agents (defenders) around a swarm of adversarial agents (attackers) to confine their motion within given bounds, and guide them to a safe area. The adversarial agents were assumed to remain close enough to each other, i.e., within a prescribed connectivity region. To handle situations when the attackers no longer stay within such a connectivity region, but rather split into smaller swarms (clusters) to maximize the chance or impact of attack, this paper proposes an approach to learn the attacking sub-swarms and reassign defenders toward the attackers. We use a “Density-based Spatial Clustering of Application with Noise (DBSCAN)” algorithm to identify the spatially distributed swarms of the attackers. Then, the defenders are assigned to each identified swarm of attackers by solving a constrained generalized assignment problem. We also provide conditions under which defenders can successfully herd all the attackers. The efficacy of the approach is demonstrated via computer simulations, as well as hardware experiments with a fleet of quadrotors.
@article{DBLP:journals/firai/ChipadeMP21, author = {Vishnu S. Chipade and Venkata Sai Aditya Marella and Dimitra Panagou}, title = {Aerial Swarm Defense by StringNet Herding: Theory and Experiments}, journal = {Frontiers Robotics {AI}}, volume = {8}, pages = {640446}, year = {2021}, url = {https://doi.org/10.3389/frobt.2021.640446}, doi = {10.3389/FROBT.2021.640446}, timestamp = {Tue, 04 May 2021 17:49:02 +0200}, biburl = {https://dblp.org/rec/journals/firai/ChipadeMP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Characterization of Domain of Fixed-time Stability under Control Input Constraints.In this paper, we study the effect of control input constraints on the domain of attraction of an FxTS equilibrium point. We first present a new result on FxTS, where we allow a positive term in the time derivative of the Lyapunov function. We provide analytical expressions for the domain of attraction and the settling time to the equilibrium in terms of the coefficients of the positive and negative terms that appear in the time derivative of the Lyapunov function. We show that this result serves as a robustness characterization of FxTS equilibria in the presence of an additive, vanishing disturbances. We use the new FxTS result in formulating a provably feasible quadratic program (QP) that computes control inputs that drive the trajectories of a class of nonlinear, control-affine systems to a goal set, in the presence of control input constraints.
@inproceedings{DBLP:conf/amcc/GargP21, author = {Kunal Garg and Dimitra Panagou}, title = {Characterization of Domain of Fixed-time Stability under Control Input Constraints}, booktitle = {2021 American Control Conference, {ACC} 2021, New Orleans, LA, USA, May 25-28, 2021}, pages = {2272--2277}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.23919/ACC50511.2021.9482780}, doi = {10.23919/ACC50511.2021.9482780}, timestamp = {Thu, 14 Oct 2021 10:23:17 +0200}, biburl = {https://dblp.org/rec/conf/amcc/GargP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Dynamic Coverage Meets Regret: Unifying Two Control Performance Measures for Mobile Agents in Spatiotemporally Varying Environments.Numerous mobile robotic applications require agents to persistently explore and exploit spatiotemporally varying, partially observable environments. Ultimately, the mathematical notion of regret, which quite simply represents the instantaneous or time-averaged difference between the optimal reward and realized reward, serves as a meaningful measure of how well the agents have exploited the environment. However, while numerous theoretical regret bounds have been derived within the machine learning community, restrictions on the manner in which the environment evolves preclude their application to persistent missions. On the other hand, meaningful theoretical properties can be derived for the related concept of dynamic coverage, which serves as an exploration measurement but does not have an immediately intuitive connection with regret. In this paper, we demonstrate a clear correlation between an appropriately defined measure of dynamic coverage and regret, then go on to derive performance bounds on dynamic coverage as a function of the environmental parameters. We evaluate the correlation for several variants of an airborne wind energy system, for which the objective is to adjust the operating altitude in order to maximize power output in a spatiotemporally evolving wind field.
@inproceedings{DBLP:conf/cdc/HaydonMKPCMV21, author = {Ben Haydon and Kirti D. Mishra and Patrick Keyantuo and Dimitra Panagou and Fotini K. Chow and Scott J. Moura and Chris Vermillion}, title = {Dynamic Coverage Meets Regret: Unifying Two Control Performance Measures for Mobile Agents in Spatiotemporally Varying Environments}, booktitle = {2021 60th {IEEE} Conference on Decision and Control (CDC), Austin, TX, USA, December 14-17, 2021}, pages = {521--526}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.1109/CDC45484.2021.9682826}, doi = {10.1109/CDC45484.2021.9682826}, timestamp = {Tue, 17 May 2022 15:53:17 +0200}, biburl = {https://dblp.org/rec/conf/cdc/HaydonMKPCMV21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Finite-Time Stabilization of Switched Systems with Unstable Modes.In this paper, we study finite-time stability and stabilization of switched systems in the presence of unstable modes. In contrast to asymptotic or exponential stability where the system trajectories reach the equilibrium point as time tends to infinity, the notion of finite-time stability requires the trajectories to reach the equilibrium within a finite amount of time. We show that even if the value of the Lyapunov function increases in between two switches, i.e., if there are unstable modes in the system, finite-time stability can still be guaranteed if the finite-time convergent mode is active for a long enough cumulative time duration. Then, we present a method for the synthesis of a finite-time stabilizing switching signal. As a case study, we design a finite-time stable, output-feedback controller for a linear switched system, in which only one of the modes is both controllable and observable.
@inproceedings{DBLP:conf/cdc/GargP21, author = {Kunal Garg and Dimitra Panagou}, title = {Finite-Time Stabilization of Switched Systems with Unstable Modes}, booktitle = {2021 60th {IEEE} Conference on Decision and Control (CDC), Austin, TX, USA, December 14-17, 2021}, pages = {3924--3929}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.1109/CDC45484.2021.9683332}, doi = {10.1109/CDC45484.2021.9683332}, timestamp = {Wed, 07 Dec 2022 23:07:58 +0100}, biburl = {https://dblp.org/rec/conf/cdc/GargP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Fixed-Time Stable Gradient Flows: Applications to Continuous-Time Optimization.Continuous-time optimization is currently an active field of research in optimization theory; prior work in this area has yielded useful insights and elegant methods for proving stability and convergence properties of the continuous-time optimization algorithms. This article proposes novel gradient-flow schemes that yield convergence to the optimal point of a convex optimization problem within a fixed time from any given initial condition for unconstrained optimization, constrained optimization, and min–max problems. It is shown that the solution of the modified gradient-flow dynamics exists and is unique under certain regularity conditions on the objective function, while fixed-time convergence to the optimal point is shown via Lyapunov-based analysis. The application of the modified gradient flow to unconstrained optimization problems is studied under the assumption of gradient dominance, a relaxation of strong convexity. Then, a modified Newton's method is presented that exhibits fixed-time convergence under some mild conditions on the objective function. Building upon this method, a novel technique for solving convex optimization problems with linear equality constraints that yields convergence to the optimal point in fixed time is developed. Finally, the general min–max problem is considered, and a modified saddle-point dynamics to obtain the optimal solution in fixed time is developed.
@article{DBLP:journals/tac/GargP21, author = {Kunal Garg and Dimitra Panagou}, title = {Fixed-Time Stable Gradient Flows: Applications to Continuous-Time Optimization}, journal = {{IEEE} Trans. Autom. Control.}, volume = {66}, number = {5}, pages = {2002--2015}, year = {2021}, url = {https://doi.org/10.1109/TAC.2020.3001436}, doi = {10.1109/TAC.2020.3001436}, timestamp = {Sun, 25 Jul 2021 11:40:11 +0200}, biburl = {https://dblp.org/rec/journals/tac/GargP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Herding an Adversarial Swarm in Three-dimensional Spaces.This paper presents a defense approach to safeguard a protected area against an attack by a swarm of adversarial agents in three-dimensional (3D) space. We extend our 2D ‘stringNet Herding’ approach, in which a closed formation of string-barriers is established around the adversarial swarm to confine their motion and herd them to a safe area, to 3D spaces by introducing 3D-StringNet. 3D-StringNet is a closed 3D formation of triangular netlike barriers. We provide a systematic approach to generate three types of 3D formations that are used in the 3D herding process and modifications to the finite-time convergent control laws developed in our earlier work. Furthermore, for given initial positions of the defenders, we provide conditions on the initial positions of the attackers for which the defenders are guaranteed to gather as a specified formation at a position on the shortest path of the attackers to the protected area before attackers reach there. The approach is investigated in simulations.
@inproceedings{DBLP:conf/amcc/ZhangCP21, author = {Weifan Zhang and Vishnu S. Chipade and Dimitra Panagou}, title = {Herding an Adversarial Swarm in Three-dimensional Spaces}, booktitle = {2021 American Control Conference, {ACC} 2021, New Orleans, LA, USA, May 25-28, 2021}, pages = {4722--4728}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.23919/ACC50511.2021.9482990}, doi = {10.23919/ACC50511.2021.9482990}, timestamp = {Fri, 30 Jul 2021 11:11:53 +0200}, biburl = {https://dblp.org/rec/conf/amcc/ZhangCP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - High Relative Degree Control Barrier Functions Under Input Constraints.This paper presents methodologies for ensuring forward invariance of sublevel sets of constraint functions with high-relative-degree with respect to the system dynamics and in the presence of input constraints. We show that such constraint functions can be converted into special Zeroing Control Barrier Functions (ZCBFs), which, by construction, generate sufficient conditions for rendering the state always inside a sublevel set of the constraint function in the presence of input constraints. We present a general form for one such ZCBF, as well as a special case applicable to a specific class of systems. We conclude with a comparison of system trajectories under the two ZCBFs developed and prior literature, and a case study for an asteroid observation problem using quadratic-program based controllers to enforce the ZCBF condition.
@inproceedings{DBLP:conf/cdc/BreedenP21, author = {Joseph Breeden and Dimitra Panagou}, title = {High Relative Degree Control Barrier Functions Under Input Constraints}, booktitle = {2021 60th {IEEE} Conference on Decision and Control (CDC), Austin, TX, USA, December 14-17, 2021}, pages = {6119--6124}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.1109/CDC45484.2021.9683705}, doi = {10.1109/CDC45484.2021.9683705}, timestamp = {Tue, 17 May 2022 15:53:17 +0200}, biburl = {https://dblp.org/rec/conf/cdc/BreedenP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Multiagent Planning and Control for Swarm Herding in 2-D Obstacle Environments Under Bounded Inputs.This article presents a method for herding a swarm of adversarial agents toward a safe area in a 2-D obstacle environment. The team of defending agents (defenders) aims to block the path of a swarm of risk-averse, adversarial agents (attackers) and guide it to a safe area while navigating in an obstacle-populated environment. To achieve this, a closed formation (StringNet) of defenders is formed around the adversarial swarm. A combination of open-loop, near time-optimal controllers (that result in forming the defenders’ formation), and state-feedback controllers with finite-time convergence guarantees under bounded inputs (that guide the formation around attackers and toward the safe area) synthesize the herding strategy. For demonstration purpose, we consider that the attacking swarm moves under a flocking model, which however is unknown to the defenders. Collision-free trajectory generation for the defenders, as well as their convergence to the desired formations, is proved formally, and simulations are provided to demonstrate the efficacy of the proposed approach. An implementation of the proposed approach on quadrotor vehicles simulated in the Gazebo simulator is also provided.
@article{DBLP:journals/trob/ChipadeP21, author = {Vishnu S. Chipade and Dimitra Panagou}, title = {Multiagent Planning and Control for Swarm Herding in 2-D Obstacle Environments Under Bounded Inputs}, journal = {{IEEE} Trans. Robotics}, volume = {37}, number = {6}, pages = {1956--1972}, year = {2021}, url = {https://doi.org/10.1109/TRO.2021.3072026}, doi = {10.1109/TRO.2021.3072026}, timestamp = {Wed, 15 Dec 2021 10:26:10 +0100}, biburl = {https://dblp.org/rec/journals/trob/ChipadeP21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Robust Control Barrier and Control Lyapunov Functions with Fixed-Time Convergence Guarantees.This paper studies control synthesis for a general class of nonlinear, control-affine dynamical systems under additive disturbances and state-estimation errors. We enforce forward invariance of static and dynamic safe sets and convergence to a given goal set within a user-defined time in the presence of input constraints. We use robust variants of control barrier functions (CBF) and fixed-time control Lyapunov functions (FxT-CLF) to incorporate a class of additive disturbances in the system dynamics, and state-estimation errors. To solve the underlying constrained control problem, we formulate a quadratic program and use the proposed robust CBF-FxT-CLF conditions to compute the control input. We showcase the efficacy of the proposed method on a numerical case study involving multiple underactuated marine vehicles.
@inproceedings{DBLP:conf/amcc/GargP21a, author = {Kunal Garg and Dimitra Panagou}, title = {Robust Control Barrier and Control Lyapunov Functions with Fixed-Time Convergence Guarantees}, booktitle = {2021 American Control Conference, {ACC} 2021, New Orleans, LA, USA, May 25-28, 2021}, pages = {2292--2297}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.23919/ACC50511.2021.9482751}, doi = {10.23919/ACC50511.2021.9482751}, timestamp = {Thu, 14 Oct 2021 10:23:01 +0200}, biburl = {https://dblp.org/rec/conf/amcc/GargP21a.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Robust Distributed Fixed-Time Economic Dispatch Under Time-Varying Topology.The centralized power generation infrastructure that defines the North American electric grid is slowly moving to the distributed architecture due to the explosion in use of renewable generation and distributed energy resources (DERs), such as residential solar, wind turbines and battery storage. Furthermore, variable pricing policies and profusion of flexible loads entail frequent and severe changes in power outputs required from the individual generation units, requiring fast availability of power allocation. To this end, a fixed-time convergent, fully distributed economic dispatch algorithm for scheduling optimal power generation among a set of DERs is proposed. The proposed algorithm incorporates both load balance and generation capacity constraints.
@article{DBLP:journals/csysl/BaranwalGPH21, author = {Mayank Baranwal and Kunal Garg and Dimitra Panagou and Alfred O. Hero III}, title = {Robust Distributed Fixed-Time Economic Dispatch Under Time-Varying Topology}, journal = {{IEEE} Control. Syst. Lett.}, volume = {5}, number = {4}, pages = {1183--1188}, year = {2021}, url = {https://doi.org/10.1109/LCSYS.2020.3020248}, doi = {10.1109/LCSYS.2020.3020248}, timestamp = {Thu, 16 Sep 2021 18:01:58 +0200}, biburl = {https://dblp.org/rec/journals/csysl/BaranwalGPH21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2020
- A Fixed-Time Convergent Distributed Algorithm for Strongly Convex Functions in a Time-Varying Network.This paper presents a novel distributed nonlinear protocol for minimizing the sum of convex objective functions in a fixed time under time-varying communication topology. In a distributed setting, each node in the network has access only to its private objective function, while exchange of local information, such as, state and gradient values, is permitted between the immediate neighbors. Earlier work in literature considers distributed optimization protocols that achieve convergence of the estimation error in a finite time for static communication topology, or under specific set of initial conditions. This study investigates first such protocol for achieving distributed optimization in a fixed time that is independent of the initial conditions, for time-varying communication topology. Numerical examples corroborate our theoretical analysis.
@inproceedings{DBLP:conf/cdc/GargBP20, author = {Kunal Garg and Mayank Baranwal and Dimitra Panagou}, title = {A Fixed-Time Convergent Distributed Algorithm for Strongly Convex Functions in a Time-Varying Network}, booktitle = {59th {IEEE} Conference on Decision and Control, {CDC} 2020, Jeju Island, South Korea, December 14-18, 2020}, pages = {4405--4410}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.1109/CDC42340.2020.9303778}, doi = {10.1109/CDC42340.2020.9303778}, timestamp = {Fri, 04 Mar 2022 13:31:02 +0100}, biburl = {https://dblp.org/rec/conf/cdc/GargBP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - A Quadratic Program based Control Synthesis under Spatiotemporal Constraints and Non-vanishing Disturbances.In this paper, we study the effect of non-vanishing disturbances on the stability of fixed-time stable (FxTS) systems. We present a new result on FxTS, which allows a positive term in the time derivative of the Lyapunov function with the aim to model bounded, non-vanishing disturbances in system dynamics. We characterize the neighborhood to which the system trajectories converge, as well as the convergence time. Then, we use the new FxTS result and formulate a quadratic program (QP) that yields control inputs which drive the trajectories of a class of nonlinear, control-affine systems to a goal set in the presence of control input constraints and nonvanishing, bounded disturbances in the system dynamics. We consider an overtaking problem on a highway as a case study, and discuss how to both set up the QP and decide when to start the overtake maneuver in the presence of sensing errors.
@inproceedings{DBLP:conf/cdc/BlackGP20, author = {Mitchell Black and Kunal Garg and Dimitra Panagou}, title = {A Quadratic Program based Control Synthesis under Spatiotemporal Constraints and Non-vanishing Disturbances}, booktitle = {59th {IEEE} Conference on Decision and Control, {CDC} 2020, Jeju Island, South Korea, December 14-18, 2020}, pages = {2726--2731}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.1109/CDC42340.2020.9304071}, doi = {10.1109/CDC42340.2020.9304071}, timestamp = {Fri, 04 Mar 2022 13:31:02 +0100}, biburl = {https://dblp.org/rec/conf/cdc/BlackGP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Decentralized Goal Assignment and Safe Trajectory Generation in Multirobot Networks via Multiple Lyapunov Functions.This article considers the problem of decentralized goal assignment and trajectory generation for multirobot networks when only local communication is available and proposes an approach based on methods related to switched systems and set invariance. A family of Lyapunov-like functions is employed to encode the (local) decision making among candidate goal assignments, under which a group of connected agents chooses the assignment that results in the shortest total distance to the goals. An additional family of Lyapunov-like barrier functions is activated in the case when the optimal assignment may lead to colliding trajectories, maintaining thus system safety while preserving the convergence guarantees. The proposed switching strategies give rise to feedback control policies that are computationally efficient and scalable with the number of agents and, therefore, suitable for applications, including first-response deployment of robotic networks under limited information sharing. The efficacy of the proposed method is demonstrated via simulation results and experiments with six ground robots.
@article{DBLP:journals/tac/PanagouTK20, author = {Dimitra Panagou and Matthew Turpin and Vijay Kumar}, title = {Decentralized Goal Assignment and Safe Trajectory Generation in Multirobot Networks via Multiple Lyapunov Functions}, journal = {{IEEE} Trans. Autom. Control.}, volume = {65}, number = {8}, pages = {3365--3380}, year = {2020}, url = {https://doi.org/10.1109/TAC.2019.2946333}, doi = {10.1109/TAC.2019.2946333}, timestamp = {Wed, 26 Aug 2020 11:05:09 +0200}, biburl = {https://dblp.org/rec/journals/tac/PanagouTK20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Determining r- and (r, s)-robustness of digraphs using mixed integer linear programming.
@article{DBLP:journals/automatica/UsevitchP20, author = {James Usevitch and Dimitra Panagou}, title = {Determining r- and (r, s)-robustness of digraphs using mixed integer linear programming}, journal = {Autom.}, volume = {111}, year = {2020}, url = {https://doi.org/10.1016/j.automatica.2019.108586}, doi = {10.1016/J.AUTOMATICA.2019.108586}, timestamp = {Thu, 20 Feb 2020 09:13:58 +0100}, biburl = {https://dblp.org/rec/journals/automatica/UsevitchP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - LIV-LAM: LiDAR and Visual Localization and Mapping.This paper presents a framework for Simultaneous Localization and Mapping (SLAM) by combining a novel method for object discovery and localization from a monocular camera with depth information provided by Light Detection and Ranging (LiDAR). One major challenge in vision is discovering unknown objects without prior training/supervision, in the wild, and on-the-fly. In our framework, no training samples are available prior to the deployment. We develop an efficient proposal-matching method to discover object temporal saliency, and then finetune these frequently matched object proposals according to tracking information. Detected features of the objects are used as landmark features, and are merged with the LiDAR data in the proposed LIV-LAM (LiDAR and Visual Localization and Mapping). Compared to most visual SLAM or LiDAR-based SLAM, the novelty of this method is the computationally-efficient object detection and localization for feature set-and-match, in order to increase the accuracy of the generated map. The results show that the presented method is superior in both accuracy and efficiency of the maps generated by LiDAR.
@inproceedings{DBLP:conf/amcc/RadmaneshWCTP20, author = {Reza Radmanesh and Ziyin Wang and Vishnu S. Chipade and Gavriil Tsechpenakis and Dimitra Panagou}, title = {{LIV-LAM:} LiDAR and Visual Localization and Mapping}, booktitle = {2020 American Control Conference, {ACC} 2020, Denver, CO, USA, July 1-3, 2020}, pages = {659--664}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.23919/ACC45564.2020.9148037}, doi = {10.23919/ACC45564.2020.9148037}, timestamp = {Thu, 14 Oct 2021 10:23:23 +0200}, biburl = {https://dblp.org/rec/conf/amcc/RadmaneshWCTP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Multi-Swarm Herding: Protecting against Adversarial Swarms.This paper studies a defense approach against one or more swarms of adversarial agents. In our earlier work, we employ a closed formation (‘StringNet’) of defending agents (defenders) around a swarm of adversarial agents (attackers) to confine their motion within given bounds, and guide them to a safe area. The control design relies on the assumption that the adversarial agents remain close enough to each other, i.e., within a prescribed connectivity region. To handle situations when the attackers no longer stay within such a connectivity region, but rather split into smaller swarms (clusters) to maximize the chance or impact of attack, this paper proposes an approach to learn the attacking sub-swarms and reassign defenders towards the attackers. We use a ‘Density-based Spatial Clustering of Application with Noise (DBSCAN)’ algorithm to identify the spatially distributed swarms of the attackers. Then, the defenders are assigned to each identified swarm of attackers by solving a constrained generalized assignment problem. Simulations are provided to demonstrate the effectiveness of the approach.
@inproceedings{DBLP:conf/cdc/ChipadeP20, author = {Vishnu S. Chipade and Dimitra Panagou}, title = {Multi-Swarm Herding: Protecting against Adversarial Swarms}, booktitle = {59th {IEEE} Conference on Decision and Control, {CDC} 2020, Jeju Island, South Korea, December 14-18, 2020}, pages = {5374--5379}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.1109/CDC42340.2020.9303837}, doi = {10.1109/CDC42340.2020.9303837}, timestamp = {Fri, 04 Mar 2022 13:31:02 +0100}, biburl = {https://dblp.org/rec/conf/cdc/ChipadeP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Prescribed-time Convergence with Input Constraints: A Control Lyapunov Function Based Approach.In this paper, we present a control framework for a general class of control-affine nonlinear systems under spatiotemporal and input constraints. Specifically, the proposed control architecture addresses the problem of reaching a given final set S in a prescribed (user-defined) time with bounded control inputs. To this end, a time transformation technique is utilized to transform the system subject to temporal constraints into an equivalent form without temporal constraints. The transformation is defined so that asymptotic convergence in the transformed time scale results into prescribed-time convergence in the original time scale. To incorporate input constraints, we characterize a set of initial conditions DM such that starting from this set, the closed-loop trajectories reach the set S within the prescribed time. We further show that starting from outside the set DM , the system trajectories reach the set DM in a finite time that depends upon the initial conditions and the control input bounds. We use a novel parameter μ in the controller, that controls the convergence-rate of the closed-loop trajectories and dictates the size of the set DM. Finally, we present a numerical example to showcase the efficacy of our proposed method.
@inproceedings{DBLP:conf/amcc/GargAP20, author = {Kunal Garg and Ehsan Arabi and Dimitra Panagou}, title = {Prescribed-time Convergence with Input Constraints: {A} Control Lyapunov Function Based Approach}, booktitle = {2020 American Control Conference, {ACC} 2020, Denver, CO, USA, July 1-3, 2020}, pages = {962--967}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.23919/ACC45564.2020.9147641}, doi = {10.23919/ACC45564.2020.9147641}, timestamp = {Sun, 08 Aug 2021 01:40:57 +0200}, biburl = {https://dblp.org/rec/conf/amcc/GargAP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Quadratic Programs for High Relative Degree Spatial Constraints and Spatiotemporal Specifications with Spacecraft Applications.This paper presents a new methodology for ensuring forward invariance of sublevel sets of high relative degree functions, and convergence of the state to these sets. We introduce the notion of the boundary layer of a set defined by multiple constraints, and develop polynomially-derived trajectory constraints as means to enforce set invariance by redirecting trajectories that enter this boundary layer. This strategy is then extended to achieve convergence to and invariance of goal sets that are specified using Signal Temporal Logic. A quadratic program computes control inputs online that yield trajectories that achieve high level objectives specified by these sets, such as obstacle avoidance and target observation. We present a case study utilizing this controller for a spacecraft position and attitude control problem requiring observation of targets on the surface of a small body.
@inproceedings{DBLP:conf/cdc/BreedenP20, author = {Joseph Breeden and Dimitra Panagou}, title = {Quadratic Programs for High Relative Degree Spatial Constraints and Spatiotemporal Specifications with Spacecraft Applications}, booktitle = {59th {IEEE} Conference on Decision and Control, {CDC} 2020, Jeju Island, South Korea, December 14-18, 2020}, pages = {1496--1502}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.1109/CDC42340.2020.9304162}, doi = {10.1109/CDC42340.2020.9304162}, timestamp = {Fri, 04 Mar 2022 13:31:02 +0100}, biburl = {https://dblp.org/rec/conf/cdc/BreedenP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Resilient Finite-Time Consensus: A Discontinuous Systems Perspective.Many algorithms have been proposed in prior literature to guarantee resilient multi-agent consensus in the presence of adversarial attacks or faults. The majority of prior work present excellent results that focus on discrete-time or discretized continuous-time systems. Fewer authors have explored applying similar resilient techniques to continuous-time systems without discretization. These prior works typically consider asymptotic convergence and make assumptions such as continuity of adversarial signals, the existence of a dwell time between switching instances for the system dynamics, or the existence of trusted agents that do not misbehave. In this paper, we expand the study of resilient continuous-time systems by removing many of these assumptions and using discontinuous systems theory to provide conditions for normally-behaving agents with nonlinear dynamics to achieve consensus in finite time despite the presence of adversarial agents.
@inproceedings{DBLP:conf/amcc/UsevitchP20, author = {James Usevitch and Dimitra Panagou}, title = {Resilient Finite-Time Consensus: {A} Discontinuous Systems Perspective}, booktitle = {2020 American Control Conference, {ACC} 2020, Denver, CO, USA, July 1-3, 2020}, pages = {3285--3290}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.23919/ACC45564.2020.9147904}, doi = {10.23919/ACC45564.2020.9147904}, timestamp = {Sun, 08 Aug 2021 01:40:57 +0200}, biburl = {https://dblp.org/rec/conf/amcc/UsevitchP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Resilient Leader-Follower Consensus to Arbitrary Reference Values in Time-Varying Graphs.Several algorithms in prior literature have been proposed, which guarantee the consensus of normally behaving agents in a network that may contain adversarially behaving agents. These algorithms guarantee that the consensus value lies within the convex hull of initial normal agents’ states, with the exact consensus value possibly being unknown. In leader-follower consensus problems, however, the objective is for normally behaving agents to track a reference state that may take on values outside of this convex hull. In this paper, we present methods for agents in time-varying graphs with discrete-time dynamics to resiliently track a reference state propagated by a set of leaders, despite a bounded subset of the leaders and followers behaving adversarially. Our results are demonstrated through simulations.
@article{DBLP:journals/tac/UsevitchP20, author = {James Usevitch and Dimitra Panagou}, title = {Resilient Leader-Follower Consensus to Arbitrary Reference Values in Time-Varying Graphs}, journal = {{IEEE} Trans. Autom. Control.}, volume = {65}, number = {4}, pages = {1755--1762}, year = {2020}, url = {https://doi.org/10.1109/TAC.2019.2934954}, doi = {10.1109/TAC.2019.2934954}, timestamp = {Tue, 30 Jun 2020 11:42:39 +0200}, biburl = {https://dblp.org/rec/journals/tac/UsevitchP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Safety-Critical Adaptive Control with Nonlinear Reference Model Systems.In this paper, a model reference adaptive control architecture is proposed for uncertain nonlinear systems to achieve prescribed performance guarantees. Specifically, a general nonlinear reference model system is considered that captures an ideal and safe system behavior. An adaptive control architecture is then proposed to suppress the effects of system uncertainties without any prior knowledge of their magnitude and rate upper bounds. More importantly, the proposed control architecture enforces the system state trajectories to evolve within a user-specified prescribed distance from the reference system trajectories, satisfying the safety constraints. This eliminates the ad-hoc tuning process for the adaptation rate that is conventionally required in model reference adaptive control to ensure safety. The efficacy of the proposed control architecture is also demonstrated through an illustrative numerical example.
@inproceedings{DBLP:conf/amcc/ArabiGP20, author = {Ehsan Arabi and Kunal Garg and Dimitra Panagou}, title = {Safety-Critical Adaptive Control with Nonlinear Reference Model Systems}, booktitle = {2020 American Control Conference, {ACC} 2020, Denver, CO, USA, July 1-3, 2020}, pages = {1749--1754}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.23919/ACC45564.2020.9147999}, doi = {10.23919/ACC45564.2020.9147999}, timestamp = {Sun, 08 Aug 2021 01:40:57 +0200}, biburl = {https://dblp.org/rec/conf/amcc/ArabiGP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Strong Invariance Using Control Barrier Functions: A Clarke Tangent Cone Approach.Many control applications require that a system be constrained to a particular set of states, often termed as safe set. A practical and flexible method for rendering safe sets forward-invariant involves computing control input using Control Barrier Functions and Quadratic Programming methods. Many prior results however require the resulting control input to be continuous, which requires strong assumptions or can be difficult to demonstrate theoretically. In this paper we use differential inclusion methods to show that simultaneously rendering multiple sets invariant can be accomplished using a discontinuous control input. We present an optimization formulation which computes such control inputs and which can be posed in multiple forms, including a feasibility problem, a linear program, or a quadratic program. In addition, we discuss conditions under which the optimization problem is feasible and show that any feasible solution of the considered optimization problem which is measurable renders the multiple safe sets forward invariant.
@inproceedings{DBLP:conf/cdc/UsevitchGP20, author = {James Usevitch and Kunal Garg and Dimitra Panagou}, title = {Strong Invariance Using Control Barrier Functions: {A} Clarke Tangent Cone Approach}, booktitle = {59th {IEEE} Conference on Decision and Control, {CDC} 2020, Jeju Island, South Korea, December 14-18, 2020}, pages = {2044--2049}, publisher = {{IEEE}}, year = {2020}, url = {https://doi.org/10.1109/CDC42340.2020.9303873}, doi = {10.1109/CDC42340.2020.9303873}, timestamp = {Fri, 04 Mar 2022 13:31:02 +0100}, biburl = {https://dblp.org/rec/conf/cdc/UsevitchGP20.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2019
- A hybrid approach to persistent coverage in stochastic environments.
@article{DBLP:journals/automatica/BentzP19, author = {William Bentz and Dimitra Panagou}, title = {A hybrid approach to persistent coverage in stochastic environments}, journal = {Autom.}, volume = {109}, year = {2019}, url = {https://doi.org/10.1016/j.automatica.2019.108554}, doi = {10.1016/J.AUTOMATICA.2019.108554}, timestamp = {Thu, 20 Feb 2020 09:15:52 +0100}, biburl = {https://dblp.org/rec/journals/automatica/BentzP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - A predictive vector-field based lane-changing controller.This paper presents a predictive vector-field based controller for the motion of an ego-vehicle through highway traffic. The design is composed of a vector field controller in closed form, whose control gains are optimized online. Upon certain assumptions on the traffic conditions, safe solutions can be derived. Simulation results illustrate the efficacy of the proposed algorithm compared to a standard NMPC approach.
@inproceedings{DBLP:conf/cdc/HuangP19, author = {Lixing Huang and Dimitra Panagou}, title = {A predictive vector-field based lane-changing controller}, booktitle = {58th {IEEE} Conference on Decision and Control, {CDC} 2019, Nice, France, December 11-13, 2019}, pages = {5748--5753}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.1109/CDC40024.2019.9029640}, doi = {10.1109/CDC40024.2019.9029640}, timestamp = {Fri, 04 Mar 2022 13:30:46 +0100}, biburl = {https://dblp.org/rec/conf/cdc/HuangP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Control-Lyapunov and Control-Barrier Functions based Quadratic Program for Spatio-temporal Specifications.This paper presents a method for control synthesis under spatio-temporal constraints. First, we consider the problem of reaching a set S in a user-defined or prescribed time T. We define a new class of control Lyapunov functions, called prescribed-time control Lyapunov functions (PT CLF), and present sufficient conditions on the existence of a controller for this problem in terms of PT CLF. Then, we formulate a quadratic program (QP) to compute a control input that satisfies these sufficient conditions. Next, we consider control synthesis under spatio-temporal objectives given as: the closed- loop trajectories remain in a given set Ss at all times; and, remain in a specific set Si during the time interval [ti,ti+1) for i = 0,1,⋯, N; and, reach the set Si+1 on or before t = ti+1. We show that such spatio-temporal specifications can be translated into temporal logic formulas. We present sufficient conditions on the existence of a control input in terms of PT CLF and control barrier functions. Then, we present a QP to compute the control input efficiently, and show its feasibility under the assumptions of existence of a PT CLF. To the best of authors’ knowledge, this is the first paper proposing a QP based method for the aforementioned problem of satisfying spatiotemporal specifications for nonlinear control-affine dynamics with input constraints. We also discuss the limitations of the proposed methods and directions of future work to overcome these limitations. We present numerical examples to corroborate our proposed methods.
@inproceedings{DBLP:conf/cdc/GargP19, author = {Kunal Garg and Dimitra Panagou}, title = {Control-Lyapunov and Control-Barrier Functions based Quadratic Program for Spatio-temporal Specifications}, booktitle = {58th {IEEE} Conference on Decision and Control, {CDC} 2019, Nice, France, December 11-13, 2019}, pages = {1422--1429}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.1109/CDC40024.2019.9029666}, doi = {10.1109/CDC40024.2019.9029666}, timestamp = {Fri, 04 Mar 2022 13:30:46 +0100}, biburl = {https://dblp.org/rec/conf/cdc/GargP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Determining r-Robustness of Digraphs Using Mixed Integer Linear Programming.Convergence guarantees of many resilient consensus algorithms are based on the graph theoretic properties of rand (r, s)-robustness. These algorithms guarantee consensus of normally behaving agents in the presence of a bounded number of arbitrarily misbehaving agents if the values of the integers $r$ and $s$ are sufficiently high. However, determining the largest integer $r$ for which an arbitrary digraph is r-robust is highly nontrivial. This paper introduces a novel method for calculating this value using mixed integer linear programming. The method only requires knowledge of the graph Laplacian matrix, and can be formulated with affine objective and constraints, except for the integer constraint. Integer programming methods such as branch-and-bound can allow both lower and upper bounds on $r$ to be iteratively tightened. Simulations suggest the proposed method demonstrates greater efficiency than prior algorithms.
@inproceedings{DBLP:conf/amcc/UsevitchP19, author = {James Usevitch and Dimitra Panagou}, title = {Determining r-Robustness of Digraphs Using Mixed Integer Linear Programming}, booktitle = {2019 American Control Conference, {ACC} 2019, Philadelphia, PA, USA, July 10-12, 2019}, pages = {2257--2263}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.23919/ACC.2019.8814405}, doi = {10.23919/ACC.2019.8814405}, timestamp = {Sun, 08 Aug 2021 01:40:57 +0200}, biburl = {https://dblp.org/rec/conf/amcc/UsevitchP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Herding an Adversarial Attacker to a Safe Area for Defending Safety-Critical Infrastructure.This paper investigates a problem of defending safety-critical infrastructure from an adversarial aerial attacker in an urban environment. A circular arc formation of defenders is formed around the attacker, and vector-field based guidance laws herd the attacker to a predefined safe area in the presence of rectangular obstacles. The defenders' formation is defined based on a novel vector field that imposes super-elliptic contours around the obstacles, to closely resemble their rectangular shape. A novel finite-time stabilizing controller is proposed to guide the defenders to their desired formation, while avoiding obstacles and inter-agent collisions. The efficacy of the approach is demonstrated via simulation results.
@inproceedings{DBLP:conf/amcc/ChipadeP19, author = {Vishnu S. Chipade and Dimitra Panagou}, title = {Herding an Adversarial Attacker to a Safe Area for Defending Safety-Critical Infrastructure}, booktitle = {2019 American Control Conference, {ACC} 2019, Philadelphia, PA, USA, July 10-12, 2019}, pages = {1035--1041}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.23919/ACC.2019.8814380}, doi = {10.23919/ACC.2019.8814380}, timestamp = {Thu, 14 Oct 2021 10:23:10 +0200}, biburl = {https://dblp.org/rec/conf/amcc/ChipadeP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Herding an Adversarial Swarm in an Obstacle Environment.This paper studies a defense approach against a swarm of adversarial agents. We employ a closed formation (‘StringNet’) of defending agents around the adversarial agents to restrict their motion and guide them to a safe area while navigating in an obstacle-populated environment. Control laws for forming the StringNet and guiding it to a safe area are developed, and the stability of the closed-loop system is analyzed formally. The adversarial swarm is assumed to move as a flock in the presence of rectangular obstacles. Simulation results are provided to demonstrate the efficacy of the approach.
@inproceedings{DBLP:conf/cdc/ChipadeP19, author = {Vishnu S. Chipade and Dimitra Panagou}, title = {Herding an Adversarial Swarm in an Obstacle Environment}, booktitle = {58th {IEEE} Conference on Decision and Control, {CDC} 2019, Nice, France, December 11-13, 2019}, pages = {3685--3690}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.1109/CDC40024.2019.9029573}, doi = {10.1109/CDC40024.2019.9029573}, timestamp = {Fri, 04 Mar 2022 13:30:46 +0100}, biburl = {https://dblp.org/rec/conf/cdc/ChipadeP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Intention-Aware Supervisory Control with Driving Safety Applications.This paper proposes a guardian architecture, consisting of an estimation and a supervisor module providing a set of inputs that guarantees safety, in driving scenarios. The main idea is to offline compute a library of robust controlled invariant sets (RCIS), for each possible driver intention model of the other vehicles, together with an intention-agnostic albeit conservative RCIS. At runtime, when the intention estimation module determines which driver model the other vehicles are following, the appropriate RCIS is chosen to provide the safe and less conservative input set for supervision. We show that the composition of the intention estimation module with the proposed intention-aware supervisor module is safe. Moreover, we show how to compute intention-agnostic and intention-specific RCIS by growing an analytically found simple invariant safe set. The results are demonstrated on a case study on how to safely interact with a human-driven car on a highway scenario, using data collected from a driving simulator.
@inproceedings{DBLP:conf/ccta/SahinLRPYO19, author = {Yunus Emre Sahin and Zexiang Liu and Kwesi J. Rutledge and Dimitra Panagou and Sze Zheng Yong and Necmiye Ozay}, title = {Intention-Aware Supervisory Control with Driving Safety Applications}, booktitle = {2019 {IEEE} Conference on Control Technology and Applications, {CCTA} 2019, Hong Kong, SAR, China, August 19-21, 2019}, pages = {1--8}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.1109/CCTA.2019.8920426}, doi = {10.1109/CCTA.2019.8920426}, timestamp = {Wed, 07 Dec 2022 23:10:43 +0100}, biburl = {https://dblp.org/rec/conf/ccta/SahinLRPYO19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Multi-agent adaptive estimation with consensus in reproducing kernel Hilbert spaces.This paper presents a framework for online adaptive estimation of unknown or uncertain systems of nonlinear ordinary differential equation (ODEs) that characterize a multiagent sensor network. This paper extends recent results in [2], [36] and here the nonlinear ODEs are embedded in the real, vector-valued reproducing kernel Hilbert space (RKHS) $\mathbb{H}:=H^{N}$ with $H$ a real, scalar RKHS. Each agent casts its local representation of the unknown function $f$ as a member of the RKHS H. The result defines a distributed parameter system that governs the state estimates and estimates of the unknown function. The convergence of state estimates is proven along similar lines to that encountered in conventional adaptive estimation for systems of unknown nonlinear ODEs. The analysis of the parameter estimates, which is studied by an evolution in Euclidean space in conventional methods, now concerns the convergence of error functions in the RKHS. We show that the convergence of the function estimates to the unknown function in the RKHS is guaranteed provided a newly introduced persistency of excitation (PE) condition holds. This PE condition is defined on functions defined over a subset $\Omega$ that contains the trajectory of the true dynamic system. It can be viewed as an extension of the notion of partial persistence of excitation to the RKHS embedding framework.
@inproceedings{DBLP:conf/eucc/BobadePK19, author = {Parag Bobade and Dimitra Panagou and Andrew J. Kurdila}, title = {Multi-agent adaptive estimation with consensus in reproducing kernel Hilbert spaces}, booktitle = {17th European Control Conference, {ECC} 2019, Naples, Italy, June 25-28, 2019}, pages = {572--577}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.23919/ECC.2019.8796214}, doi = {10.23919/ECC.2019.8796214}, timestamp = {Sun, 02 Oct 2022 16:00:47 +0200}, biburl = {https://dblp.org/rec/conf/eucc/BobadePK19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Resilient Leader-Follower Consensus with Time-Varying Leaders in Discrete-Time Systems.The problem of consensus in the presence of adversarially behaving agents has been studied extensively in the literature. The proposed algorithms typically guarantee that the consensus value lies within the convex hull of the initial states of the normally-behaving agents. In leader-follower consensus problems however, the objective for normally behaving agents is to track a time-varying reference state that may take on values outside of this convex hull. In this paper we present a method for agents with discrete-time dynamics to resiliently track a set of leaders’ common time-varying reference state despite a bounded subset of the leaders and followers behaving adversarially. The efficacy of our results are demonstrated through simulations.
@inproceedings{DBLP:conf/cdc/UsevitchP19, author = {James Usevitch and Dimitra Panagou}, title = {Resilient Leader-Follower Consensus with Time-Varying Leaders in Discrete-Time Systems}, booktitle = {58th {IEEE} Conference on Decision and Control, {CDC} 2019, Nice, France, December 11-13, 2019}, pages = {5432--5437}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.1109/CDC40024.2019.9030246}, doi = {10.1109/CDC40024.2019.9030246}, timestamp = {Fri, 04 Mar 2022 13:30:46 +0100}, biburl = {https://dblp.org/rec/conf/cdc/UsevitchP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Robust Multitask Formation Control via Parametric Lyapunov-Like Barrier Functions.An essential problem in the coordination of multiple agents is formation control. Significant challenges to the theoretical design may arise when the multiagent system is subject to uncertainty. This paper considers the robust multitask formation control problem for multiple agents, whose communication and measurements are disturbed by uncertain parameters. The control objectives include achieving the desired configuration, avoiding collisions, and preserving the connectivity of the uncertain topology. To achieve these objectives, we first provide conditions in terms of linear matrix inequalities for checking the connectivity of uncertain topologies. Then, we propose a new type of Lyapunov-like barrier function, called parametric Lyapunov-like barrier function, that is applicable to multiagent systems with uncertainties in communication and measurements. It is shown that this new type of Lyapunov-like barrier function guarantees the robust multitask formation and displays advantages over parameter-independent Lyapunov-like barrier functions. The efficacy of the proposed method is demonstrated via simulation results.
@article{DBLP:journals/tac/HanP19, author = {Dongkun Han and Dimitra Panagou}, title = {Robust Multitask Formation Control via Parametric Lyapunov-Like Barrier Functions}, journal = {{IEEE} Trans. Autom. Control.}, volume = {64}, number = {11}, pages = {4439--4453}, year = {2019}, url = {https://doi.org/10.1109/TAC.2019.2894587}, doi = {10.1109/TAC.2019.2894587}, timestamp = {Wed, 20 May 2020 21:28:39 +0200}, biburl = {https://dblp.org/rec/journals/tac/HanP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Safe Autonomous Overtaking with Intention Estimation.This paper investigates the problem of overtaking a lead car by an autonomous ego car on a two-lane road in the presence of an oncoming car. We propose an intention-aware overtaking controller for the ego car. The intention of the lead car is estimated via a combination of active model discrimination and model selection algorithms. Then, a safe overtaking controller is designed based on vector fields that take into account the estimated intent, and ensure safety of the overtaking maneuver. Simulation results demonstrate the efficacy of the proposed approach.
@inproceedings{DBLP:conf/eucc/ChipadeSHOYP19, author = {Vishnu S. Chipade and Qiang Shen and Lixing Huang and Necmiye Ozay and Sze Zheng Yong and Dimitra Panagou}, title = {Safe Autonomous Overtaking with Intention Estimation}, booktitle = {17th European Control Conference, {ECC} 2019, Naples, Italy, June 25-28, 2019}, pages = {2050--2057}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.23919/ECC.2019.8795715}, doi = {10.23919/ECC.2019.8795715}, timestamp = {Wed, 07 Dec 2022 23:07:12 +0100}, biburl = {https://dblp.org/rec/conf/eucc/ChipadeSHOYP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Safe Multiquadcopter System Continuum Deformation Over Moving Frames.This paper proposes a new scalable model for coordination of multiple quadcopter systems by treating collective motion as continuum deformation over a moving frame. The quadcopters are considered as particles in a 2-D deformable body evolving in a 3-D motion space. The 2-D continuum reference frame (CRF) can arbitrarily translate and rotate in a 3-D motion space for maneuverability. Furthermore, a quadcopter team can significantly deform over the CRF presenting risk of interagent collisions. The formulation is therefore proven in this paper to guarantee interagent collision avoidance and quadcopter containment. Quadcopter team deformation is guided by $N_L\geq 3$ leader quadcopters initially placed at the vertices of a convex polygon denoted as a leading convex polygon. The CRF is then assigned based on independent leader quadcopters’ 3-D positions defined by a homogeneous deformation, which, in turn, dictates follower motions. A local communication protocol is defined for the followers to acquire the desired continuum deformation. By formal characterization of the leading convex polygon deformation, both interagent collision avoidance and quadcopter containment are guaranteed in a large-scale continuum deformation coordination. A quadcopter team with 40 agents is simulated to illustrate a large-scale collective descent defined by continuum deformation coordination over a reference frame moving in the longitudinal plane.
@article{DBLP:journals/tcns/RastgoftarAP19, author = {Hossein Rastgoftar and Ella M. Atkins and Dimitra Panagou}, title = {Safe Multiquadcopter System Continuum Deformation Over Moving Frames}, journal = {{IEEE} Trans. Control. Netw. Syst.}, volume = {6}, number = {2}, pages = {737--749}, year = {2019}, url = {https://doi.org/10.1109/TCNS.2018.2873204}, doi = {10.1109/TCNS.2018.2873204}, timestamp = {Thu, 09 Apr 2020 17:10:56 +0200}, biburl = {https://dblp.org/rec/journals/tcns/RastgoftarAP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Unsupervised Learning of Assistive Camera Views by an Aerial Co-robot in Augmented Reality Multitasking Environments.This paper presents a novel method by which an assistive aerial robot can learn the relevant camera views within a task domain through tracking the head motions of a human collaborator. The human’s visual field is modeled as an anisotropic spherical sensor, which decays in acuity towards the periphery, and is integrated in time throughout the domain. This data is resampled and fed into an expectation maximization solver in order to estimate the environment’s visual interest as a mixture of Gaussians. A dynamic coverage control law directs the robot to capture camera views of the peaks of these Gaussians which is broadcast to an augmented reality display worn by the human operator. An experimental study is presented that assesses the influence of the assitive robot on reflex time, head motion, and task completion time.
@inproceedings{DBLP:conf/icra/BentzDP19, author = {William Bentz and Sahib Dhanjal and Dimitra Panagou}, title = {Unsupervised Learning of Assistive Camera Views by an Aerial Co-robot in Augmented Reality Multitasking Environments}, booktitle = {International Conference on Robotics and Automation, {ICRA} 2019, Montreal, QC, Canada, May 20-24, 2019}, pages = {3003--3009}, publisher = {{IEEE}}, year = {2019}, url = {https://doi.org/10.1109/ICRA.2019.8793587}, doi = {10.1109/ICRA.2019.8793587}, timestamp = {Wed, 16 Oct 2019 14:14:51 +0200}, biburl = {https://dblp.org/rec/conf/icra/BentzDP19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2018
- 3-D Decentralized Prioritized Motion Planning and Coordination for High-Density Operations of Micro Aerial Vehicles.This paper presents a decentralized motion planning method for multiple aerial vehicles moving among 3-D polygonal obstacles resembling an urbanlike environment. The algorithm combines a prioritized $A^\star$ algorithm for high-level planning, along with a coordination method based on barrier functions for low-level trajectory generation and vehicle control. To this end, we extend the barrier functions method developed in our earlier work so that it treats 2-D and 3-D polygonal obstacles, and generates collision-free trajectories for the multiagent system. We furthermore augment the low-level trajectory generation and control with a prioritized $A^\star$ path planning algorithm, in order to compute waypoints and paths that force the agents of lower priority to avoid the paths of the agents of higher priority, reducing thus congestion. This feature enhances further the performance of the barrier-based coordination, and results in shorter paths and time to the goal destinations. We finally extend the proposed control design to the agents of constrained double-integrator dynamics, compared with the single-integrator case in our earlier work. We assume that the obstacles are known to the agents, and that each agent knows the state of other agents lying in its sensing area. Simulation results in 2-D and 3-D polygonal environments, as well as experimental results with micro aerial vehicles (quadrotors) in an indoor lab environment demonstrate the efficacy of the proposed approach.
@article{DBLP:journals/tcst/MaJWP18, author = {Xiaobai Ma and Ziyuan Jiao and Zhenkai Wang and Dimitra Panagou}, title = {3-D Decentralized Prioritized Motion Planning and Coordination for High-Density Operations of Micro Aerial Vehicles}, journal = {{IEEE} Trans. Control. Syst. Technol.}, volume = {26}, number = {3}, pages = {939--953}, year = {2018}, url = {https://doi.org/10.1109/TCST.2017.2699165}, doi = {10.1109/TCST.2017.2699165}, timestamp = {Mon, 08 Jun 2020 22:20:35 +0200}, biburl = {https://dblp.org/rec/journals/tcst/MaJWP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Approximating the Region of Multi-Task Coordination via the Optimal Lyapunov-Like Barrier Function.We consider the multi-task coordination problem for multi-agent systems under the following objectives: 1. collision avoidance; 2. connectivity maintenance; 3. convergence to desired destinations. The paper focuses on the safety guaranteed region of multi-task coordination (SG-RMTC), i.e., the set of initial states from which all trajectories converge to the desired configuration, while at the same time achieve the multi-task coordination and avoid unsafe sets. In contrast to estimating the domain of attraction via Lyapunov functions, the main underlying idea is to employ the sublevel sets of Lyapunov-like barrier functions to approximate the SG-RMTC. Rather than using fixed Lyapunov-like barrier functions, a systematic way is proposed to search an optimal Lyapunov-like barrier function such that the under-estimate of SG-RMTC is maximized. Numerical examples illustrate the effectiveness of the proposed method.
@inproceedings{DBLP:conf/amcc/HanHP18, author = {Dongkun Han and Lixing Huang and Dimitra Panagou}, title = {Approximating the Region of Multi-Task Coordination via the Optimal Lyapunov-Like Barrier Function}, booktitle = {2018 Annual American Control Conference, {ACC} 2018, Milwaukee, WI, USA, June 27-29, 2018}, pages = {5070--5075}, publisher = {{IEEE}}, year = {2018}, url = {https://doi.org/10.23919/ACC.2018.8431021}, doi = {10.23919/ACC.2018.8431021}, timestamp = {Sun, 08 Aug 2021 01:40:57 +0200}, biburl = {https://dblp.org/rec/conf/amcc/HanHP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Bayesian-inferred Flexible Path Generation in Human-Robot Collaborative Networks.This paper presents a novel method for generating the trajectory of a robot assisting a human in servicing a set of tasks embedded in a convex 2-D domain. This method makes use of Bayesian inference to predict human intent in task selection. Rather than following optimal trajectory towards a single task, the robot computes a set of potentially optimal tasks each weighted by the human's posterior probability and superimposes them into a cost function that is designed to minimize the weighted Euclidean distance relative to set. The effect is a flexible path human-robot collaborative network that is shown in simulation to complete all tasks in a given domain in less time than existing methods for a certain class of highly impulsive humans, i.e., humans that tend to randomly switch tasks at times generated by a Poisson counting process. The algorithm is also illustrated through an experimental demonstration.
@inproceedings{DBLP:conf/iros/BentzP18, author = {William Bentz and Dimitra Panagou}, title = {Bayesian-inferred Flexible Path Generation in Human-Robot Collaborative Networks}, booktitle = {2018 {IEEE/RSJ} International Conference on Intelligent Robots and Systems, {IROS} 2018, Madrid, Spain, October 1-5, 2018}, pages = {1816--1822}, publisher = {{IEEE}}, year = {2018}, url = {https://doi.org/10.1109/IROS.2018.8593611}, doi = {10.1109/IROS.2018.8593611}, timestamp = {Wed, 16 Oct 2019 14:14:51 +0200}, biburl = {https://dblp.org/rec/conf/iros/BentzP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Complete 3-D dynamic coverage in energy-constrained multi-UAV sensor networks.
@article{DBLP:journals/arobots/BentzHBP18, author = {William Bentz and Tru Hoang and Enkhmurun Bayasgalan and Dimitra Panagou}, title = {Complete 3-D dynamic coverage in energy-constrained multi-UAV sensor networks}, journal = {Auton. Robots}, volume = {42}, number = {4}, pages = {825--851}, year = {2018}, url = {https://doi.org/10.1007/s10514-017-9661-x}, doi = {10.1007/S10514-017-9661-X}, timestamp = {Sat, 17 Mar 2018 15:02:27 +0100}, biburl = {https://dblp.org/rec/journals/arobots/BentzHBP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Energy-aware Persistent Coverage and Intruder Interception in 3D Dynamic Environments.This paper considers the persistent coverage of a 2-D manifold that has been embedded in 3-D space. The manifold is subject to continual collisions by intruders that are generated with random trajectories. The trajectories of intruders are estimated online with an extended Kalman filter and their predicted impact points contribute normally distributed decay terms to the coverage map. A formal hybrid control strategy is presented that allows for power-constrained 3-D free-flyer agents to persistently monitor the domain, track and intercept intruders, and periodically deploy from and return to a single charging station on the manifold. Guarantees on intruder interception with respect to agent power lifespans are formally proven. The efficacy of the algorithm is demonstrated through simulation.
@inproceedings{DBLP:conf/amcc/BentzP18, author = {William Bentz and Dimitra Panagou}, title = {Energy-aware Persistent Coverage and Intruder Interception in 3D Dynamic Environments}, booktitle = {2018 Annual American Control Conference, {ACC} 2018, Milwaukee, WI, USA, June 27-29, 2018}, pages = {4426--4433}, publisher = {{IEEE}}, year = {2018}, url = {https://doi.org/10.23919/ACC.2018.8431191}, doi = {10.23919/ACC.2018.8431191}, timestamp = {Sun, 08 Aug 2021 01:40:57 +0200}, biburl = {https://dblp.org/rec/conf/amcc/BentzP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Finite-Time Resilient Formation Control with Bounded Inputs.In this paper we consider the problem of a multiagent system achieving a formation in the presence of misbehaving or adversarial agents. We introduce a novel continuous time resilient controller to guarantee that normally behaving agents can converge to a formation with respect to a set of leaders. The controller employs a norm-based filtering mechanism, and unlike most prior algorithms, also incorporates input bounds. In addition, the controller is shown to guarantee convergence in finite time. A sufficient condition for the controller to guarantee convergence is shown to be a graph theoretical structure which we denote as Resilient Directed Acyclic Graph (RDAG). Further, we employ our filtering mechanism on a discrete time system which is shown to have exponential convergence. Our results are demonstrated through simulations.
@inproceedings{DBLP:conf/cdc/UsevitchGP18, author = {James Usevitch and Kunal Garg and Dimitra Panagou}, title = {Finite-Time Resilient Formation Control with Bounded Inputs}, booktitle = {57th {IEEE} Conference on Decision and Control, {CDC} 2018, Miami, FL, USA, December 17-19, 2018}, pages = {2567--2574}, publisher = {{IEEE}}, year = {2018}, url = {https://doi.org/10.1109/CDC.2018.8619697}, doi = {10.1109/CDC.2018.8619697}, timestamp = {Fri, 04 Mar 2022 13:30:11 +0100}, biburl = {https://dblp.org/rec/conf/cdc/UsevitchGP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Hierarchical Design of Highway Merging Controller Using Navigation Vector Fields Under Bounded Sensing Uncertainty.
@inproceedings{DBLP:conf/dars/HuangP18, author = {Lixing Huang and Dimitra Panagou}, editor = {Nikolaus Correll and Mac Schwager and Michael W. Otte}, title = {Hierarchical Design of Highway Merging Controller Using Navigation Vector Fields Under Bounded Sensing Uncertainty}, booktitle = {Distributed Autonomous Robotic Systems, The 14th International Symposium, {DARS} 2018, Boulder, CO, USA, October 15-17, 2018}, series = {Springer Proceedings in Advanced Robotics}, volume = {9}, pages = {341--356}, publisher = {Springer}, year = {2018}, url = {https://doi.org/10.1007/978-3-030-05816-6\_24}, doi = {10.1007/978-3-030-05816-6\_24}, timestamp = {Tue, 05 Mar 2019 11:11:05 +0100}, biburl = {https://dblp.org/rec/conf/dars/HuangP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - New Results on Finite-Time Stability: Geometric Conditions and Finite-Time Controllers.This paper presents novel controllers that yield finite-time stability for linear systems. We first present a necessary and sufficient condition for the origin of a scalar system to be finite-time stable. Then we present novel finite-time controllers based on vector fields and barrier functions to demonstrate the utility of this geometric condition. We also consider the general class of linear controllable systems, and present a continuous feedback control law to stabilize the system in finite time. Finally, we present simulation results for each of these cases, showing the efficacy of the designed control laws.
@inproceedings{DBLP:conf/amcc/GargP18, author = {Kunal Garg and Dimitra Panagou}, title = {New Results on Finite-Time Stability: Geometric Conditions and Finite-Time Controllers}, booktitle = {2018 Annual American Control Conference, {ACC} 2018, Milwaukee, WI, USA, June 27-29, 2018}, pages = {442--447}, publisher = {{IEEE}}, year = {2018}, url = {https://doi.org/10.23919/ACC.2018.8431699}, doi = {10.23919/ACC.2018.8431699}, timestamp = {Sun, 08 Aug 2021 01:40:57 +0200}, biburl = {https://dblp.org/rec/conf/amcc/GargP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Resilient Leader-Follower Consensus to Arbitrary Reference Values.The problem of consensus in the presence of misbehaving agents has increasingly attracted attention in the literature. Prior results have established algorithms and graph structures for multi-agent networks which guarantee the consensus of normally behaving agents in the presence of a bounded number of misbehaving agents. The final consensus value is guaranteed to fall within the convex hull of initial agent states. However, the problem of consensus tracking considers consensus to arbitrary reference values which may not lie within such bounds. Conditions for consensus tracking in the presence of misbehaving agents has not been fully studied. This paper presents conditions for a network of agents using the W-MSR algorithm to achieve this objective.
@inproceedings{DBLP:conf/amcc/UsevitchP18, author = {James Usevitch and Dimitra Panagou}, title = {Resilient Leader-Follower Consensus to Arbitrary Reference Values}, booktitle = {2018 Annual American Control Conference, {ACC} 2018, Milwaukee, WI, USA, June 27-29, 2018}, pages = {1292--1298}, publisher = {{IEEE}}, year = {2018}, url = {https://doi.org/10.23919/ACC.2018.8431573}, doi = {10.23919/ACC.2018.8431573}, timestamp = {Sun, 08 Aug 2021 01:40:57 +0200}, biburl = {https://dblp.org/rec/conf/amcc/UsevitchP18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2017
- A Distributed Feedback Motion Planning Protocol for Multiple Unicycle Agents of Different Classes.This paper presents a novel feedback method for the motion planning and coordination of multiple agents that belong to two classes, namely class-A and class-B. All agents are modeled via unicycle kinematics. Agents of class-B do not share information with agents of class-A and do not participate in ensuring safety, modeling thus agents with failed sensing/communication systems, agents of higher priority, or moving obstacles with known upper bounded velocity. The method is built upon a family of 2-D analytic vector fields, which under mild assumptions are proved to be safe feedback motion plans with a unique stable singular point. The conditions which ensure collision free and almost global convergence for a single agent and the analytical form of the vector fields are then utilized in the design the proposed distributed, semi-cooperative multi-agent coordination protocol. Semi-cooperative coordination has been defined in prior work as the ad hoc prioritization and conflict resolution among agents of the same class; more specifically, participation in conflict resolution and collision avoidance for each agent is determined on-the-fly based on whether the agent's motion results in decreasing its distance with respect to its neighbor agents; based on this condition, the agent decides to either ignore its neighbors, or adjust its velocity and avoid the neighbor agent with respect to which the rate of decrease of the pairwise inter agent distance is maximal. The proposed coordination protocol builds upon this logic and addresses the case of multiple agents of distinct classes (class-A and class-B) in conflict. Guarantees on the safety of the multi-agent system and the almost global convergence of the agents to their destinations are proved. The efficacy of the proposed methodology is demonstrated via simulation results in static and dynamic environments.
@article{DBLP:journals/tac/Panagou17, author = {Dimitra Panagou}, title = {A Distributed Feedback Motion Planning Protocol for Multiple Unicycle Agents of Different Classes}, journal = {{IEEE} Trans. Autom. Control.}, volume = {62}, number = {3}, pages = {1178--1193}, year = {2017}, url = {https://doi.org/10.1109/TAC.2016.2576020}, doi = {10.1109/TAC.2016.2576020}, timestamp = {Wed, 20 May 2020 21:27:50 +0200}, biburl = {https://dblp.org/rec/journals/tac/Panagou17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Automated turning and merging for autonomous vehicles using a Nonlinear Model Predictive Control approach.Accidents at intersections are highly related to the driver's misdecision while performing turning and merging maneuvers. This paper proposes a merging/turning controller for an automated vehicle, called the ego vehicle, which avoids collisions with surrounding (target) vehicles. An optimization-based control problem is defined based on receding horizon control, that parameterizes the system trajectory with the control input and employs a nonlinear model on the ego vehicle dynamics. Most existing solutions focus on 1-D (longitudinal) motion for the vehicles. In this paper, the 2-D motion of the turning/merging vehicle is considered instead. The intersection is modeled under realistic traffic conditions, a probabilistic model is used to predict the trajectories of the target vehicles, and is integrated within a novel collision avoidance model. These models allow our controller to perform both line following when turning/merging, and collision avoidance, while simulations of several scenarios validate its performance.
@inproceedings{DBLP:conf/amcc/HuangP17a, author = {Lixing Huang and Dimitra Panagou}, title = {Automated turning and merging for autonomous vehicles using a Nonlinear Model Predictive Control approach}, booktitle = {2017 American Control Conference, {ACC} 2017, Seattle, WA, USA, May 24-26, 2017}, pages = {5525--5531}, publisher = {{IEEE}}, year = {2017}, url = {https://doi.org/10.23919/ACC.2017.7963814}, doi = {10.23919/ACC.2017.7963814}, timestamp = {Fri, 03 Dec 2021 13:04:31 +0100}, biburl = {https://dblp.org/rec/conf/amcc/HuangP17a.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Chebyshev approximation and higher order derivatives of Lyapunov functions for estimating the domain of attraction.Estimating the Domain of Attraction (DA) of non-polynomial systems is a challenging problem. Taylor expansion is widely adopted for transforming a nonlinear analytic function into a polynomial function, but the performance of Taylor expansion is not always satisfactory. This paper provides solvable ways for estimating the DA via Chebyshev approximation. Firstly, for Chebyshev approximation without the remainder, higher order derivatives of Lyapunov functions are used for estimating the DA, and the largest estimate is obtained by solving a generalized eigenvalue problem. Moreover, for Chebyshev approximation with the remainder, an uncertain polynomial system is reformulated, and a condition is proposed for ensuring the convergence to the largest estimate with a selected Lyapunov function. Numerical examples demonstrate that both accuracy and efficiency are improved compared to Taylor approximation.
@inproceedings{DBLP:conf/cdc/HanP17a, author = {Dongkun Han and Dimitra Panagou}, title = {Chebyshev approximation and higher order derivatives of Lyapunov functions for estimating the domain of attraction}, booktitle = {56th {IEEE} Annual Conference on Decision and Control, {CDC} 2017, Melbourne, Australia, December 12-15, 2017}, pages = {1181--1186}, publisher = {{IEEE}}, year = {2017}, url = {https://doi.org/10.1109/CDC.2017.8263816}, doi = {10.1109/CDC.2017.8263816}, timestamp = {Fri, 04 Mar 2022 13:29:55 +0100}, biburl = {https://dblp.org/rec/conf/cdc/HanP17a.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Control strategies for multiplayer target-attacker-defender differential games with double integrator dynamics.This paper presents a method for deriving optimal controls and assigning attacker-defender pairs in a target-attacker-defender differential game between an arbitrary numbers of attackers and defenders, all of which are modeled using double integrator dynamics. It is assumed that each player has perfect information about the states and controls of the players within a certain range of themselves, but they are unaware of any players outside of this range. Isochrones are created based on the time-optimal trajectories needed for the players to reach any point in the shortest possible time. The intersections of the players' isochrones are used to determine whether a defender can intercept an attacker before the attacker reaches the target. Sufficient conditions on the detection range of the defenders and the guaranteed capture despite perturbations of the attackers off the nominal trajectories are derived. Then, in simulations with multiple players, attacker-defender pairs are assigned so that the maximum number of attackers are intercepted in the shortest possible time.
@inproceedings{DBLP:conf/cdc/CoonP17, author = {Mitchell Coon and Dimitra Panagou}, title = {Control strategies for multiplayer target-attacker-defender differential games with double integrator dynamics}, booktitle = {56th {IEEE} Annual Conference on Decision and Control, {CDC} 2017, Melbourne, Australia, December 12-15, 2017}, pages = {1496--1502}, publisher = {{IEEE}}, year = {2017}, url = {https://doi.org/10.1109/CDC.2017.8263864}, doi = {10.1109/CDC.2017.8263864}, timestamp = {Fri, 04 Mar 2022 13:29:55 +0100}, biburl = {https://dblp.org/rec/conf/cdc/CoonP17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Distributed Dynamic Coverage and Avoidance Control Under Anisotropic Sensing.This paper addresses dynamic coverage in multi-agent systems along with certain safety and convergence guarantees. We consider anisotropic sensing for each agent, realized as conical sensing footprints and coverage functionals. This modeling results in asymmetric (directed) interactions among agents, in the sense that connected agents may either all be in the same mode (avoidance) or in different modes (avoidance and coverage). We build local and global coverage strategies which force the agents to collaboratively search a domain of interest, and avoidance strategies which waive the assumption on only pairwise interactions among agents. The proposed approach is suitable for surveillance applications where agents explore and gather sufficient information about an environment. The efficacy of the approach is demonstrated through simulation results.
@article{DBLP:journals/tcns/PanagouSV17, author = {Dimitra Panagou and Dusan M. Stipanovic and Petros G. Voulgaris}, title = {Distributed Dynamic Coverage and Avoidance Control Under Anisotropic Sensing}, journal = {{IEEE} Trans. Control. Netw. Syst.}, volume = {4}, number = {4}, pages = {850--862}, year = {2017}, url = {https://doi.org/10.1109/TCNS.2016.2576403}, doi = {10.1109/TCNS.2016.2576403}, timestamp = {Tue, 21 Mar 2023 21:14:27 +0100}, biburl = {https://dblp.org/rec/journals/tcns/PanagouSV17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Distributed multi-task formation control under parametric communication uncertainties.Formation control is a key problem in the coordination of multiple agents. It arises new challenges to traditional formation control strategy when the communication among agents is affected by uncertainties. This paper considers the robust multi-task formation control problem of multiple nonpoint agents whose communications are disturbed by uncertain parameters. The control objectives include 1. achieving the desired configuration; 2. avoiding collisions; 3. preserving the connectedness of uncertain topology. To achieve these objectives, first, a condition of Linear Matrix Inequalities (LMIs) is proposed for checking the connectedness of uncertain topologies. Then, by preserving the initial topological connectedness, a gradient-based distributed controller is designed via Lyapunov-like barrier functions. Two numerical examples illustrate the effectiveness of the proposed method.
@inproceedings{DBLP:conf/cdc/HanP17, author = {Dongkun Han and Dimitra Panagou}, title = {Distributed multi-task formation control under parametric communication uncertainties}, booktitle = {56th {IEEE} Annual Conference on Decision and Control, {CDC} 2017, Melbourne, Australia, December 12-15, 2017}, pages = {405--410}, publisher = {{IEEE}}, year = {2017}, url = {https://doi.org/10.1109/CDC.2017.8263698}, doi = {10.1109/CDC.2017.8263698}, timestamp = {Fri, 04 Mar 2022 13:29:55 +0100}, biburl = {https://dblp.org/rec/conf/cdc/HanP17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Persistent coverage of a two-dimensional manifold subject to time-varying disturbances.This paper presents a persistent coverage algorithm for multiple agents subject to 3-D rigid body kinematics. Each agent uses a forward-facing sensing footprint, modeled as an anisotropic spherical sector, to cover a 2-D manifold. The manifold is subject to continual collisions by high speed particles. Particle trajectories are estimated online with an extended Kalman filter using noisy spherical coordinate position measurements. Predicted impact points for each particle, along with associated covariances, are used to generate normally distributed coverage decay. This directs agents to explore in the vicinity of both future and past impact points. The efficacy of the algorithm is demonstrated through simulation.
@inproceedings{DBLP:conf/cdc/BentzP17, author = {William Bentz and Dimitra Panagou}, title = {Persistent coverage of a two-dimensional manifold subject to time-varying disturbances}, booktitle = {56th {IEEE} Annual Conference on Decision and Control, {CDC} 2017, Melbourne, Australia, December 12-15, 2017}, pages = {387--392}, publisher = {{IEEE}}, year = {2017}, url = {https://doi.org/10.1109/CDC.2017.8263695}, doi = {10.1109/CDC.2017.8263695}, timestamp = {Fri, 04 Mar 2022 13:29:55 +0100}, biburl = {https://dblp.org/rec/conf/cdc/BentzP17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - r-Robustness and (r, s)-robustness of circulant graphs.There has been recent growing interest in graph theoretical properties known as r- and (r, s) -robustness. These properties serve as sufficient conditions guaranteeing the success of certain consensus algorithms in networks with misbehaving agents present. Due to the complexity of determining the robustness for an arbitrary graph, several methods have previously been proposed for identifying the robustness of specific classes of graphs or constructing graphs with specified robustness levels. The majority of such approaches have focused on undirected graphs. In this paper we identify a class of scalable directed graphs whose edge set is determined by a parameter k and prove that the robustness of these graphs is also determined by k. We support our results through computer simulations.
@inproceedings{DBLP:conf/cdc/UsevitchP17, author = {James Usevitch and Dimitra Panagou}, title = {r-Robustness and (r, s)-robustness of circulant graphs}, booktitle = {56th {IEEE} Annual Conference on Decision and Control, {CDC} 2017, Melbourne, Australia, December 12-15, 2017}, pages = {4416--4421}, publisher = {{IEEE}}, year = {2017}, url = {https://doi.org/10.1109/CDC.2017.8264310}, doi = {10.1109/CDC.2017.8264310}, timestamp = {Fri, 04 Mar 2022 13:29:55 +0100}, biburl = {https://dblp.org/rec/conf/cdc/UsevitchP17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Robust semi-cooperative multi-agent coordination in the presence of stochastic disturbances.This paper presents a robust distributed coordination protocol that achieves generation of collision-free trajectories for multiple unicycle agents in the presence of stochastic uncertainties. We build upon our earlier work on semi-cooperative coordination and we redesign the coordination controllers so that the agents counteract a class of state (wind) disturbances and measurement noise. Safety and convergence is proved analytically, while simulation results demonstrate the efficacy of the proposed solution.
@inproceedings{DBLP:conf/cdc/GargHP17, author = {Kunal Garg and Dongkun Han and Dimitra Panagou}, title = {Robust semi-cooperative multi-agent coordination in the presence of stochastic disturbances}, booktitle = {56th {IEEE} Annual Conference on Decision and Control, {CDC} 2017, Melbourne, Australia, December 12-15, 2017}, pages = {3443--3448}, publisher = {{IEEE}}, year = {2017}, url = {https://doi.org/10.1109/CDC.2017.8264163}, doi = {10.1109/CDC.2017.8264163}, timestamp = {Fri, 04 Mar 2022 13:29:55 +0100}, biburl = {https://dblp.org/rec/conf/cdc/GargHP17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Vision-based target tracking and autonomous landing of a quadrotor on a ground vehicle.This paper addresses vision-based tracking and landing of a micro-aerial vehicle (MAV) on a ground vehicle (GV). The camera onboard the MAV is mounted so that the optical axis is aligned with the downward-facing axis of the body-fixed frame. A novel supervised learning vision algorithm is proposed as the method to detect the ground vehicle in the image frame. A feedback linearization technique is developed for the MAV to fly over and track the GV so that visibility with the tracked target is maintained with certain guarantees. The efficacy of the visual detection algorithm, and of the tracking and landing controller is demonstrated in simulations and experiments with static and mobile GV.
@inproceedings{DBLP:conf/amcc/HoangBWTP17, author = {Tru Hoang and Enkhmurun Bayasgalan and Ziyin Wang and Gavriil Tsechpenakis and Dimitra Panagou}, title = {Vision-based target tracking and autonomous landing of a quadrotor on a ground vehicle}, booktitle = {2017 American Control Conference, {ACC} 2017, Seattle, WA, USA, May 24-26, 2017}, pages = {5580--5585}, publisher = {{IEEE}}, year = {2017}, url = {https://doi.org/10.23919/ACC.2017.7963823}, doi = {10.23919/ACC.2017.7963823}, timestamp = {Fri, 03 Dec 2021 13:04:31 +0100}, biburl = {https://dblp.org/rec/conf/amcc/HoangBWTP17.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2016
- An energy-aware redistribution method for multi-agent dynamic coverage networks.This paper considers dynamic coverage control of unicycle multi-agent systems under power constraints. The agents under consideration implement a visually based patrol protocol. They observe their environment via forward-facing conical anisotropic sensing regions. A local coverage control strategy is presented that allows for the cooperative search of a domain while maintaining collision avoidance guarantees using a novel control method based on the coverage level. Additionally, a novel energy-aware global coverage technique is introduced that restricts the operating range of power-constrained agents while shifting the network redistribution effort onto less constrained agents. The results of several scenarios are presented in simulation to illustrate the efficacy of these algorithms.
@inproceedings{DBLP:conf/cdc/BentzP16, author = {William Bentz and Dimitra Panagou}, title = {An energy-aware redistribution method for multi-agent dynamic coverage networks}, booktitle = {55th {IEEE} Conference on Decision and Control, {CDC} 2016, Las Vegas, NV, USA, December 12-14, 2016}, pages = {2644--2651}, publisher = {{IEEE}}, year = {2016}, url = {https://doi.org/10.1109/CDC.2016.7798661}, doi = {10.1109/CDC.2016.7798661}, timestamp = {Fri, 04 Mar 2022 13:29:43 +0100}, biburl = {https://dblp.org/rec/conf/cdc/BentzP16.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Distributed Coordination Control for Multi-Robot Networks Using Lyapunov-Like Barrier Functions.This paper addresses the problem of multi-agent coordination and control under multiple objectives, and presents a set-theoretic formulation amenable to Lyapunov-based analysis and control design. A novel class of Lyapunov-like barrier functions is introduced and used to encode multiple, non-trivial control objectives, such as collision avoidance, proximity maintenance and convergence to desired destinations. The construction is based on recentered barrier functions and on maximum approximation functions. Thus, a single Lyapunov-like function is used to encode the constrained set of each agent, yielding simple, gradient-based control solutions. The derived control strategies are distributed, i.e., based on information locally available to each agent, which is dictated by sensing and communication limitations. Furthermore, the proposed coordination protocol dictates semi-cooperative conflict resolution among agents, which can be also thought as prioritization, as well as conflict resolution with respect to an agent (the leader) which is not actively participating in collision avoidance, except when necessary. The considered scenario is pertinent to surveillance tasks and involves nonholonomic vehicles. The efficacy of the approach is demonstrated through simulation results.
@article{DBLP:journals/tac/PanagouSV16, author = {Dimitra Panagou and Dusan M. Stipanovic and Petros G. Voulgaris}, title = {Distributed Coordination Control for Multi-Robot Networks Using Lyapunov-Like Barrier Functions}, journal = {{IEEE} Trans. Autom. Control.}, volume = {61}, number = {3}, pages = {617--632}, year = {2016}, url = {https://doi.org/10.1109/TAC.2015.2444131}, doi = {10.1109/TAC.2015.2444131}, timestamp = {Tue, 21 Mar 2023 21:12:59 +0100}, biburl = {https://dblp.org/rec/journals/tac/PanagouSV16.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Multi-agent motion planning and coordination in polygonal environments using vector fields and model predictive control.In this paper, we extend earlier work on motion planning and coordination of multiple agents, to environments of arbitrary polygonal obstacles, using non-gradient vector fields to steer each agent towards their goal configurations while avoiding collisions. We formulate the vector fields so that the pattern of their integral curves depends on a parameter λ. By manipulating the value of λ, we obtain a set of vector fields whose integral curves define the flow lines for an a priori known obstacle environment. We use the vector field design in tandem with model predictive control to compute safe trajectories for multi-agent systems. The competence of the proposed methodology is demonstrated for both static and dynamic environment via simulation results. The efficacy of model predictive control in achieving control trajectories, free of chattering, for multi-agent coordination is validated through comparison to a state feedback coordination and control protocol.
@inproceedings{DBLP:conf/eucc/HegdeP16, author = {Rashmi Hegde and Dimitra Panagou}, title = {Multi-agent motion planning and coordination in polygonal environments using vector fields and model predictive control}, booktitle = {15th European Control Conference, {ECC} 2016, Aalborg, Denmark, June 29 - July 1, 2016}, pages = {1856--1861}, publisher = {{IEEE}}, year = {2016}, url = {https://doi.org/10.1109/ECC.2016.7810561}, doi = {10.1109/ECC.2016.7810561}, timestamp = {Tue, 01 Jun 2021 15:22:59 +0200}, biburl = {https://dblp.org/rec/conf/eucc/HegdeP16.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Real-time model predictive control for keeping a quadrotor visible on the camera field-of-view of a ground robot.This paper considers a cooperative control design for an aerial/ground robot system, and addresses the problem of maintaining visibility of a quadrotor within the camera field-of-view of a ground robot in the presence of external disturbances. The quadrotor needs to be tracked by the ground robot with a monocular camera, and hence its motion should facilitate the ground vision-based tracking process by remaining in the effective camera sensing area. We design a model predictive controller (MPC) strategy where the visibility constraints of the camera and the control input constraints of the quadrotor are encoded into the cost function via barrier functions, and we adopt a fast MPC solver that is able to solve the optimization problem in real time. We also propose a method to enhance the robustness of the algorithm by suitably defining a restart method for the MPC solver. The applicability of the proposed algorithm is demonstrated through simulations and experimental results on real setups.
@inproceedings{DBLP:conf/amcc/DingGSCP16, author = {Wei Ding and Madan Ravi Ganesh and Robert N. Severinghaus and Jason J. Corso and Dimitra Panagou}, title = {Real-time model predictive control for keeping a quadrotor visible on the camera field-of-view of a ground robot}, booktitle = {2016 American Control Conference, {ACC} 2016, Boston, MA, USA, July 6-8, 2016}, pages = {2259--2264}, publisher = {{IEEE}}, year = {2016}, url = {https://doi.org/10.1109/ACC.2016.7525254}, doi = {10.1109/ACC.2016.7525254}, timestamp = {Sat, 30 Sep 2023 09:34:15 +0200}, biburl = {https://dblp.org/rec/conf/amcc/DingGSCP16.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2015
- Distributed coordination protocols for aggregation and navigation in multi-agent systems under local directed interactions.This paper proposes a velocity coordination protocol for the control of multiple unicycle agents, which aims to address two distinct scenarios in a unified manner. The former case is aggregation around a goal location, while the latter case is navigation to multiple goal locations. The same linear velocity protocol is used in both cases, but slightly different angular velocity protocols are designed to achieve either aggregation or navigation, respectively. The proposed angular velocity protocols regulate the angular velocities of the agents to reference directions imposed by vector fields which are different for aggregation and navigation. The proposed linear velocity protocol imposes directed interactions among agents in the following sense: an implicit prioritization among locally connected agents is ad-hoc decided, which results in a suitable adjustment of the linear velocities of the connected agents so that each one slows down with respect to (w.r.t.) the neighbor agent who maximizes the rate of decrease of the inter-agent distance. Simulation results with multiple unicycle agents achieving either aggregation or navigation along collision-free trajectories are provided to demonstrate the efficacy of the proposed algorithm.
@inproceedings{DBLP:conf/cdc/Panagou15, author = {Dimitra Panagou}, title = {Distributed coordination protocols for aggregation and navigation in multi-agent systems under local directed interactions}, booktitle = {54th {IEEE} Conference on Decision and Control, {CDC} 2015, Osaka, Japan, December 15-18, 2015}, pages = {2780--2785}, publisher = {{IEEE}}, year = {2015}, url = {https://doi.org/10.1109/CDC.2015.7402637}, doi = {10.1109/CDC.2015.7402637}, timestamp = {Wed, 16 Oct 2019 14:14:56 +0200}, biburl = {https://dblp.org/rec/conf/cdc/Panagou15.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Dynamic Coverage Control in Unicycle Multi-Robot Networks under Anisotropic Sensing.This paper considers dynamic coverage control for nonholonomic agents along with collision avoidance guarantees. The novelties of the approach rely on the consideration of anisotropic sensing, which is realized via conic sensing footprints and sensing (coverage) functions for each agent, and on a novel form of avoidance functions. The considered sensing functions encode field-of-view and range constraints, and also the degradation of effective sensing close to the boundaries of the sensing footprint. Thus the proposed approach is suitable for surveillance applications where each agent is assigned with the task to gather enough information, such as video streaming in an obstacle environment. The efficacy of the approach is demonstrated through simulation results.
@article{DBLP:journals/firai/PanagouSV15, author = {Dimitra Panagou and Dusan M. Stipanovic and Petros G. Voulgaris}, title = {Dynamic Coverage Control in Unicycle Multi-Robot Networks under Anisotropic Sensing}, journal = {Frontiers Robotics {AI}}, volume = {2}, pages = {3}, year = {2015}, url = {https://doi.org/10.3389/frobt.2015.00003}, doi = {10.3389/FROBT.2015.00003}, timestamp = {Tue, 21 Mar 2023 21:08:09 +0100}, biburl = {https://dblp.org/rec/journals/firai/PanagouSV15.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2014
- Cooperative Visibility Maintenance for Leader-Follower Formations in Obstacle Environments.Vision-based formation control of multiple agents, such as mobile robots or fully autonomous cars, has recently received great interest due to its application in robotic networks and automated highways. This paper addresses the cooperative motion coordination of leader-follower formations of nonholonomic mobile robots, under visibility and communication constraints in known polygonal obstacle environments. We initially consider the case of N = 2 agents moving in L-F fashion and propose a feedback control strategy under which L ensures obstacle avoidance for both robots, while F ensures visibility maintenance with L and intervehicle collision avoidance. The derived algorithms are based on set-theoretic methods to guarantee visibility maintenance, dipolar vector fields to maintain the formation shape, and the consideration of the formation as a tractor-trailer system to ensure obstacle avoidance. We furthermore show how the coordination and control design extends to the case of N > 2 agents, and provide simulation results, which demonstrate the efficacy of the control solutions. The proposed algorithms do not require information exchange among robots, but are instead based on information locally available to each agent. In this way, the desired tasks are executed and achieved in a decentralized manner, with each robot taking care of converging to a desired configuration, while maintaining visibility with its target.
@article{DBLP:journals/trob/PanagouK14, author = {Dimitra Panagou and Vijay Kumar}, title = {Cooperative Visibility Maintenance for Leader-Follower Formations in Obstacle Environments}, journal = {{IEEE} Trans. Robotics}, volume = {30}, number = {4}, pages = {831--844}, year = {2014}, url = {https://doi.org/10.1109/TRO.2014.2304774}, doi = {10.1109/TRO.2014.2304774}, timestamp = {Sat, 20 May 2017 00:25:23 +0200}, biburl = {https://dblp.org/rec/journals/trob/PanagouK14.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Decentralized goal assignment and trajectory generation in multi-robot networks: A multiple Lyapunov functions approach.This paper considers the problem of decentralized goal assignment and trajectory generation for multi-robot networks when only local communication is available, and proposes an approach based on methods related to switched systems and set invariance. A family of Lyapunov-like functions is employed to encode the (local) decision making among candidate goal assignments, under which the agents pick the assignment which results in the shortest total distance to the goals. An additional family of Lyapunov-like barrier functions is activated in the case when the optimal assignment may lead to colliding trajectories, thus maintaining system safety while preserving the convergence guarantees. The proposed switching strategies give rise to feedback control policies which are scalable as the number of agents increases, and therefore are suitable for applications including first-response deployment of robotic networks under limited information sharing. Simulations demonstrate the efficacy of the proposed method.
@inproceedings{DBLP:conf/icra/PanagouTK14, author = {Dimitra Panagou and Matthew Turpin and Vijay Kumar}, title = {Decentralized goal assignment and trajectory generation in multi-robot networks: {A} multiple Lyapunov functions approach}, booktitle = {2014 {IEEE} International Conference on Robotics and Automation, {ICRA} 2014, Hong Kong, China, May 31 - June 7, 2014}, pages = {6757--6762}, publisher = {{IEEE}}, year = {2014}, url = {https://doi.org/10.1109/ICRA.2014.6907857}, doi = {10.1109/ICRA.2014.6907857}, timestamp = {Wed, 16 Oct 2019 14:14:51 +0200}, biburl = {https://dblp.org/rec/conf/icra/PanagouTK14.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Dynamic positioning for an underactuated marine vehicle using hybrid control.The increasing interest in autonomous marine systems and related applications has motivated, among others, the development of systems and algorithms for the dynamic positioning of underactuated marine vehicles (ships, surface vessels and underwater vehicles) under the influence of unknown environmental disturbances. In this paper, we present a state feedback control solution for the navigation and practical stabilisation of an underactuated marine vehicle under non-vanishing current disturbances, by means of hybrid control. The proposed solution involves a logic-based switching control strategy among simple state feedback controllers, which renders the position trajectories of the vehicle practically stable to a goal set around a desired position. The control scheme consists of three control laws; the first one is active out of the goal set and drives the system trajectories into this set, based on a novel dipolar vector field. The other two control laws are active in the goal set and alternately regulate the position and the orientation of the vehicle, so that the switched system is practically stable around the desired position. The overall system is shown to be robust, in the sense that the vehicle enters and remains into the goal set even if the external current disturbance is unknown, varying and only its maximum bound (magnitude) is given. The efficacy of the proposed solution is demonstrated through simulation results.
@article{DBLP:journals/ijcon/PanagouK14, author = {Dimitra Panagou and Kostas J. Kyriakopoulos}, title = {Dynamic positioning for an underactuated marine vehicle using hybrid control}, journal = {Int. J. Control}, volume = {87}, number = {2}, pages = {264--280}, year = {2014}, url = {https://doi.org/10.1080/00207179.2013.828853}, doi = {10.1080/00207179.2013.828853}, timestamp = {Mon, 06 Nov 2017 12:13:15 +0100}, biburl = {https://dblp.org/rec/journals/ijcon/PanagouK14.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Motion planning and collision avoidance using navigation vector fields.This paper presents a novel method on the motion and path planning for unicycle robots in environments with static circular obstacles. The method employs a family of 2-dimensional analytic vector fields, which have singular points of high-order type and whose integral curves exhibit various patterns depending on the value of a parameter λ. More specifically, for a known value of λ the vector field has a unique singular point of dipole type and its integral curves are suitable for steering the unicycle to a goal configuration. Furthermore, for the value of λ that the vector field has a continuum of singular points, the integral curves can be used to define flows around circular obstacles. An almost global feedback motion plan is then constructed by suitably blending attractive and repulsive vector fields in a static obstacle environment. The proposed motion planning and control design is also extended to the multi-agent case, where each agent needs to converge to a desired configuration while avoiding collisions with other agents. The efficacy of the approach is demonstrated via simulation results.
@inproceedings{DBLP:conf/icra/Panagou14, author = {Dimitra Panagou}, title = {Motion planning and collision avoidance using navigation vector fields}, booktitle = {2014 {IEEE} International Conference on Robotics and Automation, {ICRA} 2014, Hong Kong, China, May 31 - June 7, 2014}, pages = {2513--2518}, publisher = {{IEEE}}, year = {2014}, url = {https://doi.org/10.1109/ICRA.2014.6907210}, doi = {10.1109/ICRA.2014.6907210}, timestamp = {Wed, 16 Oct 2019 14:14:51 +0200}, biburl = {https://dblp.org/rec/conf/icra/Panagou14.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Vision-based dynamic coverage control for nonholonomic agents.This paper considers dynamic coverage control for nonholonomic agents along with collision avoidance guarantees. The novelties of the approach rely on the consideration of anisotropic sensing, which is realized via conic sensing footprints and sensing (coverage) functions for each agent, and on a novel form of avoidance functions. The considered sensing functions encode field-of-view and range constraints, and also the degradation of effective sensing close to the boundaries of the sensing footprint. Thus the proposed approach is suitable for surveillance applications where each agent is assigned with the task to gather enough information, such as video streaming in an obstacle environment. The efficacy of the approach is demonstrated through simulation results.
@inproceedings{DBLP:conf/cdc/PanagouSV14, author = {Dimitra Panagou and Dusan M. Stipanovic and Petros G. Voulgaris}, title = {Vision-based dynamic coverage control for nonholonomic agents}, booktitle = {53rd {IEEE} Conference on Decision and Control, {CDC} 2014, Los Angeles, CA, USA, December 15-17, 2014}, pages = {2198--2203}, publisher = {{IEEE}}, year = {2014}, url = {https://doi.org/10.1109/CDC.2014.7039724}, doi = {10.1109/CDC.2014.7039724}, timestamp = {Tue, 21 Mar 2023 20:52:20 +0100}, biburl = {https://dblp.org/rec/conf/cdc/PanagouSV14.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2013
- Cooperative formation control of underactuated marine vehicles for target surveillance under sensing and communication constraints.This paper presents a Leader-Follower formation control strategy for underactuated marine vehicles which move under sensing and communication constraints in the presence of bounded persistent environmental disturbances. We assume that the vehicles do not communicate for exchanging information regarding on their states (pose and velocities), and that their sensing capabilities are restricted, due to limited range and angle-of-view. Sensing constraints are thus realized as a set of inequality state constraints which should never be violated (viability constraints). The viability constraints define a closed subset K of the configuration space (viability set K). The control objective is thus reduced into to coordinating the motion of the vehicles in a Leader-Follower formation, while system trajectories starting in K always remain viable in K. The proposed control design employs dipolar vector fields and a viability-based switching control scheme, which guarantees that system viability is always maintained. The efficacy of the proposed algorithm, as well as its relevance with surveillance of (stationary) targets are demonstrated through simulations.
@inproceedings{DBLP:conf/icra/PanagouK13, author = {Dimitra Panagou and Kostas J. Kyriakopoulos}, title = {Cooperative formation control of underactuated marine vehicles for target surveillance under sensing and communication constraints}, booktitle = {2013 {IEEE} International Conference on Robotics and Automation, Karlsruhe, Germany, May 6-10, 2013}, pages = {1871--1876}, publisher = {{IEEE}}, year = {2013}, url = {https://doi.org/10.1109/ICRA.2013.6630824}, doi = {10.1109/ICRA.2013.6630824}, timestamp = {Wed, 16 Oct 2019 14:14:51 +0200}, biburl = {https://dblp.org/rec/conf/icra/PanagouK13.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Model Predictive Control for the navigation of a nonholonomic vehicle with field-of-view constraints.This paper considers the problem of navigating a differentially driven nonholonomic vehicle while maintaining visibility with a (stationary) target by means of Model Predictive Control (MPC). The approach combines the convergence properties of a dipolar vector field within a constrained nonlinear MPC formulation, in which visibility and input saturation constraints are encoded via recentered barrier functions. A dipolar vector field offers by construction a global feedback motion plan to a goal configuration, yet it does not ensure that visibility is always maintained. For this reason, it is suitably combined with recentered barrier functions so that convergence to the goal and satisfaction of visibility and input constraints are both achieved. The control strategy falls into the class of dual-mode MPC schemes and its efficacy is demonstrated through simulation results in the case of a mobile robot with unicycle kinematics.
@inproceedings{DBLP:conf/amcc/ManiatopoulosPK13, author = {Spyros Maniatopoulos and Dimitra Panagou and Kostas J. Kyriakopoulos}, title = {Model Predictive Control for the navigation of a nonholonomic vehicle with field-of-view constraints}, booktitle = {American Control Conference, {ACC} 2013, Washington, DC, USA, June 17-19, 2013}, pages = {3967--3972}, publisher = {{IEEE}}, year = {2013}, url = {https://doi.org/10.1109/ACC.2013.6580446}, doi = {10.1109/ACC.2013.6580446}, timestamp = {Sun, 08 Aug 2021 01:40:56 +0200}, biburl = {https://dblp.org/rec/conf/amcc/ManiatopoulosPK13.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Multi-objective control for multi-agent systems using Lyapunov-like barrier functions.This paper addresses the problem of multi-agent coordination and control under multiple objectives, and presents a set-theoretic formulation which is amenable to Lyapunov-based analysis and control design. A novel class of Lyapunov-like barrier functions is introduced and used to encode multiple, non-trivial control objectives, such as collision avoidance, proximity maintenance and convergence to desired destinations. The construction is based on the concept of recentered barrier functions and on approximation functions. A single Lyapunov-like function encodes the constrained set of each agent, yielding simple, closed-form control solutions. The proposed construction allows also for distributed control design based on information locally available to each agent. The scenario considered here involves nonholonomic vehicles, while simulation results demonstrate the efficacy of the approach.
@inproceedings{DBLP:conf/cdc/PanagouSV13, author = {Dimitra Panagou and Dusan M. Stipanovic and Petros G. Voulgaris}, title = {Multi-objective control for multi-agent systems using Lyapunov-like barrier functions}, booktitle = {Proceedings of the 52nd {IEEE} Conference on Decision and Control, {CDC} 2013, Florence, Italy, December 10-13, 2013}, pages = {1478--1483}, publisher = {{IEEE}}, year = {2013}, url = {https://doi.org/10.1109/CDC.2013.6760091}, doi = {10.1109/CDC.2013.6760091}, timestamp = {Tue, 21 Mar 2023 20:52:20 +0100}, biburl = {https://dblp.org/rec/conf/cdc/PanagouSV13.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Viability control for a class of underactuated systems.
@article{DBLP:journals/automatica/PanagouK13, author = {Dimitra Panagou and Kostas J. Kyriakopoulos}, title = {Viability control for a class of underactuated systems}, journal = {Autom.}, volume = {49}, number = {1}, pages = {17--29}, year = {2013}, url = {https://doi.org/10.1016/j.automatica.2012.09.002}, doi = {10.1016/J.AUTOMATICA.2012.09.002}, timestamp = {Thu, 20 Feb 2020 09:16:44 +0100}, biburl = {https://dblp.org/rec/journals/automatica/PanagouK13.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2012
- Maintaining visibility for leader-follower formations in obstacle environments.This paper addresses the problem of controlling a leader-follower (L - F) formation of two unicycle mobile robots moving under visibility constraints in a known obstacle environment. Visibility constraints are realized as inequality state constraints that determine a visibility set K. Maintaining visibility is translated into controlling the robots so that system trajectories starting in K always remain in K. We provide the conditions under which visibility is maintained, as well as a feedback control scheme that forces F to converge and remain into a set of desired configurations w.r.t. L while maintaining visibility. We also propose a cooperative control scheme for the motion of the formation in a known obstacle environment, so that both collision avoidance and maintaining visibility are ensured. The proposed control schemes are decentralized, in the sense that there is no direct communication between the robots. The efficacy of our algorithms is evaluated through simulations.
@inproceedings{DBLP:conf/icra/PanagouK12, author = {Dimitra Panagou and Vijay Kumar}, title = {Maintaining visibility for leader-follower formations in obstacle environments}, booktitle = {{IEEE} International Conference on Robotics and Automation, {ICRA} 2012, 14-18 May, 2012, St. Paul, Minnesota, {USA}}, pages = {1811--1816}, publisher = {{IEEE}}, year = {2012}, url = {https://doi.org/10.1109/ICRA.2012.6224893}, doi = {10.1109/ICRA.2012.6224893}, timestamp = {Wed, 16 Oct 2019 14:14:51 +0200}, biburl = {https://dblp.org/rec/conf/icra/PanagouK12.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2011
- Control of nonholonomic systems using reference vector fields.This paper presents a control design methodology for n-dimensional nonholonomic systems. The main idea is that, given a nonholonomic system subject to κ Pfaffian constraints, one can define a smooth, N-dimensional reference vector field F, which is nonsingular everywhere except for a submanifold containing the origin. The dimension N ≤ n of F depends on the structure of the constraint equations, which induces a foliation of the configuration space. This foliation, together with the objective of having the system vector field aligned with F, suggests a choice of Lyapunov-like functions V. The proposed approach recasts the original nonholonomic control problem into a lower-dimensional output regulation problem, which although nontrivial, can more easily be tackled with existing design and analysis tools. The methodology applies to a wide class of nonholonomic systems, and its efficacy is demonstrated through numerical simulations for the cases of the unicycle and the n-dimensional chained systems, for n = 3, 4.
@inproceedings{DBLP:conf/cdc/PanagouTK11, author = {Dimitra Panagou and Herbert G. Tanner and Kostas J. Kyriakopoulos}, title = {Control of nonholonomic systems using reference vector fields}, booktitle = {50th {IEEE} Conference on Decision and Control and European Control Conference, 11th European Control Conference, {CDC/ECC} 2011, Orlando, FL, USA, December 12-15, 2011}, pages = {2831--2836}, publisher = {{IEEE}}, year = {2011}, url = {https://doi.org/10.1109/CDC.2011.6160922}, doi = {10.1109/CDC.2011.6160922}, timestamp = {Wed, 24 Feb 2021 08:49:08 +0100}, biburl = {https://dblp.org/rec/conf/cdc/PanagouTK11.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Control of underactuated systems with viability constraints.This paper addresses the control design for a class of nonholonomic systems which are subject to inequality state constraints defining a constrained (viability) set K. Based on concepts from viability theory, the necessary conditions for selecting viable controls for a nonholonomic system are given. Furthermore, a class of nonholonomic control solutions are redesigned by means of switching control, so that system trajectories are viable in K and converge to a goal set G in K. The motion control for an underactuated marine vehicle in a constrained configuration set K is treated as a case study. The set K essentially describes the limited sensing area of a vision-based sensor system, and viable control laws which establish convergence to a goal set G in K are constructed. The efficacy of the methodology is demonstrated through simulation results.
@inproceedings{DBLP:conf/cdc/PanagouK11, author = {Dimitra Panagou and Kostas J. Kyriakopoulos}, title = {Control of underactuated systems with viability constraints}, booktitle = {50th {IEEE} Conference on Decision and Control and European Control Conference, 11th European Control Conference, {CDC/ECC} 2011, Orlando, FL, USA, December 12-15, 2011}, pages = {5497--5502}, publisher = {{IEEE}}, year = {2011}, url = {https://doi.org/10.1109/CDC.2011.6160925}, doi = {10.1109/CDC.2011.6160925}, timestamp = {Wed, 24 Feb 2021 08:49:08 +0100}, biburl = {https://dblp.org/rec/conf/cdc/PanagouK11.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } - Switching control approach for the robust practical stabilization of a unicycle-like marine vehicle under non-vanishing perturbations.This paper presents a solution to the robust practical stabilization of a unicycle-like marine vehicle, under non-vanishing current-induced perturbations. A hysteresis-based switching control strategy is proposed, rendering the system globally practically stable to a set G around the origin. The control scheme consists of three control laws; the first one is active out of G and drives the system trajectories into G, based on a dipole-like vector field. The other two control laws are active in G and alternately regulate the position and the orientation of the vehicle. The system is shown to be robust, in the sense that the vehicle enters and remains into G even if only a maximum bound of the perturbation is known. The efficacy of the solution is demonstrated through simulation results.
@inproceedings{DBLP:conf/icra/PanagouK11, author = {Dimitra Panagou and Kostas J. Kyriakopoulos}, title = {Switching control approach for the robust practical stabilization of a unicycle-like marine vehicle under non-vanishing perturbations}, booktitle = {{IEEE} International Conference on Robotics and Automation, {ICRA} 2011, Shanghai, China, 9-13 May 2011}, pages = {1525--1530}, publisher = {{IEEE}}, year = {2011}, url = {https://doi.org/10.1109/ICRA.2011.5979747}, doi = {10.1109/ICRA.2011.5979747}, timestamp = {Mon, 06 Nov 2017 12:15:03 +0100}, biburl = {https://dblp.org/rec/conf/icra/PanagouK11.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2010
- Dipole-like fields for stabilization of systems with Pfaffian constraints.This paper introduces a framework that guides the design of stabilizing feedback control laws for systems with Pfaffian constraints. A new class of N-dimensional vector fields, the dipole-like vector fields is proposed, inspired by the form of the flow lines of the electric point dipole. A general connection between the dipole-like field and the Pfaffian constraints of catastatic nonholonomic systems is exploited, to establish systematic guidelines on the design of stabilizing control laws. The methodology is applied to the stabilization of the unicycle and of the nonholonomic double integrator. Based on these guidelines, switching control laws are constructed. The efficacy of the methodology is demonstrated through simulation results.
@inproceedings{DBLP:conf/icra/PanagouTK10, author = {Dimitra Panagou and Herbert G. Tanner and Kostas J. Kyriakopoulos}, title = {Dipole-like fields for stabilization of systems with Pfaffian constraints}, booktitle = {{IEEE} International Conference on Robotics and Automation, {ICRA} 2010, Anchorage, Alaska, USA, 3-7 May 2010}, pages = {4499--4504}, publisher = {{IEEE}}, year = {2010}, url = {https://doi.org/10.1109/ROBOT.2010.5509296}, doi = {10.1109/ROBOT.2010.5509296}, timestamp = {Mon, 06 Nov 2017 12:15:02 +0100}, biburl = {https://dblp.org/rec/conf/icra/PanagouTK10.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2009
- A viability approach for the stabilization of an underactuated underwater vehicle in the presence of current disturbances.In this paper we present a viability-based formulation for the stabilization of an underactuated underwater vehicle under the influence of a known, constant current and state constraints. The stabilization problem is described by three problems in terms of viability theory. We present a solution to the first problem which addresses the safety of the system, i.e. guarantees that there exists a control law such that the vehicle always remains into the safe set of state constraints. In order to overcome the computational limitations due to the high dimension of the system we develop a two-stage approach, based on forward reachability and game theory. The control law is thus the safety controller when the system viability is at stake, i.e. close to the boundary of the safe set. The viability kernel and the control law are numerically computed.
@inproceedings{DBLP:conf/cdc/PanagouMSLK09, author = {Dimitra Panagou and Kostas Margellos and Sean Summers and John Lygeros and Kostas J. Kyriakopoulos}, title = {A viability approach for the stabilization of an underactuated underwater vehicle in the presence of current disturbances}, booktitle = {Proceedings of the 48th {IEEE} Conference on Decision and Control, {CDC} 2009, combined withe the 28th Chinese Control Conference, December 16-18, 2009, Shanghai, China}, pages = {8612--8617}, publisher = {{IEEE}}, year = {2009}, url = {https://doi.org/10.1109/CDC.2009.5400954}, doi = {10.1109/CDC.2009.5400954}, timestamp = {Fri, 04 Mar 2022 13:27:41 +0100}, biburl = {https://dblp.org/rec/conf/cdc/PanagouMSLK09.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }