DASC Lab UMich

Distributed Autonomous Systems and Control Lab

The Distributed Autonomous Systems and Control Laboratory (3010 Ford Robotics Building) is directed by Dimitra Panagou.

The lab's research focuses on advancing planning, learning, and control methods for autonomous robotic systems, with a strong emphasis on safety, resilience, and provable guarantees. We address real-world challenges in robotics, including multi-agent, networked, and sensor-based systems, operating in uncertain, dynamic, or adversarial environments. Our interests include nonlinear systems, estimation, risk-aware decision making, learning-based control, uncertainty quantification, and control under constraints, with applications across aerial, ground, marine, and space domains.

If you are interested to join our lab, get in touch with Prof. Panagou or some of the PhD lab members.

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Recent Publications

Distributed Resilience-Aware Control in Multi-Robot Networks
Distributed Resilience-Aware Control in Multi-Robot Networks
Haejoon Lee Dimitra Panagou

IEEE CDC 2025

pdf / code / arxiv /
How to Adapt Control Barrier Functions? A Learning-Based Approach with Applications to a VTOL Quadplane
How to Adapt Control Barrier Functions? A Learning-Based Approach with Applications to a VTOL Quadplane
Taekyung Kim Randal W. Beard Dimitra Panagou

IEEE CDC 2025

project page / code / arxiv /
Safe Navigation in Uncertain Crowded Environments Using Risk Adaptive CVaR Barrier Functions
Safe Navigation in Uncertain Crowded Environments Using Risk Adaptive CVaR Barrier Functions
Xinyi Wang Taekyung Kim Bardh Hoxha Georgios Fainekos Dimitra Panagou

IEEE IROS 2025

video / arxiv /
Fusion of Indirect Methods and Iterative Learning for Persistent Velocity Trajectory Optimization of a Sustainably Powered Autonomous Surface Vessel
Fusion of Indirect Methods and Iterative Learning for Persistent Velocity Trajectory Optimization of a Sustainably Powered Autonomous Surface Vessel
Kavin M. Govindarajan Devansh Agrawal Dimitra Panagou Christopher Vermillion

IEEE Conference on Control Technology and Applications (CCTA) 2025

code / arxiv /
Certifiably-Correct Mapping for Safe Navigation Despite Odometry Drift
Certifiably-Correct Mapping for Safe Navigation Despite Odometry Drift
Devansh Agrawal Taekyung Kim Rajiv Govindjee Trushant Adeshara Jiangbo Yu Anuerkha Ravikumar Dimitra Panagou

RSS 2025

project page / video / code / arxiv /
meSch: Multi-Agent Energy-Aware Scheduling for Task Persistence
meSch: Multi-Agent Energy-Aware Scheduling for Task Persistence
Kaleb Ben Naveed An Dang Rahul H Kumar Dimitra Panagou

IEEE/RSJ IROS 2025

video / code / arxiv /
Conformal Prediction in the Loop: Risk-Aware Control Barrier Functions for Stochastic Systems with Data-Driven State Estimators
Conformal Prediction in the Loop: Risk-Aware Control Barrier Functions for Stochastic Systems with Data-Driven State Estimators
Junhui Zhang Bardh Hoxha Georgios Fainekos Dimitra Panagou

IEEE Control Systems Letters 2025

paper /
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