Projects

Safety-critical planning, verification, and learning-enabled control for trusted autonomous air mobility and multi-agent systems under uncertainty.

Autonomous, persistent, and adaptive mobile observational networks that balance energy harvesting against information gathering.

Safe and reliable planning, control, and learning for autonomous mobility and robotic systems operating in complex and uncertain environments.

Safe planning and attack-tolerant control and estimation for multi-robot networks that must stay resilient to adversaries while operating in confined, obstacle-rich environments.

Foundations of perceivability: when and how an autonomous system can safely build knowledge of an unknown, uncertain, dynamic environment under physical and informational constraints.