Research
My work spans safe autonomy, multi-agent systems, and bio-inspired robotics — developing controllers and planners that are provably correct and deployable on resource-constrained hardware. Full research statement →
Collective Intelligence
Minimalist Robotic Swarms for Target Encapsulation
Provably correct decentralized control for robot swarms with no memory, no communication, and no localization.
Neuromorphic Decision Dynamics and Control
Environment Monitoring in the Wild
Decentralized, game-theoretic, and neuromorphic control for scalable environment monitoring in resource-constrained robot teams.
Neuromorphic Decision Dynamics and Control
Multi-Robot Social Navigation in Crowded Environments
Safe, scalable, and deadlock-free multi-robot navigation through continuous adaptation and local interaction rules.
Task and Motion Planning
Affordance-Aware Task and Motion Planning
Reactive task and motion planning using object affordances, feasibility checks, and tool substitution — demonstrated on a Stretch robot.
Motion Planning and Control
Provably Safe Motion Planning for Resource-Constrained UAVs
Provably safe aerial motion planning under uncertainty, limited computation, and complex workspace constraints.
Collective Intelligence
Electronically Programmable Shape-Morphing MetaBots
Micrometer-scale origami robots that fold into 3D shapes, locomote in solution, and are controlled by surface electrochemical actuators.
Motion Planning and Control
Aerospace Systems and Control
Control, estimation, and modeling for distributed spacecraft systems, autonomous navigation, and propulsion.