MULTI-AGENT ROBOTIC SYSTEMS

Our research focuses on principled robotic decision making, centred around combining traditional analytical methods in robotics and modern data-driven techniques. We address theoretical and computational challenges in robotic safety, connect control-theoretic algorithms with perception and machine learning, and bridge the gap between theory and practical implementation.