Geometric control for motion planning and coordination

Francesco Bullo, Coordinated Science Lab, University of Illinois at Urbana-Champaign

Motion planning and coordination are key technological problems in the development of dexterous and autonomous robotic systems. This talks presents analysis and design methodologies that build on concepts from dynamical systems, nonlinear control theory, and differential and computational geometry. For single vehicle systems, we review three sets of results: (1) the notion of kinematic controllability and its application in planning problems, (2) a novel comprehensive approach to perturbation analysis for nonlinear control systems, and (3) a power series approach to motion planning and optimization. For multi-vehicle networks, we introduce decentralized control laws for the coordination of multiple agents performing spatially distributed sensing tasks.