Abstract. Imitation learning is a powerful approach to humanoid behavior generation, however, the most existing methods assume the availability of the information on the internal s...
— We present an algorithm that probabilistically covers a bounded region of the state space of a nonlinear system with a sparse tree of feedback stabilized trajectories leading t...
Abstract— We provide a method for planning under uncertainty for robotic manipulation by partitioning the configuration space into a set of regions that are closed under complia...
Abstract— This paper presents the Discrete Search Leading continuous eXploration (DSLX) planner, a multi-resolution approach to motion planning that is suitable for challenging p...
— We consider motion planning problems for a vehicle with kinodynamic constraints, where there is partial knowledge about the environment and replanning is required. We present a...