A probabilistic algorithm for manipulation planning under continuous grasps and placements

An important skill of autonomous robots is the ability to carry out manipulation tasks. The solution to a manipulation problem generally consists in a sequence of elementary paths where an object is moved by a robot or it stays at a stable placement while the robot performs a re-grasping motion. Most existing planners require a finite set of configurations to achieve this task decomposition. We recently proposed an approach to automatically compute such intermediate configurations from continuous sets of stable placements and possible grasps of the movable object. This paper describes an improved algorithm based on this approach. It also presents several complex manipulation problems that illustrate the efficiency of the planner.