Humanoid Mobile Manipulation Using Controller Refinement

摘要

An important class of mobile manipulation problems are "move-to-grasp" problems where a mobile robot must navigate to and pick up an object. One of the distinguishing features of this class of tasks is its coarse-to-fine structure. Near the beginning of the task, the robot can only sense the target object coarsely or indirectly and make gross motion toward the object. However, after the robot has located and approached the object, the robot must finely control its grasping contacts using precise visual and haptic feedback. This paper proposes that move-to-grasp problems are naturally solved by a sequence of controllers that iteratively refines what ultimately becomes the final solution. This paper introduces the notion of a refining sequence of controllers and defines it in terms of controller goal regions and domains of attraction. Refining sequences are shown to be more robust than other types of controller sequences. In addition, a procedure for converting a refining sequence into an equivalent "parallelized" controller is proposed. Executing this parallelized controller confers all the advantages of iteratively executing the controllers sequentially. The approach is demonstrated in a move-to-grasp task where Robonaut, the NASA/JSC dexterous humanoid, is mounted on a mobile base and navigates to and picks up a geological sample box