Planning Motions Compliant to Complex Contact States

Many robotic tasks require compliant motions, but planning such motions pose special challenges not present in collision-free motion planning. One challenge is how to achieve exactness, i.e., how to make sure that a planned path is exactly compliant to a desired contact state, especially when the con guration manifold of such a contact state is hard to describe analytically due to high geometrical complexity and/or high dimensionality. We tackle the problem with a hybrid approach of direct exploitation of contact constraints and randomized planning. We particularly focus on planning motion that maintains certain contact state or contact formation (CF), called a CF-compliant motion, since a general compliant motion is a sequence of such CF-compliant motions with respect to di erent CFs. In this paper, we describe a randomized planner for planning CF-compliant motion between two arbitrary polyhedral solids, extending the PRM paradigm [9] for planning collision-free motion to the space of contact con gurations. Key to our approach is a novel sampling strategy to generate random CF-compliant con gurations. We also present and discuss examples of sampling and planning results.