| Many robotic tasks require
compliant motions, but planning such motions poses special challenges not
present in collision-free motion planning. One challenge is how to achieve
exactness, that is, how to make sure that a planned path is exactly compliant
to a desired contact state, especially when the configuration manifold of
such a contact state is hard to describe analytically due to high geometrical
complexity and/or high dimensionality. The authors tackle the problem with
a hybrid approach of direct exploitation of contact constraints and randomized
planning. They particularly focus on planning motion that maintains certain
contact state or contact formation (CF), called a CF-compliant motion, because
a general compliant motion is a sequence of such CF-compliant motions with
respect to different CFs. This paper describes a randomized planner for
planning CF-compliant motion between two arbitrary polyhedral solids, extending
the probabilistic roadmap paradigm for planning collision-free motion to
the space of contact configurations. Key to this approach is a novel sampling
strategy to generate random CF-compliant configurations. The authors also
present and discuss examples of sampling and planning results. |
