Towards reactive whole-body motion planning in cluttered environments by precomputing feasible motion spaces

To solve complex whole-body motion planning problems in near real-time, we think it essentials to precompute as much information as possible, including our intended movements and how they affect the geometrical reasoning process. In this paper, we focus on the precomputation of the feasibility of contact transitions in the context of discrete contact planning. Our contribution is two-fold: First, we introduce the contact transition and object (CTO) space, a joint space of contact states and geometrical information. Second, we develop an algorithm to precompute the decision boundary between feasible and non-feasible spaces in the CTO space. This boundary is used for online-planning in classical contact-transition spaces to quickly prune the number of possible future states. By using a classical planning setup of A* together with a l2-norm heuristic, we demonstrate how the prior knowledge about object geometries can achieve near real-time performance in highly-cluttered environments, thereby not only outperforming the state-of-the-art algorithm, but also having a significantly lower model sparsity.