Motion planning of human-like robots using constrained coordination

We present a whole-body motion planning algorithm for human-like robots. The planning problem is decomposed into a sequence of low-dimensional sub-problems. Our formulation is based on the fact that a human-like model is a tightly coupled system and we use a constrained coordination scheme to solve the sub-problems in an incremental manner. We also present a local path refinement algorithm to compute collision-free paths in tight spaces and satisfy the statically stable constraint on CoM. We demonstrate the performance of our algorithm on an articulated human-like model and generate efficient motion strategies in complex CAD models.