Hierarchical Optimization-based Planning for High-DOF Robots

We present an optimization-based motion planning algorithm for high degree-of-freedom (DOF) robots in dynamic environments. Our formulation decomposes the highdimensional motion planning problem into a sequence of low-dimensional sub-problems. We compute collision-free and smooth paths using optimization-based planning and trajectory perturbation for each sub-problem. The high-DOF robot is treated as a tightly coupled system, and we use constrained coordination in an incremental manner to plan its motion. We highlight the performance on robots with tens of DOFs and demonstrate performance benefits over prior methods.