A hierarchical and adaptive mobile manipulator planner

We present a Hierarchical and Adaptive Mobile Manipulator Planner (HAMP) that plans for both the base and the arm in a judicious manner - allowing the manipulator to change its configuration autonomously when needed if the current arm configuration is in collision with the environment as the mobile manipulator moves along the planned path. This is in contrast to current implemented approaches that are conservative and fold the arm into a fixed home configuration. Our planner first constructs a base roadmap and then for each node in the roadmap it checks for collision status of current manipulator configuration along the edges formed with adjacent nodes, if the current manipulator configuration is in collision, the manipulator C-space is searched for a new reachable configuration such that it is collision-free as the mobile manipulator moves along the edge. We show that HAMP is probabilistically complete. We compared HAMP with full 9D PRM and observed that HAMP outperforms the full 9D PRM in each of the performance criteria, i.e., computational time, percentage of successful attempts, base path length, and most importantly, undesired motions of the arm.