Probabilistically complete kinodynamic planning for robot manipulators with acceleration limits

We introduce acceleration-limited planning for manipulators as a middle ground between pure geometric planning and planning with full robot dynamics. It is more powerful than geometric planning and can be solved more efficiently than planning with full robot dynamics. We present a probabilistically complete RRT motion planner that considers joint acceleration limits and potentially non-zero start and goal velocities. It uses a fast, non-iterative steering method. We demonstrate both the power and efficiency of our planner using the problem of hitting a nail with a hammer, which requires the robot to reach a given goal velocity while avoiding obstacles. Our planner is able to solve this problem in less than 100 ms. In contrast, a purely geometric planner is unable to hit the nail at the desired velocity, whereas a standard kinodynamic RRT is multiple orders of magnitude slower.