Sampling-based motion planning of manipulator with goal-oriented sampling

A sampling-based planning algorithm is one of the most powerful tools for collision avoidance in the motion planning of manipulators. However, this algorithm takes a long time to generate motions of the manipulator. This work proposes a goal-oriented (GO) sampling method for the motion planning of a manipulator. The GO sampling method can identify the initial solution in a shorter time than other sampling-based algorithms, leading to significant improvement in computational efficiency. Based on the GO sampling method, cases involving configuration space and collision checking are implemented based on the proposed equations in the planning of manipulator motion. Different combinations of configuration space settings are mainly analyzed and compared through experiments using a six-degree-of-freedom manipulator.