Motion Planning of Robot Arm with Rotating Table for a Multiple-Goal Task

Motion planning of a manipulator system is important when using it to complete a task. In this study, we consider a manipulator system with a robot arm and a rotating table for a multiple-goal task. We first assign the goals around the object into several clusters based on the face in the geometric shape of the object. And then search for the shortest path for the goals in a cluster by coordinating the motion of robot arm and the motion of rotating table based on the particle swarm optimization (PSO). Finally connect the paths found in each cluster. The collisions between the components of the manipulator system is taken into account. The proposed method is compared to a method that only uses nearest neighborhood algorithm (NNA) to coordinate the motion of the robot arm and the rotating table. The effectiveness of the proposed method is verified through a simulation with a set of tasks.