Real-Time Motion Planning for a Volleyball Robot Task Based on a Multi-Agent Technique

This paper takes the volleyball robot task as an example of a dynamic manipulation task and presents a multi-agent-based motion-planning framework for it. Each subtask in the motion planning is defined as an agent. The motion planning is accomplished by the solution of each agent activated by a blackboard. It is convenient to extend the module and enable real-time control compared to the hierarchy and subsumption architecture. In the solution of each subtask, one difference from the motion planning of other ball-playing robots is that simple fuzzy rules are adopted to determine the hitting position, which leads to smaller hitting velocities beneficial for task control. The other difference is that the task-based directional manipulability measure (TDMM) is used to optimize the robot configuration on the basis of optimal hitting path, so as to improve the manipulating ability on task direction. The simulation of a planar three-link manipulator ball-hitting task is implemented by the MATLAB/Simulink tool. The virtual target of the hitting motion is validated on the ABB manipulator by the ball-catching experiment.