Kinematic Control of Multiple Manipulators Collaborative Handling System

This paper proposes a dynamic-neural-network based kinematic controller for multi-robot collaborative handling systems. Due to the closed chain structure of multi robot systems and the physical constraints of the robot system, the kinematic modeling and controller design become very challenging. In this regard, based on the relative position of the robot end effector to the common payload, a kinematic model between the load and joint motion of each robot is derived. Furthermore, combined with inequality modeling of the system’s physical constraints, a dynamic programming type problem model is constructed that takes into account system motion performance optimization, load centroid trajectory tracking, and physical constraints. Then a model driven dynamic neural network is designed. The effectiveness of the proposed algorithm was verified through simulation of a planar dual robotic arm.