Collision avoidance in a multiple-robot system using intelligent control and neural networks

A new hierarchical collision avoidance scheme is proposed to coordinate multiple robots in a common workspace by combining the techniques of intelligent control and neural networks (NNs). The high level in the hierarchy is formed by a knowledge-based coordinator (KBC) and an NN-based predictor, and the low level consists of the robots to be coordinated. The authors state the problem of coordinating multiple robots for collision avoidance and the basic principles of the KBC. The knowledge acquisition and representation of collision detection and avoidance for both cylindrical- and revolute-type robots are discussed. Design of the NN-based predictor and the KBC is summarized. The proposed scheme was tested extensively via simulations for both types of robots, showing promising performance