ARTIFICIAL IMMUNE NETWORK-BASED MULTI-ROBOT FORMATION PATH PLANNING WITH OBSTACLE AVOIDANCE

Abstract

Artificial immune network algorithm (AINA) combined with position tracking control method is used for multi-robot formation path planning. The proposed algorithm avoids obstacles and recovers formation for follower robot after passing around obstacles. Different methods are adopted to calculate the steering direction and the linear velocity of the follower robot. Steering direction of the follower robot is computed with AINA. AINA has abilities of selfrecognition and diversity, and solves the problems of local minima and immature convergence. The optimal steering direction selected with AINA quickly tends towards the steering direction of leader robot, and successfully avoids obstacles. The linear velocity of follower robot is computed with position tracking control method.