FORMATION DRIVING USING PARTICLE SWARM OPTIMIZATION AND REACTIVE OBSTACLE AVOIDANCE

This paper presents a new leader following approach for a formation of carlike robots. The path planning problem is solved for the leader with optimized spline functions, which are generated by an evolutionary technique called particle swarm optimization. Because of the expansion of the formation, a collision free path is not guaranteed for the following vehicles. In our approach the followers reactively avoid collisions with path-blocking obstacles and also with other robots within the formation. The developed algorithms have been tested intensively in various simulations.