Multi-mode sequential flocking strategy integrating wall-following behavior for motion control of multiple mobile robots

Flocking control is gradually attended to coordinates the motions among multiple agents or robots stably based on potential principles. To provide a generic and efficient solution to the local minimum problem encountered within various flocking systems in unexpected and irregular obstacle environment, a design of a multi-model flocking control for multiple mobile robots in terms of behavior-based robotics is presented. Within this framework, animal-imitating wall-following behavior modes are integrated with the new sequential flocking strategy. In this way, the unity of stable aggregation in flocking and efficient obstacle avoidance motion can be efficiently and simultaneously achieved. The simulation studies are comprehensively conducted to show the effectiveness of the proposed method.