Cooperative Motion of Swarm Mobile Robots Based on Particle Swarm Optimization and Multibody System Dynamics

This paper addresses the problem of cooperative motion of a swarm mobile robotic system with the purpose of searching a target in a complicated environment. The solution is inspired from Particle Swarm Optimization (PSO) and combined with multibody system dynamics which also includes the consideration of robots' physical properties like mass, inertia, force, acceleration, etc. The entire robot swarm is mainly guided by this physical PSO and an independent obstacle avoidance module is active when robots encounter any conflicts during missions. This paper considers an artificial swarm mobile robot system to perform searching tasks and each member of the system may interact with its neighbors or the environment by limited local communication ability. Several groups of simulations are set up for the verification of the strategy and the results show that this method creates the desired behavior well. The simulation experiments also investigate the feature of fault tolerance of this strategy. Finally, a framework for the future application on real robots is briefly discussed.