A centroidal Voronoi tessellation based intelligent control algorithm for the self-assembly path planning of swarm robots

Swarm robots have been an active topic in the field of intelligent machines in recent years. Self-assembly is an important function of swarm robots that provides an effective way for building different kinds of configurations by autonomous docking. For a self-assembly process, the path planning control is a key technique. The present paper proposes a CVT (Centroidal Voronoi Tessellation) based intelligent control algorithm for the self-assembly path planning. It can enable swarm robots to move from an initial virtual region into the target virtual region by a synchronous collaborative scheduling method. Matlab simulations are performed on the self-assembly control of three typical configurations including the line-shape, cross-shape and H-shape. The time consumption is compared under different error conditions, the effectiveness of the new algorithm is validated and its limitation is also pointed out. Overall, this algorithm provides a promising way for the intelligent control of self-assembly path planning of swarm robots.