Distributed deformable configuration control for multi-robot systems with low-cost platforms

This work presents a deformable configuration controller-a fully distributed algorithm that enables a swarm of robots to avoid an obstacle while maintaining network connectivity. We assume a group of robots flocking in an unknown environment, each of which has only incomplete knowledge of the geometry without a map, a shared coordinate, or the use of a centralized control scheme. Instead, the controller requires only local information about the area around individual robots. We devise a phase transition machine, which designs overall obstacle avoidance procedures in a fully distributed way. Robots in collision with an obstacle distributively measure the topology of the sensor network formed by the robots in order to estimate the shape of the obstacle, and choose a motion model, either obstacle-detouring or bouncing-off, each of which deforms the network to avoid an obstacle without knowledge of the geometry around the obstacle. The robots then sense the maximum tree angle, which detects the straightness of a configuration to ensure the completion of the obstacle avoidance procedure, and perform flocking with a modified heading consensus to reconstruct a volumed network with their original headings. We provide theoretical performance analyses of the controller. We also validate the theoretical results by multiple simulations with a swarm with various population sizes.