A Decentralized and Adaptive Flocking Algorithm for Autonomous Mobile Robots

Abstract

Recently, flocking of a group of mobile robots is gained a lot of attentions due to its wide applications, such as manufacturing, surveillance and space exploration. It is necessary for all robots to adapt to the complex environment during flocking. In this paper, we propose a decentralized flocking algorithm, which can avoid collision between a robot and its neighbors and the collision between robots and obstacles when there are obstacles in the environment. By simulation results, we find this algorithm can effectively achieve the goal of collision avoidance.