Analysis and Control in Obstacle Clustering by Distributed Autonomous Robots

Abstract

In this paper, we discuss some phenomena of obstacle clustering by distributed autonomous robots, in the light of space-discretization (or cellular automata) approach. This work was motivated by Swiss Robots which collect scattered obstacles into some clusters without any global information nor intelligent concentrated controller. Then we define fundamental event rules in this cellular world, and introduce two types of local rules for robot action: one is the Push & Turn rule, which can collect obstacles, the other is Pull & Turn rule, which can scatter obstacles. By defining several indices (ratio of immobile obstacles, ratio of moved obstacles), we investigate the dynamic equilibrium of obstacle clustering by heterogeneous agents. And, this paper also presents a control method of ratio of immobile obstacles from the estimation of each robot's local information even if all the states of obstacles cannot be measured.