Adaptive Scale-free Behavior Selection for Autonomous Distributed Mobile Robots

Abstract

We previously proposed a search method inspired by the scale-free behavior of living organisms, aiming to devise an effective search behavior for autonomous distributed mobile robots. Scale-free behavior is behavior in which the distance traveled from a given point or the time spent at a given point follow a power distribution. We also proposed a method for each robot to adaptively select between two types of scale-free behavior. However, this adaptive method was not suitable for an autonomous distributed environment in which information can only be shared between geographically local robots. In this paper, we propose an adaptive scale-free behavior selection method suitable for an autonomous distributed environment, and evaluate it through simulations.