A Distributed Hunting Approach for Multiple Autonomous Robots

Abstract

A novel distributed hunting approach for multiple autonomous robots in unstructured mode-free environments, which is based on effective sectors and local sensing, is proposed in this paper. The visual information, encoder and sonar data are integrated in the robot's local frame, and the effective sector is introduced. The hunting task is modelled as three states: search state, round-obstacle state, and hunting state, and the corresponding switching conditions and control strategies are given. A form of cooperation will emerge where the robots interact only locally with each other. The evader, whose motion is a priori unknown to the robots, adopts an escape strategy to avoid being captured. The approach is scalable and may cope with problems of communication and wheel slippage. The effectiveness of the proposed approach is verified through experiments with a team of wheeled robots.