A Bio-Inspired Algorithm for Autonomous Task Coordination of Multiple Mobile Robots

Abstract

Efficient task co-ordination is an important problem in multirobot systems. The explicit programming of each robot to perform specific tasks (e.g., cleaning) is too cumbersome and inefficient, as the areas to serve in a map may vary with time. Moreover, the number of available robots to serve may also vary, as some of the robots may be charging and not available. Improper task division can cause two or more robots to serve the same areas of the map, which is a waste of computation and resources. Hence, there is a need for a simpler scheme for the autonomous task co-ordination of multiple robots without the need for explicit programming. This paper presents a bioinspired algorithm that uses the attractive and repelling behavior of pheromones for autonomous task co-ordination. The proposed algorithm uses a node representation of navigational paths for autonomous exploration. This repelling mechanism also allows robots to capture areas or subareas of the map so that there is efficient task co-ordination, and robots work without interruption from other robots. We show through experiments that the proposed scheme enables multiple service robots to intelligently perform co-operative tasks without any explicit programming or commands.