Efficient task coordination is an important problem in multi-robot systems. Explicit programming of each robot to perform specific tasks (ex. cleaning) is too cumbersome and inefficient as the areas to serve in a map may vary with time. Moreover, the number of the robots available 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 same areas of the map, which is a waste of computation and resources. Hence, there is a need for a simpler scheme for autonomous task coordination of multiple robots without the need of explicit programming. This paper presents a bio-inspired algorithm, which uses the repelling behavior of pheromones for autonomous task coordination. The proposed algorithm uses a node representation of the navigational paths, and integrates the pheromone signaling mechanism in robot localization which allows the robots to capture areas or sub-areas of the map so that there is efficient task coordination, and robots work without interruption from other robots. We show through experiments that the proposed scheme enables multiple service robots to perform cooperative tasks intelligently without any explicit programming.
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A Bio-Inspired Algorithm for Autonomous Task Coordination of Multiple Mobile Robots
Published: 14 November 2018 by MDPI in 5th International Electronic Conference on Sensors and Applications session Sensors networks
Keywords: Multi-robot system; robot task coordination; bio-inspired algorithm, robots in sensor networks