Market-Based Task Allocation in a Multi-robot Surveillance System

Abstract

This paper presents a market-based cooperation strategy for task allocation in a multi-robot system oriented to surveillance tasks. A global grid-based map is used by the robots in order to share information about recently visited cells, where each cell represents a task to be done. Here the concept of stigmergy is applied, where each cell value represents the concentration of pheromone left by the robots. In order to reduce computational load, groups of tasks are being formed using K-means for the task decomposition phase, and a market-based algorithm is executed in order to assign each task to a robot. The strategy has been evaluated in a simulated environment using up to three robots.