VARIABLE PATROL PLANNING OF MULTI-ROBOT SYSTEMS BY A COOPERATIVE AUCTION SYSTEM

Abstract

A cooperative auction system (CAS) is proposed to solve the large-scale multi-robot patrol planning problem. Each robot picks its own patrol points via the cooperative auction system and the system continuously re-auctions, based on the team work performance. The proposed method not only works in static environments but also considers variable path planning when the number of mobile robots increases or decreases during patrol. From the results of the simulation, the proposed approach demonstrates decreased time complexity, a lower routing path cost, improved balance of workload among robots, and the potential to scale to a large number of robots and is adaptive to environmental perturbations when the number of robots changes during patrol.