Performance Optimisation of Mobile Robots for Search-and-Rescue

Abstract

This paper presents a team performance optimisation system for multiple mobile robots in search-and-rescue operations, in which refugees are first discovered and subsequently robots are dispatched to transport themto shelters. Coordination of mobile robots involves two fundamental issues, namely task allocation and motion planning. While task allocation assigns jobs to robots, motion planning generates routes for robots to execute the assigned jobs. Task allocation and motion planning together play a pivotal role in optimisation of the robot team performance. These two issues become more challenging in dynamic search-and-rescue environments, where the refugees are unpredictably discovered at different locations and the traffic conditions of rescue zones keep changing. Weaddress these two issues by proposing an auction-based closed-loop module for task allocation and a bio-inspired intelligent module for motion planning. The task allocation module is characterised with a closed-loop bid adjustment mechanism to improve the bid accuracy even in light of stochastic rescue requests. The motion planning module is bio-inspired intelligent in that it features detection of imminent neighbours and responsiveness of virtual force navigation in dynamic traffic conditions. Simulations show that the proposed system is a practical tool to optimise the dynamic operations of search-and-rescue by a team of mobilerobots.