Decentralized Dynamic Task Allocation in Swarm Robotic Systems for Disaster Response
Abstract
Multiple robotic systems, working together, can provide important solutions to different real-world applications (e.g., disaster response), among which task allocation problems feature prominently. Very few existing decentralized multi-robotic task allocation (MRTA) methods simultaneously offer the following capabilities: consideration of task deadlines, consideration of robot range and task completion capacity limitations, and allowing asynchronous decision-making under dynamic task spaces. To provision these capabilities, this paper presents a computationally efficient algorithm that involves novel construction and matching of bipartite graphs. Its performance is tested on a multi-UAV flood response application.
Cite
@article{arxiv.1907.04394,
title = {Decentralized Dynamic Task Allocation in Swarm Robotic Systems for Disaster Response},
author = {Payam Ghassemi and David DePauw and Souma Chowdhury},
journal= {arXiv preprint arXiv:1907.04394},
year = {2020}
}
Comments
Accepted for poster presentation in (and publication as extended abstract in the proceedings of) The IEEE 2019 International Symposium on Multi-Robot and Multi-Agent Systems (MRS)