@inproceedings{ghassemi2019decmrta,
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.},
address = {New Brunswick, NJ},
archivePrefix = {arXiv},
arxivId = {1907.04394},
author = {Ghassemi, Payam and DePauw, David and Chowdhury, Souma},
booktitle = {2019 International Symposium on Multi-Robot and Multi-Agent Systems (MRS)},
doi = {10.1109/MRS.2019.8901062},
eprint = {1907.04394},
file = {:C$\backslash$:/Users/payamgha/Box/Payam/iPublication/Conference/ghassemi2019decmrta.pdf:pdf},
isbn = {978-1-7281-2876-4},
keywords = {Conference,Swarm},
mendeley-tags = {Conference,Swarm},
month = {aug},
pages = {83--85},
publisher = {IEEE},
title = {{Decentralized Dynamic Task Allocation in Swarm Robotic Systems for Disaster Response: Extended Abstract}},
url = {http://arxiv.org/abs/1907.04394 https://ieeexplore.ieee.org/document/8901062/},
year = {2019}
}