@inproceedings{0d81f73950004facbb72cf9a5b4c55ef,
title = "Pareto optimal multi-robot motion planning",
abstract = "This paper studies a class of multi-robot coordination problems where a team of robots aim to reach their goal regions with minimum time and avoid collisions with obstacles and other robots. A novel numerical algorithm is proposed to identify the Pareto optimal solutions where no robot can unilaterally reduce its traveling time without extending others'. The consistent approximation of the algorithm in the epigraphical profile sense is guaranteed using set-valued numerical analysis. Simulations show the anytime property and increasing optimality of the proposed algorithm.",
author = "Guoxiang Zhao and Minghui Zhu",
note = "Funding Information: This work was partially supported by the grant NSF ECCS-1710859. G. Zhao and M. Zhu are with School of Electrical Engineering and Computer Science, Pennsylvania State University, University Park, PA 16802. (email: {gxzhao, muz16}@psu.edu) Publisher Copyright: {\textcopyright} 2018 AACC.; 2018 Annual American Control Conference, ACC 2018 ; Conference date: 27-06-2018 Through 29-06-2018",
year = "2018",
month = aug,
day = "9",
doi = "10.23919/ACC.2018.8431249",
language = "English (US)",
isbn = "9781538654286",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4020--4025",
booktitle = "2018 Annual American Control Conference, ACC 2018",
address = "United States",
}