@inproceedings{4172e6a35414472abda02e025f4657a7,
title = "A Multi-Robot Planning Algorithm with Quad Tree Map Division for Obstacles of Irregular Shape",
abstract = "This paper proposes an algorithm to improve the efficiency of the multi-robot system in simulated global information map containing obstacles. The designed multi-AGV scheduling algorithm is based on an optimal shortest path algorithm with the combination of the waiting mode and motion coordination. The proposed shortest path algorithm not only has lower time delay but also decreases the possibility of collision of the multi-robot system. In addition, simulated global information maps are established to test the efficacy of the algorithm.",
keywords = "Robot planning, collision avoidance, scheduling optimization, shortest path algorithm",
author = "Tongpo Zhang and Chenyuan Li and Xu(Judy) Zhu and Enggee Lim and Fei Ma and Limin Yu",
note = "Funding Information: This research was funded by Research Enhancement Fund of XJTLU (REF-19-01-04), National Natural Science Foundation of China (NSFC) (Grant No. 61501380), and by AI University Research Center (AI-URC) and XJTLU Laboratory for Intelligent Computation and Financial Technology through XJTLU Key Programme Special Fund (KSF-P-02). Publisher Copyright: {\textcopyright} 2022 The authors and IOS Press.",
year = "2022",
doi = "10.3233/FAIA220007",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "24--32",
editor = "Jain, {Lakhmi C.} and Balas, {Valentina Emilia} and Qun Wu and Fuqian Shi",
booktitle = "Design Studies and Intelligence Engineering",
}