@inproceedings{c6ad015214bb4ef4809b5cde1e35ab99,
title = "FVFH: An Improved Navigation Algorithm for UGVs in the Complex Disaster Environment",
abstract = "The problem of navigation by unmanned ground vehicles (UGVs) in disaster areas is widely investigated. An environmental simulation model of disaster areas is established in order to solve this problem. The Focus Vector Field Histogram (FVFH) navigation algorithm for UGVs is designed: 1) A screening mechanism for the moving direction of the UGV is proposed; 2) The dynamic constraints of realistic UGVs are considered. The performance of the algorithm is tested on the Gym and CoppeliaSim platforms. The experimental results show that the FVFH algorithm can effectively shorten the planning time and navigation paths, and overcome special terrain obstacles with a high navigation success rate. Thus, the FVFH algorithm is helpful for navigation in complex disaster environment.",
keywords = "Complex Environment Modeling, FVFH, Path Planning, UGV",
author = "Nengwei Xu and Kun Yang and Chen Chen",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 China Automation Congress, CAC 2023 ; Conference date: 17-11-2023 Through 19-11-2023",
year = "2023",
doi = "10.1109/CAC59555.2023.10450252",
language = "English",
series = "Proceedings - 2023 China Automation Congress, CAC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4360--4365",
booktitle = "Proceedings - 2023 China Automation Congress, CAC 2023",
address = "United States",
}