@inproceedings{b5de4a41b40942bcb6a0874e046de07d,
title = "Multi-UGVs Collaborative Path Planning and Conflicts Eliminating in Emergent Situations",
abstract = "The centralized path planning framework for multi-unmanned vehicles tends to get messy when emergency occurs, creating a series of systemic conflicts and almost impossible to return to normal spontaneously. Thus, this paper improves the Multi-UGVs Collaborative Path Planning system through emergency response planning and system recovery to eliminate the conflicts caused by emergencies. The rapid emergency response planning method is developed based on heuristic search to quickly locate a shelter with a response trajectory without disturbing other normal vehicles for each affected vehicle in real time. And then the affected vehicles can complete recovery process by introducing an asynchronous starting conflict based search (CBS) algorithm. The experiments carried out in Rviz simulation environments prove that the proposed method has good practicability and stability.",
keywords = "Collaborative path planning, Emergency response, Multi-UGVs, System recovery",
author = "Linzhi Zeng and Siyuan Feng and Jining Liu and Wenjie Song",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 9th International Conference on Automation, Robotics and Applications, ICARA 2023 ; Conference date: 10-02-2023 Through 12-02-2023",
year = "2023",
doi = "10.1109/ICARA56516.2023.10125885",
language = "English",
series = "2023 9th International Conference on Automation, Robotics and Applications, ICARA 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "273--277",
booktitle = "2023 9th International Conference on Automation, Robotics and Applications, ICARA 2023",
address = "United States",
}