@inproceedings{ce87fbd56dc345ceb2625ee887996bfe,
title = "Hierarchical Path Planning and Obstacle Avoidance Control for Unmanned Surface Vehicle",
abstract = "It is necessary to plan a feasible path and avoid moving obstacles in real time, while the unmanned surface vehicle (USV) performs tasks in the archipelago environment. This paper focuses on the obstacle avoidance of USV in dynamic environment. A hierarchical framework is proposed for the underactuated dynamic system of USV. Devolution of the dynamic obstacle avoidance from planner to controller is more effective. Rapidly-exploring Random Trees Star is used as a global planner to search for a feasible path, combined with a reactive approach to modulate the control input to avoid moving obstacles in real time. The feasibility of the proposed method is verified by the numerical simulation, which can improve the real-time performance of dynamic obstacle avoidance. Different from the replanning, we adjust the controller to avoid local collision, while adopt the planner to generate a global path.",
keywords = "Collision avoidance, Dynamic obstacle, Motion planning, Unmanned surface vehicle",
author = "Hongbao Du and Zhengjie Wang and Zhide Zhang and Qiaoyi Li",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th International Conference on Mechatronics, Robotics and Automation, ICMRA 2021 ; Conference date: 22-10-2021 Through 24-10-2021",
year = "2021",
doi = "10.1109/ICMRA53481.2021.9675500",
language = "English",
series = "2021 4th International Conference on Mechatronics, Robotics and Automation, ICMRA 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "134--138",
booktitle = "2021 4th International Conference on Mechatronics, Robotics and Automation, ICMRA 2021",
address = "United States",
}