@inproceedings{fb42984e4b7c4c5fa145373c3422be7c,
title = "UAV Path Planning Simulating Driver's Visual Behavior with RRT algorithm",
abstract = "To solve the problem of long time-consuming and low success rate of UAV path planning in the complex blockage environment, we combine the RRT algorithm with the driver's visual behavior and propose a RRT UAV path planning method simulating driver's visual behavior in this paper. We use the RRT algorithm with fast search capability to expand the nodes and incorporate the UAV's partial constraints into the path planning algorithm. The driver's visual behavior is used to provide visual guidance points for the UAV. Finally, the greedy method is used to process the obtained paths to get a shorter and smoother path. The simulation results show that the proposed algorithm can quickly find a feasible path in complex environment space, which can be used for UAV path planning.",
keywords = "Rapidly-exploring Random Trees, UAV, driver's visual behavior, path planning",
author = "Liguo Tan and Yaohua Zhang and Jianwen Huo and Shenmin Song",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Chinese Automation Congress, CAC 2019 ; Conference date: 22-11-2019 Through 24-11-2019",
year = "2019",
month = nov,
doi = "10.1109/CAC48633.2019.8996233",
language = "英语",
series = "Proceedings - 2019 Chinese Automation Congress, CAC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "219--223",
booktitle = "Proceedings - 2019 Chinese Automation Congress, CAC 2019",
address = "美国",
}