@inproceedings{ff155b229cbd4a9781ecfdff63648478,
title = "Local path planning for off-road environment considering terrian and obstacle risk field",
abstract = "Off-road environment with complex road terrain and obstacles brings great difficulties to autonomous navigation of unmanned vehicles. In order to improve the safety of vehicles traveling on unstructured road, this paper proposes a dynamic planning algorithm integrating the artificial potential field(DP-APF) and a path optimization method. Firstly, the risk potential fields of obstacles and undulating areas are established, and the avoidance of obstacles and undulating terrain is realized by combining the dynamic planning algorithm. Secondly, in order to further improve the path quality, the optimal local path for vehicle tracking is obtained by convex optimization method combined with vehicle kinematic constraints.",
keywords = "Off-road, optimization, path planning, potential field, undulating terrain",
author = "Yingjie Song and Lijin Han and Hongcai Li and Shida Nie and Congshuai Guo and Yujia Xie and Ke Chen",
note = "Publisher Copyright: {\textcopyright} 2024 ACM.; 3rd International Symposium on Control Engineering and Robotics, ISCER 2024 ; Conference date: 24-05-2024 Through 26-05-2024",
year = "2024",
month = may,
day = "24",
doi = "10.1145/3679409.3679445",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "181--186",
booktitle = "Proceedings of 2024 3rd International Symposium on Control Engineering and Robotics, ISCER 2024",
}