@inproceedings{1510871349e941d1afeeca94ec788a33,
title = "Three-Dimensional Path Planning of UAV Based on Improved Artificial Potential Field",
abstract = "In order to find a safe path for Unmanned Aerial Vehicle (UAV) in forest fires, a global path planning method based on improved artificial potential field (APF) is proposed. This method applies the grid model to model threats in three-dimensional space; then uses the target as the source of gravity to establish a gravitational field, and the threat as the source of repulsion to establish a repulsive field. At the same time, it improves the modeling of gravitational and repulsive fields to overcome the disadvantages of the traditional artificial potential field; then with dynamic obstacle avoidance, the UAV can quickly escape the threat of dynamic obstacles. Simulation results prove that this method can get the optimal route in a given environment.",
keywords = "UAV, artificial potential field, obstacle avoidance, path planning",
author = "Haitao Xie and Yaohong Qu and Guangpei Fan and Xiaoping Zhu",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9549529",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "7862--7867",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
}