Three-Dimensional Path Planning of UAV Based on Improved Artificial Potential Field

Haitao Xie, Yaohong Qu, Guangpei Fan, Xiaoping Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the 40th Chinese Control Conference, CCC 2021
EditorsChen Peng, Jian Sun
PublisherIEEE Computer Society
Pages7862-7867
Number of pages6
ISBN (Electronic)9789881563804
DOIs
StatePublished - 26 Jul 2021
Event40th Chinese Control Conference, CCC 2021 - Shanghai, China
Duration: 26 Jul 202128 Jul 2021

Publication series

NameChinese Control Conference, CCC
Volume2021-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference40th Chinese Control Conference, CCC 2021
Country/TerritoryChina
CityShanghai
Period26/07/2128/07/21

Keywords

  • UAV
  • artificial potential field
  • obstacle avoidance
  • path planning

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