The Algorithm for UAV Obstacle Avoidance and Route Planning Based on Reinforcement Learning

Jiantong Liu, Zhengjie Wang*, Zhide Zhang

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

An algorithm for UAV collision avoidance based on the reinforcement learning is used for small fixed-wing unmanned aerial vehicles (UAVs). The proposed algorithm realized the obstacle avoidance of UAV in unknown environment and the result is close to the global optimal path. The simulation results show that the collision avoidance algorithm can adapt to various complex environments. Meanwhile, the UAV can quickly get close to the target while avoiding obstacles.

Original languageEnglish
Title of host publicationProceedings of the 11th International Conference on Modelling, Identification and Control, ICMIC 2019
EditorsRui Wang, Zengqiang Chen, Weicun Zhang, Quanmin Zhu
PublisherSpringer
Pages747-754
Number of pages8
ISBN (Print)9789811504730
DOIs
Publication statusPublished - 2020
Event11th International Conference on Modelling, Identification and Control, ICMIC 2019 - Tianjin, China
Duration: 13 Jul 201915 Jul 2019

Publication series

NameLecture Notes in Electrical Engineering
Volume582
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference11th International Conference on Modelling, Identification and Control, ICMIC 2019
Country/TerritoryChina
City Tianjin
Period13/07/1915/07/19

Keywords

  • Collision avoidance
  • Complex environment
  • Reinforcement learning
  • UAV

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