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Obstacle Avoidance Control Method for High-Speed Aircraft Cluster Intelligent Formation Under Hierarchical Control Framework

  • Yanyang Hu
  • , Wenjiang Yu
  • , Chengchao Bai*
  • *Corresponding author for this work

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

Abstract

To address the safety issues faced by high-speed UAV swarms during formation flight in densely obstructed areas, we propose an intelligent swarm formation control framework that combines constrained A* path planning with deep reinforcement learning. A high-speed UAV swarm model is established, and an obstacle model considering the volume of the swarm is designed. Continuous planned flight trajectories are obtained by truncating path points. A reward function is designed based on the relative position and velocity relationships between UAVs, between UAVs and the target, and between UAVs and obstacles. The lower-level distributed formation intelligent controller is trained using this reward function. Simulation experiments demonstrate the effectiveness of this hierarchical control framework.

Original languageEnglish
Title of host publicationProceedings of 4th 2024 International Conference on Autonomous Unmanned Systems, 4th ICAUS 2024
EditorsLianqing Liu, Yifeng Niu, Wenxing Fu, Yi Qu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages412-422
Number of pages11
ISBN (Print)9789819635511
DOIs
StatePublished - 2025
Event4th International Conference on Autonomous Unmanned Systems, ICAUS 2024 - Shenyang, China
Duration: 19 Sep 202421 Sep 2024

Publication series

NameLecture Notes in Electrical Engineering
Volume1374 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference4th International Conference on Autonomous Unmanned Systems, ICAUS 2024
Country/TerritoryChina
CityShenyang
Period19/09/2421/09/24

Keywords

  • A-star Algorithm
  • Deep Reinforcement Learning
  • Formation Control
  • High Speed Flight Vehicle

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