Multi-target Penetration Path Planning for UAV Swarms Based on Time Synchronization Constraints

Jiusong Feng, Liyuan Fan, Jinwen Hu, Zhao Xu, Junwei Han

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

Abstract

In today’s evolving technology landscape, unmanned aerial vehicles (UAVs) have become a high-profile technology. Although reinforcement learning can successfully solve UAV path planning problems in simple environments, its research is still insufficient for complex tasks with time synchronization constraints. This paper primarily focuses on the rapid penetration strategy planning of UAV swarms against multiple targets. Aiming at the mission requirements of synchronized attacks by UAV swarms, a multi-target collaborative planning strategy for unmanned swarms based on the fusion of time constraints and migration reinforcement learning is proposed. This strategy adds time constraints on the basis of the swarm-to-single-target planning strategy, and achieves the simultaneous arrival of UAV swarms to multiple targets. The reward function of reinforcement learning is improved, and the training method of transfer reinforcement learning is adopted to improve the training efficiency.

Original languageEnglish
Title of host publicationAdvances in Guidance, Navigation and Control - Proceedings of 2024 International Conference on Guidance, Navigation and Control Volume 12
EditorsLiang Yan, Haibin Duan, Yimin Deng
PublisherSpringer Science and Business Media Deutschland GmbH
Pages71-80
Number of pages10
ISBN (Print)9789819622436
DOIs
StatePublished - 2025
EventInternational Conference on Guidance, Navigation and Control, ICGNC 2024 - Changsha, China
Duration: 9 Aug 202411 Aug 2024

Publication series

NameLecture Notes in Electrical Engineering
Volume1348 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Guidance, Navigation and Control, ICGNC 2024
Country/TerritoryChina
CityChangsha
Period9/08/2411/08/24

Keywords

  • Path Planning
  • Penetration
  • Reinforcement Learning
  • UAV

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