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Path Planning based on Artificial Potential Field with Particle Swarm Optimization

  • Beihang University

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

Abstract

The artificial potential field method is commonly utilized in path planning, with its basic idea resembling an electromagnetic field. However, traditional artificial potential field methods suffer from issues such as unreachable targets and easily falling into local minima. To address these limitations, this paper proposes an enhanced artificial potential field method. It proposes an improved repulsive potential field function, which effectively resolves the problem of unreachable targets, and incorporates a road potential field, significantly enhancing the practicality of the algorithm. A fused particle swarm artificial potential field method is proposed, which solves the local optimum problem and improves the search efficiency. The proposed algorithm is subsequently validated using MATLAB, and the experimental results demonstrate that it effectively addresses the aforementioned challenges and plans a collision - free, safe path.

Original languageEnglish
Title of host publicationProceedings of the 37th Chinese Control and Decision Conference, CCDC 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4061-4066
Number of pages6
ISBN (Electronic)9798331510565
DOIs
StatePublished - 2025
Event37th Chinese Control and Decision Conference, CCDC 2025 - Xiamen, China
Duration: 16 May 202519 May 2025

Publication series

NameProceedings of the 37th Chinese Control and Decision Conference, CCDC 2025

Conference

Conference37th Chinese Control and Decision Conference, CCDC 2025
Country/TerritoryChina
CityXiamen
Period16/05/2519/05/25

Keywords

  • artificial potential field method
  • particle swarm algorithm
  • path planning

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