Dual-Loop Iterative Optimization for Coarse Reference Path With Obstacle Avoidance

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Abstract

Path planning is the core technique for mobile robots, and how to optimize and handle coarse reference path is an important part of robot motion planning. This paper presents a global path optimization algorithm based on a dual-loop iterative framework, focusing on the challenges of optimizing and avoiding obstacles for coarse reference paths in complex environments. The dual-loop iterative optimization framework incorporates slack variables to address the issues of path smoothness and safety optimization. Both simulation and real-world experimental results demonstrate that the proposed algorithm significantly surpasses traditional search-based or sampling-based methods in terms of path smoothness, obstacle avoidance performance, and computational efficiency. The work provides valuable insights and a practical foundation for mobile robot navigation path optimization.

Original languageEnglish
Title of host publicationProceedings of the 44th Chinese Control Conference, CCC 2025
EditorsJian Sun, Hongpeng Yin
PublisherIEEE Computer Society
Pages3301-3306
Number of pages6
ISBN (Electronic)9789887581611
DOIs
Publication statusPublished - 2025
Externally publishedYes
Event44th Chinese Control Conference, CCC 2025 - Chongqing, China
Duration: 28 Jul 202530 Jul 2025

Publication series

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

Conference

Conference44th Chinese Control Conference, CCC 2025
Country/TerritoryChina
CityChongqing
Period28/07/2530/07/25

Keywords

  • Curvature corridor
  • Dual-loop iterative optimization framework
  • Obstacle-separating hyperplane

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