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Improved ant colony optimization for safe path planning of AUV.
Ronghua, Meng; Xinhao, Cheng; Zhengjia, Wu.
Afiliação
  • Ronghua M; Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance, China Three Gorges University, Yichang, Hubei, 443002, China.
  • Xinhao C; Intelligent Manufacturing Innovation Technology Center, China Three Gorges University, Yichang, Hubei, 443002, China.
  • Zhengjia W; Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance, China Three Gorges University, Yichang, Hubei, 443002, China.
  • Du Xuan; Intelligent Manufacturing Innovation Technology Center, China Three Gorges University, Yichang, Hubei, 443002, China.
Heliyon ; 10(7): e27753, 2024 Apr 15.
Article em En | MEDLINE | ID: mdl-38560125
ABSTRACT
In order to address the autonomous underwater vehicle navigation challenge for dam inspections, with the goal of enabling safe inspections and reliable obstacle avoidance, an improved smooth Ant Colony Optimization algorithm is proposed for path planning. This improved algorithm would optimize the smoothness of the path besides the robustness, avoidance of local optima, and fast computation speed. To achieve the goal of reducing turning time and improving the directional effect of path selection, a corner-turning heuristic function is introduced. Experimental simulation results show that the improved algorithm performs best than other algorithms in terms of path smoothness and iteration stability in path planning.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article