Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms

• Published in: 水下无人系统学报 Vol. 33; no. 3; pp. 410 - 419
• Main Authors: Yuhong MA, Wen PANG, Daqi ZHU
• Format: Journal Article
• Language: Chinese
• Published: Science Press (China) 01.06.2025
• Subjects: autonomous undersea vehicle; fluid disturbance algorithm; multi-target; path planning; travelling salesman problem; whale optimization algorithm
• ISSN: 2096-3920
• DOI: 10.11993/j.issn.2096-3920.2025-0054

To address the challenges of low path planning efficiency for autonomous undersea vehicle(AUV) in multi-target environments, as well as the limitations of the traditional whale optimization algorithm(WOA) in terms of susceptibility to local optima and inadequate adaptability to three-dimensional obstacle avoidance requirements, this study proposed a collaborative planning strategy that integrated a fluid perturbation algorithm with an improved WOA. A hybrid population initialization method was developed by combining chaotic mapping to generate high-coverage initial solutions and a greedy algorithm to construct locally optimal sequences, effectively addressing the issue of poor solution quality caused by random initialization in traditional WOA. For the discrete characteristics of the traveling salesman problem(TSP), a discrete position update strategy based on random insertion and local inversion was proposed, significantly enhancing the algorithm’s capability to escape from local optima. An elite retention m