Solving the 3D Multi-Objective Dynamic AUV Path Planning Problem Based on the Improved Morphin-Altruistic NSGAII Algorithm - Man Zhang; Jianhong Chen; Haibin Ouyang; Shangbin Long; Steven Li; Chunliang Zhang; Weiping Ding; Essam H. Houssein (Engineering Science and Technology, an International Journal, 2025)
As ocean exploration delves deeper, autonomous underwater vehicles (AUVs) have become essential tools for ocean missions. Dynamic path planning seeks to find an optimal path for AUVs from a start point to the target while avoiding collisions with moving obstacles. However, current dynamic path planning faces several challenges such as three-dimensional environments and multi-objective problems, resulting in impractical solutions. To address these challenges, this paper proposes improved Morphin-Altruistic Nondominated Sorting Genetic Algorithm II (ANSGAII). More specifically, contributions presented in this paper are as follows: (1) An improved Three-dimension multi-objective path planning model is proposed, which incorporates depth considerations and simultaneously optimises for path length, safety, and smoothness. An enhanced path collision detection mechanism is also designed. (2) The ANSGAII, inspired by altruism in animal populations, is proposed to enhance optimisation efficiency and reduce computational load by transferring update opportunities from the weak to the strong individuals. (3) The best path is selected based on weighted criteria, and the Morphin algorithm is utilised to timely get around dynamic dangers. Experimental results demonstrate that the paths generated by the improved Morphin-ANSGAII algorithm better balance the objectives and effectively help AUVs avoid dynamic obstacles.