A two-level optimization algorithm for path planning of bionic robotic fish in the three-dimensional environment with ocean currents and moving obstacles. (15th December 2022)

• Record Type: Journal Article
• Authors: Tian, Qunhong; Wang, Tao; Wang, Yunxia; Wang, Zhiwei; Liu, Cuiwei
• Is Part Of: Ocean engineering. Volume 266(2022) Part 3
• Publication Date: 2022-12-15
• Subjects: Bionic robotic fish -- Path planning -- Two-level optimization -- Ocean currents -- Moving obstacles; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2022.112829
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Path planning is not only the premise of underwater navigation and obstacle avoidance, but also the core and key to improve the operation durability for the bionic robotic fish. In this paper, the path length, smoothness and safety factor are selected as the optimization performance indexes. In order to solve the path planning with ocean currents and moving obstacles, a two-level optimization algorithm is proposed for the bionic robotic fish. In the first level of optimization, it solves the global path planning problem with known environment. In the second level of optimization, based on the optimization results of the first level of optimization, the local optimal path is obtained by the dynamic optimization method in the environment with unknown static and moving obstacles, which can solve the problem of obstacle avoidance for irregular obstacles effectively. The two-level optimization algorithm improves the accuracy of the path planning. Fuzzy adaptive genetic algorithm (FAGA) is given to further improve the optimization performance. The proposed algorithm can improve the optimization performance of the path planning, whose effectiveness is demonstrated by the simulation and experiment results. Graphical abstract: Image 1 Highlights: A two-level optimization algorithm is initially developed to improve the optimization accuracy. The dynamic optimization mechanism is proposed to solve the path planning with unknown ocean currents and obstacles. Simulations and experiments are presented to demonstrate the proposed approach.