A meta-heuristic assisted underwater glider path planning method

Path planning is a key technology in underwater glider navigation system, however, due to the complex and time variant ocean environment, the development of underwater path planning faces great difficulties. In this paper, a novel path planner for the underwater glider is proposed. Firstly, a three-dimensional ocean environment model is established, including seabed topographies and ocean currents. Secondly, a novel path parameterization method and a new velocity synthesis method are presented. Besides, the constrained optimization model of the underwater glider path planning is established in detail. To solve the problem, a grey wolf enhanced equilibrium optimizer (GWEEO) is put forward. In GWEEO, a grey wolf search phase is designed to improve the quality of the candidate solutions. Moreover, a well-designed competition mechanism is introduced to accelerate the convergence. In the end, different groups of simulation experiments and corresponding statistical analysis results convincingly demonstrate that the proposed algorithm can plan a satisfactory path for the underwater glider and the comprehensive performance of GWEEO is better than EO, GWO, DE and JADE algorithm.