Multidisciplinary optimization-based path planning for underwater gliders executing multi-point exploration missions

Abstract

The underwater glider is an energy-saving autonomous observation platform for long-term ocean exploration missions. In this paper, we carry out theoretical research to solve the path planning problem for multi-point exploration missions of underwater gliders. First, performance evaluation models of the glider are established, including the dynamic model, the voyage range and velocity models, and the energy consumption and utilization rate models. Based on the performance evaluation models, a path planning method is proposed to determine the optimal path that can make the glider complete the multi-point exploration mission by consuming less energy and time. The path planning method consists of three steps. In the first step, the surrogate models of performance evaluation parameters are obtained by using the polynomial functions to fit the dynamic simulation results. In the second step, the multi-objective optimization algorithms and the surrogate models are used for determining the control parameter values that can maximize the glider energy utilization rate and voyage velocity simultaneously. Then, under the given path, the correlation between the glider performance and the number of profiles is studied. In the third step of the path planning method, we establish an optimization objective function by using the energy consumption and time consumption of the glider motion. Meanwhile, the path planning problem is regarded as a traveling salesman problem, and it is solved by using the genetic algorithm. Finally, several numerical cases are given to demonstrate the proposed path planning method. The research work can provide certain theoretical guidance for the actual application of underwater gliders.