Three-dimensional path planning for a novel sediment sampler in ocean environment based on an improved mutation operator genetic algorithm.

A stable and efficient path planning algorithm can improve the accuracy and efficiency of sediment sampling process. To determine a path that can guide the sampler to the preset landing point within the shortest traveling time, an improved mutation operator genetic algorithm (IMOGA) is proposed herein. First, an attitude-adjusting mechanism is introduced. Then, a three-dimensional ocean current model is developed. A hydrodynamic model of the sediment sampler is developed via CFD simulations, and an adaptive cost function for the path-planning mathematical model is proposed to improve the convergence problem. Finally, the problem is solved using a basic genetic algorithm and IMOGA separately. The comparison of the simulation results reveals that the IMOGA can achieve a better global optimal solution in less computing time than the basic genetic algorithm. The improved path planning algorithm can be used for sediment samplers and landers that deploy instruments at a designated point as well as for profiles that need to adjust their position. • Accurate and efficient sediment sampling through three-dimensional path planning based on genetic algorithm. • The adaptive cost function solves the convergence problem. • The algorithm based on a mutation probability distribution function saves computing time and sampler falling time. • The influence of algorithm control parameters is evaluated and the achievable region is analyzed. [ABSTRACT FROM AUTHOR]