Parameter optimization of eel robot based on NSGA-II algorithm

Abstract

In order to obtain an efficient gait, this paper studies the swimming efficiency of underwater eel robot in different gaits. The optimal gait parameters combination of three gaits is studied by using Non-dominated Sorting in Genetic algorithm (NSGA-II). The relationship between input power and velocity in different gait patterns is analyzed, and the optimal gait parameters combination in each gait patterns is obtained. The simulation results show that the new gait only need less input power than the serpentine gait in the same velocity, and the new gait has faster velocity compared to the eel gait using the same joint input power. Finally, the above founds have further verified by experiments. The experiments have proved that the new gait has higher swimming efficiency. Besides, It is found that both the optimal gait amplitude and optimal phase shift exist in both the new gait and the serpentine gait.