Multi-objective optimization on the shock absorber design for the lunar probe using nondominated sorting genetic algorithm II

Abstract

In this article, the design on the shock absorber of the lunar probe soft landing can be considered as a single-or multiobjective optimization problem. Here, the optimized objective parameters include the maximum toppling stability, defined as D min , and the minimum stroke of primary strut energy absorption, S Pmax. However, the two optimized variables are conflict objectives. In order to give an overall consideration about the multi-performances of landing, the multi-objective optimization strategy is proposed and nondominated sorting genetic algorithm II is employed to find the best decision parameters of the shock absorber design. To conduct the optimizations, firstly, the worst landing cases and safety boundaries for both toppling and primary strut energy absorptions are obtained by the computer simulation experiments. Both single-and multi-objective optimizations are then implemented aiming to expand the stability boundary. The results show that the landing stability is effectively improved after optimizations, and also demonstrate that the multi-objective optimization strategy is superior to that of the single-objective optimization.

Dynamic Modeling and Simulation of a Robotic Lander Based on Variable Radius Drums

“…In particular, the normal contact force between the pads of the lander and the soil is modeled as a non-linear spring damper system as depicted in Figure 2, and is described by the following [13],…”

“…For example, Wang et al in 2019 studied the use of magnetorheological fluid dampers with semi-active control on damping force in order to adjust to landing conditions [11]. Furthermore, the shock absorber design [12] and the lander stability [13] have been investigated numerically by mean of optimization algorithms. Moreover, legged landers with capabilities of walking on planet surface after the landing have been studied in [14,15].…”

Multimodal fusion for robotics

“…Then, a work 21 proposes an objective method for quality assessment of colored multiexposure image fusion based on image saturation, together with texture and structure similarities, which can measure the perceived color, texture, and structure information of fused images. In another approach, 22 the design on the shock absorber of the lunar probe soft landing is formulated as a single- or multi-objective optimization problem. The multi-objective optimization strategy is proposed and nondominated sorting genetic algorithm II is employed to find the best decision parameters of the shock absorber design.…”