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基于改进遗传算法的移动着陆机构系统的运动和轨迹规划建模。

Motion and trajectory planning modeling for mobile landing mechanism systems based on improved genetic algorithm.

机构信息

College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

出版信息

Math Biosci Eng. 2020 Nov 26;18(1):231-252. doi: 10.3934/mbe.2021012.

Abstract

In many traditional soft-landing missions, researchers design the lander and the rover as two separate individuals, which has its limitations. At present, research on landers mainly focuses on the performance analysis of those who cannot move, and the motion of legged mobile lander has not yet been studied. In this paper, a novel Mobile Landing Mechanism (MLM) is proposed. Firstly, the monte-Carlo method is used to solve the workspace, and the motion feasibility of the mechanism is verified. Secondly, combining with the constraints of velocity, acceleration and secondary acceleration of each driving joint of the MLM, the trajectory of its joint space is planned by using cubic spline curve. And based on the weighted coefficient method, an optimal time-jerk pedestal trajectory planning model is established. Finally, by comparing the genetic algorithm (GA) with the adaptive genetic algorithm (AGA), an optimization algorithm is proposed to solve the joint trajectory optimization problem of the MLM, which can obtain better trajectory under constraints. Simulation shows that the motion performance of the mechanism is continuous and stable, which proves the rationality and effectiveness of the foot trajectory planning method.

摘要

在许多传统的软着陆任务中,研究人员将着陆器和漫游者设计为两个独立的个体,这存在一定的局限性。目前,着陆器的研究主要集中在那些无法移动的着陆器的性能分析上,而腿式移动着陆器的运动尚未得到研究。本文提出了一种新型的移动着陆机构(MLM)。首先,利用蒙特卡罗方法求解工作空间,验证机构的运动可行性。其次,结合 MLM 各驱动关节速度、加速度和二次加速度的约束条件,采用三次样条曲线规划其关节空间轨迹。并基于加权系数法,建立最优时间冲击基座轨迹规划模型。最后,通过遗传算法(GA)与自适应遗传算法(AGA)的比较,提出了一种优化算法来解决 MLM 的关节轨迹优化问题,可以在约束条件下获得更好的轨迹。仿真表明,该机构的运动性能连续稳定,验证了足轨迹规划方法的合理性和有效性。

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