Dynamics Modeling and Configuration Optimization of a Flexible Transportation System Using Two Space Robots

作     者：Zhang, Yinbo Jia, Shiyuan Chen, Gang Chen, Ti Wang, Yifan 

作者机构：Beijing Univ Posts & Telecommun Sch Intelligent Engn & Automat Beijing 100876 Peoples R China Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Aerosp Struct Nanjing 210016 Peoples R China 

出 版 物：《IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS》 (IEEE Trans. Aerosp. Electron. Syst.)

年 卷 期：2025年第61卷第2期

页      面：4685-4696页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0825[工学-航空宇航科学与技术] 

基　　金：National Natural Science Foundation of China [12302054, 62103058] Fundamental Research Funds for the Central Universities 

主　　题：Robots Space vehicles Transportation Robot kinematics Flexible structures Vibrations Aerodynamics Vehicle dynamics Optimization Aerospace electronics Configuration optimization dynamics modeling flexible structure transportation particle swarm optimization (PSO) algorithm space robots 

摘      要：Space robots have been considered vehicles for the assembly of large spacecraft. Space robots offer the advantage of transporting modular structures to the target positions. This article investigates the dynamics and configuration optimization of a transportation system that contains two space robots and a flexible structure. The assumed mode method is employed to describe the vibration of the flexible structure, while the dynamics is modeled by the Kane method. Based on the dynamic model, a comprehensive performance index incorporating energy consumption and vibration amplitude is proposed to optimize the capture positions of the end-effectors and the configuration of each space robot on the flexible structure. The particle swarm optimization algorithm is adopted to solve the optimization problem. Various cases involving two transportation directions, four configurations of robot manipulators, and two magnitudes of vibration amplitude metrics are investigated. Numerical simulations are conducted to verify the feasibility of the optimized placement.