南京航空航天大学学报2025，Vol.57Issue(3)：467-474,8.DOI:10.16356/j.1005-2615.2025.03.008
基于强化学习的双臂空间机器人应急姿态控制
Attitude Control for Emergency Recovery Based on Reinforcement Learning Method for Dual-arm Space Robots
摘要
Abstract
Aiming at the traditional attitude control failure in on-orbit service dual-arm space robots under extreme abnormal conditions such as flywheel and engine malfunctions,an emergency attitude control algorithm for dual-arm space robots based on reinforcement learning is proposed.This approach achieves limited attitude recovery of the spacecraft using only the two robotic arms configured on the spacecraft which differs from traditional attitude control algorithms.A physical environment for algorithm training is constructed and a model-free proximal policy optimization(PPO)algorithm is used for attitude control.By incorporating the kinematic constraints of manipulators movements during on-orbit operations,the reward function is designed to optimize the precision of spacecraft attitude control.To validate the effectiveness of the proposed strategy,numerical simulations of the space robot attitude recovery are conducted in the MuJoCo environment.The adaptability of the algorithm is evaluated under various conditions,including various masses of the base,various masses of the end.Results demonstrate that the reinforcement learning method is suitable for spacecraft limited attitude control and show a certain robustness without the need of parameter fine-tuning.关键词
机器人/强化学习/双臂协同/姿态控制Key words
robot/reinforcement learning/dual-arm collaboration/attitude control分类
计算机与自动化引用本文复制引用
黎丰,李宁,邹怀武,靳永强,张崇峰..基于强化学习的双臂空间机器人应急姿态控制[J].南京航空航天大学学报,2025,57(3):467-474,8.基金项目
国家自然科学基金委与中国航天科技集团公司联合基金(U21B6002). （U21B6002）
