华中科技大学学报（自然科学版）2024，Vol.52Issue(5)：150-157,8.DOI:10.13245/j.hust.240607
基于强化学习的空间机器人柔性捕获控制研究
Study on compliance control of space robot capturing satellite based on reinforcement learning
摘要
Abstract
Aiming at the problem that the joints were easily destroyed by the impact torque during the process of dual-arm space robot on-orbit capturing satellite,a compliance control algorithm based on reinforcement learning was proposed.First,the dynamic models of dual-arm space robot and the satellite system before capture were derived by the Lagrange approach and Newton-Euler method.Then,based on the impulse theorem,the geometrical conditions and Newton's third law,the dynamic model of the hybrid system of space robot and the satellite after capture was established.Considering the unstable hybrid system,a buffer compliance reinforcement learning controller was proposed.The real-time optimization control strategy was generated by interaction with dynamic environment,which could realize optimal control of the stabilization phase.Numerical simulation results show that the proposed control strategy can reduce the impact torque by 54.2%at most,while ensuring the joint impact torque to be limited to a safe range during stabilization phase,which can avoid damage from the impact torque for the joint.关键词
空间机器人/柔性机构/双臂捕获卫星操作/闭链系统/缓冲柔顺控制/强化学习Key words
space robot/compliant mechanism/dual-arm capture satellite operation/closed chain system/buffer compliance control/reinforcement learning分类
信息技术与安全科学引用本文复制引用
艾海平,鄂凯欣,朱安,陈力..基于强化学习的空间机器人柔性捕获控制研究[J].华中科技大学学报（自然科学版）,2024,52(5):150-157,8.基金项目
江西省自然科学基金资助项目(20232BAB212030) （20232BAB212030）
国家自然科学基金资助项目(51741502,11372073). （51741502,11372073）
