Abstract:[Objective] The assembly of spacecraft components plays an important role in their production, and the quality and efficiency of assembly have a direct impact on the quality and efficiency of their production. Currently, spacecraft components are often constructed by hand, which results in low accuracy and efficiency. The aerospace industry's research focus is on utilizing robots to complete the assembly tasks of spacecraft components, which can improve the quality and efficiency of their production. The current assembly robots mostly use the position control mode, which measures the relative pose between the assembly features of two spacecraft components and then moves the robot to complete the robotic assembly tasks according to the measurement results. In this control mode, assembly errors are unavoidable due to measurement and robot motion errors, which will result in a huge contact force between the two contact surfaces of the spacecraft components. Excessive contact forces can damage the surface quality and coatings of spacecraft components, ultimately affecting their service lives. Therefore, the contact forces are required to be controlled by compliance control. The control parameters in the current study of compliance control are established based on the operator's experience, which is closely related to the contact forces. Because the spacecraft components are manufactured in small batches, pre-assembly cannot be used to determine the control parameters without damaging their surface quality and coatings. And improper control parameters can lead to uncontrolled contact forces. [Methods] To address this issue, a compliance control method is proposed in this paper based on the classical admittance control, which can adaptively adjust the control parameters according to the contact forces and system status. In this adaptive compliance control, the target pose and stiffness matrix are changed during the assembly process. This research examines the control effects of adaptive compliance, position, and classical admittance controls to validate the practicality of this strategy. Taking the control moment gyroscope (CMG) assembly task as an example, this research designs and develops a CMG robotic assembly prototype. The F/T sensor is installed between the CMG and the robot's end-effector to measure the contact forces during the assembly process. And Kalman filtering is utilized in this paper to filter the measurement noise of the F/T sensor. [Results] The position and orientation of the CMG were modified according to the adaptive compliance control presented in this study. After adjusting the position and orientation, the CMG's contact surface and the mounted base's contact surface were fitted together, and the contact forces of the two surfaces were guaranteed to be small. [Conclusions] The outcomes of the simulation and experiment results show that adaptive compliance control has advantages, including fast convergence, minimal residual contact force, and adaptive adjustment of the control parameters. Additionally, the adaptive compliance control suggested in this study can be quickly applied to various spacecraft component assembly tasks. This method establishes the theoretical and technical foundation for autonomous robotic assembly of spacecraft components and is expected to be employed for real-world spacecraft component assembly tasks.
陈书清, 李铁民. 基于自适应柔顺控制的航天器部件装配[J]. 清华大学学报(自然科学版), 2023, 63(11): 1808-1819.
CHEN Shuqin, LI Tiemin. Assembly of spacecraft components based on adaptive compliance control. Journal of Tsinghua University(Science and Technology), 2023, 63(11): 1808-1819.
[1] ZHANG B, ZHANG C L, XIE F G, et al. Design of an end-effector for spacecraft automatic assembly robot[C]//3rd International Conference on Advanced Technologies in Design, Mechanical and Aeronautical Engineering. Shanghai, China:IOP Publishing, 2019:012010. [2] ZHANG L J, HU R Q, YI W M, et al. A study of flexible force control method on robotic assembly for spacecraft[J]. Applied Mechanics and Materials, 2014, 681:79-85. [3] REALYVÁSQUEZ-VARGAS A, ARREDONDO-SOTO K C, GARCÍA-ALCARAZ J L, et al. Introduction and configuration of a collaborative robot in an assembly task as a means to decrease occupational risks and increase efficiency in a manufacturing company[J]. Robotics and Computer-Integrated Manufacturing, 2019, 57:315-328. [4] WANG J, ZHANG X H, CHEN H, et al. Relative pose measurement of satellite and rocket based on photogrammetry[C]//20172nd International Conference on Image, Vision and Computing. Chengdu, China:IEEE, 2017:1117-1122. [5] ZULKIFLI A, ABDULLAH N H, WAI N S, et al. Alignment measurement technique for satellite assembly, integration, and test[J]. International Journal of Advanced and Applied Sciences, 2017, 4(9):119-124. [6] CHEN S Q, LI T M, JIANG Y. Pose measurement and assembly of spacecraft components based on assembly features and a consistent coordinate system[J]. The International Journal of Advanced Manufacturing Technology, 2022, 120(3):2429-2442. [7] KIM H S. Kinematic calibration of a Cartesian parallel manipulator[J]. International Journal of Control, Automation, and Systems, 2005, 3(3):453-460. [8] DU G L, ZHANG P. Online robot calibration based on vision measurement[J]. Robotics and Computer-Integrated Manufacturing, 2013, 29(6):484-492. [9] TAKAHASHI J, FUKUKAWA T, FUKUDA T. Passive alignment principle for robotic assembly between a ring and a shaft with extremely narrow clearance[J]. IEEE/ASME Transactions on Mechatronics, 2016, 21(1):196-204. [10] WANG S, CHEN G D, XU H, et al. A robotic peg-in-hole assembly strategy based on variable compliance center[J]. IEEE Access, 2019, 7:167534-167546. [11] ZHANG K G, SHI M H, XU J, et al. Force control for a rigid dual peg-in-hole assembly[J]. Assembly Automation, 2017, 37(2):200-207. [12] LIU S, XING D P, LI Y F, et al. Robust insertion control for precision assembly with passive compliance combining vision and force information[J]. IEEE/ASME Transactions on Mechatronics, 2019, 24(5):1974-1985. [13] LEFEBVRE T, XIAO J, BRUYNINCKX H, et al. Active compliant motion:A survey[J]. Advanced Robotics, 2005, 19(5):479-499. [14] WHITNEY D E. Quasi-static assembly of compliantly supported rigid parts[J]. Journal of Dynamic Systems, Measurement, and Control, 1982, 104(1):65-77. [15] CHEN F, CANNELLA F, HUANG J, et al. A study on error recovery search strategies of electronic connector mating for robotic fault-tolerant assembly[J]. Journal of Intelligent&Robotic Systems, 2016, 81(2):257-271. [16] XU J, HOU Z M, LIU Z, et al. Compare contact model-based control and contact model-free learning:A survey of robotic peg-in-hole assembly strategies[J]. ArXiv, 2019:1-15. [17] LUO W Q, ROJAS J, GUAN T Q, et al. Cantilever snap assemblies failure detection using SVMs and the RCBHT[C]//Proceedings of the 2014 IEEE International Conference on Mechatronics and Automation. Tianjin, China:IEEE, 2014:384-389. [18] JAKOVLJEVIC Z, PETROVIC P B, HODOLIC J. Contact states recognition in robotic part mating based on support vector machines[J]. The International Journal of Advanced Manufacturing Technology, 2012, 59(1-4):377-395. [19] GAI Y H, GUO J M, WU D, et al. Feature-based compliance control for precise peg-in-hole assembly[J]. IEEE Transactions on Industrial Electronics, 2022, 69(9):9309-9319. [20] ZHANG K G, XU J, CHEN H P, et al. Jamming analysis and force control for flexible dual peg-in-hole assembly[J]. IEEE Transactions on Industrial Electronics, 2019, 66(3):1930-1939. [21] 李思奇,黄远灿. SEAs导纳控制的μ综合方法[J].自动化学报, 2021, 47(7):1539-1547. LI S Q, HUANG Y C. μ-synthesis for admittance control of SEAs[J]. Acta Automatica Sinica, 2021, 47(7):1539-1547.(in Chinese) [22] HUANG Y C, LI S Q, HUANG Q. Robust impedance control for SEAs[J]. Journal of the Franklin Institute, 2020, 357(12):7921-7943. [23] MENDEZ J D D F, SCHIØLER H, BAI S P, et al. Force estimation and control of delta robot for assembly[C]//2021 IEEE Conference on Control Technology and Applications (CCTA). San Diego, USA:IEEE, 2021:640-647. [24] 李正义,唐小琦,熊烁,等.卡尔曼状态观测器在机器人力控制中的应用[J].华中科技大学学报(自然科学版), 2012, 40(2):1-4. LI Z Y, TANG X Q, XIONG S, et al. Application of Kalman active observers in robot force control[J]. Journal of Huazhong University of Science&Technology (Natural Science Edition), 2012, 40(2):1-4.(in Chinese) [25] 朱文超,许德章.自适应Kalman滤波修复六维力传感器下E膜模型误差[J].计算机应用, 2014, 34(3):915-920. ZHU W C, XU D Z. Model error restoration for lower E-type membrane of six-axis force sensor based on adaptive Kalman filtering[J]. Journal of Computer Applications, 2014, 34(3):915-920.(in Chinese)