Static stiffness modeling for optimizing drilling and riveting robots
GUAN Liwen1, CHEN Zhixiong2, LIU Chun3, XUE Jun4
1. School of Mechanical Engineering, Tsinghua University, Beijing 100084, China; 2. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611173, China; 3. Chengdu Aircraft Industrial (Group) Co., Ltd., Chengdu 610092, China; 4. AVIC Manufacturing Technology Institute, Beijing 100025, China
Abstract:Automatic robotic drilling and riveting greatly improve aircraft assembly quality and flexibility while reducing costs, so automatic drilling and riveting are being widely used for aircraft assembly. However, almost all robotic drilling and riveting systems are based on six degrees of freedom serial robots. However, these robots have an inherent weakness due to their poor rigidity. Large pressing and drilling forces during drilling and riveting can lead to deformation and even flutter of the robot end actuator, which seriously affect the drilling and riveting accuracy and quality. A static stiffness model of a drilling and riveting robot is developed with joint stiffness measurements to predict robot joint stiffnesses. A stiffness evaluation index is then used to characterize the robotic arm stiffness in the working space. The stiffness index can be used to optimize the robot position and posture for a specific operation using a particle swarm algorithm to improve the stiffness. This improves the system stability and quality.
[1] 杜兆才, 姚艳彬, 王健. 机器人钻铆系统研究现状及发展趋势[J]. 航空制造技术, 2015(4): 26-31.DU Z C, YAO Y B, WANG J. Research status and development trends of robot drilling and riveting system [J]. Aeronautical Manufacturing Technology, 2015(4): 26-31. (in Chinese) [2] LI C J, QU R X, LI S Q, et al. Robotic three-dot force feedback to suppress surface contact slipping in robot drilling [J]. Applied Mechanics and Materials, 2013, 404: 650-656. [3] CHEN S F, KAO I. Geometrical approach to the conservative congruence transformation (CCT) for robotic stiffness control [C]//Proceedings 2002 IEEE International Conference on Robotic and Automation. Washington DC, USA, 2002: 544-549. [4] ABELE E, WEIGOLD M, ROTHENBÜCHER S. Modeling and identification of an industrial robot for machining applications [J]. CIRP Annals, 2007, 56(1): 387-390. [5] 曲巍崴, 侯鹏辉, 杨根军, 等. 机器人加工系统刚度性能优化研究[J]. 航空学报, 2013, 34(12): 2823-2832. QU W W, HOU P H, YANG G J, et al. Research on the stiffness performance for robot machining systems [J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(12): 2823-2832. (in Chinese) [6] 侯鹏辉. 机器人加工系统刚度性能优化研究[D]. 杭州: 浙江大学, 2013. HOU P H. Study on the stiffness performance optimization for robot machining system [D]. Hangzhou: Zhejiang University, 2013. (in Chinese) [7] 布音. 工业机器人精密制孔系统刚度特性研究[D]. 南京: 南京航空航天大学, 2017. BU Y. Analysis of stiffness properities for robotic precise drilling system [D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2017. (in Chinese) [8] HARTENBERG R S, DENAVIT J. Kinematic synthesis of linkages [M]. New York, USA: McGraw-Hill, 1964. [9] KHALIL W, DOMBRE E. Compliant motion control [M]//Modeling, identification and control of robots. Amsterdam, Netherlands: Elsevier, 2004: 377-393. [10] 蔡自兴. 机器人学[M]. 北京: 清华大学出版社, 2000. CAI Z X. Robotics [M]. Beijing: Tsinghua University Press, 2000. (in Chinese) [11] ALICI G, SHIRINZADEH B. Enhanced stiffness modeling, identification and characterization for robot manipulators [J]. IEEE Transactions on Robotics, 2005, 21(4): 554-564. [12] 陈首彦. 机器人的切削加工模型及其控制方法研究[D]. 广州: 华南理工大学, 2017. CHEN S Y. Modeling and control research on robotic machining process [D]. Guangzhou: South China University of Technology, 2017. (in Chinese) [13] 陈玉山. 6R型工业机器人关节刚度辨识与实验研究[D]. 武汉: 华中科技大学, 2011. CHEN Y S. Joint stiffness identification of 6R industrial robot and experimental verification [D]. Wuhan: Huazhong University of Science and Technology, 2011. (in Chinese) [14] CAMPOLO D. Cartesian stiffness for wrist joints: Analysis on the Lie group of 3D rotations and geometric approximation for experimental evaluation [J]. Computer Methods in Biomechanics and Biomedical Engineering, 2013, 16(9): 975-986. [15] 张永贵, 刘晨荣, 刘鹏. 6R工业机器人刚度分析[J]. 机械设计与制造, 2015(2): 257-260. ZHANG Y G, LIU C R, LIU P. 6R industrial robot stiffness analysis [J]. Machinery Design & Manufacture, 2015(2): 257-260. (in Chinese) [16] 汪博文. 多机械臂协同加工系统静刚度建模与优化研究[D]. 上海: 上海大学, 2018. WANG B W. The research on stiffness modeling and optimization of multiple coordinated robots system [D]. Shanghai: Shanghai University, 2018. (in Chinese) [17] 蔡蒂, 谢存禧, 张铁, 等. 基于蒙特卡洛法的喷涂机器人工作空间分析及仿真[J]. 机械设计与制造, 2009(3): 161-162. CAI D, XIE C X, ZHANG T, et al. Study on workspace analysis and simulation of 6-DOF painting robot based on Monte-Carlo method [J]. Machinery Design & Manufacture, 2009(3): 161-162. (in Chinese) [18] 方峻. 粒子群算法及其应用研究[D]. 成都: 电子科技大学, 2006. FANG J. Research on particle swarm optimization and its application [D]. Chengdu: University of Electronic Science and Technology of China, 2006. (in Chinese)