基于弹性摩擦模型的机器人免力矩传感器拖动示教方法
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摘要
基于广义动量的外力观测器和导纳控制方案,采用弹性摩擦模型估计关节摩擦力,并对关节起动阶段的摩擦估计值进行规划,实现了免力矩传感器的机器人拖动示教。基于机器人的动力学模型和运动状态,建立了基于广义动量的机器人外力观测器,观测操作者对机器人施加外力。采用导纳控制方案,根据观测的外力生成关节运动轨迹,实现机器人的拖动示教。采用弹性摩擦模型对关节摩擦进行建模,并在模型中引入Stribeck摩擦项,实现关节在低速和静止状态下的摩擦力估计。为解决关节在静止状态下拖动困难的问题,对关节起动阶段的摩擦力估计进行规划,通过短暂增加关节摩擦的估计值以增加关节驱动力矩,从而实现关节的轻松拖动,且起动规划算法不会对机器人关节的其他运动阶段造成影响。实验表明,采用本文控制方案可有效实现免力矩传感器的工业机器人拖动示教。采用起动规划方案可有效增加关节起动外力和缩短关节起动时间,在起动阶段关节可以短暂产生26 N·m以上的估计力矩,相比未使用规划时关节的起动时间至少可减少70%。同时,关节在起动阶段具有一定的抗干扰能力。
Through the external torque observer based on generalized momentum and the admittance control scheme,the robotic dragging teaching without torque sensor was realized,in which the elastic friction model was used to estimate the joint friction torque,and the friction estimation value of the joint starting stage was planned. Based on the dynamics model and motion information of the robot,an external torque observer based on generalized momentum was established to observe the external torque exerted by the operator on the robot. Admittance control scheme was adopted to generate the joint motion trajectory according to the observed external torque,and the dragging teaching robot was realized. The elastic friction model was used to model the friction of the joint,and the Stribeck friction term was introduced into the model to estimate the friction torque of the joint at low speed and static state. In order to solve the difficulty of dragging in the stationary state of joint,the friction estimation of the joint starting stage was planned,and the joint driving torque was also increased temporarily,so as to realize the easy drag of the joint. Meanwhile,the starting planning scheme did not affect other movement stages of the robot joints.Experiment results showed that the control scheme can effectively realize the dragging teaching of industrial robot without torque sensor. At the same time,the starting planning scheme can effectively reduce the external torque and time of joint starting stage. The estimated torque of more than 26 N·m was generated in the starting stage. The starting time of the joint can be reduced by 70% compared with the unused starting planning scheme. The joint had a certain anti-interference ability in the starting stage.
Through the external torque observer based on generalized momentum and the admittance control scheme,the robotic dragging teaching without torque sensor was realized,in which the elastic friction model was used to estimate the joint friction torque,and the friction estimation value of the joint starting stage was planned. Based on the dynamics model and motion information of the robot,an external torque observer based on generalized momentum was established to observe the external torque exerted by the operator on the robot. Admittance control scheme was adopted to generate the joint motion trajectory according to the observed external torque,and the dragging teaching robot was realized. The elastic friction model was used to model the friction of the joint,and the Stribeck friction term was introduced into the model to estimate the friction torque of the joint at low speed and static state. In order to solve the difficulty of dragging in the stationary state of joint,the friction estimation of the joint starting stage was planned,and the joint driving torque was also increased temporarily,so as to realize the easy drag of the joint. Meanwhile,the starting planning scheme did not affect other movement stages of the robot joints.Experiment results showed that the control scheme can effectively realize the dragging teaching of industrial robot without torque sensor. At the same time,the starting planning scheme can effectively reduce the external torque and time of joint starting stage. The estimated torque of more than 26 N·m was generated in the starting stage. The starting time of the joint can be reduced by 70% compared with the unused starting planning scheme. The joint had a certain anti-interference ability in the starting stage.
引文
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[18]席万强,陈柏,丁力,等.考虑非线性摩擦模型的机器人动力学参数辨识[J/OL].农业机械学报,2017,48(2):393-399. http:∥www. j-csam. org/jcsam/ch/reader/view_abstract. aspx? flag=1&file_no=20170253&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2017. 02. 053.XI Wanqiang,CHEN Bai,DING Li,et al. Dynamic parameter identification for robot manipulators with nonlinear friction model[J/OL]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):393-399.(in Chinese)
[19] LAMPAERT V,SWEVERS J,Al-BENDER F. Modification of the Leuven integrated friction model structure[J]. IEEE Transactions on Automatic Control,2002,47(4):683-687.
[20]吴文祥,朱世强,靳兴来.基于改进傅里叶级数的机器人动力学参数辨识[J].浙江大学学报(工学版),2013,47(2):231-237.WU Wenxiang,ZHU Shiqiang,JIN Xinglai. Dynamic identification for robot manipulators based on modified fourier series[J]. Journal of Zhejiang University(Engineering Science),2013,47(2):231-237.(in Chinese)
[2] LUCA A D,MATTONE R. Sensorless robot collision detection and hybrid force/motion control[C]∥IEEE International Conference on Robotics and Automation. IEEE,2005:999-1004.
[3] ALCOCER A,ROBERTSSON A,VALERA A,et al. Force estimation and control in robot manipulators[J]. IFAC Proceedings Volumes,2003,36(17):55-60.
[4] DAMME M V,BEYL P,VANDERBORGHT B,et al. Estimating robot end-effector force from noisy actuator torque measurements[C]∥IEEE International Conference on Robotics and Automation. IEEE,2011:1108-1113.
[5] SOUSA C D,RUI C. Physical feasibility of robot base inertial parameter identification:a linear matrix inequality approach[J].International Journal of Robotics Research,2014,33(6):931-944.
[6] LIU G,GOLDENBERG A A,ZHANG Y. Precise slow motion control of a direct-drive robot arm with velocity estimation and friction compensation[J]. Mechatronics,2004,14(7):821-834.
[7] MOREL G,IAGNEMMA K,DUBOWSKY S. The precise control of manipulators with high joint-friction using base force/torque sensing[J]. Automatica,2000,36(7):931-941.
[8] LIU L L,WU Z Y. A new identification method of the Stribeck friction model based on limit cycles[J]. ARCHIVE Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science,2014,228(15):2678-2683.
[9] SWEVERS J,AL-BENDER F,GANSEMAN C G,et al. An integrated friction model structure with improved presliding behavior for accurate friction compensation[J]. IEEE Transactions on Automatic Control,1998,45(4):675-686.
[10] AL-BENDER F,LAMPAERT V,SWEVERS J. The generalized Maxwell-slip model:a novel model for friction simulation and compensation[J]. IEEE Transactions on Automatic Control,2005,50(11):1883-1887.
[11]倪风雷,刘宏,介党阳.基于速度观测器的GMS摩擦模型辨识与补偿[J].电机与控制学报,2012,16(11):70-75.NI Fenglei,LIU Hong,JIE Dangyang. GMS friction model identification and compensation based on velocity observer[J].Electric Machines and Control,2012,16(11):70-75.(in Chinese)
[12] IWATANI M,KIKUUWE R. An external force estimator using elastoplastic friction model with improved static friction behavior[C]∥International Conference on Control,Automation,Robotics and Vision. IEEE,2017.
[13] TUTTLE T D,SEERING W P. A nonlinear model of a harmonic drive gear transmission[J]. IEEE Trans Robotics Autom,1996,12(3):368-374.
[14] IWATANI M,KIKUUWE R. An elastoplastic friction force estimator and its application to external force estimation and forcesensorless admittance control[C]∥IEEE/SICE International Symposium on System Integration. IEEE,2017.
[15] IWATANI M,KIKUUWE R. Some improvements in elastoplastic friction compensator[J]. SICE Journal of Control Measurement&System Integration,2017,10(3):141-148.
[16] OTT C,MUKHERJEE R,NAKAMURA Y. Unified impedance and admittance control[C]∥IEEE International Conference on Robotics and Automation. IEEE,2010:554-561.
[17]游有鹏,张宇,李成刚.面向直接示教的机器人零力控制[J].机械工程学报,2014,50(3):10-17.YOU Youpeng,ZHANG Yu,LI Chenggang. Force-free control for the direct teaching of robots[J]. Journal of Mechanical Engineering,2014,50(3):10-17.(in Chinese)
[18]席万强,陈柏,丁力,等.考虑非线性摩擦模型的机器人动力学参数辨识[J/OL].农业机械学报,2017,48(2):393-399. http:∥www. j-csam. org/jcsam/ch/reader/view_abstract. aspx? flag=1&file_no=20170253&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2017. 02. 053.XI Wanqiang,CHEN Bai,DING Li,et al. Dynamic parameter identification for robot manipulators with nonlinear friction model[J/OL]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):393-399.(in Chinese)
[19] LAMPAERT V,SWEVERS J,Al-BENDER F. Modification of the Leuven integrated friction model structure[J]. IEEE Transactions on Automatic Control,2002,47(4):683-687.
[20]吴文祥,朱世强,靳兴来.基于改进傅里叶级数的机器人动力学参数辨识[J].浙江大学学报(工学版),2013,47(2):231-237.WU Wenxiang,ZHU Shiqiang,JIN Xinglai. Dynamic identification for robot manipulators based on modified fourier series[J]. Journal of Zhejiang University(Engineering Science),2013,47(2):231-237.(in Chinese)