Parameters Identification of Industrial Robots Based on WLS-ABC Algorithm

doi:10.3969/j.issn.1000-565X.2016.05.014

Journal of South China University of Technology (Natural Science Edition) ›› 2016, Vol. 44 ›› Issue (5): 90-95.doi: 10.3969/j.issn.1000-565X.2016.05.014

• Mechanical Engineering • Previous Articles Next Articles

Parameters Identification of Industrial Robots Based on WLS-ABC Algorithm

DING Li¹ WU Hong-tao¹ YAO Yu² LI Yao¹ XIE Ben-hua¹ CHEN Bai¹

1.College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,Jiangsu,China; 2.College of Aerospace Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,Jiangsu,China

Received:2015-09-02 Revised:2015-12-02 Online:2016-05-25 Published:2016-04-12
Contact: 吴洪涛(1963-)，男，教授，博士生导师，主要从事机器人动力学、并联机构研究． E-mail:mehtwu@126.com
About author:丁力(1989-)，男，博士生，主要从事机器人动力学及控制研究． E-mail:NUAADLi@163． com
Supported by:
Supported by the National Natural Science Foundation of China(51375230) and the Key Project of Science and Technology Support Plan of Jiangsu Province(BE2013003-1，BE2013010-2)

Abstract

Abstract: Aiming at the kinetic parameter identification of industrial robots without loads,a novel hybrid algo- rithm,which combines weighted least square method with artificial bee colony algorithm (WLS-ABC),is pro- posed.Firstly,a linear dynamic model of the robot considering the friction characteristics of joints is deduced． Secondly,a five-order Fourier series is designed to be the exciting trajectory and experimental data are collected and identified.Then,WLS is employed to obtain the initial solution of the collected experimental data.Moreo- ver,bee colony is used as a search unit to find global optimal parameters through exchanging the information and retaining the superior individual.Finally,the established model is validated and analyzed.Experimental results show that the predicted torques well match the measured ones,and that the proposed model well reflects the kinetic characteristics of robots.

Key words: industrial robots, parameter identification, weighted least square method, artificial bee colony algorithm

DING Li WU Hong-tao YAO Yu LI Yao XIE Ben-hua CHEN Bai. Parameters Identification of Industrial Robots Based on WLS-ABC Algorithm[J]. Journal of South China University of Technology (Natural Science Edition), 2016, 44(5): 90-95.

References

[1] 申浩宇, 吴洪涛, 丁力, 等. 基于主从任务转化的冗余度机器人避障算法[J]. 机器人, 2014, 36(004): 425-429. Shen H Y, Wu H T, Ding L, et al. Obstacle avoidance algorithm for redundant robots based on transitioning between the primary and the secondary task[J]. ROBOT, 2014,36(004):425-429.() [2] Ranjbar B, Mahmoodi J, Karbasi H, et al. Robot Manipulator Path Planning Based on Intelligent Multi-resolution Potential Field[J]. International Journal of u-and e-Service, Science and Technology, 2015, 8(1): 11-26. [3] 管贻生, 邓休, 李怀珠, 等. 工业机器人的结构分析与优化[J]. 华南理工大学学报 (自然科学版), 2013, 41(9). Guan Y, Deng X, Li H, et al. Structural analysis and optimization of industrial robot[J]. Journal of South China University of Technology (Natural Science Edition), 2013, 41(9). [4] Atkeson C, An C H, Hollerbach J M. Estimation of inertial parameters of manipulator loads and links[J]. The International Journal of Robotics Research, 1986, 5(3): 101-119. [5] Dutkiewicz P, Kozlowski K, Wroblewski W S. Experimental identification of robot and load dynamics parameters[C]//Proceedings of the 2th Conference on Control Applications. Vancouver: IEEE, 1993: 767-776. [6] Olsen M M, Petersen H G. A new method for estimating parameters of a dynamic robot model[J]. Robotics and Automation, IEEE Transactions on, 2001, 17(1): 95-100. [7] 刘宇, 李瑰贤, 夏丹, 等. 基于改进遗传算法辨识空间机器人动力学参数[J]. 哈尔滨工业大学学报, 2010 (11): 1734-1739. Liu Y, Li G X, Xia D, et al. Identifying dynamic parameters of a space robot based on improved genetic algorithm[J]. JOURNAL OF HARBIN INSTITUTE OF TECHNOLOGY, 2010 (11): 1734-1739. [8] 袁伟杰, 刘贵杰, 朱绍锋. 基于遗传算法的自治水下机器人水动力参数辨识方法[J]. 机械工程学报, 2010 (11): 96-100. Xuan J, Liu G J, Zhu S F. Identification method of hydrodynamic parameters of autonomous underwater vehicle based on genetic algorithm[J]. JOURNAL OF MECHANICAL ENGINEERING，2010 (11): 96-100. [9] Ding L, Wu H T, Yao Y. Chaotic Artificial Bee Colony Algorithm for System Identification of a Small-Scale Unmanned Helicopter[J]. International Journal of Aerospace Engineering, 2015, 2015. [10] Calanca A, Capisani L M, Ferrara A, et al. MIMO closed loop identification of an industrial robot[J]. Control Systems Technology, IEEE Transactions on, 2011, 19(5): 1214-1224. [11] Vuong N D, Ang M H. Dynamic model identification for industrial robots[J]. Acta Plolytechnica Hungarica, 2009, 6(5): 51-68. [12] Swevers J, Verdonck W, Schutter D S. Dynamic model identification for industrial robots[J]. IEEE Control Systems, 2007, 27(5): 58-71. [13] Grotjahn M, Daemi M, Heimann B. Frictionand rigid body identification of robot dynamics[J]. International Journal of Solids and Structures, 2001, 38(10-13): 889-1902. [14] Qin Z K, Baron L, Birglen L. A new Approach to the dynamic parameter identification of robotic manipulators[J]. Robotica, 2010, 28: 539-547. [15] Swevers J, Ganseman C, Tukel D B, et al. Optimal robot excitation and identification[J]. IEEE Transactions on Robotics and Automation, 1997, 13(5): 730-740. [16] 王济, 胡晓. MATLAB 在振动信号处理中的应用[M]. 北京：中国水利水电出版社, 2006: 73-82. Wang J, Hu X. The application of matlabin the vibration signal processing[M]. Beijing: China publication of hydraulic and hydropower, 2006: 73-82. [17] Kinsheel A, Taha Z, Deboucha1 A, et al. Robust least square estimation of the CRS A465 robot arm’s dynamic model parameters[J]. Journal of Mechanical Engineering Research, 2012, 4(3): 89-99.

Parameters Identification of Industrial Robots Based on WLS-ABC Algorithm

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