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摘要: 设计了一种遥操作护理机器人系统,为实现从端同构式机器人的随动运动控制,对主端操作者人体姿态解算方法进行了研究.首先,构建由惯性传感单元构成的动作捕捉系统,对用作从端机器人动作指令的操作者人体姿态信息进行采集,采用四元数法对人体运动原始数据进行初步求解.其次,将四元数法得到的姿态数据解算成依据仿人结构设计的护理机器人各关节运动的目标姿态角,实现人体姿态到机器人动作的同构性映射.最后,为验证本文所提姿态解算方法的性能,设计了操作者控制护理机器人完成递送和拿取药瓶动作的实验.结果表明,本文姿态解算方法的解算性能与参考系统基本相同;在操作者动作姿态快速变化的时间段,系统仍可获得较高精度的目标姿态数据,其误差在动态条件下依旧能保持在2%以下;护理机器人可较好地实时复现操作者的人体动作.本文方法能满足机器人进行一般护理作业时对人体姿态数据处理的快速性和准确性要求.Abstract: This paper presents a telerobotic nursing system using inertial navigation information. In order to realize following control of the slave nursing robot, an attitude solution method is proposed for operator attitude in the master system. First, a motion capture system based on inertial units is built. To meet real-time demand, quaternion method with relatively low computation is performed in attitude solution for human data acquired from the master system, and then data fusion and compensation are conducted. Second, the attitude data obtained by quaternion method are further calculated as attitude of each joint of the slave robot with a humanoid structure, and thus an isomorphic motion mapping from human operator to slave robot is completed. Finally, experiments of taking and delivering bottle of the telerobotic system are described, and solution performance analysis on the attitude data from the master motion capture system are presented. The results show that there is a small measuring deviation with an absolute error less than 2% between the proposed method and the reference system. The attitude solving method can satisfy the requirements for fast and accurate attitude processing when the slave robot conducts a nursing task by following the nurse operator.1) 本文责任编委 赵新刚
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表 1 对应机械臂各关节的解算姿态数据精度
Table 1 Average errors of five calculated joint angles
关节角 角度变化均值(°) 比较误差均值(°) 相对误差 肩部俯仰角 4.653 0.594 0.127 肩部横滚角 4.02 0.451 0.112 肩部偏航角 4.942 0.722 0.146 肘部俯仰角 2.145 0.547 0.255 肘部横滚角 3.581 0.695 0.194 -
[1] 王田苗, 陶永, 陈阳.服务机器人技术研究现状与发展趋势.中国科学:信息科学, 2012, 42(9):1049-1066 http://www.cnki.com.cn/Article/CJFDTOTAL-PZKX201209001.htmWang Tian-Miao, Tao Yong, Chen Yang. Research status and development trends of the service robotic technology. Scientia Sinica Informationis, 2012, 42(9):1049-1066 http://www.cnki.com.cn/Article/CJFDTOTAL-PZKX201209001.htm [2] 谭民, 王硕.机器人技术研究进展.自动化学报, 2013, 39(7):963-972 http://www.aas.net.cn/CN/abstract/abstract18124.shtmlTan Min, Wang Shuo. Research progress on robotics. Acta Automatica Sinica, 2013, 39(7):963-972 http://www.aas.net.cn/CN/abstract/abstract18124.shtml [3] Joubair A, Zhao L F, Bigras P, Bonev I. Absolute accuracy analysis and improvement of a hybrid 6-DOF medical robot. Industrial Robot:An International Journal, 2015, 42(1):44-53 doi: 10.1108/IR-09-2014-0396 [4] Chen T L, Kemp C C. A direct physical interface for navigation and positioning of a robotic nursing assistant. Advanced Robotics, 2011, 25(5):605-627 doi: 10.1163/016918611X558243 [5] Kawasaki H, Kimura H, Ito S, Nishimoto Y, Hayashi H, Sakaeda H. Hand rehabilitation support system based on self-motion control, with a clinical case report. In:Proceedings of the 2006 World Automation Congress. Budapest, Hungary:IEEE, 2006. 1-6 [6] Mihelj M, Nef T, Riener R. ARMin-toward a six DoF upper limb rehabilitation robot. In:Proceedings of the 1st IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics. Pisa, Italy:IEEE, 2006. 1154-1159 [7] Li J M, Wang S X, Wang X F, He C. Optimization of a novel mechanism for a minimally invasive surgery robot. The International Journal of Medical Robotics and Computer Assisted Surgery, 2010, 6(1):83-90 doi: 10.1002/rcs.293/abstract [8] Miyamoto H, Leechavengvongs S, Atik T, Facca S, Liverneaux P. Nerve transfer to the deltoid muscle using the nerve to the long head of the triceps with the da vinci robot:six cases. Journal of Reconstructive Microsurgery, 2014, 30(6):375-380 doi: 10.1055/s-00000029 [9] Ma G W, Pytel M, Trejos A L, Hornblower V, Smallwood J, Patel R, Fenster A, Malthaner R A. Robot-assisted thoracoscopic brachytherapy for lung cancer:comparison of the ZEUS robot, VATS, and manual seed implantation. Computer Aided Surgery, 2007, 12(5):270-277 doi: 10.3109/10929080701626961 [10] Mukai T, Hirano S, Nakashima H, Sakaida Y, Guo S J. Realization and safety measures of patient transfer by nursing-care assistant robot RIBA with tactile sensors. Journal of Robotics and Mechatronics, 2011, 23(3):360-369 doi: 10.20965/jrm.issn.1883-8049 [11] Wester B A, Para M P, Sivakumar A, Kutzer M D, Katyal K D, Ravitz A D, Beaty J D, McLoughlin M P, Johannes M S. Experimental validation of imposed safety regions for neural controlled human patient self-feeding using the modular prosthetic limb. In:Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. Tokyo, Japan:IEEE, 2013. 877-884 [12] Windolf M, Götzen N, Morlock M. Systematic accuracy and precision analysis of video motion capturing systems-exemplified on the Vicon-460 system. Journal of Biomechanics, 2008, 41(12):2776-2780 doi: 10.1016/j.jbiomech.2008.06.024 [13] Seeberger R, Kane G, Hoffmann J, Eggers G. Accuracy assessment for navigated maxillo-facial surgery using an electromagnetic tracking device. Journal of Cranio-Maxillofacial Surgery, 2012, 40(2):156-161 doi: 10.1016/j.jcms.2011.03.003 [14] Hess W. Head-tracking techniques for virtual acoustics applications. In:Proceedings of the 2012 Audio Engineering Society Convention 133. Erlangen, Germany:Fraunhofer Institute for Integrated Circuits IIS, 2012. (8782):1-15 [15] Rudas I J, Gáti J, Szakál A, Némethy K. From exoskeleton to the Antal Bejczy center for intelligent robotics. In:Proceedings of the 2015 IEEE Intelligent Systems and Informatics. Subotica, Serbia:IEEE, 2015. 11 [16] Simeone A L. Substitutional reality:towards a research agenda. In:Proceedings of the 1st IEEE Workshop on Everyday Virtual Reality. Arles, France:IEEE, 2015. 19-22 [17] Zhang F, DiSanto W, Ren J, Dou Z, Yang Q, Huang H. A novel CPS system for evaluating a neural-machine interface for artificial legs. In:Proceedings of the 2011 IEEE/ACM International Conference on Cyber-Physical Systems. Chicago, IL, USA:IEEE, 2011. 67-76 [18] Ogawa M, Honda K, Sato Y, Kudoh S, Oishi T, Ikeuchi K. Motion generation of the humanoid robot for teleoperation by task model. In:Proceedings of the 24th IEEE International Symposium on Robot and Human Interactive Communication. Kobe, Japan:IEEE, 2015. 71-76 [19] Dai J S. Euler-Rodrigues formula variations, quaternion conjugation and intrinsic connections. Mechanism and Machine Theory, 2015, 92:144-152 doi: 10.1016/j.mechmachtheory.2015.03.004 [20] Xinjilefu X, Feng S Y, Huang W W, Atkeson C G. Decoupled state estimation for humanoids using full-body dynamics. In:Proceedings of the 2014 IEEE International Conference on Robotics and Automation. Hong Kong, China:IEEE, 2014. 195-201 [21] Zhang Z Q, Meng X L, Wu J K. Quaternion-based Kalman filter with vector selection for accurate orientation tracking. IEEE Transactions on Instrumentation and Measurement, 2012, 61(10):2817-2824 doi: 10.1109/TIM.2012.2196397 [22] Fresk E, Nikolakopoulos G. Full quaternion based attitude control for a quadrotor. In:Proceedings of the 2013 European Control Conference. Zurich, Switzerland:IEEE, 2013. 3864-3869 [23] Carminati M, Ferrari G, Grassetti R, Sampietro M. Real-time data fusion and MEMS sensors fault detection in an aircraft emergency attitude unit based on Kalman filtering. IEEE Sensors Journal, 2012, 12(10):2984-2992 doi: 10.1109/JSEN.2012.2204976 [24] 葛泉波, 李文斌, 孙若愚, 徐姿.基于EKF的集中式融合估计研究.自动化学报, 2013, 39(6):816-825 http://www.aas.net.cn/CN/abstract/abstract18107.shtmlGe Quan-Bo, Li Wen-Bin, Sun Ruo-Yu, Xu Zi. Centralized fusion algorithms based on EKF for multisensor non-linear systems. Acta Automatica Sinica, 2013, 39(6):816-825 http://www.aas.net.cn/CN/abstract/abstract18107.shtml [25] 彭孝东, 张铁民, 李继宇, 陈渝.基于传感器校正与融合的农用小型无人机姿态估计算法.自动化学报, 2015, 41(4):854-860 http://www.aas.net.cn/CN/abstract/abstract18659.shtmlPeng Xiao-Dong, Zhang Tie-Min, Li Ji-Yu, Chen Yu. Attitude estimation algorithm of agricultural small-UAV based on sensors fusion and calibration. Acta Automatica Sinica, 2015, 41(4):854-860 http://www.aas.net.cn/CN/abstract/abstract18659.shtml [26] Zhao H, Wang Z Y. Motion measurement using inertial sensors, ultrasonic sensors, and magnetometers with extended Kalman filter for data fusion. IEEE Sensors Journal, 2012, 12(5):943-953 doi: 10.1109/JSEN.2011.2166066 [27] Valenti R G, Dryanovski I, Xiao J Z. Keeping a good attitude:a quaternion-based orientation filter for IMUs and MARGs. Sensors, 2015, 15(8):19302-19330 doi: 10.3390/s150819302