基于模型的微创手术机器人力检测技术研究
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摘要
微创外科手术机器人系统不仅可以拓展医生进行微创外科手术的能力,而且可以增加医生手术操作精度、灵活性和视觉。力和触觉反馈在微创外科手术中起着极其重要的作用,它能够使医生感觉器官组织硬度和强度、测量组织属性、评估解剖学结构并且允许医生进行安全操作组织,实施恰当的力控制行为。目前商业上可获得的机器人系统缺乏力和触觉反馈,其最主要原因是由于在微创外科手术这个特殊环境下难以获取末端执行器和环境间的力和力矩信息。本文针对上述问题,提出了基于模型的力检测技术,实现了在无力和力矩传感器情况下,提取手术工具与环境之间的交互作用力,为微创外科机器人实现力检测和力反馈提供一切实可行的理论研究基础。论文主要研究内容和成果如下:
1、根据腹腔微创外科手术特点,提出了MicroHand A系统的设计要求,并详细介绍了系统各部分组成和功能。在丝传动操作臂的运动学基础上,提出了“半回路丝传动法”,可直接列写电机角位移和关节角之间关系方程。利用旋量理论分析了主从操作臂的运动学,建立了部分丝传动的主动环节在笛卡尔空间、关节空间和电机驱动空间之间的映射关系。推导了主从操作臂的空间和物体雅克比矩阵。为实现后续主从异构直觉运动控制和基于模型的力检测技术奠定了前提基础。
2、利用拉格朗日方法,建立了计及电机转子动力学和关节摩擦在内的通用开环链机器人操作臂和丝传动操作臂完整动力学模型。导出了基于动力学模型的机器人末端执行器和环境交互作用力的检测模型,为实现无力和力矩传感器情况下的力和力矩信息的获取奠定了理论研究基础。
3、采用指数积公式和拉格朗日方法建立了MicroHand A系统中包含远程运动中心机构和丝传动的手术工具在内的主动环节的完整动力学模型。该模型计及了关节摩擦和电机转子动力学模型及丝传动对关节力矩耦合的影响。对该动力学模型进行了线性化处理,并通过实验方法利用最小二乘原理辨识了动力学参数,为实现基于模型的力检测技术提供了有力保障。
4、设计了MicroHand A系统的主从控制硬件结构和软件算法,实现了在内窥镜图像系统下的直觉运动控制和缩放运动控制,解决了手眼不协调、主从操作臂运动学不一致和工作空间不匹配问题。为实现双边运动和力反馈控制,建立了简化为一自由度主从遥操作系统的动力学模型,并应用二端口网络理论进行了描述,推导了满足绝对稳定性的充分必要条件,并定性分析了控制参数对系统的稳定性和透明性的影响。
5、有效的进行了基于模型的力检测实验和位置跟踪性能实验。力检测实验包括基于动力学模型的力检测精度测试实验和不同实验任务打结与缝合时的手术工具和环境之间的交互作用力的检测实验。进行了从操作臂对主操作臂的位置跟踪性能实验。验证了基于模型的力检测原理的正确性与技术可行性。
Minimally invasive surgical robot system can not only expand the ability of surgeons in minimally invasive surgery, but can increase the precision of surgical operation, flexibility and vision. Force and haptic feedback plays a very important role in minimally invasive surgery. It can enable the surgeon to feel organic tissue hardness, measure tissue properties, evaluate anatomical structures, and allows him/her to commit appropriate force control actions for safe tissue manipulation. Currently commercially available robot systems lack force and tactile feedback, the main reason is that it is difficult for the special environment of minimally invasive surgery to acquire the force and torque information between end-effector and the environment. According to the above-mentioned problem, force measurement technology based on dynamic model is proposed to extract the interaction force between the surgical instruments and the environment without force and torque sensors. It provides a basis theory for the implementation of force sensing and force feedback in minimally invasive surgical robot. The following aspects in the dissertation have been achieved:
1. The design requirements of MicroHand A system are proposed according to minimally invasive abdominal surgery and the components and functions of the system are introduced in detail. Half-loop tendon-driven method based on the kinematics of tendon-driven manipulator is put forward. The relationship equation between motor angular displacement and joint angle can be directly written by half-loop tendon-driven method. The kinematics of master manipulator and slave manipulator are analyzed by screw theory and the mapping relationship among the Cartesian space, joint space and motor-driven space is established. Space and body Jacobian matrixes of the master and the slave manipulators are derived. Those laid the foundation of realizing intuitive motion control under kinematically dissimilar master-slave manipulators and force measurement technology based on model.
2. The complete dynamic model of the general open-loop chain manipulator and the tendon-driven manipulator including motor rotor dynamics and joint friction are modelled by Lagrangian method. Force measurement model based on dynamic model between end effector and environment is derived to acquire force and torque information without force and torque sensors.
3. The whole dynamic model for active part of the MicroHand A system with the remote center of motion and the tendon-driven surgical instruments is established by product of exponentials formula and Lagrangian method. The joint friction, rotor dynamics and coupling of tendon-driven joint are taken into account in the model. The dynamic model is linearly parameterized and the dynamic parameters are experimentally identified using least squares method, which provides a strong guarantee for the realization of force measurement technology based on model.
4. The hardware architecture and the software algorithms of master-slave control system are designed for the MicroHand A system. Intuitive motion control and motion scaling control are accomplished to solve absonant hand-eye coordination, kinematic dissimilarity and workspace mismatch of master-slave manipulators. The dynamics model of a simplified master-slave teleoperation system with one degree of freedom is derived to accomplish bilateral motion and force feedback control. The teleoperation system can be presented by a two-port network theory. The necessary and sufficient conditions for absolute stability are derived and the stability and the transparency of the system are qualitatively analyzed.
5. Force measurement based on model experiments and position tracking experiments are carried out. Force measurement experiments include the force measurement accuracy experiments based on dynamic model and the interaction force measurement experiments between the surgical instrument and the environment under different experimental tasks such as knot tying and suturing. Position tracking experiment between the desired trajectory commanded by the master manipulator and the actual trajectory of the slave manipulator is carried out. The correctness and the technical feasibility of force measurement principle are validated.
1、根据腹腔微创外科手术特点,提出了MicroHand A系统的设计要求,并详细介绍了系统各部分组成和功能。在丝传动操作臂的运动学基础上,提出了“半回路丝传动法”,可直接列写电机角位移和关节角之间关系方程。利用旋量理论分析了主从操作臂的运动学,建立了部分丝传动的主动环节在笛卡尔空间、关节空间和电机驱动空间之间的映射关系。推导了主从操作臂的空间和物体雅克比矩阵。为实现后续主从异构直觉运动控制和基于模型的力检测技术奠定了前提基础。
2、利用拉格朗日方法,建立了计及电机转子动力学和关节摩擦在内的通用开环链机器人操作臂和丝传动操作臂完整动力学模型。导出了基于动力学模型的机器人末端执行器和环境交互作用力的检测模型,为实现无力和力矩传感器情况下的力和力矩信息的获取奠定了理论研究基础。
3、采用指数积公式和拉格朗日方法建立了MicroHand A系统中包含远程运动中心机构和丝传动的手术工具在内的主动环节的完整动力学模型。该模型计及了关节摩擦和电机转子动力学模型及丝传动对关节力矩耦合的影响。对该动力学模型进行了线性化处理,并通过实验方法利用最小二乘原理辨识了动力学参数,为实现基于模型的力检测技术提供了有力保障。
4、设计了MicroHand A系统的主从控制硬件结构和软件算法,实现了在内窥镜图像系统下的直觉运动控制和缩放运动控制,解决了手眼不协调、主从操作臂运动学不一致和工作空间不匹配问题。为实现双边运动和力反馈控制,建立了简化为一自由度主从遥操作系统的动力学模型,并应用二端口网络理论进行了描述,推导了满足绝对稳定性的充分必要条件,并定性分析了控制参数对系统的稳定性和透明性的影响。
5、有效的进行了基于模型的力检测实验和位置跟踪性能实验。力检测实验包括基于动力学模型的力检测精度测试实验和不同实验任务打结与缝合时的手术工具和环境之间的交互作用力的检测实验。进行了从操作臂对主操作臂的位置跟踪性能实验。验证了基于模型的力检测原理的正确性与技术可行性。
Minimally invasive surgical robot system can not only expand the ability of surgeons in minimally invasive surgery, but can increase the precision of surgical operation, flexibility and vision. Force and haptic feedback plays a very important role in minimally invasive surgery. It can enable the surgeon to feel organic tissue hardness, measure tissue properties, evaluate anatomical structures, and allows him/her to commit appropriate force control actions for safe tissue manipulation. Currently commercially available robot systems lack force and tactile feedback, the main reason is that it is difficult for the special environment of minimally invasive surgery to acquire the force and torque information between end-effector and the environment. According to the above-mentioned problem, force measurement technology based on dynamic model is proposed to extract the interaction force between the surgical instruments and the environment without force and torque sensors. It provides a basis theory for the implementation of force sensing and force feedback in minimally invasive surgical robot. The following aspects in the dissertation have been achieved:
1. The design requirements of MicroHand A system are proposed according to minimally invasive abdominal surgery and the components and functions of the system are introduced in detail. Half-loop tendon-driven method based on the kinematics of tendon-driven manipulator is put forward. The relationship equation between motor angular displacement and joint angle can be directly written by half-loop tendon-driven method. The kinematics of master manipulator and slave manipulator are analyzed by screw theory and the mapping relationship among the Cartesian space, joint space and motor-driven space is established. Space and body Jacobian matrixes of the master and the slave manipulators are derived. Those laid the foundation of realizing intuitive motion control under kinematically dissimilar master-slave manipulators and force measurement technology based on model.
2. The complete dynamic model of the general open-loop chain manipulator and the tendon-driven manipulator including motor rotor dynamics and joint friction are modelled by Lagrangian method. Force measurement model based on dynamic model between end effector and environment is derived to acquire force and torque information without force and torque sensors.
3. The whole dynamic model for active part of the MicroHand A system with the remote center of motion and the tendon-driven surgical instruments is established by product of exponentials formula and Lagrangian method. The joint friction, rotor dynamics and coupling of tendon-driven joint are taken into account in the model. The dynamic model is linearly parameterized and the dynamic parameters are experimentally identified using least squares method, which provides a strong guarantee for the realization of force measurement technology based on model.
4. The hardware architecture and the software algorithms of master-slave control system are designed for the MicroHand A system. Intuitive motion control and motion scaling control are accomplished to solve absonant hand-eye coordination, kinematic dissimilarity and workspace mismatch of master-slave manipulators. The dynamics model of a simplified master-slave teleoperation system with one degree of freedom is derived to accomplish bilateral motion and force feedback control. The teleoperation system can be presented by a two-port network theory. The necessary and sufficient conditions for absolute stability are derived and the stability and the transparency of the system are qualitatively analyzed.
5. Force measurement based on model experiments and position tracking experiments are carried out. Force measurement experiments include the force measurement accuracy experiments based on dynamic model and the interaction force measurement experiments between the surgical instrument and the environment under different experimental tasks such as knot tying and suturing. Position tracking experiment between the desired trajectory commanded by the master manipulator and the actual trajectory of the slave manipulator is carried out. The correctness and the technical feasibility of force measurement principle are validated.
引文
[1] D. Paolo, G.. Eugenio. Robotics for Medical Applications. IEEE Robotics and Automation Magazine, 1996, 3(3): 44-56
[2] H. Kang, J. T. Wen. EndoBot: A robotic assistant in minimally invasive surgeries. IEEE Int. Conf. Robot. Autom., 2001, 2: 2031-2036
[3] S. R. Payne, T. F. Ford, J. E. Wickham. Endoscopic management of upper urinary stones, British Journal of Surgery, 1985, 72: 822-824
[4] P. Mouret. How I developed Laparoscopic choleeystectomy. Ann Acad Med Singapore, 1996, 25: 744-747
[5] R. H. Taylor, J. Funda, B. Eldridge, et al. A Telerobotic Assistant for Laparoscopic Surgery. IEEE Eng in Med Biol Mag, 1995, 3: 279-288
[6] P. S. Green, W. HillJ, J. F. Jensen, et al. Telepresence Surgery. IEEE Eng in Med Biol Mag, 1995, (3): 324-329
[7] G. S. Guthart, J. K. Salisbury, Jr., et al. The IntutiveTM Telesurgery System: Overview and Application. IEEE Int. Conf. Robot. Autom., 2000: 618-621
[8] D.S. Kwon, K.Y. Woo, S.K. Song, et al. Microsurgical Telerobot system. Proceedings of IEEE International Conference on Intelligent Robots and Systems, 1998, (2): 945-950
[9] M. C. Cavusogln, F. Tendick, M. Cohn, et al. A Laparoscopic Telesurgical Workstation. IEEE Transaction Robotics and Autoation, 1999, 15: 728-739
[10] M. Lazeroms, W. Jongkind, G. Honderd. Telemanipulator Design for Minimally Invasive Surgery. Proceedings of American Control Conference, 1997, 2: 2982-2986
[11]刘少强,黄惟一,王爱民等,用于微创外科手术的遥控机器人系统研究现状及趋势,机器人,2002,24 (3):283-288
[12] L. Mettler, M. Irahim, W. Jonat. One year of experience working with the aid of a robotic assistant (the voice-controlled optic holder AESOP) in gynaecological endoscopic surgery. Human Reproduction, 1998, 13(10): 2748-2750
[13] S. E. Butner, M. Ghodoussi. A real-time system for tele-surgery. Proceedings of the 21st International Conference on Distributed Computing Systems, 2001: 236-243
[14] M. Ghodoussi, S. E. Butner, Y. L. Wang. Robotic surgery the transatlantic case. IEEE Int. Conf. Robot. Autom., 2002, 2(2): 1882-1888
[15] D. Stoianovici, R. Webster, L. Kavoussi. Robotic Tools for Minimally Invasive Urologic Surgery. Chapter in Complications of Urologic Laparoscopic Surgery: Recognition, Management & Prevention, December 2002: 1-17
[16] R. M. Satava. Surgical Robotics: The Early Chronicles: A Personal Historical Perspective. In Surgical Laparoscopy Endoscopy&Percercutaneous Techniques, Lipincott Williams&Wikins, Inc. Philadelphia, 2002, 12: 6-16
[17] M. Menon, A. Shrivastava, A. Tewari, et al. Laparoscopic and Robot Assisted Radical Prostatectomy: Establishment of a Structured Program and Preliminary Analyses of Outomes. J Urol, 2002, 168: 945-949
[18] M. O. Urr, G. Buess, B. Neisius, et al. Robotics and telemanipulation technologies for endoscopic surgery. A review of the ARTEMIS project. Advanced Robotic Telemanipulator for Minimally Invasive Surgery. Surg Endosc, Apr 2000, 14(4): 375-381
[19] J. H. Lum Mitchell, C. W. Friedman Diana, R. Jacob, etc. The RAVEN: Design and Validation of a Telesurgery System. International Journal of Robotics Research, 2009, 28: 1183-1197
[20] M. J. H. Lum, MSEE, C.W. Diana, etc. Objective Assessment of Telesurgical Robot Systems: Telerobotic FLS. Medicine meets virtual reality, 2008, 132: 263-265
[21] M. J. H. Lum,D. C. W. Friedman,H. H. I. King. Teleoperation of a Surgical Robot via Airborne Wireless Radio and Transatlantic Internet Links. In Advanced Robotics, 2008, 42: 305-314
[22] H. H. King, B. Hannaford, K. Kwok, et al. Plugfest 2009: Global Interoperabil- ity in Telerobotics and Telemedicine. IEEE Int. Conf. Robot. Autom., 2010: 1733-1738
[23] M. C. Cavusoglu, F. Tendick, M. Cohn, et al. A Laparoscopic Telesurgical Workstation. IEEE Transactions on Robotics and Automation, 1999, 15: 728-739
[24] D. S. Kwon, K. Y. Woo, S. K. Song, W. S. Kim, et al. Microsurgical Telerobot System. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998, 2: 945-950
[25] D. S. Kwon, K. Y. Woo, H. S. Cho, et al. Haptic Control of the Master Hand Controller for a Microsurgical Telerobot System. IEEE Int. Conf. Robot. Autom., 1999, 3: 1722-1727
[26] K. Ikuta, T. Hasegawa, S. Daifu. Hyper Redundant Miniature Manipulator“hyper Finger”for Remote Minimally Invasive Surgery in Deep Area. IEEE Int. Conf. Robot. Autom., 2003, 1: 1098-1102
[27] K. Ikuta, K. Yamamoto, K. Sasaki. Development of Remote Micro Surgery Robot and New Surgical Procedure for Deep and Narrow Space. IEEE Int. Conf. Robot. Autom., 2003, 1: 1103-1108
[28]李群智,机器人辅助显微外科手术系统的研究与开发:[硕士学位论文],天津;天津大学,2004
[29]董玉涛,张建勋,微操作机器人底层控制系统设计,机器人,2000,22(4):310-314
[30] Q. Z. Li, S. X. Wang, J. T. Yun, et al, Haptic device with gripping force feedback. IEEE Int. Conf. Robot. Autom., 2005: 1190-1195
[31] S. X.Wang, L. W. Yue, Q. Z. Li, et al. Conceptual Design and Dimensional Synthesis of“MicroHand”. Journal of Mechanism and Machine Theory, 2008, 43: 1186-1197
[32]王树新,丁杰男,贠今天,显微外科手术机器人——“妙手”系统的研究,机器人,2006,28(2):130-135
[33] L. Podsedkowski. Robin Heart 0, 1, and 3-Mechanical Construction Development, Bulletin of the Polish Academy of Sciences. Technical Sciences, 2005, 53 (1): 79-85
[34] J. R. Shi, M. Pascal, P. Viviane, et al. Preliminary Results on the Design of a Novel Laparoscopic Manipulator. Proceeding of the 11th World Congress in Mechanism and Machine Science, 2004: 1181-1185
[35] http://www.hansenmedical.com/products/sensei.aspx
[36] H. Mayer, I. Nagy, A. Knoll, et al. An Experimental System for Robotic Heart Surgery. 18th IEEE Symposium on Computer-Based Medical System, 2005: 56-60
[37] N. Simaan, R. H. Taylor, P. Flint. A Dexterous System for Laryngeal Surgery. IEEE Int. Conf. Robot. Autom., 2004: 351-357
[38] P. Puangmali, K.Althoefer, L. D. Seneviratne, et al. State-of-the-Art in Force and Tactile Sensing for Minimally Invasive Surgery. IEEE Sensors Journal, 2008: 371-381
[39] J. D. Brown, J. Rosen, M. Moreyra, et al. Computer-controlled motorized endoscopic grasper for in vivo measurement of soft tissue biomechanical characteristics. Medicine Meets Virtual Reality, 2002: 71-73
[40] J. D. Brown, J. Rosen, Y. S. Kim, et al. In-vivo and in-situ compressive properties of porcine abdominal soft tissues. Medicine Meets Virtual Reality, 2003: 26-32
[41] J. Rosen, B. Hannaford, M. P. MacFarlane. Force controlled and teleoperated endoscopic grasper for minimally invasive surgery-experimental performance evaluation. IEEE Trans. Biomed.Eng., 1999, 46: 1212-1221
[42] A.Tholey, W. Pillarisetti, J. P. Desai. Design, development and testing of an automated laparoscopic grasper with 3-D force measurement capability. Medical Simulation, 2004: 38-48
[43] K. S. Eom, I. H. Suh, W. K. Chung, et al. Disturbance observer based force control of robot manipulator without force sensor. IEEE Int. Conf. Robot. Autom., 1998, 1:3012-3017
[44] L. J. Jung, K. Huh. Robust contact force estimation for robot manipulators in three-dimensional space. Journal of Mechanical Engineering Science, 2006, 220(9): 1317-1327
[45] S. Katsura, Y. Matsumoto, K. Ohnishi. Modeling offeree sensing and validation of disturbance observer for force control. IEEE Trans. Ind. Electron., 2007, 54: 530-538
[46] K. Tadano and K. Kawashima. Development of 4-DOFs forceps with force sensing using pneumatic servo system. IEEE Int. Conf. Robot. Autom., 2006: 2250-2255
[47] N. Zemiti, G. Morel, N. Bonnet. Mechatronic Design of a New Robot for Force Control in Minimally Invasive Surgery. IEEE/ASME Transactions on Mechatronics, 2007: 143-153
[48] S. Shimachi, Y. Hakozaki, T. Tada, et al. Measurement of force acting on surgical instrument for force-feedback to master robot console. International Congress Series, 2003, 1256: 538-546
[49] S. Shimachi, S. Hirunyanitiwatna, Y. Fujiwara, et al. Adapter for contact force sensing of the da Vinci robot. Int J Med Robotics Comput Assist Surg, 2008, 4(2): 121-130
[50] H. Mayer, I. Nagy, A. Knoll, et al. The Endo[PA]R system for minimally invasive surgery. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004: 3637-3642
[51] G. Tholey, J. P. Desai. A Modular, Automated Laparoscopic Grasper with Three-Dimensional Force Measurement Capability. IEEE Int. Conf. Robot. Autom., 2007: 250-255
[52] S. Hirose, K. Yoneda. Development of optical 6-axial force sensor and its signal calibration considering non-linear interferenc. IEEE Int. Conf. Robot. Autom., 1990: 46-53
[53] U. Seibold, B. Kuebler, G. Hirzinger. Prototype of instrument for minimally invasive surgery with 6-axis force sensing capability. IEEE Int. Conf. Roboti. Autom., 2005: 496-501
[54] G. S. Fischer, T. Akinbiyi, S. Saha, et al. Ischemia and force sensing surgical instruments for augmenting available surgeon information. Int. Conf. Biomed. Roboti. Biomechatron., 2006: 1030-1035
[55] J. Dargahi, M. Parameswaran, S. Payandeh. A micromachined piezoelectric tactile sensor for an endoscopic grasper-theory, fabrication and experiments. J. Microelectromech. Syst., 2000, 9: 329-335
[56] S. Sokhanvar, M. Packirisamy, J. Dargahi. A multifunctional PVDF-based tactile sensor for minimally invasive surgery. Smart Mater. Struct., 2007, 16: 989-998
[57] M. V. Ottermo, O. Stavdahl, T. A. Johansen. Palpation instrument for augmented minimally invasive surgery. IEEE/RSJInt. Conf. Intell. Robot. Syst., 2004: 3960-3964
[58] S. Schostek, C. Ho, D. Kalanovic, et al. Artificial tactile sensing in minimally invasive surgery-a new technical approach. Minimally Invasive Therapy, 2006, 15: 296-304
[59] G. F. Buess, M. O. Schurr, S. C. Fischer. Robotics and allied technologies in endoscopic surgery. Arch. Surg., 2000, 135: 229-235
[60] P.Valdastri, K. Harada, A. Menciassi, et al. Integration of a miniaturized triaxial force sensor in a minimally invasive surgical tool. IEEE Trans. Biomed. Eng., 2006, 53: 2397-2400
[61] B. L. Gray, R. S. Fearing. A surface micromachined microtactile sensor array. IEEE Int. Conf. Robot. Autom., 1996, 1-6
[62] R. D. Howe, W. J. Peine, D. A. Kontarinis, et al. Remote palpation technology. IEEE Eng. Med. Biol. Mag., 1995, 14: 318-323
[63] E. Fetter, M. Biehl, J. Meyer. Vibrotactile palpation instrument for use in minimally invasive surgery. IEEE Eng. Medicine Biol. Soc. Int. Conf., 1996, 179-180
[64] I. Baumann, P. K. Plinkert, W. Kunert et al. Vibrotactile characteristics of different tissues in endoscopic otolaryngologic surgery-in vivo and ex vivo measurements. Min. Invas. Ther. Allied Technol., 2001, 10(6): 323-327
[65] A. Menciassi, A. Eisinberg, M. C. Carrozza, et al. Force sensing micro instrum- ent for measuring tissue properties and pulse in microsurgery. IEEE/ASME Trans. Mechatron., 2003, 8: 10-17
[66] M. O. Culjat, C. H. King, M. L. Franco, et al. A Tactile Feedback System for Robotic Surgery. 30th Annual International IEEE EMBS Conference Vancouver, 2008: 1930-1934
[67] S. X. Wang, J. N. Ding, J. T. Yun , et al. A Robotic System with Force Feedback for Micro-Surgery. IEEE Int. Conf. Robot. Autom., 2005: 199-204.
[68] G. S. Buja. Disturbance torque estimation in a sensorless DC drive. Proceedings of International Conference on Industrial Electronics, Control, and Instrumentation, 1993, 2: 977-982
[69] S. Komadar, M. Ishidar, K. Ohnishiir, et al. Motion control of linear synchronous motors based on disturbance observer. 16th Annual Conference of IEEE Industrial Electronics Society, 1990, 1: 154-159
[70] S. Komada, M. Ishidar, K. Ohnishi, et al. Disturbance Observer Based Motion Control of Direct Drive Motors. IEEE Transaction on Energy Conversion, 1991, 6, (3): 553-559
[71] K. Kaneko, K. Komoria, K. Ohnishi, et al. Manipulator Control based on a Disturbance Observer in the Operational Space. IEEE Int. Conf. on Robotics and Automation, 1994, 2: 902-909
[72] E. Leksono, T. Murakami, K. Ohnishi. Observer Based Robust Force Control in cooperative Motion Systems. The 24th Annual Conf. of the IEEE Industrial Electronics Society, 1998, 3: 1801-1806
[73] C. S .Liu, H. Peng. Disturbance observer based tracking control. Journal of Dynamic Systems, Measurement, and Control, 2000, 122(2): 332-335
[74] J. P. Jiang, S. Chen, P. K. Sinha. Optimal Feedback Control of Direct-Current Motors. IEEE Transactions on Industrial Electronics, 1990, 37(4): 269-274
[75] P. P. AcarnIey, J. K. AI-Tayie. Estimation of speed and armature temperature in a brushed DC drive using the extended Kalman filter. Proc.IEE Electric Power Applications, 1997, 144(1): 13-20
[76] M. Barut, S. Bogosyan, M. Gokasan. EKF Based Sensorless Direct Torque Control of IMs in the Low Speed Range. The IEEE International Symposium on Industrial Electronics, 2005, 3: 969-974
[77] Z. Y. Ran, H. D. Li, S. J. Chen. Application of Optimized EKF in Direct Torque Control System of induction motor. Int. Con. On Innovative Computing, Information and Control, 2006, 1:331-335
[78] Y. Liu, Z. Q. Zhu, D. Howe. Instantaneous Torque Estimation in Sensorless Direct-Torque-Controlled Brushless DC Motors. IEEE Transactions on Industry Applications, 2006, 42 (5):1275-1283
[79] S. C. Lee, H. S. Ahn. Sensorless Torque Estimation using Adaptive Kalman Filter and Disturbance Estimator. IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications, 2010: 87-92
[80] M. J. Massimino.Improved force perception through sensory substitution. Control Engineering Practice, 1995, 3(2): 215-222
[81] P.Richard, P. Coiffet. Human perceptual issues in virtual environments: sensory substitution and information redundancy. Proceedings of the IEEE International Workshop on Robot and Human Communication, 1995: 301-306
[82] T. Debus, T. Becker, P. Dupont, et al. Multichannel vibrotactile display for sensory substitution during teleoperation. Proceedings of the International Society for Optical Engineering, 2001, 4570: 42-49
[83] C. Kennedy, J. P. Desai. Force feedback using vision. IEEE. International Conference on Advanced Robotics, 2003: 179-184
[84] C. W. Kennedy, J. P. Desai. A vision-based approach for estimating contact forces: Applications to robot-assisted surgery. Applied Bionics and Biomechan -ics, 2005, 2(1): 53-60
[85] D. Aarno, S. Ekvall, D. Kragic. Adaptive virtual fixtures for machine assisted teleoperation tasks. IEEE Int'l. Conf. on Robotics and Automation, 2005: 1151-1156
[86] A. B. Kuang, S. Payandeh, B. Zheng, et al. Assembling virtual fixtures for guidance in training environments. Proc. 12th Symposium on Haptic Interfaces for Virtual Environments and Teleoperator Systems, 2004: 367-374
[87] Y. S. Park, H. Kang, T. F. Ewing, et al. Enhanced teleoperation for D & D. Proc. IEEE Int'l. Conf. on Robotics and Automation, 2004: 3702-3707
[88] L. Rosenberg. Virtual fixtures: Perceptual tools for telerobotic manipulation. Proc. IEEE Virtual Reality Int'l. Symposium, 1993: 76-82
[89] J. J. Abbott, A. M. Okamura. Virtual Fixture Architectures for Telemanipulation. IEEE Int. Conf. Robotics and Automation, 2003: 2798-2805
[90] S. Park, R. D. Howe, D. F. Torchiana. Virtual Fixtures for Robotic Cardiac Surgery. Fourth Intl. Conf. on Medical Image Computing and Computer- Assisted Intervention, 2001: 419-1420
[91] J. Abbot, A. Okamura. Analysis of virtual fixture contact stability for telemanipulation. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003: 2699-2706
[92] R. B. Gillespie, M. R. Cutkosky. Stable User Specifc Haptic Rendering of the Virtual Wall. ASME Dynamic Systems and Control, 1996, 58:397-406
[93] S. Payandeh, Z. Stanisic. On application of virtual fixtures as an aid telemanipulation and training. Proc. 10th Symposium on Haptic Interfaces for Virtual Environments and Teleoperator Systems, 2002: 18-23
[94] C. A. Moore, M. A. Peshkin, J. E. Colgate. Cobot Implementation of 3D Virtual Surfaces. IEEE Intl. Conf. Robotics and Automation, 2002: 3242-3247.
[95] A. Bettini, S. Lang, A. Okamura, et al. Vision Assisted Control for Manipulation Using Virtual Fixtures. IEEE/RSJ Intl. Conf. Intelligent Robots and Systems, 2001: 1171-1176
[96] J. Duffy. Analysis of Mechanisms and Robot Manipulators, London: Edword Arnold, 1980
[97]廖启征,梁崇高,张启先,空间7R机构位移分析的新研究,机械工程学报,1986,22(3):1-8
[98]理查德·P·保罗(美)著,郑时雄,谢存禧译,张启先校,机器人操作手:数学、编程与控制,北京:机械工业出版社,1986
[99] A. T. Yang, F. Freudenstein. Application of dual number quaternion algebra to the analysis of spatial mechanisms. ASME J, Appl. Mech., 1964, 86(6): 300-308
[100] H. Y. Lee, C. G. Liang. A new vetor theory for the analysis of spatial mechanisms. Mechanism and Machine Theory, 1988, 23(3): 209-217
[101] J. Denavit, R. S. Hartenberg. A kinematic notation for lower-pair mechanisms based on matrices. Trans. ASME, J. of Applied Mechanics, 1955, 77(6): 215-221
[102]理查德·摩雷(美),李泽湘(中),夏恩卡·萨恩特学(美)著,徐卫良,钱瑞明译,机器人操作的数学导论,北京:机械工业出版社,1997
[103] J. J. Uicker, J. Denavit, R. S. Hartenberg. An iterative method for displacement analysis of spatial mechanisms. ASME J. Mech., 1964, 86(2): 309-314
[104] J. M. Selig. Geometrical Method in Robotics. New York: Springer Verlag, 1996
[105] C. T. Lin, C. S. Georgee Lee. Fault-tolerant reconfigurable architecture for robot kinematics and dynamics computations.IEEE transactions on system, man, cybernetics, 1991, 21(5): 983-999
[106] Calafiore, M. Indri, B. Bona. Robot dynamic calibration: optimal excitation trajectories and experimental parameter estimation. Journal of robotic systems, 2001, 18(2): 55-68
[107] C. J. Lin. An efficient method for linearization of dynamic models of robot manipulators. IEEE transactions on robotics and automation, 1989, 5 (4): 397-408
[108] C. J. Lin. A new method for linearization of dynamic robot models. IEEE transactions on system, man, cybernetics, 1990, 20(11): 2-17
[109] A. Jain, G. Rodriguez. Diagonalized Lagrangian robot dynamics. IEEE transactions on robotics and automation, 1995, 11(4):571-584
[110] T. R. Kane, D. A. Levision. The use of Kane’s dynamic equation in robotics. International Journal of robotic research, 1983, 2(3): 3-2l
[111] S. K. Lin. Dynamics of the manipulator with closed chain. IEEE transactions on robotics and automation, 1990, 6(4): 496-501
[112]苏暑,机器人动力学分析的图论方法,机械设计, 1994,l: 6-8
[113] B. Armstrong, O. Khatib, J. Burdick. Explicit dynamic model and inertial parameters of the PUMA 560 arm. IEEE Int. Conf. Robot. Autom., 1986: 510-518
[114] V. D. Tourassis, C. P. Neuman. The inertial characteristics of dynamic robot models. Mechanism and Machine Theory, 1985, 20(1): 41-52
[115] L. M. Da, A. Doria, R. Lot. Spatial mechanism for the measurement of the inertia tensor: theory and experimental results. Journal of Dynamic Systems, Measurement and Control, 1999, 121(1): 111-116
[116] A. Fregolent, A. Sestieri, M. Falzetti. Identification of rigid body inertia properties from experimental frequency response. 10th International modal analysis conference, 1992: 219-225
[117] J. Toivola, O. Nuutila. Comparison of three methods for determining rigid body inertia properties from frequency response functions. Proceedings of the 11th International modal analysis conference, 1997: 1126-1132
[118] P. S. Hu. Determination of rigid body characteristics from time domain modal analysis. Journal of Sound and Vibration, 1994, 177(1): 31-41
[119]王树新,张海根,黄铁球等,机器人动力学参数辨识方法的研究,机械工程学报,1999,35(1):23-26
[120] S. Guegan, W. Khalil, P. Lemoine. Identification of the dynamic parameters of the Orthoglide. IEEE Int. Conf. Robot. Autom., 2003: 3272-3277
[121] E. Burdet, A. Codourey. Evaluation of parametric and nonparametric nonlinear adaptive controllers. Robotica, 1998, 16(1): 59-73
[122] K. S. Narendra, K. Parthasaraphy. Identification and control of dynamical systems using neural network. IEEE Transaction on Neural Network, 1990, 1(1): 5-27
[123] Z. H Jiang, T. Ishida, M. Sunawada. Neural network aided dynamic parameter identification of robot manipulators. Proceedings of the IEEE international conference on systems, man and cybernetics, 2007: 3298-3303
[124] A. J. Madhani, G. Niemeyer, J. K. Salisbury. The black falcon: a teleoperated surgical instrument for minimally invasive surgery. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998, 2: 936-944
[125] G. J. Hamlin, A. C. Sanderson. A novel concentric multilink spherical joint with parallel robotics applications. IEEE Int. Conf. Robot. Autom., 1994:1267-1272
[126]张林安,力反馈型主操作手设计及其控制策略研究:[硕士学位论文],天津;天津大学,2010
[127]李建民,微创外科手术机器人本体系统设计方法研究:[硕士学位论文],天津;天津大学,2008
[128] J. M. Li, S. X. Wang, X. F. Wang, et al. Optimization of a novel mechanism for a minimally invasive surgery robot. Int J Med Robotics Comput Assist Surg, 2010, 6: 83-90
[129] A. Morecki, Z. Busko, H. Gasztold, et al. Synthesis and control of the anthropomorphic twohanded manipulator, Proc. of the 10th Int’l Symposiumon Industrial Robots, 1980: 461-474
[130] J. K. Salisbury. Kinematic and force analysis of articulated hands. Ph.D dissertation, Dept. of Mechanical Engineering, Stanford University, Stanford, CA, 1982
[131] L. W. Tsai, J. J. Lee, Kinematic analysis of tendon driven robotic mechanisms using graph theory. ASME J Mech Transm Autom Des, 1989, 111(1): 59-65
[132] J. J. Lee, Y. H. Lee. Dynamic Analysis of Tendon Driven Robotic Mechanisms. Journal of Robotic Systems, 2003, 20: 229-238
[133] L. W. Tsai. Robot analysis-the mechanics of serial and parallel manipulators. Wiley, New York, 1999
[134] R. M. Murray, Z. Li, S. S. Sastry. A Mathematical Introduction to Robotic Manipulation. CRC Press, Inc., 1994
[135] P. R. Dahl. Solid Friction Damping of Mechanical Vibrations. AIAA, 1976, 14 (12): 1675-1682
[136] P. R. Dahl. Solid Friction Damping of Spacecraft Vibrations. AIAA Guidance and Control Conf, 1975: 75-1104
[137] D. A. Hassig, B. Friedland. On the Modeling and simulation of friction. ASME Journal of Dynamic systems, Measurement and control, 1991, 113: 354-362
[138] B. Armstrong-Helouvry, P. Dupont, C. Canudas De Wit. A survey of models, analysis tools and compensation methods for the control of machine with friction. Automatica, 1994, 30(7): 1083-1138
[139] C. Canudas de Wit, H. Olsson, K. J. Astrom, et al.A New Model for Control of Systems with Friction. IEEE Trans. on Automatic Control, 1995, 40(3): 419-425
[140] E. J. Berger. Friction modeling for dynamic system simulation. ASME App Mech Rev, 2002, 55(6): 535-577
[141] P. A. Bliman, M.Sorine. Easy-to-Use Realistic Dry Friction Models for Automatic Control. Proceedings of 3rd European Control Conference, 1995, 3788-3794
[142] D. Karnopp. Computer simulation of slip-stick friction in mechanical dynamic systems. Journal of Dynamic Systems, Measurement and Control, 1985, 107(1): 100-103
[143] P. Hsu, P. M. Bodson, S. Sastry, et al. Adaptive identification and control of manipulators without using joint accelerations, Proc. IEEE Intl. Conf. Rob.& Auto., 1987, 1210-1215
[144] D. A. Lawrence. Stability and Transparency in Bilateral Teleoperation. IEEE Transactions on Robotics and Automation, 1993, 9(5): 624-637
[145]陈惠开,吴新余,吴叔美,现代网络分析,北京:人民邮电出版社, 1992
[146] H. C. Cho, J. H. Park. Impedance Controller Design of Internet-based Teleoperation Using Absolute Stability Concept. IEEE Int.Conf Intelligent robots and Systems, 2002: 2256-2261
[147] L. Y. Ni, D. L. Wang. Contact Transition Stability Analysis for a Bilateral Teleoperation System. IEEE International Conference on Robotics and Automation, 2002: 3272-3277
[148] K. Hashtrudi-Zaad, S. E. Salcudean. Analysis and Evaluation of Stability and Performance Robustness for Teleoperation Control Architectures. IEEE Int. Conf. Robot. Autom., 2000, 3107-3113
[149] D. A. Lawrence. Stability and transparency in bilateral teleoperation. IEEE Transactions on Robotics and Automation, 1993, 624-637
[150] J. E. Speich, K. Fite, M. Goldfarb. A Method for Simultaneously Increasing Transparency and Stability Robustness in Bilateral Telemanipulation. IEEE Int. Conf. Robot. Autom., 2000, 2671-2676
[151]邓启文,空间机器人遥操作双边控制技术研究:[博士论文],湖南;国防科学技术大学, 2006
[152] M. C. Cavusoglu, J. Yan, S. S. Sastry. A hybrid system approach to contact stability and force control in robotic manipulators. Proc.12th IEEE Int. Symp. Intell. Contr., 1997, 143-148
[153] John J.Craig著,贠超等译,机器人学导论,北京:机械工业出版社, 2008
[154] D. A. Lawrence. Designing teleoperator architectures for transparency. IEEE Int. Conf. Robot. Autom., 1992, 1406-1411
[2] H. Kang, J. T. Wen. EndoBot: A robotic assistant in minimally invasive surgeries. IEEE Int. Conf. Robot. Autom., 2001, 2: 2031-2036
[3] S. R. Payne, T. F. Ford, J. E. Wickham. Endoscopic management of upper urinary stones, British Journal of Surgery, 1985, 72: 822-824
[4] P. Mouret. How I developed Laparoscopic choleeystectomy. Ann Acad Med Singapore, 1996, 25: 744-747
[5] R. H. Taylor, J. Funda, B. Eldridge, et al. A Telerobotic Assistant for Laparoscopic Surgery. IEEE Eng in Med Biol Mag, 1995, 3: 279-288
[6] P. S. Green, W. HillJ, J. F. Jensen, et al. Telepresence Surgery. IEEE Eng in Med Biol Mag, 1995, (3): 324-329
[7] G. S. Guthart, J. K. Salisbury, Jr., et al. The IntutiveTM Telesurgery System: Overview and Application. IEEE Int. Conf. Robot. Autom., 2000: 618-621
[8] D.S. Kwon, K.Y. Woo, S.K. Song, et al. Microsurgical Telerobot system. Proceedings of IEEE International Conference on Intelligent Robots and Systems, 1998, (2): 945-950
[9] M. C. Cavusogln, F. Tendick, M. Cohn, et al. A Laparoscopic Telesurgical Workstation. IEEE Transaction Robotics and Autoation, 1999, 15: 728-739
[10] M. Lazeroms, W. Jongkind, G. Honderd. Telemanipulator Design for Minimally Invasive Surgery. Proceedings of American Control Conference, 1997, 2: 2982-2986
[11]刘少强,黄惟一,王爱民等,用于微创外科手术的遥控机器人系统研究现状及趋势,机器人,2002,24 (3):283-288
[12] L. Mettler, M. Irahim, W. Jonat. One year of experience working with the aid of a robotic assistant (the voice-controlled optic holder AESOP) in gynaecological endoscopic surgery. Human Reproduction, 1998, 13(10): 2748-2750
[13] S. E. Butner, M. Ghodoussi. A real-time system for tele-surgery. Proceedings of the 21st International Conference on Distributed Computing Systems, 2001: 236-243
[14] M. Ghodoussi, S. E. Butner, Y. L. Wang. Robotic surgery the transatlantic case. IEEE Int. Conf. Robot. Autom., 2002, 2(2): 1882-1888
[15] D. Stoianovici, R. Webster, L. Kavoussi. Robotic Tools for Minimally Invasive Urologic Surgery. Chapter in Complications of Urologic Laparoscopic Surgery: Recognition, Management & Prevention, December 2002: 1-17
[16] R. M. Satava. Surgical Robotics: The Early Chronicles: A Personal Historical Perspective. In Surgical Laparoscopy Endoscopy&Percercutaneous Techniques, Lipincott Williams&Wikins, Inc. Philadelphia, 2002, 12: 6-16
[17] M. Menon, A. Shrivastava, A. Tewari, et al. Laparoscopic and Robot Assisted Radical Prostatectomy: Establishment of a Structured Program and Preliminary Analyses of Outomes. J Urol, 2002, 168: 945-949
[18] M. O. Urr, G. Buess, B. Neisius, et al. Robotics and telemanipulation technologies for endoscopic surgery. A review of the ARTEMIS project. Advanced Robotic Telemanipulator for Minimally Invasive Surgery. Surg Endosc, Apr 2000, 14(4): 375-381
[19] J. H. Lum Mitchell, C. W. Friedman Diana, R. Jacob, etc. The RAVEN: Design and Validation of a Telesurgery System. International Journal of Robotics Research, 2009, 28: 1183-1197
[20] M. J. H. Lum, MSEE, C.W. Diana, etc. Objective Assessment of Telesurgical Robot Systems: Telerobotic FLS. Medicine meets virtual reality, 2008, 132: 263-265
[21] M. J. H. Lum,D. C. W. Friedman,H. H. I. King. Teleoperation of a Surgical Robot via Airborne Wireless Radio and Transatlantic Internet Links. In Advanced Robotics, 2008, 42: 305-314
[22] H. H. King, B. Hannaford, K. Kwok, et al. Plugfest 2009: Global Interoperabil- ity in Telerobotics and Telemedicine. IEEE Int. Conf. Robot. Autom., 2010: 1733-1738
[23] M. C. Cavusoglu, F. Tendick, M. Cohn, et al. A Laparoscopic Telesurgical Workstation. IEEE Transactions on Robotics and Automation, 1999, 15: 728-739
[24] D. S. Kwon, K. Y. Woo, S. K. Song, W. S. Kim, et al. Microsurgical Telerobot System. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998, 2: 945-950
[25] D. S. Kwon, K. Y. Woo, H. S. Cho, et al. Haptic Control of the Master Hand Controller for a Microsurgical Telerobot System. IEEE Int. Conf. Robot. Autom., 1999, 3: 1722-1727
[26] K. Ikuta, T. Hasegawa, S. Daifu. Hyper Redundant Miniature Manipulator“hyper Finger”for Remote Minimally Invasive Surgery in Deep Area. IEEE Int. Conf. Robot. Autom., 2003, 1: 1098-1102
[27] K. Ikuta, K. Yamamoto, K. Sasaki. Development of Remote Micro Surgery Robot and New Surgical Procedure for Deep and Narrow Space. IEEE Int. Conf. Robot. Autom., 2003, 1: 1103-1108
[28]李群智,机器人辅助显微外科手术系统的研究与开发:[硕士学位论文],天津;天津大学,2004
[29]董玉涛,张建勋,微操作机器人底层控制系统设计,机器人,2000,22(4):310-314
[30] Q. Z. Li, S. X. Wang, J. T. Yun, et al, Haptic device with gripping force feedback. IEEE Int. Conf. Robot. Autom., 2005: 1190-1195
[31] S. X.Wang, L. W. Yue, Q. Z. Li, et al. Conceptual Design and Dimensional Synthesis of“MicroHand”. Journal of Mechanism and Machine Theory, 2008, 43: 1186-1197
[32]王树新,丁杰男,贠今天,显微外科手术机器人——“妙手”系统的研究,机器人,2006,28(2):130-135
[33] L. Podsedkowski. Robin Heart 0, 1, and 3-Mechanical Construction Development, Bulletin of the Polish Academy of Sciences. Technical Sciences, 2005, 53 (1): 79-85
[34] J. R. Shi, M. Pascal, P. Viviane, et al. Preliminary Results on the Design of a Novel Laparoscopic Manipulator. Proceeding of the 11th World Congress in Mechanism and Machine Science, 2004: 1181-1185
[35] http://www.hansenmedical.com/products/sensei.aspx
[36] H. Mayer, I. Nagy, A. Knoll, et al. An Experimental System for Robotic Heart Surgery. 18th IEEE Symposium on Computer-Based Medical System, 2005: 56-60
[37] N. Simaan, R. H. Taylor, P. Flint. A Dexterous System for Laryngeal Surgery. IEEE Int. Conf. Robot. Autom., 2004: 351-357
[38] P. Puangmali, K.Althoefer, L. D. Seneviratne, et al. State-of-the-Art in Force and Tactile Sensing for Minimally Invasive Surgery. IEEE Sensors Journal, 2008: 371-381
[39] J. D. Brown, J. Rosen, M. Moreyra, et al. Computer-controlled motorized endoscopic grasper for in vivo measurement of soft tissue biomechanical characteristics. Medicine Meets Virtual Reality, 2002: 71-73
[40] J. D. Brown, J. Rosen, Y. S. Kim, et al. In-vivo and in-situ compressive properties of porcine abdominal soft tissues. Medicine Meets Virtual Reality, 2003: 26-32
[41] J. Rosen, B. Hannaford, M. P. MacFarlane. Force controlled and teleoperated endoscopic grasper for minimally invasive surgery-experimental performance evaluation. IEEE Trans. Biomed.Eng., 1999, 46: 1212-1221
[42] A.Tholey, W. Pillarisetti, J. P. Desai. Design, development and testing of an automated laparoscopic grasper with 3-D force measurement capability. Medical Simulation, 2004: 38-48
[43] K. S. Eom, I. H. Suh, W. K. Chung, et al. Disturbance observer based force control of robot manipulator without force sensor. IEEE Int. Conf. Robot. Autom., 1998, 1:3012-3017
[44] L. J. Jung, K. Huh. Robust contact force estimation for robot manipulators in three-dimensional space. Journal of Mechanical Engineering Science, 2006, 220(9): 1317-1327
[45] S. Katsura, Y. Matsumoto, K. Ohnishi. Modeling offeree sensing and validation of disturbance observer for force control. IEEE Trans. Ind. Electron., 2007, 54: 530-538
[46] K. Tadano and K. Kawashima. Development of 4-DOFs forceps with force sensing using pneumatic servo system. IEEE Int. Conf. Robot. Autom., 2006: 2250-2255
[47] N. Zemiti, G. Morel, N. Bonnet. Mechatronic Design of a New Robot for Force Control in Minimally Invasive Surgery. IEEE/ASME Transactions on Mechatronics, 2007: 143-153
[48] S. Shimachi, Y. Hakozaki, T. Tada, et al. Measurement of force acting on surgical instrument for force-feedback to master robot console. International Congress Series, 2003, 1256: 538-546
[49] S. Shimachi, S. Hirunyanitiwatna, Y. Fujiwara, et al. Adapter for contact force sensing of the da Vinci robot. Int J Med Robotics Comput Assist Surg, 2008, 4(2): 121-130
[50] H. Mayer, I. Nagy, A. Knoll, et al. The Endo[PA]R system for minimally invasive surgery. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004: 3637-3642
[51] G. Tholey, J. P. Desai. A Modular, Automated Laparoscopic Grasper with Three-Dimensional Force Measurement Capability. IEEE Int. Conf. Robot. Autom., 2007: 250-255
[52] S. Hirose, K. Yoneda. Development of optical 6-axial force sensor and its signal calibration considering non-linear interferenc. IEEE Int. Conf. Robot. Autom., 1990: 46-53
[53] U. Seibold, B. Kuebler, G. Hirzinger. Prototype of instrument for minimally invasive surgery with 6-axis force sensing capability. IEEE Int. Conf. Roboti. Autom., 2005: 496-501
[54] G. S. Fischer, T. Akinbiyi, S. Saha, et al. Ischemia and force sensing surgical instruments for augmenting available surgeon information. Int. Conf. Biomed. Roboti. Biomechatron., 2006: 1030-1035
[55] J. Dargahi, M. Parameswaran, S. Payandeh. A micromachined piezoelectric tactile sensor for an endoscopic grasper-theory, fabrication and experiments. J. Microelectromech. Syst., 2000, 9: 329-335
[56] S. Sokhanvar, M. Packirisamy, J. Dargahi. A multifunctional PVDF-based tactile sensor for minimally invasive surgery. Smart Mater. Struct., 2007, 16: 989-998
[57] M. V. Ottermo, O. Stavdahl, T. A. Johansen. Palpation instrument for augmented minimally invasive surgery. IEEE/RSJInt. Conf. Intell. Robot. Syst., 2004: 3960-3964
[58] S. Schostek, C. Ho, D. Kalanovic, et al. Artificial tactile sensing in minimally invasive surgery-a new technical approach. Minimally Invasive Therapy, 2006, 15: 296-304
[59] G. F. Buess, M. O. Schurr, S. C. Fischer. Robotics and allied technologies in endoscopic surgery. Arch. Surg., 2000, 135: 229-235
[60] P.Valdastri, K. Harada, A. Menciassi, et al. Integration of a miniaturized triaxial force sensor in a minimally invasive surgical tool. IEEE Trans. Biomed. Eng., 2006, 53: 2397-2400
[61] B. L. Gray, R. S. Fearing. A surface micromachined microtactile sensor array. IEEE Int. Conf. Robot. Autom., 1996, 1-6
[62] R. D. Howe, W. J. Peine, D. A. Kontarinis, et al. Remote palpation technology. IEEE Eng. Med. Biol. Mag., 1995, 14: 318-323
[63] E. Fetter, M. Biehl, J. Meyer. Vibrotactile palpation instrument for use in minimally invasive surgery. IEEE Eng. Medicine Biol. Soc. Int. Conf., 1996, 179-180
[64] I. Baumann, P. K. Plinkert, W. Kunert et al. Vibrotactile characteristics of different tissues in endoscopic otolaryngologic surgery-in vivo and ex vivo measurements. Min. Invas. Ther. Allied Technol., 2001, 10(6): 323-327
[65] A. Menciassi, A. Eisinberg, M. C. Carrozza, et al. Force sensing micro instrum- ent for measuring tissue properties and pulse in microsurgery. IEEE/ASME Trans. Mechatron., 2003, 8: 10-17
[66] M. O. Culjat, C. H. King, M. L. Franco, et al. A Tactile Feedback System for Robotic Surgery. 30th Annual International IEEE EMBS Conference Vancouver, 2008: 1930-1934
[67] S. X. Wang, J. N. Ding, J. T. Yun , et al. A Robotic System with Force Feedback for Micro-Surgery. IEEE Int. Conf. Robot. Autom., 2005: 199-204.
[68] G. S. Buja. Disturbance torque estimation in a sensorless DC drive. Proceedings of International Conference on Industrial Electronics, Control, and Instrumentation, 1993, 2: 977-982
[69] S. Komadar, M. Ishidar, K. Ohnishiir, et al. Motion control of linear synchronous motors based on disturbance observer. 16th Annual Conference of IEEE Industrial Electronics Society, 1990, 1: 154-159
[70] S. Komada, M. Ishidar, K. Ohnishi, et al. Disturbance Observer Based Motion Control of Direct Drive Motors. IEEE Transaction on Energy Conversion, 1991, 6, (3): 553-559
[71] K. Kaneko, K. Komoria, K. Ohnishi, et al. Manipulator Control based on a Disturbance Observer in the Operational Space. IEEE Int. Conf. on Robotics and Automation, 1994, 2: 902-909
[72] E. Leksono, T. Murakami, K. Ohnishi. Observer Based Robust Force Control in cooperative Motion Systems. The 24th Annual Conf. of the IEEE Industrial Electronics Society, 1998, 3: 1801-1806
[73] C. S .Liu, H. Peng. Disturbance observer based tracking control. Journal of Dynamic Systems, Measurement, and Control, 2000, 122(2): 332-335
[74] J. P. Jiang, S. Chen, P. K. Sinha. Optimal Feedback Control of Direct-Current Motors. IEEE Transactions on Industrial Electronics, 1990, 37(4): 269-274
[75] P. P. AcarnIey, J. K. AI-Tayie. Estimation of speed and armature temperature in a brushed DC drive using the extended Kalman filter. Proc.IEE Electric Power Applications, 1997, 144(1): 13-20
[76] M. Barut, S. Bogosyan, M. Gokasan. EKF Based Sensorless Direct Torque Control of IMs in the Low Speed Range. The IEEE International Symposium on Industrial Electronics, 2005, 3: 969-974
[77] Z. Y. Ran, H. D. Li, S. J. Chen. Application of Optimized EKF in Direct Torque Control System of induction motor. Int. Con. On Innovative Computing, Information and Control, 2006, 1:331-335
[78] Y. Liu, Z. Q. Zhu, D. Howe. Instantaneous Torque Estimation in Sensorless Direct-Torque-Controlled Brushless DC Motors. IEEE Transactions on Industry Applications, 2006, 42 (5):1275-1283
[79] S. C. Lee, H. S. Ahn. Sensorless Torque Estimation using Adaptive Kalman Filter and Disturbance Estimator. IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications, 2010: 87-92
[80] M. J. Massimino.Improved force perception through sensory substitution. Control Engineering Practice, 1995, 3(2): 215-222
[81] P.Richard, P. Coiffet. Human perceptual issues in virtual environments: sensory substitution and information redundancy. Proceedings of the IEEE International Workshop on Robot and Human Communication, 1995: 301-306
[82] T. Debus, T. Becker, P. Dupont, et al. Multichannel vibrotactile display for sensory substitution during teleoperation. Proceedings of the International Society for Optical Engineering, 2001, 4570: 42-49
[83] C. Kennedy, J. P. Desai. Force feedback using vision. IEEE. International Conference on Advanced Robotics, 2003: 179-184
[84] C. W. Kennedy, J. P. Desai. A vision-based approach for estimating contact forces: Applications to robot-assisted surgery. Applied Bionics and Biomechan -ics, 2005, 2(1): 53-60
[85] D. Aarno, S. Ekvall, D. Kragic. Adaptive virtual fixtures for machine assisted teleoperation tasks. IEEE Int'l. Conf. on Robotics and Automation, 2005: 1151-1156
[86] A. B. Kuang, S. Payandeh, B. Zheng, et al. Assembling virtual fixtures for guidance in training environments. Proc. 12th Symposium on Haptic Interfaces for Virtual Environments and Teleoperator Systems, 2004: 367-374
[87] Y. S. Park, H. Kang, T. F. Ewing, et al. Enhanced teleoperation for D & D. Proc. IEEE Int'l. Conf. on Robotics and Automation, 2004: 3702-3707
[88] L. Rosenberg. Virtual fixtures: Perceptual tools for telerobotic manipulation. Proc. IEEE Virtual Reality Int'l. Symposium, 1993: 76-82
[89] J. J. Abbott, A. M. Okamura. Virtual Fixture Architectures for Telemanipulation. IEEE Int. Conf. Robotics and Automation, 2003: 2798-2805
[90] S. Park, R. D. Howe, D. F. Torchiana. Virtual Fixtures for Robotic Cardiac Surgery. Fourth Intl. Conf. on Medical Image Computing and Computer- Assisted Intervention, 2001: 419-1420
[91] J. Abbot, A. Okamura. Analysis of virtual fixture contact stability for telemanipulation. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003: 2699-2706
[92] R. B. Gillespie, M. R. Cutkosky. Stable User Specifc Haptic Rendering of the Virtual Wall. ASME Dynamic Systems and Control, 1996, 58:397-406
[93] S. Payandeh, Z. Stanisic. On application of virtual fixtures as an aid telemanipulation and training. Proc. 10th Symposium on Haptic Interfaces for Virtual Environments and Teleoperator Systems, 2002: 18-23
[94] C. A. Moore, M. A. Peshkin, J. E. Colgate. Cobot Implementation of 3D Virtual Surfaces. IEEE Intl. Conf. Robotics and Automation, 2002: 3242-3247.
[95] A. Bettini, S. Lang, A. Okamura, et al. Vision Assisted Control for Manipulation Using Virtual Fixtures. IEEE/RSJ Intl. Conf. Intelligent Robots and Systems, 2001: 1171-1176
[96] J. Duffy. Analysis of Mechanisms and Robot Manipulators, London: Edword Arnold, 1980
[97]廖启征,梁崇高,张启先,空间7R机构位移分析的新研究,机械工程学报,1986,22(3):1-8
[98]理查德·P·保罗(美)著,郑时雄,谢存禧译,张启先校,机器人操作手:数学、编程与控制,北京:机械工业出版社,1986
[99] A. T. Yang, F. Freudenstein. Application of dual number quaternion algebra to the analysis of spatial mechanisms. ASME J, Appl. Mech., 1964, 86(6): 300-308
[100] H. Y. Lee, C. G. Liang. A new vetor theory for the analysis of spatial mechanisms. Mechanism and Machine Theory, 1988, 23(3): 209-217
[101] J. Denavit, R. S. Hartenberg. A kinematic notation for lower-pair mechanisms based on matrices. Trans. ASME, J. of Applied Mechanics, 1955, 77(6): 215-221
[102]理查德·摩雷(美),李泽湘(中),夏恩卡·萨恩特学(美)著,徐卫良,钱瑞明译,机器人操作的数学导论,北京:机械工业出版社,1997
[103] J. J. Uicker, J. Denavit, R. S. Hartenberg. An iterative method for displacement analysis of spatial mechanisms. ASME J. Mech., 1964, 86(2): 309-314
[104] J. M. Selig. Geometrical Method in Robotics. New York: Springer Verlag, 1996
[105] C. T. Lin, C. S. Georgee Lee. Fault-tolerant reconfigurable architecture for robot kinematics and dynamics computations.IEEE transactions on system, man, cybernetics, 1991, 21(5): 983-999
[106] Calafiore, M. Indri, B. Bona. Robot dynamic calibration: optimal excitation trajectories and experimental parameter estimation. Journal of robotic systems, 2001, 18(2): 55-68
[107] C. J. Lin. An efficient method for linearization of dynamic models of robot manipulators. IEEE transactions on robotics and automation, 1989, 5 (4): 397-408
[108] C. J. Lin. A new method for linearization of dynamic robot models. IEEE transactions on system, man, cybernetics, 1990, 20(11): 2-17
[109] A. Jain, G. Rodriguez. Diagonalized Lagrangian robot dynamics. IEEE transactions on robotics and automation, 1995, 11(4):571-584
[110] T. R. Kane, D. A. Levision. The use of Kane’s dynamic equation in robotics. International Journal of robotic research, 1983, 2(3): 3-2l
[111] S. K. Lin. Dynamics of the manipulator with closed chain. IEEE transactions on robotics and automation, 1990, 6(4): 496-501
[112]苏暑,机器人动力学分析的图论方法,机械设计, 1994,l: 6-8
[113] B. Armstrong, O. Khatib, J. Burdick. Explicit dynamic model and inertial parameters of the PUMA 560 arm. IEEE Int. Conf. Robot. Autom., 1986: 510-518
[114] V. D. Tourassis, C. P. Neuman. The inertial characteristics of dynamic robot models. Mechanism and Machine Theory, 1985, 20(1): 41-52
[115] L. M. Da, A. Doria, R. Lot. Spatial mechanism for the measurement of the inertia tensor: theory and experimental results. Journal of Dynamic Systems, Measurement and Control, 1999, 121(1): 111-116
[116] A. Fregolent, A. Sestieri, M. Falzetti. Identification of rigid body inertia properties from experimental frequency response. 10th International modal analysis conference, 1992: 219-225
[117] J. Toivola, O. Nuutila. Comparison of three methods for determining rigid body inertia properties from frequency response functions. Proceedings of the 11th International modal analysis conference, 1997: 1126-1132
[118] P. S. Hu. Determination of rigid body characteristics from time domain modal analysis. Journal of Sound and Vibration, 1994, 177(1): 31-41
[119]王树新,张海根,黄铁球等,机器人动力学参数辨识方法的研究,机械工程学报,1999,35(1):23-26
[120] S. Guegan, W. Khalil, P. Lemoine. Identification of the dynamic parameters of the Orthoglide. IEEE Int. Conf. Robot. Autom., 2003: 3272-3277
[121] E. Burdet, A. Codourey. Evaluation of parametric and nonparametric nonlinear adaptive controllers. Robotica, 1998, 16(1): 59-73
[122] K. S. Narendra, K. Parthasaraphy. Identification and control of dynamical systems using neural network. IEEE Transaction on Neural Network, 1990, 1(1): 5-27
[123] Z. H Jiang, T. Ishida, M. Sunawada. Neural network aided dynamic parameter identification of robot manipulators. Proceedings of the IEEE international conference on systems, man and cybernetics, 2007: 3298-3303
[124] A. J. Madhani, G. Niemeyer, J. K. Salisbury. The black falcon: a teleoperated surgical instrument for minimally invasive surgery. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998, 2: 936-944
[125] G. J. Hamlin, A. C. Sanderson. A novel concentric multilink spherical joint with parallel robotics applications. IEEE Int. Conf. Robot. Autom., 1994:1267-1272
[126]张林安,力反馈型主操作手设计及其控制策略研究:[硕士学位论文],天津;天津大学,2010
[127]李建民,微创外科手术机器人本体系统设计方法研究:[硕士学位论文],天津;天津大学,2008
[128] J. M. Li, S. X. Wang, X. F. Wang, et al. Optimization of a novel mechanism for a minimally invasive surgery robot. Int J Med Robotics Comput Assist Surg, 2010, 6: 83-90
[129] A. Morecki, Z. Busko, H. Gasztold, et al. Synthesis and control of the anthropomorphic twohanded manipulator, Proc. of the 10th Int’l Symposiumon Industrial Robots, 1980: 461-474
[130] J. K. Salisbury. Kinematic and force analysis of articulated hands. Ph.D dissertation, Dept. of Mechanical Engineering, Stanford University, Stanford, CA, 1982
[131] L. W. Tsai, J. J. Lee, Kinematic analysis of tendon driven robotic mechanisms using graph theory. ASME J Mech Transm Autom Des, 1989, 111(1): 59-65
[132] J. J. Lee, Y. H. Lee. Dynamic Analysis of Tendon Driven Robotic Mechanisms. Journal of Robotic Systems, 2003, 20: 229-238
[133] L. W. Tsai. Robot analysis-the mechanics of serial and parallel manipulators. Wiley, New York, 1999
[134] R. M. Murray, Z. Li, S. S. Sastry. A Mathematical Introduction to Robotic Manipulation. CRC Press, Inc., 1994
[135] P. R. Dahl. Solid Friction Damping of Mechanical Vibrations. AIAA, 1976, 14 (12): 1675-1682
[136] P. R. Dahl. Solid Friction Damping of Spacecraft Vibrations. AIAA Guidance and Control Conf, 1975: 75-1104
[137] D. A. Hassig, B. Friedland. On the Modeling and simulation of friction. ASME Journal of Dynamic systems, Measurement and control, 1991, 113: 354-362
[138] B. Armstrong-Helouvry, P. Dupont, C. Canudas De Wit. A survey of models, analysis tools and compensation methods for the control of machine with friction. Automatica, 1994, 30(7): 1083-1138
[139] C. Canudas de Wit, H. Olsson, K. J. Astrom, et al.A New Model for Control of Systems with Friction. IEEE Trans. on Automatic Control, 1995, 40(3): 419-425
[140] E. J. Berger. Friction modeling for dynamic system simulation. ASME App Mech Rev, 2002, 55(6): 535-577
[141] P. A. Bliman, M.Sorine. Easy-to-Use Realistic Dry Friction Models for Automatic Control. Proceedings of 3rd European Control Conference, 1995, 3788-3794
[142] D. Karnopp. Computer simulation of slip-stick friction in mechanical dynamic systems. Journal of Dynamic Systems, Measurement and Control, 1985, 107(1): 100-103
[143] P. Hsu, P. M. Bodson, S. Sastry, et al. Adaptive identification and control of manipulators without using joint accelerations, Proc. IEEE Intl. Conf. Rob.& Auto., 1987, 1210-1215
[144] D. A. Lawrence. Stability and Transparency in Bilateral Teleoperation. IEEE Transactions on Robotics and Automation, 1993, 9(5): 624-637
[145]陈惠开,吴新余,吴叔美,现代网络分析,北京:人民邮电出版社, 1992
[146] H. C. Cho, J. H. Park. Impedance Controller Design of Internet-based Teleoperation Using Absolute Stability Concept. IEEE Int.Conf Intelligent robots and Systems, 2002: 2256-2261
[147] L. Y. Ni, D. L. Wang. Contact Transition Stability Analysis for a Bilateral Teleoperation System. IEEE International Conference on Robotics and Automation, 2002: 3272-3277
[148] K. Hashtrudi-Zaad, S. E. Salcudean. Analysis and Evaluation of Stability and Performance Robustness for Teleoperation Control Architectures. IEEE Int. Conf. Robot. Autom., 2000, 3107-3113
[149] D. A. Lawrence. Stability and transparency in bilateral teleoperation. IEEE Transactions on Robotics and Automation, 1993, 624-637
[150] J. E. Speich, K. Fite, M. Goldfarb. A Method for Simultaneously Increasing Transparency and Stability Robustness in Bilateral Telemanipulation. IEEE Int. Conf. Robot. Autom., 2000, 2671-2676
[151]邓启文,空间机器人遥操作双边控制技术研究:[博士论文],湖南;国防科学技术大学, 2006
[152] M. C. Cavusoglu, J. Yan, S. S. Sastry. A hybrid system approach to contact stability and force control in robotic manipulators. Proc.12th IEEE Int. Symp. Intell. Contr., 1997, 143-148
[153] John J.Craig著,贠超等译,机器人学导论,北京:机械工业出版社, 2008
[154] D. A. Lawrence. Designing teleoperator architectures for transparency. IEEE Int. Conf. Robot. Autom., 1992, 1406-1411
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