手臂康复训练机器人控制及实验研究
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摘要
将机器人辅助治疗技术引入到偏瘫康复训练中，已经逐渐得到国内外研究人员的重视，并发展成为热门课题之一。其难点主要集中于运动康复训练方法如何通过机器人的控制策略得以实现。而我国在康复工程领域的研究刚刚起步，因此课题的研究更具有实际应用意义。
本论文从国内外上肢康复训练机器人的发展现状及应用、机器人机构设计和控制模式等方面，分析了机器人辅助上肢运动功能康复的可行性和方法的实现，具体研究如下：
本文依据康复机器人的应用对象和偏瘫康复理论，确定了机器人的设计目标和控制系统方案，并对机器人系统的关键技术进行了研究和论述，包括，安全性设计、力传感器特性研究以及传动机构对控制精度的影响问题，同时利用MATLAB软件解算操作臂的运动域。在此基础上，确定了康复机器人的控制算法和策略，机器人主要能完成轨迹跟踪控制、力示教再现控制、采用力外环的阻抗控制和抗阻运动控制，分别设计了这四种训练模式的具体实施策略，并建立了控制模型。
基于理论研究，利用dSPACE实时仿真平台进行了康复机器人的半实物仿真设计。将康复机器人系统引入控制回路，将实现各模式的控制模型、力信号处理模型、位置初始化模型等转化为Simulink与RTI联系的仿真模型，并令其成为相对独立的模块，确定各模块间的相互关系，同时对驱动电机伺服系统进行了模型辨识。此后，对正常人进行了机器人辅助训练的实验。分别对各种训练模式进行实验研究，实时调整控制参数，监测机器人系统的状态并反馈机器人的信息，对实验结果进行分析和评价。
The therapy technology of hemiplegia rehabilitation aided by robot has gradually acquired the recognition of the native and abroad researchers, and it is becoming one of the hottest subjects. The difficulties of these studies mainly focus on how to realize the training means of rehabilitation via robot controlling. Since the study in the field of rehabilitation engineering in our country is inchoate, the research is practical.
This paper systematically overviews the development situation and application of the upper limbs rehabilitation robot. Together with the organ design and control mode, it analyzes the feasibility of the aided-robot for upper-limb-motor rehabilitation and the way to realize it. The concrete researches are as follows:
According as the application objects and hemiplegia rehabilitation theory, it is confirmed the design arm and the control system scheme. The key technologies of the robot system are studied and presented, including the security design, the characteristic of the force sensor, the influence caused by the transmission organ toward the control precision. At the meantime, it calculates the motion region of robot's operation arm using the MATLAB. On the basis of above, it confirms the control algorithm and the strategy of rehabilitation robot. The robot can basically accomplish the trajectory tracking, force teaching and reappearance, impedance control adopting the force outer loop and resistance motion. The material methods of the four kinds of training mode are respectively achieved, and the control model is established.
Based on the dSPACE real-time platform, the HIL simulation is designed. Here the robot system is located in the control loop. The control model actualizing all kinds of modes, force signal model and position initialization model are all translated into the simulation models. These models are independent to each other and relate the Simulink with the RTI. Finally, through training the healthy subjects by robot, the feasibility of rehabilitation training with robot's aid is proved elementarily. With the control parameters momentarily adjusted and the feedback information, the results of the experiments are attained. Then the results are analyzed and estimated.
本论文从国内外上肢康复训练机器人的发展现状及应用、机器人机构设计和控制模式等方面，分析了机器人辅助上肢运动功能康复的可行性和方法的实现，具体研究如下：
本文依据康复机器人的应用对象和偏瘫康复理论，确定了机器人的设计目标和控制系统方案，并对机器人系统的关键技术进行了研究和论述，包括，安全性设计、力传感器特性研究以及传动机构对控制精度的影响问题，同时利用MATLAB软件解算操作臂的运动域。在此基础上，确定了康复机器人的控制算法和策略，机器人主要能完成轨迹跟踪控制、力示教再现控制、采用力外环的阻抗控制和抗阻运动控制，分别设计了这四种训练模式的具体实施策略，并建立了控制模型。
基于理论研究，利用dSPACE实时仿真平台进行了康复机器人的半实物仿真设计。将康复机器人系统引入控制回路，将实现各模式的控制模型、力信号处理模型、位置初始化模型等转化为Simulink与RTI联系的仿真模型，并令其成为相对独立的模块，确定各模块间的相互关系，同时对驱动电机伺服系统进行了模型辨识。此后，对正常人进行了机器人辅助训练的实验。分别对各种训练模式进行实验研究，实时调整控制参数，监测机器人系统的状态并反馈机器人的信息，对实验结果进行分析和评价。
The therapy technology of hemiplegia rehabilitation aided by robot has gradually acquired the recognition of the native and abroad researchers, and it is becoming one of the hottest subjects. The difficulties of these studies mainly focus on how to realize the training means of rehabilitation via robot controlling. Since the study in the field of rehabilitation engineering in our country is inchoate, the research is practical.
This paper systematically overviews the development situation and application of the upper limbs rehabilitation robot. Together with the organ design and control mode, it analyzes the feasibility of the aided-robot for upper-limb-motor rehabilitation and the way to realize it. The concrete researches are as follows:
According as the application objects and hemiplegia rehabilitation theory, it is confirmed the design arm and the control system scheme. The key technologies of the robot system are studied and presented, including the security design, the characteristic of the force sensor, the influence caused by the transmission organ toward the control precision. At the meantime, it calculates the motion region of robot's operation arm using the MATLAB. On the basis of above, it confirms the control algorithm and the strategy of rehabilitation robot. The robot can basically accomplish the trajectory tracking, force teaching and reappearance, impedance control adopting the force outer loop and resistance motion. The material methods of the four kinds of training mode are respectively achieved, and the control model is established.
Based on the dSPACE real-time platform, the HIL simulation is designed. Here the robot system is located in the control loop. The control model actualizing all kinds of modes, force signal model and position initialization model are all translated into the simulation models. These models are independent to each other and relate the Simulink with the RTI. Finally, through training the healthy subjects by robot, the feasibility of rehabilitation training with robot's aid is proved elementarily. With the control parameters momentarily adjusted and the feedback information, the results of the experiments are attained. Then the results are analyzed and estimated.
引文
[1] 寄婧，王兴武，杨瑞芳．被动训练对脑卒中恢复期患者运动功能的影响．中国临床康复．2003，7(16)：2380页
[2] 胡宇川，季林红．从医学角度探讨偏瘫上肢康复训练机器人的设计．中国临床康复．2004，8(34)：7754-7756页
[3] 金德闻，季林红，张济川．康复工程研究的新进展．中国康复医学杂志．2001，16(6)：328-330页
[4] 张付祥，付宜利，王树国．康复机器人研究进展．河北工业科技．2005，22(2)：100-105页
[5] 吕广明，孙立宁，彭龙刚．康复机器人技术发展现状及关键技术分析．哈尔滨工业大学学报．2004，36(9)：1224-1227，1231页
[6] Krebs HI, Hogan N, Aisen ML, et al. Robot-aided neurorehabilitation. IEEE Transactions on Rehabilitation Engineering, 1998, 6(1): 75-87P
[7] Volpe BT, Krebs HI, Hogan N, et al. A novel approach to stroke rehabilitation: Robot-aided sensorimotor stimulation. Neurology, 2000, 54(10): 1938-1944P
[8] Volpe BT, Krebs HI, Hogan N. Robot-aided sensorimotor training in stroke rehabilitation. Adv Neurol, 2003(92): 429-433P
[9] M. J. Johnson, H. F. M. Van der Loos, et al. Driver's SEAT: Simulation environment for arm therapy. ICORR'99: 227-234P
[10] Reinkensmeyer DJ, Kahn LE, Averbuch M, et al. Understanding and treating arm movement impairment after chronic brain injury: Progress with the ARM guide. Rehabil. Res. Dev, 2000, 37(6): 653-662P
[11] Burgar CG, Lum PS, Shor PC, et al. Development of robot for rehabilitation therapy: The PALO Alto VA/Stanford experience. J Rehabil Res Der 2000, 37(6): 663-673P
[12] Lum PS, Burgar CG, Shor PC, et al. Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Arch. Phys. Med. Rehabil. 2002, 83(7): 952-959P
[13] Loureiro R, Amirabdollahian F, Topping M, et al. Upper limb rob.or mediated stroke therapy Gentle/s approach. Autonomous Robots, 2003(15): 35-51P
[14] R C V Loureiro, C F Collin, W S Harwin. Robot aided therapy: challenges ahead for upper limb stroke rehabilitation. Proc. 5th Intl Conf. Disability, Virtual Reality & Assoc. Tech., Oxford, UK, 2004: 33-39P
[15] Roberto Colombo, Fabrizio Pisano, Silvestro Micera, et al. Robotic techniques for upper limb evaluation and rehabilitation of stroke patients. IEEE Transaction on Neural Systems and Rehabilitation Engineering, 2005, 13(3): 311-324P
[16] Johannes Feuser, Oleg Ivlev, Axel Graer. Collision prevention for rehabilitation robots with mapped virtual reality. Proceedings of the 2005 IEEE 9th International Conference on Rehabilitation Robotics, 2005: 461-464P
[17] Schmidt H, Hesse S, Werner C, Bardeleben A. Upper and lower extremity robotic devices to promote motor recovery after stroke-recent developments. Proceeding of the 26th Annual International Conference of the IEEE EMBS, 2004: 4825-4828P
[18] Robert Richardson, Michael Brown, et al. Impedance control for a pneumatic robot-based around pole-placement, joint space controllers. Control Engineering Practice, 2005(13): 291-303P
[19] Toshiro Noritsugu, Toshihiro Tanaka. Application of rubber artificial muscle manipulator as a rehabilitation robot. IEEE, 1997, 2(4): 259-267P
[20] Ken'ichi Koyanagi, Yusuke Imada, Junji Furusho, et al. 3-D rehabilitation robot system for upper limbs and its force display techniques. ICAT, 2003: 56-65P
[21] Tobias Nef, Robert Riener. ARMin-design of a novel arm rehabilitation robot. Proceedings of the 9th International Conference on Rehabilitation Robotics, 2005: 57-60P
[22] 胡宇川．偏瘫上肢复合运动康复训练机器人的研制．清华大学工学硕士学位论文．2004：9-11，25-33页
[23] 杨勇，张立勋，谭爱华，伊永峰．由单片机实现的多功能手臂康复训练器．自动化技术与应用．2004，23(2)：55-57页
[24] Dijkers M, deBear P, Patti C. Patient and staff acceptance of robotic technology in occupational therapy: A pilot study. Journal of Rehabilitation Research & Development. 1991, 28(2): 33-44P
[25] 胡建元．影响机器人高精度装配诸因素分析．兵工自动化．1995(2)：42-46页
[26] 胡宇川，季林红．一种偏瘫上肢复合运动的康复训练机器人．机械设计与制造．2004(6)：47-49页
[27] 陈则仕，张秋菊．一种五轴联动机器人运动学建模与仿真研究．制造业自动化．2005，27(12)：36-39页
[28] 温淑焕．不确定性机器人力／位置智能控制及轨迹跟踪实验的研究．燕山大学工学博士学位论文．2005：3-7页
[29] Kiguchi, Kazuo, Watanabe. Two-stage adaptive robot position/force control using fuzzy reasoning and neural networks. Advanced Robotics, 2000, 14(3): 153-168P
[30] 熊有伦，唐立新等编著．机器人技术基础．第一版．华中科技大学出版社，2001：94-95页
[31] 殷跃红，朱剑英．智能机器力觉及力控制研究综述．航空学报．1999，20(1)：1-7页
[32] 袁军．采用力外环的机器人运动和力控制研究．电气自动化．1996(6)：24-27页
[33] Nevile Hogan. Impedance control an approach to manipulation Ⅰ Ⅱ Ⅲ[J]. ASME. J. DSMC. 1985, 107: 1-24P
[34] Heinrichs B, Sepehri N, Thorton Trump A. B. Position-based impedance control of an industrial hydraulic manipulator. IEEE Control Systems Magazine, 1997(17): 46-52P
[35] Cheah C C. Learning impedance control for robotic manipulators. Proc. of the IEEE Int. Conf. on robot and automation, 1995: 2150-2155P
[36] Danwei Wang. An iterative learning control scheme for impedance control of robotic manipulators. Int. J. robo. research, 1998(17): 1091-1104P
[37] S Jung. Robot neural force control scheme under uncertainties in robot dynamics and unknown environment. IEEE Trans. on Industrial electronics, 2000(47): 403-412P
[38] J. A. Maples, J. J. Becker. Experiments in force control of robotics manipulators. Proc IEEE Conf on Robotics & Automation, 1986(11): 1108-1114P
[39] 王耀南．机器人智能控制工程．第一版．科学出版社．2004：41-45页
[40] Alin Albu-Achaffer, Gerd Hirzinger. Cartesian impedance control techniques for torque controlled light-weight robots. IEEE, 2002: 657-663P
[41] Chien-Chern Cheah, Danwei Wang. Learning impedance control for robotic manipulators. IEEE, 1998, 14(3): 452-465P
[42] 刘伊威，金明和，杨磊．HIT／DLR灵巧手单手指的阻抗控制．机械与电子．2005(10)：62-64页
[43] 杨磊，高晓辉，刘宏等．基于指尖力传感器的HIT机器人灵巧手笛卡尔阻抗控制．控制与决策．2004，19(11)：1255-1158页
[44] 胡建元，黄心汉．机器人刚度控制及实验研究．兵工自动化．1994(4)：11-14页
[45] 张爱红，张秋菊．机器人示教编程方法．组合机床与自动化加工技术．2003(4)：47-49页
[46] 陈文略，王子羊．三次样条插值在工程拟合中的应用．华中师范大学学报(自然科学版)．2004，38(4)：418-422页
[47] 吴进华，刘洪兴，史贤俊．dSPACE仿真平台的实时仿真原理研究及其应用．电子测量与仪器学报．2004：720-724页
[48] 潘峰，薛定宇，徐心和．基于dSPACE半实物仿真技术的伺服控制研究与应用．系统仿真学报．2004，16(5)：936-939页
[49] 夏娟，周治平，纪志成．基于dSPACE电气传动控制系统的在线仿真． 微特电机．2004(5)：36-39页
[50] 田广来，谢利理．航空机轮刹车系统的半实物仿真实现．航空精密制造技术．2006，42(3)：28-31页
[51] 田友明，戴先中，王新．基于dSPACE的感应电动机矢量控制系统．电气时代．2006(2)：43-46，50页
[52] 张立勋，董玉红，王怀军．基于半物理仿真技术的机电伺服系统模型辨识研究．机电一体化．2006(2)：30-32页
[53] 潘峰，张云洲等．微型足球机器人伺服控制实时仿真系统研究．系统仿真学报．2006，18(6)：1601-1604页
[2] 胡宇川，季林红．从医学角度探讨偏瘫上肢康复训练机器人的设计．中国临床康复．2004，8(34)：7754-7756页
[3] 金德闻，季林红，张济川．康复工程研究的新进展．中国康复医学杂志．2001，16(6)：328-330页
[4] 张付祥，付宜利，王树国．康复机器人研究进展．河北工业科技．2005，22(2)：100-105页
[5] 吕广明，孙立宁，彭龙刚．康复机器人技术发展现状及关键技术分析．哈尔滨工业大学学报．2004，36(9)：1224-1227，1231页
[6] Krebs HI, Hogan N, Aisen ML, et al. Robot-aided neurorehabilitation. IEEE Transactions on Rehabilitation Engineering, 1998, 6(1): 75-87P
[7] Volpe BT, Krebs HI, Hogan N, et al. A novel approach to stroke rehabilitation: Robot-aided sensorimotor stimulation. Neurology, 2000, 54(10): 1938-1944P
[8] Volpe BT, Krebs HI, Hogan N. Robot-aided sensorimotor training in stroke rehabilitation. Adv Neurol, 2003(92): 429-433P
[9] M. J. Johnson, H. F. M. Van der Loos, et al. Driver's SEAT: Simulation environment for arm therapy. ICORR'99: 227-234P
[10] Reinkensmeyer DJ, Kahn LE, Averbuch M, et al. Understanding and treating arm movement impairment after chronic brain injury: Progress with the ARM guide. Rehabil. Res. Dev, 2000, 37(6): 653-662P
[11] Burgar CG, Lum PS, Shor PC, et al. Development of robot for rehabilitation therapy: The PALO Alto VA/Stanford experience. J Rehabil Res Der 2000, 37(6): 663-673P
[12] Lum PS, Burgar CG, Shor PC, et al. Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Arch. Phys. Med. Rehabil. 2002, 83(7): 952-959P
[13] Loureiro R, Amirabdollahian F, Topping M, et al. Upper limb rob.or mediated stroke therapy Gentle/s approach. Autonomous Robots, 2003(15): 35-51P
[14] R C V Loureiro, C F Collin, W S Harwin. Robot aided therapy: challenges ahead for upper limb stroke rehabilitation. Proc. 5th Intl Conf. Disability, Virtual Reality & Assoc. Tech., Oxford, UK, 2004: 33-39P
[15] Roberto Colombo, Fabrizio Pisano, Silvestro Micera, et al. Robotic techniques for upper limb evaluation and rehabilitation of stroke patients. IEEE Transaction on Neural Systems and Rehabilitation Engineering, 2005, 13(3): 311-324P
[16] Johannes Feuser, Oleg Ivlev, Axel Graer. Collision prevention for rehabilitation robots with mapped virtual reality. Proceedings of the 2005 IEEE 9th International Conference on Rehabilitation Robotics, 2005: 461-464P
[17] Schmidt H, Hesse S, Werner C, Bardeleben A. Upper and lower extremity robotic devices to promote motor recovery after stroke-recent developments. Proceeding of the 26th Annual International Conference of the IEEE EMBS, 2004: 4825-4828P
[18] Robert Richardson, Michael Brown, et al. Impedance control for a pneumatic robot-based around pole-placement, joint space controllers. Control Engineering Practice, 2005(13): 291-303P
[19] Toshiro Noritsugu, Toshihiro Tanaka. Application of rubber artificial muscle manipulator as a rehabilitation robot. IEEE, 1997, 2(4): 259-267P
[20] Ken'ichi Koyanagi, Yusuke Imada, Junji Furusho, et al. 3-D rehabilitation robot system for upper limbs and its force display techniques. ICAT, 2003: 56-65P
[21] Tobias Nef, Robert Riener. ARMin-design of a novel arm rehabilitation robot. Proceedings of the 9th International Conference on Rehabilitation Robotics, 2005: 57-60P
[22] 胡宇川．偏瘫上肢复合运动康复训练机器人的研制．清华大学工学硕士学位论文．2004：9-11，25-33页
[23] 杨勇，张立勋，谭爱华，伊永峰．由单片机实现的多功能手臂康复训练器．自动化技术与应用．2004，23(2)：55-57页
[24] Dijkers M, deBear P, Patti C. Patient and staff acceptance of robotic technology in occupational therapy: A pilot study. Journal of Rehabilitation Research & Development. 1991, 28(2): 33-44P
[25] 胡建元．影响机器人高精度装配诸因素分析．兵工自动化．1995(2)：42-46页
[26] 胡宇川，季林红．一种偏瘫上肢复合运动的康复训练机器人．机械设计与制造．2004(6)：47-49页
[27] 陈则仕，张秋菊．一种五轴联动机器人运动学建模与仿真研究．制造业自动化．2005，27(12)：36-39页
[28] 温淑焕．不确定性机器人力／位置智能控制及轨迹跟踪实验的研究．燕山大学工学博士学位论文．2005：3-7页
[29] Kiguchi, Kazuo, Watanabe. Two-stage adaptive robot position/force control using fuzzy reasoning and neural networks. Advanced Robotics, 2000, 14(3): 153-168P
[30] 熊有伦，唐立新等编著．机器人技术基础．第一版．华中科技大学出版社，2001：94-95页
[31] 殷跃红，朱剑英．智能机器力觉及力控制研究综述．航空学报．1999，20(1)：1-7页
[32] 袁军．采用力外环的机器人运动和力控制研究．电气自动化．1996(6)：24-27页
[33] Nevile Hogan. Impedance control an approach to manipulation Ⅰ Ⅱ Ⅲ[J]. ASME. J. DSMC. 1985, 107: 1-24P
[34] Heinrichs B, Sepehri N, Thorton Trump A. B. Position-based impedance control of an industrial hydraulic manipulator. IEEE Control Systems Magazine, 1997(17): 46-52P
[35] Cheah C C. Learning impedance control for robotic manipulators. Proc. of the IEEE Int. Conf. on robot and automation, 1995: 2150-2155P
[36] Danwei Wang. An iterative learning control scheme for impedance control of robotic manipulators. Int. J. robo. research, 1998(17): 1091-1104P
[37] S Jung. Robot neural force control scheme under uncertainties in robot dynamics and unknown environment. IEEE Trans. on Industrial electronics, 2000(47): 403-412P
[38] J. A. Maples, J. J. Becker. Experiments in force control of robotics manipulators. Proc IEEE Conf on Robotics & Automation, 1986(11): 1108-1114P
[39] 王耀南．机器人智能控制工程．第一版．科学出版社．2004：41-45页
[40] Alin Albu-Achaffer, Gerd Hirzinger. Cartesian impedance control techniques for torque controlled light-weight robots. IEEE, 2002: 657-663P
[41] Chien-Chern Cheah, Danwei Wang. Learning impedance control for robotic manipulators. IEEE, 1998, 14(3): 452-465P
[42] 刘伊威，金明和，杨磊．HIT／DLR灵巧手单手指的阻抗控制．机械与电子．2005(10)：62-64页
[43] 杨磊，高晓辉，刘宏等．基于指尖力传感器的HIT机器人灵巧手笛卡尔阻抗控制．控制与决策．2004，19(11)：1255-1158页
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[45] 张爱红，张秋菊．机器人示教编程方法．组合机床与自动化加工技术．2003(4)：47-49页
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