摘要
近年来,由脑中风后遗症,脊髓损伤,肌肉、神经和大脑病变以及自然和人为灾害引起的手部功能残疾患者逐年增多,为了解决我国手部残疾患者的饮食护理问题,本文对助餐机器人进行了研究。一方面增强手残患者自主进餐的生活自信心,另一方面将护理人员从繁重的护理工作中释放出来,解放了社会生产力,对提高我国残疾人自主就餐水平、促进社会和谐进步具有重要的现实意义。
本文在国家科技型中小企业创新基金(08C26212301760)和哈尔滨市创新基金(2009RFKXG009)的资助下,针对如何开发一款实用、智能、安全、操作简单灵活的助餐机器人,在助餐机器人的机械结构、人机交互方式、运动规划、动力学、控制策略和视觉系统等方面进行了较深入的理论分析和实验研究。
通过对助餐机器人应用对象的症状分析,根据患者不同残障程度的需求,设计了一款由旋转餐桌和带有勺筷结合式餐具的助餐机械手组成的助餐机器人,对机器人的机构方案、控制方案和人机交互方式进行了总体方案研究。
对机器人进行了运动学分析;通过对机器人的助餐路径规划和助餐定向灵活工作空间分析,确定了机器人各连杆参数及在各助餐路径标识点机器人末端餐勺位姿参数;通过对机器人进行餐盘分区设计,使四餐盘中所有区域的食物规划到相对机械手的三类不同的取餐位置;对机器人进行了速度平滑的运动规划,规划的机器人轨迹加速度曲线连续,速度、位置曲线光滑,为机器人平稳助餐的控制系统研究奠定了基础。
利用拉格朗日方程建立了机器人动力学模型,利用MATLAB软件对助餐机器人进行了动力学特性分析。利用ADAMS软件建立了基于球形刚体和弹簧阻尼约束的正八面体食物模型,分析了勺筷结合式餐具和普通餐勺取餐时餐食的动力学特性及餐食盛取率问题,证明勺筷结合式餐具取餐效率高,取餐更优越。为了提高控制精度,除传统PID控制外,对机器人的整个助餐任务进行了模糊PID控制研究。对接触环境作业的助餐段,进行了阻抗控制研究,得出了阻抗参数调整规律,通过调整阻抗控制器参数,可使助餐机器人满足特定的柔顺性,在取餐过程中既不损伤机器人,也不损坏餐盘及餐食。
对助餐机器人视觉系统进行了研究,主要包括食物识别系统和残疾人头部识别视觉系统设计。食物识别系统是视觉系统模仿人类视觉去辨别餐盘中食物的分布情况,将得到的餐盘食物信息作为上位机信号,控制机器人完成助餐任务;头部识别视觉系统即通过采集患者的头部运动信息,作为失语的重度四肢残疾患者使用机器人的人机交互方式。
研制了助餐机器人样机,利用dSPACE半物理仿真实验平台对助餐机器人样机进行轨迹跟踪实验研究,验证了机器人机构的合理性及控制策略的可行性,进而验证了本文研制的助餐机器人能够达到帮助手残患者进行饮食护理的目的。
Recently, because of stroke sequelae and the lesions of spinal cord, muscles, nervesand brain, as well as natural and man-made disasters, the number of the patients disabled inthe hand increases year by year. In order to solve the diet care problem of the patients withhand disability, the research on meal-assistance robot has been done in the paper. On onehand, the robot enhances the self-confidence of the disabled to have meal on their own; onthe other hand, it can reduce the workload of the nursing staff and liberate the socialproductive forces. And it has great practical significance for improving the independentdining level of the disabled and promoting social harmony and progress.
With the funding of the National SME Innovation Fund (08C26212301760) andHarbin Innovation Fund (2009RFKXG009), in order to develop a meal assistance robotwhich is practical, smart, safe, simple and flexible, theoretical analysis and experimentalresearch of the meal assistance robot, in terms of the mechanical structure, man-machineinteractive mode, motion planning, dynamics analysis, control strategies and the visualsystem, have been carried out deeply.
Through the symptoms analysis of the application objects of meal assistance robot, andaccording to the needs of patients with different degree of disability, a kind of mealassistance robot was designed in the paper, which consists of a rotary table and amanipulator with spoon-chopsticks style tableware. A general research on the robot'smechanical structure, control scheme and man-machine interactive mode has been done.
Kinematic analysis, path planning and work space analysis of the robot have been donein the paper, and then the link parameters of the robot and the position and orientationparameters of the robot’s spoon at each track identification point have been decided. Theplate zoning design of the robot has been done, so that the food in four dishes is planned tothree different locations of the meal assistance manipulator. The motion planning in whichthe curves of velocity are smooth has been done, which lays the foundation for the controlstudy of the robot.
The dynamic model of the robot has been established based on Lagrange equations,and the dynamics analysis of the robot has been carried out using MATLAB software. Theoctahedral food model based on spherical rigid body constrained by spring-damper wasestablished using ADAMS software. Dynamics characteristics analysis and scoopingefficiency issues of spoon-chopsticks style tableware and a common spoon are analyzed,which verifies that spoon-chopsticks style tableware is better in getting food. In order to improve control accuracy, in addition to the conventional PID control, the fuzzy self-tuningPID control of the entire meal assistance task was carried out. In the meal assistance sectionof contacting environment operations, the study of impedance control was carried out andthe impedance parameter adjustment law was deduced. By adjusting the impedancecontroller parameters, meal assistance robot can meet specific flexibility. So the robot canavoid damage, as well as the plates and meal, through the process of taking meal.
The visual system research of the robot, including food recognition system and headidentify system has been done. Food recognition system imitates the human visual systemto identify the distribution of food in the plates, and then transmits the information into thehost computer, so as to control the robot to accomplish the meal assistance task. Headidentify visual system can collect the information of head movement, which is thehuman-computer interaction of aphasia patients with severe limb disabilities.
The robot prototypes is developed, and the trajectory tracking experiment is studied bydSPACE semi-physical simulation experimental platform. The reasonableness of the robotmechanical structure and the feasibility of the control strategy are verified. Thus, the mealassistance robot studied in the paper can achieve the diet care of the disabled in the hand.
引文
[1]第二次全国残疾人抽样调查最新数据公报.中国听力语言康复科学杂志.2007(1):38页
[2] http://www.cdpf.org.cn/ywkx/content/2011-05/11/content_30332343.htm
[3] http://www.gov.cn/fwxx/cjr/content_1839338.htm
[4]许琳.残疾人就业难与残疾人就业促进政策的完善.西北大学学报.2010,40(1):116-118页
[5]高从军.欧洲康复机器人发展现况及前景.机器人技术与应用.1999(5):1-4页
[6] Mounir Mokhtari, Mohamed Ali Feki, Bessam Abdulrazak, et al.3Toward aHuman-Friendly User Interface to Controlan Assistive Robot in the Context of SmartHomes. Journal of Advances in Rehabilitation Robotics.2004, LNCIS306:47-56P
[7]高峻.助餐机器人的视觉伺服控制.哈尔滨工程大学硕士论文.2008:1-4页
[8] Michael J. Topping, Jane K. Smith. The development of handy1-A robotic system toassist the severely disabled. Journal of Technology and Disability.1999,10:95-105P
[9]裴立坤.助餐机器人的机构设计与伺服系统研究.哈尔滨工程大学硕士论文.2008:4-9页
[10] Mike Topping. Flexibot-a multi-functional general purpose service robot. Journal ofIndustrial Robot: An International Journal.2001,5(28):395-401P
[11] Oliver Prenzel, Johannes Feuser, Axel Gr ser. Rehabilitation Robot in IntelligentHome Environment Software Architecture and Implementation of a DistributedSystem. Proceedings of the2005IEEE9th International Conference on RehabilitationRobotics, Chicago, IL, United states,2005. United states: Institute of Electrical andElectronics Engineers Computer Society,530-535P
[12] Volosyak Ivan, Ivlev Oleg1, Gr ser Axel1. Rehabilitation robot FRIEND II-thegeneral concept and current implementation. Proceedings of the2005IEEE9thInternational Conference on Rehabilitation Robotics, Chicago, IL, United states,2005.United states: Institute of Electrical and Electronics Engineers Computer Society,540-544P
[13] http://www.iat.uni-bremen.de/sixcms/detail.php?id=447
[14] http://en.wikipedia.org/wiki/Care-Providing_Robot_FRIEND
[15] Xiu Zhang, Xingyu Wang, Bei Wang, et al. Real-time Control Strategy forEMG-drive Meal Assistance Robot-My Spoon. Proceedings of the InternationalConference on Control, Automation and Systems2008, Seoul, Korea,2008. Seoul,Korea, Republic of,800-803P
[16] Ryoji Soyama, Sumio Ishii, Azuma Fukase.8Selectable Operating Interfaces of theMeal-Assistance Device “My Spoon”. Journal of the Advances in RehabilitationRobotics,2004, LNCIS306:155-163P
[17] Xiu Zhang, Xingyu Wang, Bei Wang, et al. Meal Assistance System Operated byElectromyogram (EMG) Signals: Movement Onset Detection with AdaptiveThreshold. International Journal of Control.2010,8(2):392-397P
[18] Taisuke Sakaki. An Effective Design Method for Welfare Robot and its Applicationto the Design of Meal-Assistance Robot. Proceedings of the17th IEEE InternationalSymposium on Robot and Human Interactive Communication, Munich, Germany,2008. United States: Inst. of Elec. and Elec. Eng. Computer Society,309-314P
[19] Yoshihiko Takahashi, Shinichiro Suzukawa. Intelligent Robot Human Interface usingCheek Movement for Severely Handicapped Persons. Journal of Service RobotApplications, June2008:103-114P
[20] Frank D. Layman, Sr. Self-feeding appliance. United States Patent, Aug.16,1983.Patent No.4398857
[21] William Joseph Osborne, Jr. Self-feeding apparatus with hover mode. United StatesPatent, Jul.15,2003. Patent No.6592315B2
[22] Homeyra Pourmohammadali. Design of a Multiple-User Intelligent Feeding Robot forElderly and Disabled. A thesis presented to the University of Waterloo in fulfillmentof the thesis requirement for the degree of Master of Applied Science in MechanicalEngineering,2007:7-24,55-56,82-86P
[23] Therafin Corporation, URL: http://www.therafin.com
[24] http://www.flaghouse.com
[25] http://pattersonmedical.com/app.aspx?cmd=get_product&id=44288
[26] http://www.bestic.se/eng/
[27] Mattias. Robots-In industry and beyond. ISO Focus December2007:34-36P
[28] http://www.maddak.com/
[29] http://www.wisdomking.com/self-feeders
[30] Rebecca I. Estes, Jimmy H, Ishee. Introduction of an emerging technology devicethrough powerpoint training. The Internet Journal of Allied Health Sciences andPractice.2007,5(2)
[31] http://mealtimepartners.com/description/description.htm
[32] Frische, Eric A. Assistive dining device, system and method, United States Patent,Jan.2,1994Patent No.5282711
[33] Kazuhiko Kawamura, Sugato Bagchi, Moenes Iskarous. Intelligent Robotic Systemsin Service of the Disabled. Proceedings of the19955IEEE Transactions onRehabilitation Engineering,1995,3(1):14-21P
[34] S. Thongchai, M. Goldfarb, N. Sarkar. A Frequency Modeling Method ofRubbertuators for Control Application in an IMA Framework. Proceedings of the2001American Control Conference, Arlington, VA, United states,2001. United states:Institute of Electrical and Electronics Engineers Inc.,1710-1714P
[35] Kawamura, K., Peters, R.A, Wilkes, D.M. ISAC: foundations in human-humanoidinteraction. Proceedings of the Intelligent Systems and their Applications.2000:38-45P
[36] http://eecs.vanderbilt.edu/cis/crl/isac.shtml
[37]朱俊杰,田野,罗江洪等.可控式用餐机.实用新型专利.专利号:CN200998019
[38] Munlsang Ki. Challenges on the Development of Robotic Intelligence. Proceedings ofthe16th IEEE International Conference on Robot&Human InteractiveCommunication MB3-1,2007, Jeju, Korea:344P
[39] Sumio Ishii, Shinji Tanaka, Fumiaki Hiramatsu. Meal Assistance Robot for SeverelyHandicapped People. Proceedings of the1995IEEE International Conference onRobotics and Automation,1995:1308-1313P
[40] Medhat Moussa. Categorizing arbitrarily shaped objects based on graspingconfigurations. Robotics and Autonomous Systems,2006,10(54):858–863P
[41] X. Zhang, B. Wang, X.Y. Wang, et al. Human Intention Extracted fromElectromyography Signals for Tracking Motion of Meal Assistance Robot.Proceedings of the2007IEEE/ICME International Conference on Complex MedicalEngineering, Beijing, China,2007. United States: Inst. of Elec. and Elec. Eng.Computer Society,1384-1387P
[42] Tanaka, Y. Kodani, M. Oka, et al. Meal assistance robot with ultra sonic motors.International Journal of Applied Electromagnetics and Mechanics.2011,1-2(36):177-181P
[43] Xiu Zhang, Xingyu Wang, Bei Wang, et al. Finite State Machine with AdaptiveElectromyogram (EMG) Feature Extraction to Drive Meal Assistance Robot. Journalof the IEEJ Transactions on Electronics, Information and Systems.2009,2(129):308-313P
[44] Fangju Wanga, Shaidah Jusohb, Simon X. Yang. A collaborative behavior-basedapproach for handling ambiguity, uncertainty, and vagueness in robot naturallanguage interfaces. Journal of Engineering Applications of Artificial Intelligence.2006,8(19):939-951P
[45] Huiyu Zhou, Huosheng Hu. Human motion tracking for rehabilitation-A surv-eyJournal of Biomedical Signal Processing and Control.2008,1(3):1-18P
[46] Alexandra Kirsch. Robot learning language-Integrating programming and learning forcognitive systems. Journal of Robotics and Autonomous Systems.2009,9(57):943-954P
[47] X. Zhang, B. Wang, X.Y. Wang, et al. Human Intention Extracted fromElectromyography Signals for Tracking Motion of Meal Assistance Robot.Proceedings of the CME2007. IEEE/ICME International Conference on ComplexMedical Engineering, Beijing, China,2007. United States: Inst. of Elec. and Elec.Eng. Computer Society,1384-1387P
[48] Bulka J., Izworski A., Koleszynska J., et al. Automatic meal planning using artificialintelligence algorithms in computer aided diabetes therapy. Proceedings of the4thInternational Conference on Autonomous Robots and Agents, Wellington, NewZealand,2009. United States: Inst. of Elec. and Elec. Eng. Computer Society,393-397P
[49] Saeko Tanigawa, Hideaki Nishihara, Shigeo Kaneda, et al. Detecting mastication byusing microwave Doppler sensor. Proceedings of the1st international conference onPErvasive Technologies Related to Assistive Environments, Athens, Greece,2008.United States: Association for Computing Machinery,1-7P
[50] Hideyuki Tanaka, Yasushi Sumi, Yoshio Matsumoto. Assistive Robotic ArmAutonomously Bringing a Cup to the Mouth by Face Recognition. Proceedings of the2010IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Seoul,Korea, Republic of,2010. United States: IEEE Computer Society,34-39P
[51] Satoru Goto, Akinori Yamada, Wataru Hashimoto, et al. Determination of TargetPosition of Meal Assistance Orthosis Using EOG Signal and Dish Image. Proceedingsof the SICE Annual Conference2007, Takamatsu, Japan,2007. Japan: Society ofInstrument and Control Engineers (SICE),1877-1882P
[52] Ken’ichi Yano, Yoshifumi Kuriyama.3-D Transfered Control using SpillingAvoidance Control for Meal Assist Robot by using CFD Simulator. Proceedings ofthe200810th Intl. Conf. on Control, Automation, Robotics and Vision, Hanoi, Vietnam,2008. United States: Inst. of Elec. and Elec. Eng. Computer Society,1758-1763P
[53] Ohara, E., Yano, K., Horihata, S., et al. Tremor suppression control of Meal-AssistRobot with adaptive filter. Proceedings of the ICORR2009IEEE InternationalConference on Rehabilitation Robotics, Kyoto, Japan,2009. United States: IEEEComputer Society,498-503P
[54] Xiu Zhang, Xingyu Wang. A Genetic Algorithm based Time-Frequency Approach toa Movement Prediction Task. Proceedings of the7th World Congress on IntelligentControl and Automation, Chongqing, China,2008. United States: Institute ofElectrical and Electronics Engineers Inc.,1032-1036P
[55] Kazuhiko Kawamura, Sugato Bagchi, Moenes Iskarous, et al. Intelligent RoboticSystems in Service of the Disabled. Journal of IEEE Transactions on RehabilitationEngineering.1995,1(3):14-21P
[56] Tao Zhang, Member, Masatoshi Nakamura. Neural Network-Based HybridHuman-in-the-Loop. Proceedings of the IEEE Transactions on Neural Systems andRehabilitation Engineering.2006,1(14):64-75P
[57] Yoshifumi Kuriyama, Ken’ichi Yano, Masafumi Hamaguchi. Trajectory Planning forMeal Assist Robot Considering Spilling Avoidance. Proceedings of the17th IEEEInternational Conference on Control Applications Part of2008IEEEMulti-conference on Systems and Control San Antonio, Texas, USA,2008. UnitedStates: Institute of Electrical and Electronics Engineers Inc.,1220-1225P
[58] Kenji Nishiwaki, Ken’ichi Yano. Variable Impedance Control of Meal AssistanceRobot Using Potential Method. Proceedings of the2008IEEE/RSJ InternationalConference on Intelligent Robots and Systems Acropolis Convention Center Nice,France,2008. United States: Institute of Electrical and Electronics Engineers Inc.,3242-3247P
[59] Christian Biihler. Approach to the analysis of user requirements in assistivetechnology. International Journal of Industrial Ergonomics.1996,2(17):187-192P
[60] Satoru Gotoa, Tatsumi Usuia, Nobuhiro Kyurab, et al. Forcefree control withindependent compensation for industrial articulated robot arms. Journal of ControlEngineering Practice.2007,6(15):627-638P
[61] Ken’ichi Yano, Kenji Nishiwaki, Shota Hiramatsu. Tremor Suppression Control for aMeal-Assist Robot. International Conference on Haptics: Generating and PerceivingTangible Sensations, EuroHaptics2010, Amsterdam, Netherlands,2010. Germany,Springer Verlag,354-359P
[62] http://www.abledata.com/abledata.cfm?pageid=19327&top=12236&trail=22,11860,12232
[63] http://wenku.baidu.com/view/8e6935106c175f0e7cd137e0.html
[64] http://www.jskf123.com/do/bencandy.php?fid=41&id=828
[65] http://wenku.baidu.com/view/71a3f9d950e2524de5187ec5.html
[66] http://wenku.baidu.com/view/c8b5a72b915f804d2b16c17e.html
[67] http://baike.baidu.com/view/1204167.htm
[68] http://www.xiangya.com.cn/lcks/ylks/mzk/tszl/200901/lcks_20090105232043_2227.html
[69]杨勇.手臂康复机器人系统研究.哈尔滨工程大学博士学位论文.2009:31-32页
[70] Parasuraman S, Zhen C C S. Development of robot assisted hand stroke rehabilitationsystem. Proceedings2009International Conference on Computer and AutomationEngineering, Bangkok, Thailand,2009. United States: Institute of Electrical andElectronics Engineers Inc.,70-74P
[71] Roy A, Krebs H I, Williams D J,et al. Robot-aided neurorehabilitation: A novel robotfor ankle rehabilitation. IEEE Transactions on Robotics.2009,25(3):569-582P
[72]孙兴超,徐熙平,苏拾等.基于PID算法的全向足球机器人控制方法研究.长春理工大学学报.2010,33(3):52-54页
[73]屈毅,宁铎,刘飞航等.模糊PID控制器的设计及其仿真.计算机仿真.2009,26(12):130-132页
[74]李萍,李峰,赵虎等.模糊自整定PID控制器的设计和仿真.计算机仿真.2009,26(12):130-132页
[75]李趁前.手臂康复训练机器人系统控制研究.哈尔滨工程大学硕士论文.2008:17-23页
[76]文忠,钱晋武,沈林勇等.基于阻抗控制的步行康复训练机器人的轨迹自适应.机器人.2011,33(1):142-147页
[77]徐国政,宋爱国,李会军等.基于模糊逻辑的上肢康复机器人阻抗控制实验研究.机器人.2010,33(6):792-797页
[78]徐国政,宋爱国,李会军等.基于模糊推理的上肢康复机器人自适应阻抗控制.东南大学大学学报.2009,39(1):156-160页
[79] Huang Jianbina, Xie Zongwua, Jin Minghe, et al. A daptive Impedance ControlledManipulator Based on Collision Detection. Chinese Journal of Aeronautics.2009,22:105-112P
[80]孙洪颖.卧式下肢康复机器人研究.哈尔滨大学博士论文.2011:71-81页
[81] KJ.Salisbury. Active Stiffness Control of a ManiPulator in Cartesian Coordinates. The19th IEEE Conf. on Decision and Control, Albuquerque, NM,1980. IEEE, Piscataway,NJ95-100P
[82] D.E.Whitney. Force-Feedbaek Control of ManiPulator Fine Motion. ASME Journal ofDynamic Systems,Measurements and Control.1977P
[83] Hogan N. Impedance Control of Industrial Robots. Journal of Robotic and Computerintegrated Manufacturing.1984.1(1):97-113P
[84]王宪伦.不确定环境下机器人柔顺控制及可视化仿真的研究.山东大学博士论文.2006:2-5,30-32页
[85] J.A.Maples, J.J.Becker. Experiments in force control of robotics manipulators.Proceedings of IEEE Conference on roboties&Antomation, San Francisco, CA, USA,1986. United States: Institute of Electrical and Electronics Engineers Inc.,1108-1114P
[86]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.燕山大学博士论文.2005:71-72页
[87]王沐楠,王立权,孟庆鑫等.两栖仿生机器蟹行走过程运动学研究.哈尔滨工程大学学报.2003,24(2):179-183页
[88]王战中,张大卫,安艳松等.非球型手腕6R串联型喷涂机器人逆运动学分析.天津大学学报.2007,40(6):665-670页
[89]杨双华,王以伦,张立勋等.水下机器人自动工具库的位姿精度分析研究.哈尔滨工程大学学报.2001,22(2):46-50页
[90]韩翔宇,都东,陈强等.基于运动学分析的工业机器人轨迹精度测量的研究.机器人.2002,24(1):1-5页
[91]陈学东,郭鸿勋,渡边桂吾.四足机器人爬行步态的正运动学分析.机械工程学报.2003,39(2):8-12页
[92]杜海艳,贾裕祥,张永德等.弓丝弯制机器人运动运动规划.中国机械工程.2010,21(13):1605-1606页
[93]刘松国.六自由度串联机器人运动优化与轨迹跟踪控制研究.浙江大学博士学位论文.2009:40-41页
[94]朱世强,刘松国,王宣银等.机械手时间最优脉动连续运动规划算法.机械工程学报.2010,46(3):47-48页
[95]潘博.腹腔镜操作机器人运动规划研究.哈尔滨工业大学工学博士学位论文.2009:48-49页
[96]丁渊明.6R型串联弧焊机器人结构优化及其控制研究.浙江大学博士学位论文.2009:23-24页
[97]张永贵.喷漆机器人若干关键技术研究.西安理工大学博士学位论文.2009:26页
[98]曹毅,王树新,邱燕等.面向灵活工作空间的显微外科手术机器人设计.机器人,2005,27(3):220-221页
[99]李群智.面向喉部微创外科手术的机器人系统设计与实验研究.天津大学博士论文.2006:55-56页
[100]董九志.辅助腹腔镜手术机器人研究.哈尔滨工程大学博士论文.2009:70-71页
[101]蔡建羡,阮晓刚,甘家飞.两轮自平衡机器人系统建模与模糊自整定PID控制.北京工业大学学报.2009,35(12):1603-1607页
[102]刘金琨.先进PID控制MATLAB仿真.北京:电子工业出版社,2007:115-118页
[103]强艳辉.基于X-Y平台的力/位置智能控制研究.燕山大学硕士论文.2009:40-50页
[104] Fu Jie Huang, Trsuhan Chen. Tracking of Multiple Faces for Human-computerInterfaces and Virtual Environments.2000:1563-1566P
[105]张宏林.Visual C++数字图像模式识别技术及工程实践.人民邮电出版社.2003:364-370页
[106]朱长仁,王润生.基于单视图的多姿人脸识别算法.计算机学报.2003,26(1):104-109页
[107]邵平,杨路,黄海滨等.基于多姿态知识模型和模板的快速人脸检测.小型微型计算机系统.2007,28(2):346-350页
[108]雷明,张军英,董济扬.一种可变光照条件下的肤色检测算法.计算机工程与应用.2002,24:123-125页
[109]孙建.基于外骨骼机器人技术的人体手臂震颤抑制关键技术研究.中国科学技术大学博士论文.2010:108-109页
[110]谷善茂.永磁同步电动机无传感器控制关键技术研究.中国矿业大学博士论文.2009:105-106页
[111]刘攀.绳索牵引机器人及虚拟重力研究.哈尔滨工程大学博士论文.2010:99-103页
[112]张立勋.机电系统建模与仿真.哈尔滨:哈尔滨工业大学出版社.2010:280-283页