Haptic Physical Human Assistance

This dissertation covers three aspects of upper-extremity exoskeleton design: 1) Kinematics & motion: How to support the full range of motion of the human shoulder? We present a 2D visualization method that can show coupling between the range of motion (ROM) of rotations of the glenohumeral joint. This visualization helps in communication, comparison, design and analysis of human and assistive device ROM. We furthermore provide a conceptual design and differential inverse kinematics method for a redundant 4 degree of freedom (DOF) shoulder-exoskeleton. The extra DOF allows for movement redundancy to steer away from body collisions and kinematic singularity. 2) Haptics & Control: How to get devices such robots or exoskeletons to behave as some defined impedance in a stable manner when interacting with human users; how to implement stable admittance control with inertia reduction? We analyze the energetic behavior of the control method ‘admittance control’. During admittance control an interaction force with a human user is measured, which is used in a dynamical mechanical model that prescribes a motion for the exoskeleton to follow. Such a method is inherently active (i.e. it generates energy that can result in coupled instability) when it is used to reduce the apparent inertia of the exoskeleton. We provide insight into why this energetically active behavior occurs, and provide guidelines to design a controller that is (close to) passive and is therefore (almost) always stable when in contact with a human limb. 3) Human Factors: How do humans respond to dissipative shared control forces? Passive and active exoskeletons can apply forces to the human user to steer or help the person and share control authority. A passive force that only dissipates energy is a damping force. We investigate how position dependent damping forces around reaching targets influence human reaching time and kinematics. Results show that humans increase their accelerations and decrease their reaching time when assisted in this manner. We pose the hypothesis that damping forces attenuate neural activation dependent motor noise. Without the damping, this higher noise for higher accelerations would have had too much of a negative effect on the required task accuracy.

[1]  Singiresu S Rao,et al.  A Comparative Study of Evidence Theories in the Modeling, Analysis, and Design of Engineering Systems , 2013 .

[2]  Mark Mulder,et al.  Neuromuscular Analysis as a Guideline in designing Shared Control , 2010 .

[3]  H. Goldstein,et al.  The rise of the body bots [robotic exoskeletons] , 2005, IEEE Spectrum.

[4]  Ian M Franks,et al.  Updating of an internal model without proprioception: a deafferentation study , 2006, Neuroreport.

[5]  Kevin Cleary,et al.  Closed-Loop Force Control for Haptic Simulation of Virtual Environments , 2000 .

[6]  Journal of Dynamic Systems, Measurement, and Control Guest Editorial Special Issue on Novel Robotics and Control , .

[7]  G. Oriolo,et al.  Robotics: Modelling, Planning and Control , 2008 .

[8]  James A. Maples,et al.  Experiments in force control of robotic manipulators , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[9]  Tetsuro Yabuta,et al.  Comparison Between Admittance and Impedance Control of a Multi-Finger-Arm Robot using the Guaranteed Manipulability Method , 2013 .

[10]  Yoshihiko Nakamura,et al.  Base force/torque sensing for position based Cartesian impedance control , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Raffaello D'Andrea,et al.  Admittance control for physical human-quadrocopter interaction , 2013, 2013 European Control Conference (ECC).

[12]  Sameer Nagda,et al.  Defining functional shoulder range of motion for activities of daily living. , 2012, Journal of shoulder and elbow surgery.

[13]  Dikai Liu,et al.  Admittance control scheme for implementing model-based assistance-as-needed on a robot , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[14]  R. Colbaugh,et al.  Simulation Studies in Manipulator Impedance Control , 1992, 1992 American Control Conference.

[15]  Kelvin E. Jones,et al.  Sources of signal-dependent noise during isometric force production. , 2002, Journal of neurophysiology.

[16]  Mitsuo Kawato,et al.  TOPS (Task Optimization in the Presence of Signal-Dependent Noise) model , 2004, Systems and Computers in Japan.

[17]  J. Diedrichsen.  Optimal Task-Dependent Changes of Bimanual Feedback Control and Adaptation , 2007, Current Biology.

[18]  P. Fitts.  The information capacity of the human motor system in controlling the amplitude of movement. , 1954, Journal of experimental psychology.

[19]  Paolo Rocco,et al.  Walk-through programming for robotic manipulators based on admittance control , 2013, Robotica.

[20]  Ho Shing Lo,et al.  Optimization of a redundant 4R robot for a shoulder exoskeleton , 2013, 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[21]  R Kerr,et al.  Diving, adaptation, and Fitts law. , 1978, Journal of motor behavior.

[22]  C. Ware,et al.  An evaluation of an eye tracker as a device for computer input2 , 1987, CHI '87.

[23]  Xiaoou Li,et al.  Neural PID admittance control of a robot , 2013, 2013 American Control Conference.

[24]  J. Edward Colgate,et al.  Intelligent assist devices in industrial applications: a review , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[25]  G. Murrell,et al.  Reliability of five methods for assessing shoulder range of motion. , 2001, The Australian journal of physiotherapy.

[26]  A.H.A. Stienen,et al.  Dampace: dynamic force-coordination trainer for the upper extremities , 2007, 2007 IEEE 10th International Conference on Rehabilitation Robotics.

[27]  Mark Mulder,et al.  Haptic shared control: smoothly shifting control authority? , 2012, Cognition, Technology & Work.

[28]  Sheng Quan Xie,et al.  Exoskeleton robots for upper-limb rehabilitation: state of the art and future prospects. , 2012, Medical engineering & physics.

[29]  Arno H. A. Stienen,et al.  The ACT-4D: A novel rehabilitation robot for the quantification of upper limb motor impairments following brain injury , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[30]  Reza Shadmehr,et al.  Motor Adaptation as a Process of Reoptimization , 2008, The Journal of Neuroscience.

[31]  Arjan van der Schaft,et al.  A novel theory for sampled data system passivity , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[32]  Dragoljub Surdilovic,et al.  Contact stability issues in position based impedance control: theory and experiments , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[33]  Craig R. Carignan,et al.  Development of an exoskeleton haptic interface for virtual task training , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[34]  Jee-Hwan Ryu,et al.  Stable haptic interaction with admittance type virtual environments based on time-domain passivity approach , 2012, 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).

[35]  I. Scott MacKenzie,et al.  Towards a standard for pointing device evaluation, perspectives on 27 years of Fitts' law research in HCI , 2004, Int. J. Hum. Comput. Stud..

[36]  Kazuhiro Kosuge,et al.  Stability and Variable Admittance Control in the Physical Interaction with a Mobile Robot , 2015 .

[37]  J. Lenarcic,et al.  Simple Model of Human Arm Reachable Workspace , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[38]  Devendra P. Garg,et al.  Fuzzy logic based reinforcement learning of admittance control for automated robotic manufacturing , 1997, Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97.

[39]  J. Krakauer,et al.  A computational neuroanatomy for motor control , 2008, Experimental Brain Research.

[40]  Jacob Rosen,et al.  Comparison of multi-sensor admittance control in joint space and task space for a seven degree of freedom upper limb exoskeleton , 2010, 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[41]  Craig R. Carignan,et al.  Manipulator impedance accuracy in position-based impedance control implementations , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[42]  J. A. Houck,et al.  Theoretical three-and four-axis gimbal robot wrists , 1986 .

[43]  R. Ivry,et al.  The coordination of movement: optimal feedback control and beyond , 2010, Trends in Cognitive Sciences.

[44]  John Paulin Hansen,et al.  Command Without a Click: Dwell Time Typing by Mouse and Gaze Selections , 2003, INTERACT.

[45]  Arno H. A. Stienen,et al.  Switching proportional EMG control of a 3D endpoint arm support for people with duchenne muscular dystrophy , 2015, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR).

[46]  Reza Shadmehr,et al.  On-Line Processing of Uncertain Information in Visuomotor Control , 2008, The Journal of Neuroscience.

[47]  Wan Kyun Chung,et al.  Human-guided surgical robot system for spinal fusion surgery: CoRASS , 2008, 2008 IEEE International Conference on Robotics and Automation.

[48]  Dik J. Hermes,et al.  The Effect of Coulomb Friction in a Haptic Interface on Positioning Performance , 2010, EuroHaptics.

[49]  Olivier Chapuis,et al.  Small Targets: Why are they So Difficult to Acquire? , 2008 .

[50]  Myo Thant Sin Aung,et al.  Acceleration feedback and friction compensation for improving the stability of admittance control , 2015, 2015 10th Asian Control Conference (ASCC).

[51]  Michael I. Jordan,et al.  Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.

[52]  Blake Hannaford,et al.  Time domain passivity control with reference energy behavior , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[53]  Jake J. Abbott,et al.  On the Ability of Humans to Apply Controlled Forces to Admittance-Type Devices , 2011, Adv. Robotics.

[54]  J. Edward Colgate,et al.  A high performance 6-DOF haptic Cobot , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[55]  Bryan Buchholz,et al.  ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion--Part II: shoulder, elbow, wrist and hand. , 2005, Journal of biomechanics.

[56]  Martin Buss,et al.  Haptic Rendering of Actuated Mechanisms by Active Admittance Control , 2008, EuroHaptics.

[57]  Jian Huang,et al.  Control of upper-limb power-assist exoskeleton based on motion intention recognition , 2011, 2011 IEEE International Conference on Robotics and Automation.

[58]  Takeo Kanade,et al.  What you can see is what you can feel-development of a visual/haptic interface to virtual environment , 1996, Proceedings of the IEEE 1996 Virtual Reality Annual International Symposium.

[59]  N Klopcar,et al.  A kinematic model of the shoulder complex to evaluate the arm-reachable workspace. , 2007, Journal of biomechanics.

[60]  R. Sainburg,et al.  Differences in control of limb dynamics during dominant and nondominant arm reaching. , 2000, Journal of neurophysiology.

[61]  Jiting Li,et al.  An adaptive haptic interaction architecture for knee rehabilitation robot , 2009, 2009 International Conference on Mechatronics and Automation.

[62]  David A. Abbink,et al.  Using position dependent damping forces around reaching targets for transporting heavy objects: A Fitts' law approach , 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[63]  Neville Hogan,et al.  An analysis of contact instability in terms of passive physical equivalents , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[64]  Alin Albu-Schäffer,et al.  Passivity of virtual free-floating dynamics rendered on robotic facilities , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[65]  T. Waters,et al.  Evaluation of the revised NIOSH lifting equation. A cross-sectional epidemiologic study. , 1999, Spine.

[66]  E. Todorov,et al.  A generalized iterative LQG method for locally-optimal feedback control of constrained nonlinear stochastic systems , 2005, Proceedings of the 2005, American Control Conference, 2005..

[67]  Daniel M. Wolpert,et al.  Making smooth moves , 2022 .

[68]  Frans C. T. van der Helm,et al.  A Task-Specific Analysis of the Benefit of Haptic Shared Control During Telemanipulation , 2013, IEEE Transactions on Haptics.

[69]  R. Riener,et al.  Shoulder actuation mechanisms for arm rehabilitation exoskeletons , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[70]  Jaap Harlaar,et al.  The globe system: an unambiguous description of shoulder positions in daily life movements. , 2003, Journal of rehabilitation research and development.

[71]  Reza Shadmehr,et al.  The Computational Neurobiology of Reaching and Pointing: A Foundation for Motor Learning , 2004 .

[72]  Daniel E. Whitney,et al.  Force Feedback Control of Manipulator Fine Motions , 1977 .

[73]  Clément Gosselin,et al.  General Model of Human-Robot Cooperation Using a Novel Velocity Based Variable Impedance Control , 2007, Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (WHC'07).

[74]  Louis B. Rosenberg,et al.  The Use of Virtual Fixtures as Perceptual Overlays to Enhance Operator Performance in Remote Environments. , 1992 .

[75]  Herman van der Kooij,et al.  LIMPACT:A Hydraulically Powered Self-Aligning Upper Limb Exoskeleton , 2015, IEEE/ASME Transactions on Mechatronics.

[76]  S. Micera,et al.  Robotic techniques for upper limb evaluation and rehabilitation of stroke patients , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[77]  Luc Tremblay,et al.  How one breaks Fitts's Law and gets away with it: Moving further and faster involves more efficient online control. , 2015, Human movement science.

[78]  Nikos A. Aspragathos,et al.  Admittance neuro-control of a lifting device to reduce human effort , 2013, Adv. Robotics.

[79]  M. Mullaney,et al.  Reliability of shoulder range of motion comparing a goniometer to a digital level , 2010, Physiotherapy theory and practice.

[80]  Michael A. Peshkin,et al.  The robustness of an admittance control law designed for force guided assembly to the disturbance of contact friction , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[81]  Emanuel Todorov,et al.  Iterative linearization methods for approximately optimal control and estimation of non-linear stochastic system , 2007, Int. J. Control.

[82]  M.A. Peshkin,et al.  Active-Impedance Control of a Lower-Limb Assistive Exoskeleton , 2007, 2007 IEEE 10th International Conference on Rehabilitation Robotics.

[83]  Fatih Ozkul,et al.  Design of an admittance control with inner robust position control for a robot-assisted rehabilitation system RehabRoby , 2011, 2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).

[84]  W. S. Newman.  Stability and Performance Limits of Interaction Controllers , 1992 .

[85]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[86]  Robert Richardson,et al.  A Control Strategy for Upper Limb Robotic Rehabilitation With a Dual Robot System , 2010, IEEE/ASME Transactions on Mechatronics.

[87]  Gerd Hirzinger,et al.  A new generation of ergonomic exoskeletons - The high-performance X-Arm-2 for space robotics telepresence , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[88]  David A. Abbink,et al.  A novel self-aligning mechanism to decouple force and torques for a planar exoskeleton joint , 2014 .

[89]  Blake Hannaford,et al.  Time domain passivity control of haptic interfaces , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[90]  Delano R. Carter,et al.  Weighted least-squares based control for a four axis gimbal set , 2010, Defense + Commercial Sensing.

[91]  Andre Schiele,et al.  Time Domain Passivity Controller for 4-Channel Time-Delay Bilateral Teleoperation , 2015, IEEE Transactions on Haptics.

[92]  Clément Gosselin,et al.  Variable admittance control of a four-degree-of-freedom intelligent assist device , 2012, 2012 IEEE International Conference on Robotics and Automation.

[93]  Wyatt S. Newman,et al.  The passivity of natural admittance control implementations , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[94]  Xiaoou Li,et al.  PID admittance control for an upper limb exoskeleton , 2011, Proceedings of the 2011 American Control Conference.

[95]  Frank Krause,et al.  Exoskeletons for industrial application and their potential effects on physical work load , 2016, Ergonomics.

[96]  S.J. Ball,et al.  MEDARM: a rehabilitation robot with 5DOF at the shoulder complex , 2007, 2007 IEEE/ASME international conference on advanced intelligent mechatronics.

[97]  Alin Albu-Schäffer,et al.  A passivity based Cartesian impedance controller for flexible joint robots - part II: full state feedback, impedance design and experiments , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[98]  Joan Lobo-Prat,et al.  Comparison between sEMG and force as control interfaces to support planar arm movements in adults with Duchenne: a feasibility study , 2017, Journal of NeuroEngineering and Rehabilitation.

[99]  Mark R. Cutkosky,et al.  The Effects of Real and Computer Generated Friction on Human Performance in a Targeting Task , 2000, Dynamic Systems and Control: Volume 2.

[100]  F A Mussa-Ivaldi,et al.  Central representation of time during motor learning. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[101]  Jos Meuleman,et al.  Novel actuation design of a gait trainer with shadow leg approach , 2013, 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR).

[102]  Muhammad Nabeel,et al.  Increasing the impedance range of admittance-type haptic interfaces by using Time Domain Passivity Approach , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[103]  J. Edward Colgate.  The control of dynamically interacting systems , 1988 .

[104]  Christian Ott,et al.  Unified Impedance and Admittance Control , 2010, 2010 IEEE International Conference on Robotics and Automation.

[105]  Arno H. A. Stienen,et al.  Assessing the usability of remote control servos for admittance-controlled haptic finger manipulators , 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[106]  Gregory D. Hager,et al.  Human-Machine Collaborative Systems for Microsurgical Applications , 2005, Int. J. Robotics Res..

[107]  Sandra Hirche,et al.  Human-preference-based control design: Adaptive robot admittance control for physical human-robot interaction , 2012, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.

[108]  P. Culmer,et al.  An Admittance Control Scheme for a Robotic Upper- Limb Stroke Rehabilitation System , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[109]  J. Krakauer,et al.  Why Don't We Move Faster? Parkinson's Disease, Movement Vigor, and Implicit Motivation , 2007, The Journal of Neuroscience.

[110]  Frans C. T. van der Helm,et al.  Design of a Rotational Hydroelastic Actuator for a Powered Exoskeleton for Upper Limb Rehabilitation , 2010, IEEE Transactions on Biomedical Engineering.

[111]  Roderic A. Grupen,et al.  Learning reactive admittance control , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[112]  Blake Hannaford,et al.  Control law design for haptic interfaces to virtual reality , 2002, IEEE Trans. Control. Syst. Technol..

[113]  F.C.T. van der Helm,et al.  Kinematic Design to Improve Ergonomics in Human Machine Interaction , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[114]  Wan Kyun Chung,et al.  A passivity-based admittance control design using feedback interconnections , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[115]  Ryojun Ikeura,et al.  Investigating the impedance characteristic of human arm for development of robots to co-operate with human operators , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[116]  Nikolaos G. Tsagarakis,et al.  Control strategies for ankle rehabilitation using a high performance ankle exerciser , 2010, 2010 IEEE International Conference on Robotics and Automation.

[117]  Wyatt S. Newman,et al.  Stable interaction control and coulomb friction compensation using natural admittance control , 1994, J. Field Robotics.

[118]  Daniel M. Wolpert,et al.  Forward Models for Physiological Motor Control , 1996, Neural Networks.

[119]  Ho Shing Lo,et al.  An upper limb exoskeleton with an optimized 4R spherical wrist mechanism for the shoulder joint , 2014, 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[120]  Mahdi Tavakoli,et al.  Is the human operator in a teleoperation system passive? , 2013, 2013 World Haptics Conference (WHC).

[121]  Stefano Stramigioli,et al.  Mechanical design of a manipulation system for unmanned aerial vehicles , 2012, 2012 IEEE International Conference on Robotics and Automation.

[122]  A. H. Norris,et al.  Speed and accuracy of movement and their changes with age. , 1969, Acta psychologica.

[123]  Robert Riener,et al.  ARMin II - 7 DoF rehabilitation robot: mechanics and kinematics , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[124]  Mojtaba Ahmadi,et al.  Safely Rendering Small Impedances in Admittance-Controlled Haptic Devices , 2016, IEEE/ASME Transactions on Mechatronics.

[125]  Christian Marchal,et al.  Three-body problem , 1984 .

[126]  Mitsuo Kawato,et al.  Internal models for motor control and trajectory planning , 1999, Current Opinion in Neurobiology.

[127]  Daniel Liberzon,et al.  Switching in Systems and Control , 2003, Systems & Control: Foundations & Applications.

[128]  Dale Lawrence,et al.  Position-based impedance control - Achieving stability in practice , 1987 .

[129]  D.J. Reinkensmeyer,et al.  Biomimetic orthosis for the neurorehabilitation of the elbow and shoulder (BONES) , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[130]  R. Kerr,et al.  Movement time in an underwater environment. , 1973, Journal of motor behavior.

[131]  Shengquan Xie,et al.  Optimization and analysis of a redundant 4R spherical wrist mechanism for a shoulder exoskeleton , 2014, Robotica.

[132]  Masayoshi Tomizuka,et al.  Kinematic Design and Analysis of a 6-DOF Upper Limb Exoskeleton Model for a Brain-Machine Interface Study , 2013 .

[133]  Frans C. T. van der Helm,et al.  Self-Aligning Exoskeleton Axes Through Decoupling of Joint Rotations and Translations , 2009, IEEE Transactions on Robotics.

[134]  J. Edward Colgate,et al.  Design of an active one-degree-of-freedom lower-limb exoskeleton with inertia compensation , 2011, Int. J. Robotics Res..

[135]  J. W. Wilson.  Analysis and mechanization of three and four gimbal systems , 1968 .

[136]  Joan Lobo-Prat,et al.  Evaluation of EMG, force and joystick as control interfaces for active arm supports , 2014, Journal of NeuroEngineering and Rehabilitation.

[137]  Olivier Chapuis,et al.  Effects of motor scale, visual scale, and quantization on small target acquisition difficulty , 2011, TCHI.

[138]  Etienne Burdet,et al.  Human Robotics: Neuromechanics and Motor Control , 2013 .

[139]  Piet Lammertse,et al.  HapticMaster - a generic force controlled robot for human interaction , 2003, Ind. Robot.

[140]  Septimiu E. Salcudean,et al.  Analysis of Control Architectures for Teleoperation Systems with Impedance/Admittance Master and Slave Manipulators , 2001, Int. J. Robotics Res..

[141]  Lorenzo Marconi,et al.  Developing an Aerial Manipulator Prototype: Physical Interaction with the Environment , 2014, IEEE Robotics & Automation Magazine.

[142]  Emanuel Todorov,et al.  Stochastic Optimal Control and Estimation Methods Adapted to the Noise Characteristics of the Sensorimotor System , 2005, Neural Computation.

[143]  J.C. Perry,et al.  Design of a 7 Degree-of-Freedom Upper-Limb Powered Exoskeleton , 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006..

[144]  Neville Hogan,et al.  Robust control of dynamically interacting systems , 1988 .

[145]  F A Mussa-Ivaldi,et al.  Adaptive representation of dynamics during learning of a motor task , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[146]  Arno H. A. Stienen,et al.  Design and control of the Active A-Gear: A wearable 5 DOF arm exoskeleton for adults with Duchenne muscular dystrophy , 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[147]  P. Fitts,et al.  INFORMATION CAPACITY OF DISCRETE MOTOR RESPONSES. , 1964, Journal of experimental psychology.

[148]  Hyung-Soon Park,et al.  IntelliArm: An exoskeleton for diagnosis and treatment of patients with neurological impairments , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[149]  J. Edward Colgate,et al.  Haptic Display of Constrained Dynamic Systems via Admittance Displays , 2007, IEEE Transactions on Robotics.

[150]  Nariman Sepehri,et al.  Position-based impedance control of an industrial hydraulic manipulator , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[151]  Ferdinando A. Mussa-Ivaldi,et al.  Sequence, time, or state representation: how does the motor control system adapt to variable environments? , 2003, Biological Cybernetics.

[152]  John W. Wilson.  Four-gimbal systems for simulation display , 1969 .

[153]  Dragoljub Surdilovic,et al.  Robust Control of Interaction with Haptic Interfaces , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[154]  Nikolaos G. Tsagarakis,et al.  A passivity based admittance control for stabilizing the compliant humanoid COMAN , 2012, 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012).

[155]  Arno H. A. Stienen,et al.  Visualization of shoulder range of motion for clinical diagnostics and device development , 2015, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR).

[156]  Kyle B. Reed,et al.  Physical Collaboration of Human-Human and Human-Robot Teams , 2008, IEEE Transactions on Haptics.

[157]  Homayoun Seraji,et al.  Force Tracking in Impedance Control , 1997, Int. J. Robotics Res..

[158]  José Luis Pons Rovira,et al.  A robotic exoskeleton for overground gait rehabilitation , 2013, 2013 IEEE International Conference on Robotics and Automation.

[159]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part I—Theory , 1985 .

[160]  Ji Ma,et al.  Effects of Friction Parameters on Completion Times for Sustained Planar Positioning Tasks with a Haptic Interface , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[161]  S. Leonhardt,et al.  A survey on robotic devices for upper limb rehabilitation , 2014, Journal of NeuroEngineering and Rehabilitation.

[162]  Robert Riener,et al.  ARMin III --arm therapy exoskeleton with an ergonomic shoulder actuation , 2009 .

[163]  Jacob Rosen,et al.  Admittance control of an upper limb exoskeleton - Reduction of energy exchange , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[164]  Wyatt S. Newman,et al.  The implementation of a natural admittance controller on an industrial manipulator , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[165]  Alin Albu-Schäffer,et al.  A Unified Passivity-based Control Framework for Position, Torque and Impedance Control of Flexible Joint Robots , 2007, Int. J. Robotics Res..

[166]  Arno H. A. Stienen,et al.  Adaptive gravity and joint stiffness compensation methods for force-controlled arm supports , 2015, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR).

[167]  Arno H. A. Stienen,et al.  Design and control of an experimental active elbow support for adult Duchenne Muscular Dystrophy patients , 2014, 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics.

[168]  Blake Hannaford,et al.  Stable haptic interaction with virtual environments , 1999, IEEE Trans. Robotics Autom..

[169]  Gregory S. Sawicki,et al.  Reducing the energy cost of human walking using an unpowered exoskeleton , 2015, Nature.

[170]  C. L. Clover.  A control-system architecture for robots used to simulate dynamic force and moment interaction between humans and virtual objects , 1999, IEEE Trans. Syst. Man Cybern. Part C.

[171]  Ganwen Zeng,et al.  An overview of robot force control , 1997, Robotica.

[172]  Frans C. T. van der Helm,et al.  The influence of human-robot interaction order during fast lifting tasks for different levels of weight compensation , 2014, 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics.

[173]  D. Wolpert,et al.  Temporal and amplitude generalization in motor learning. , 1998, Journal of neurophysiology.

[174]  Dominiek Reynaerts,et al.  Bounded environment passivity of the classical Position-Force teleoperation controller , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[175]  J. Edward Colgate,et al.  Factors affecting the Z-Width of a haptic display , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[176]  David A. Abbink,et al.  The Effect of Trial-by-Trial Adaptation on Conflicts in Haptic Shared Control for Free-Air Teleoperation Tasks , 2016, IEEE Transactions on Haptics.

[177]  Dale A. Lawrence.  Stability and transparency in bilateral teleoperation , 1993, IEEE Trans. Robotics Autom..

[178]  Stephen P. Buerger,et al.  Relaxing Passivity for Human-Robot Interaction , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[179]  R. Fischer,et al.  The effects of age, sex, and shoulder dominance on range of motion of the shoulder. , 2001, Journal of shoulder and elbow surgery.

[180]  Frans C. T. van der Helm,et al.  Haptic Shared Control in Tele-Manipulation: Effects of Inaccuracies in Guidance on Task Execution , 2015, IEEE Transactions on Haptics.

[181]  M. Doyon,et al.  On the implementation and performance of impedance control on position controlled robots , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[182]  Neville Hogan,et al.  Controlling impedance at the man/machine interface , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[183]  M. A. Peshkin,et al.  Inertia Compensation Control of a One-Degree-of-Freedom Exoskeleton for Lower-Limb Assistance: Initial Experiments , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[184]  G. Raisbeck.  A Definition of Passive Linear Networks in Terms of Time and Energy , 1954 .

[185]  J. Lackner,et al.  Congenitally blind individuals rapidly adapt to coriolis force perturbations of their reaching movements. , 2000, Journal of Neurophysiology.

[186]  C. Carignan,et al.  Design of an arm exoskeleton with scapula motion for shoulder rehabilitation , 2005, ICAR '05. Proceedings., 12th International Conference on Advanced Robotics, 2005..