Abstract
In this paper, experimental implementation and comparative accuracy evaluation of five methods for estimation of human-robot interaction torques are presented. These methods vary from the simplest case of using solely commanded motor torques, to partial consideration of the robot dynamics, to advanced methods considering full robot dynamics such as inverse dynamics (ID) and nonlinear disturbance observer (NDO) based algorithms. Dynamic and friction models of the exoskeleton were developed and their parameters were identified using an evolutionary optimization algorithm to ensure high parameter accuracy. When used with accurate model parameters, ID method led to 20 to 22% average error, while NDO method generated 12 to 18% average error, as evaluated in experiments with a force sensor. These values compare to average error values of up to 132% for using motor torques only, and between 25 to 69% when partial dynamics were used. A sensitivity analysis of the ID and NDO methods to inaccuracies in model parameter estimations revealed considerable sensitivity of these advanced methods to model parameter variations. A summary is provided for the typical estimation accuracy levels that can be expected of these methods and discuss the limitations and considerations that should be taken into account for their use.
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Aksman, L.M., Carignan, C.R., Akin, D.L.: Force estimation based compliance control of harmonically driven manipulators. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp 4208–4213 (2007)
Alcocer, A., Robertsson, A., Valera, A., Johansson, R.: Force estimation and control in robot manipulators. In: Robot Control 2003 (SYROCO’03): a Proceedings Volume from the 7th IFAC Symposium, Wrocław, Poland, 1–3 September 2003, vol. 1, p 55. International Federation of Automatic Control (2004)
Altpeter, F.: Friction Modeling, Identification and Compensation. Ph.D. thesis, Ecole Polytechnique Federale de Lausanne (1999)
An, C., Atkeson, C., Hollerbach, J.: Estimation of inertial parameters of rigid body links of manipulators. In: 24th IEEE Conference on Decision and Control. pp 990–995 (1985). https://doi.org/10.1109/CDC.1985.268648
Bélanger, P. R., Dobrovolny, P., Helmy, A., Zhang, X.: Estimation of angular velocity and acceleration from shaft-encoder measurements. Int. J. Robot. Res. 17(11), 1225–1233 (1998)
Berkowitz, M.: Spinal Cord Injury: an Analysis of Medical and Social Costs. Demos Medical Publishing (1998)
Bernstein, N.L., Lawrence, D., Pao, L.Y., et al.: Friction modeling and compensation for haptic interfaces. In: IEEE International Conference on First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (World Haptics Conference), pp 290–295 (2005)
Brewer, B., McDowell, S., Worthen-Chaudhari, L.: Poststroke upper extremity rehabilitation: a review of robotic systems and clinical results. Top. Stroke Rehabil. 14(6), 22–44 (2007)
Burgar, C.G., Lum, P.S., Shor, P.C., Van der Loos, H.F.M.: Development of robots for rehabilitation therapy: the Palo Alto VA/Stanford experience. J. Rehabil. Res. Dev. 37(6), 663–73 (2000)
Bütefisch, C., Hummelsheim, H., Denzler, P., Mauritz, K.H.: Repetitive training of isolated movements improves the outcome of motor rehabilitation of the centrally paretic hand. J. Neurol. Sci. 130(1), 59–68 (1995)
Caputo, J.M., Collins, S.H.: A universal ankle–foot prosthesis emulator for human locomotion experiments. J. Biomech. Eng. 136(3), 035,002 (2014)
Celik, O., O’Malley, M.K., Boake, C., Levin, H.S., Yozbatiran, N., Reistetter, T.A.: Normalized movement quality measures for therapeutic robots strongly correlate with clinical motor impairment measures. IEEE Trans. Neural Syst. Rehabil. Eng. 18(4), 433–444 (2010)
Chawda, V., Celik, O., O’Malley, M.K.: Application of levant’s differentiator for velocity estimation and increased z-width in haptic interfaces. In: IEEE World Haptics Conference (WHC 2011), pp 403–408 (2011)
Chen, W.H., Ballance, D.J., Gawthrop, P.J., nReilly, J.: A nonlinear disturbance observer for robotic manipulators. IEEE Trans. Ind. Electron. 47(4), 932–938 (2000)
Collins, S.H.: What do walking humans want from mechatronics? In: Proceedings of 2013 IEEE International Conference on Mechatronics (ICM), pp 24–27. IEEE (2013)
Colomé, A., Pardo, D., Alenya, G., Torras, C.: External force estimation during compliant robot manipulation. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp 3535–3540 (2013)
Dehghan, S.A.M., Danesh, M., Sheikholeslam, F.: Adaptive hybrid force/position control of robot manipulators using an adaptive force estimator in the presence of parametric uncertainty. Adv. Robot. 29(4), 209–223 (2015)
Engelbrecht, A.P.: Computational Intelligence: an Introduction. Wiley, New York (2007)
Eom, K.S., Suh, I.H., Chung, W.K., Oh, S.R.: Disturbance observer based force control of robot manipulator without force sensor. In: Proceedings of the IEEE International Conference on Robotics and Automation, vol. 4, pp 3012–3017 (1998)
García, J.G., Robertsson, A., Ortega, J.G., Johansson, R.: Generalized contact force estimator for a robot manipulator. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp 4019–4024 (2006)
Gupta, A., O’Malley, M.K.: Disturbance-observer-based force estimation for haptic feedback. J. Dyn. Syst. Meas. Control. 133(1), 014,505 (2011)
Gupta, A., O’Malley, M.K., Patoglu, V., Burgar, C.: Design, control and performance of ricewrist: a force feedback wrist exoskeleton for rehabilitation and training. Int. J. Robot. Res. 27(2), 233–251 (2008)
Hacksel, P., Salcudean, S.: Estimation of environment forces and rigid-body velocities using observers. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp 931–936 (1994)
Hogan, N., Krebs, H.I., Rohrer, B., Fasoli, S., Stein, J., Volpe, B.T.: Technology for recovery after stroke. In: Barnes, M.P., Dobkin, B.H., Bogousslavsky, J. (eds.) Recovery After Stroke, pp 604–622. Cambridge University Press (2005)
Jones, T.A., Allred, R.P., Adkins, D.A.L., Hsu, J.E., O’Bryant, A., Maldonado, M.A.: Remodeling the brain with behavioral experience after stroke. Stroke 40(3 suppl 1), S136–S138 (2009)
Jung, J., Lee, J., Huh, K.: Robust contact force estimation for robot manipulators in three-dimensional space. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. 220(9), 1317–1327 (2006)
Korayem, M.H., Haghighi, R.: Nonlinear disturbance observer for robot manipulators in 3d space. In: Intelligent Robotics and Applications, pp 14–23. Springer (2008)
Krebs, H.I., Hogan, N., Aisen, M.L., Volpe, B.T.: Robot-aided neurorehabilitation. IEEE Trans. Rehabil. Eng. 6(1), 75–87 (1998)
Lee, H.S., Tomizuka, M.: Robust motion controller design for high-accuracy positioning systems. IEEE Trans. Ind. Electron. 43(1), 48–55 (1996)
Lloyd-Jones, D., Adams, R., Carnethon, M., De Simone, G., Ferguson, T.B., Flegal, K., Ford, E., Furie, K., Go, A., Greenlund, K., et al.: Heart disease and stroke statistics–2009 update: a report from the american heart association statistics committee and stroke statistics subcommittee. Circulation 119(3), e21 (2009)
Martinez, J.A., Ng, P., Lu, S., Campagna, M.S., Celik, O.: Design of wrist gimbal: a forearm and wrist exoskeleton for stroke rehabilitation. In: IEEE International Conference on Rehabilitation Robotics (ICORR 2013), pp 1–6 (2013)
Masia, L., Casadio, M., Giannoni, P., Sandini, G., Morasso, P.: Performance adaptive training control strategy for recovering wrist movements in stroke patients: a preliminary, feasibility study. J. Neuroeng. Rehabil. 6 (1), 1 (2009)
Mohammadi, A., Tavakoli, M., Marquez, H., Hashemzadeh, F.: Nonlinear disturbance observer design for robotic manipulators. Control. Eng. Pract. 21(3), 253–267 (2013)
Muir, G.D., Steeves, J.D.: Sensorimotor stimulation to improve locomotor recovery after spinal cord injury. Trends Neurosci. 20(2), 72–77 (1997)
Murakami, T., Yu, F., Ohnishi, K.: Torque sensorless control in multidegree-of-freedom manipulator. IEEE Trans. Ind. Electron. 40(2), 259–265 (1993)
Naerum, E., Cornellà, J., Elle, O.J.: Contact force estimation for backdrivable robotic manipulators with coupled friction. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 3021–3027 (2008)
Ohishi, K., Miyazaki, M., Fujita, M.: Hybrid control of force and position without force sensor. In: Proceedings of the IEEE International Conference on Industrial Electronics, Control, Instrumentation, and Automation, pp 670–675 (1992)
Ohnishi, K., Shibata, M., Murakami, T.: Motion control for advanced mechatronics. IEEE/ASME Trans. Mechatron. 1(1), 56–67 (1996)
Price, K., Storn, R.M., Lampinen, J.A.: Differential Evolution: a Practical Approach to Global Optimization. Springer Science & Business Media, New York (2006)
Saadatzi, M., Long, D.C., Celik, O.: Torque estimation in a wrist rehabilitation robot using a nonlinear disturbance observer. In: ASME 2015 Dynamic Systems and Control Conference (2015)
Spong, M.W., Hutchinson, S., Vidyasagar, M.: Robot Modeling and Control, vol. 3. Wiley, New York (2006)
Stolt, A., Linderoth, M., Robertsson, A., Johansson, R.: Force controlled robotic assembly without a force sensor. In: IEEE International Conference on Robotics and Automation (ICRA), pp 1538–1543. IEEE (2012)
Storn, R., Price, K.: Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11(4), 341–359 (1997)
Ugurlu, B., Nishimura, M., Hyodo, K., Kawanishi, M., Narikiyo, T.: A framework for sensorless torque estimation and control in wearable exoskeletons. In: 12th IEEE International Workshop on Advanced Motion Control (AMC), pp 1–7 (2012)
Ugurlu, B., Nishimura, M., Hyodo, K., Kawanishi, M., Narikiyo, T.: Proof of concept for robot-aided upper limb rehabilitation using disturbance observers. IEEE Transactions on Human-Machine Systems 45(1), 110–118 (2015). https://doi.org/10.1109/THMS.2014.2362816
Wahrburg, A., Zeiss, S., Matthias, B., Ding, H.: Contact force estimation for robotic assembly using motor torques. In: IEEE International Conference on Automation Science and Engineering (CASE), pp 1252–1257. IEEE (2014)
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Appendix: Dynamic Equations of the Exoskeleton
Appendix: Dynamic Equations of the Exoskeleton
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Saadatzi, M., Long, D.C. & Celik, O. Comparison of Human-Robot Interaction Torque Estimation Methods in a Wrist Rehabilitation Exoskeleton. J Intell Robot Syst 94, 565–581 (2019). https://doi.org/10.1007/s10846-018-0786-8
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DOI: https://doi.org/10.1007/s10846-018-0786-8