Abstract
In this paper, we use modular design method to construct an upper limb exoskeleton. This new design method is more simple and easy for exoskeletons than the other techniques, and it is facility to be extended into more joints robots. We also propose a novel admittance control, which works in task space. The admittance control has PID form, and does not need the inverse kinematic and the dynamic model of the exoskeleton. The experimental results show that both the design and the controller work well for the upper limb exoskeleton.
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References
C. P. Joel, J. Rosen and S. Burns, Upper-limb powered exoskeleton design, IEEE Transactions on Mechatronics, 12 (4) (2007) 408–417.
Z. Tang, K. Zhang, S. Sun and Z. Gao, An upper-limb power-assist exoskeleton using proportional myoelectric control, Sensors, 14 (2014) 6677–6694.
H. Shing and S. Xi, Exoskeleton robots for upper-limb rehabilitation: State of the art and future prospects, Medical Engineering & Physics, 34 (3) (2012) 261–268.
A. M. Dollar and H. Herr, Lower extremity exoskeletons and active orthoses: Challenges and state-of-the-art, IEEE Transactions on Robotics, 24 (1) (2008) 1–15.
H. Kazerooni and R. Steger, The Berkeley lower extremity exoskeleton, Journal of Dynamic Systems, Measurements, and Control-Transactions of the ASME, 128 (2006) 14–25.
H. Kim and J. Rosen, Predicting redundancy of a 7 DOF upper limb exoskeleton toward improved transparency between human and robot, Journal of Intelligent & Robotic Systems, Feburary (2015).
J. J. Craig, Introduction to robotic mechanics and control, 3rd Edition, Prentice Hall, Upper Saddle River (2005).
P. Culmer, A. Jackson, M. C. Levesley, J. Savage, R. Richardson, J. A. Cozens and B. B Bhakta, An admittance control scheme for a robotic upper-limb stroke rehabilitation system, 27th Annual Conference on Engineering in Medicine and Biology (2005) 5081–5084.
P. Maciejasz and J. Eschweiler, A survey on robotic devices for upper limb rehabilitation, Journal of Neuro Engineering and Rehabilitation, 11 (3) (2014).
S. Moubarak, M. T. Pham, T. Pajdla and T. Redarce, Design and modeling of an upper extremity exoskeleton, 11th International Congress on Medical Physics and Biomedical Engineering, Munich, Germany (2009) 476–482.
J. T. Wen and S. Murphy, Stability analysis of position and force control for robot arms, IEEE Trans. Automat. Contr., 36 (1991) 365–371.
S. Ali and M. Dehghana, Adaptive hybrid force/position control of robot manipulators using an adaptive force estimator in the presence of parametric uncertainty, Advanced Robotics, 29 (4) (2015).
M. Raibert and J. Craig, Hybrid position/force control of manipulators, ASME J. Dynam. Syst., Meas., Contr., 102 (1981) 126–132.
N. Hogan, Impedance control: An approach to manipulation, PartsI—III, ASME J. Dynam. Syst., Meas., Contr., 107 (1985) 1–24.
W. Yu, J. Rosen and X. Li, PID admittance control for an upper limb exoskeleton, 2011 American Control Conference, San Francisco, USA (2011) 1124–1129.
T. Tsuji and Y. Tanaka, Tracking control properties of human-Robotic systems based on impedance control, IEEE Trans. Systems, Man, and Cyberbetucs-Part A, 35 (4) (2005) 523–535.
H. Kim, L. M. Miller, I. Fedulow, G. Abrams, N. Byl and J. Rosen, Kinematic data analysis for post stroke patients following bilateral versus unilateral rehabilitation with an upper limb wearable robotic system, IEEE Transactions on Neural System and Rehabilitation Engineering, 21 (2013) 153–164.
M. Simkins, A. Al-Refai and J. Rosen, Upper limb joint space modeling of stroke induced synergies using isolated and voluntary arm perturbations, IEEE Transactions on Neural System and Rehabilitation Engineering, 22 (3) (2014) 491–500.
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Recommended by Associate Editor Kyoungchul Kong
Javier Garrido is a Ph.D. student in the Automatic Control Department at Cinvestav-IPN. He received his undergraduate degree in Electronic Engineering in 2002 and M.S. in automatic control in 2004 from Cinvestav-IPN. His research interests include learning and interaction in robotic systems.
Wen Yu received the B.S. degree from Tsinghua University, Beijing, China in 1990 and the M.S. and Ph.D. degrees, both in Electrical Engineering, from Northeastern University, Shenyang, China, in 1992 and 1995, respectively. Since 1996, he has been with CINVESTAV-IPN, Mexico City, Mexico, where he is currently a Professor with the Departamento de Control Automatico. Dr. Wen Yu serves as an associate editor of Neurocomputing, and Journal of Intelligent and Fuzzy Systems. He is a member of the Mexican Academy of Sciences.
Xiaoou Li received the B.S. and the Ph.D. degree in applied mathematics and electrical engineering from Northeastern University, China, in 1991 and 1995. From 1998 to 1999, she was an associate professor of computer science at Centro de Instrumentos-UNAM. Since 2000, she has been a professor of computer science at Sección de Computación, Departamento de Ingeniería Eléctrica, CINVESTAV-IPN, México. Her research interests include Petri net theory and application, neural networks, advanced database systems, computer integrated manufacturing and discrete event systems.
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Garrido, J., Yu, W. & Li, X. Modular design and control of an upper limb exoskeleton. J Mech Sci Technol 30, 2265–2271 (2016). https://doi.org/10.1007/s12206-015-0843-1
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DOI: https://doi.org/10.1007/s12206-015-0843-1