Abstract
This paper describes the design and control of a portable and lightweight knee exoskeleton for people with knee dysfunction. The knee exoskeleton is designed based on our custom quasi-direct drive actuation composed of a DC motor unit and a transmission mechanism encompassing three gears. An online gait generation method based on gait step calculation and direct measurement using Inertial Measurement Unit (IMU) sensors is proposed to provide continuous assistance during walking. Based on the generated gait trajectory online, Active Disturbance Rejection Control (ADRC) incorporating the feedforward compensation approach is proposed to help the human leg move in consideration of external disturbances. The developed knee exoskeleton has been employed successfully to assist impaired users with knee dysfunction to walk in a health recovery center. The experimental results indicate that the online gait generation method and the proposed control method are suitable for the knee exoskeleton. The maximum value of the target knee angular position is approximately 50° and the mean of the control torque for the knee joint is located in the interval of [− 2 Nm, 4 Nm]. The developed knee exoskeleton has the potential to regain normal gait to improve strength and endurance during walking in their activities of daily life.
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References
Long, Y., Du, Z. J., Wang, W. D., & Dong, W. (2018). Human motion intent learning based adaptive motion assistance control for a wearable exoskeleton. Robotics and Computer-integrated Manufacturing, 49, 317–327.
Pinto-Fernandez, D., Torricelli, D., Sanchez-Villamanan, M., Aller, F., & Pons, J. L. (2020). Performance evaluation of lower limb exoskeletons: A systematic review. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(7), 1573–1583.
Esquenazi, A., Talaty, M., Packel, A., & Saulino, M. (2012). The ReWalk powered exoskeleton to restore ambulatory function to individuals with thoracic-level motor-complete spinal cord injury. American Journal of Physical Medicine & Rehabilitation, 91(11), 911–921.
Witte, K. A., Fiers, P., Sheets-Singer, A. L., & Collins, S. H. (2020). Improving the energy economy of human running with powered and unpowered ankle exoskeleton assistance. Science Robotics, 5(40), 9108.
Liu, X. H., & Wang, Q. N. (2020). Real-time locomotion mode recognition and assistive torque control for unilateral knee exoskeleton on different terrains. IEEE/ASME Transactions on Mechatronics, 25(6), 2722–2732.
Naghavi, N., Akbarzadeh, A., Tahamipour, S. M., & Kardan, I. (2020). Assist-as-needed control of a hip exoskeleton based on a novel strength index. Robotics and Autonomous Systems, 134, 103667.
Shamaei, K., Cenciarini, M., Adams, A. A., Gregorczyk, K. N., Schiffman, J. M., & Dollar, A. M. (2014). Design and evaluation of a quasi-passive knee exoskeleton for investigation of motor adaptation in lower extremity joint. IEEE Transactions on Biomedical Engineering, 61(6), 1809–1821.
Zhang, L., Liu, G., Han, B., Wang, Z., & Jiao, Y. (2019). Assistive devices of human knee joint: A review. Robotics and Autonomous Systems, 125, 1–30.
Knaepen, K., Beyl, P., Duerinck, S., Hagman, F., Lefeber, D., & Meeusen, R. (2014). Human-robot interaction: Kinematics and muscle activity inside a powered compliant knee exoskeleton. IEEE transactions on neural systems and rehabilitation engineering, 22(6), 1128–1137.
Yang, L., Zhou, Z. H., & Wang, Q. N. (2015). BioKEX: A bionic knee exoskeleton with proxy-based sliding mode control. IEEE International Conference on Industrial Technology (ICIT), Seville, Spain, 125–130.
Yu, S., Huang, T. H., Yang, X. L., Jiao, C. H., Yang, J. F., Hu, H., Zhang, S. N., Chen, Y., Yi, J. G., & Su, H. (2020). Quasi-direct drive actuation for a lightweight hip exoskeleton with high backdrivability and high bandwidth. IEEE/ASME Transactions on Mechatronics, 25(4), 1–10.
Zhu, H., Nesler, C., Divekar, N., Ahmad, M. T., & Gregg, R. D. (2019). Design and validation of a partial-assist knee orthosis with compact, backdrivable actuation. IEEE 16th International Conference on Rehabilitation Robotics, Toronto, Canada, 917–924 .
Han, Y. L., Zhu, S. Q., Gao, H. T., Wu, Z. Y., Xu, Y. X., & Zhou, W. J. (2020). The swing control of knee exoskeleton based on admittance model and nonlinear oscillator. Journal of Intelligent & Robotic Systems, 99(3–4), 747–756.
Li, F., Wang, Q. D., Xie, Y., & Xie, H. L. (2020). Admittance control of four-link bionic knee exoskeleton with inertia compensation. Tehnicki Vjesnik-Technical Gazette, 27(3), 891–897.
Beyl, P., Knaepen, K., Duerinck, S., Damme, M. V., Vanderborght, B., Meeusen, R., & Lefeber, D. (2011). Safe and compliant guidance by a powered knee exoskeleton for robot-assisted rehabilitation of gait. Advanced Robotics, 25(5), 513–535.
Shepherd, M., & Rouse, E. (2017). Design and validation of a torque-controllable knee exoskeleton for sit-to-stand assistance. IEEE/ASME Transactions on Mechatronics, 22(4), 1695–1704.
Zhang, L. C., Huang, Q., Cai, K. J., Wang, Z. H., Wang, W. K., & Liu, J. (2020). A wearable soft knee exoskeleton using vacuum-actuated rotary actuator. IEEE Access, 8, 61311–61326.
Wang, J. L., Li, X., Huang, T. H., Yu, S. Y., Li, Y. J., Chen, T. Y., Carriero, A., Oh-Park, M., & Su, H. (2018). Comfort-centered design of a lightweight and backdrivable knee exoskeleton. IEEE Robotics and Automation Letters, 3(4), 4265–4272.
Li, D. Z., Ding, P., & Gao, Z. Q. (2016). Fractional active disturbance rejection control. ISA Transactions, 62, 109–119.
Chen, C. F., Du, Z. J., He, L., Wang, J. Q., & Dong, W. (2019). Active disturbance rejection with fast terminal sliding mode control for a lower limb exoskeleton in swing phase. IEEE Access, 7, 72343–72357.
Aole, S., Elamvazuthi, I., Waghmare, L., Patre, B., & Meriaudeau, F. (2020). Improved active disturbance rejection control for trajectory tracking control of lower limb robotic rehabilitation exoskeleton. Sensors, 20(13), 3681.
Long, Y., Du, Z. J., Wang, W., & Dong, W. (2016). Development of a wearable exoskeleton rehabilitation system based on hybrid control mode”. International Journal of Advanced Robotic Systems, 13(5), 1–13.
Long, Y., Du, Z. J., Wang, W., & Dong, W. (2016). Robust sliding mode control based on GA optimization and CMAC compensation for lower limb exoskeleton. Applied Bionics and Biomechanics, 2016, 1–13.
Liu, C. J., Geng, W. D., Liu, M., & Chen, Q. J. (2020). Workspace trajectory generation method for humanoid adaptive walking with dynamic motion primitives. Access IEEE, 8, 54652–54662.
Vanderborght, B., Verrelst, B., Ham, R. V., Damme, M. V., & Lefeber, D. (2008). Objective locomotion parameters based inverted pendulum trajectory generator. Robotics & Autonomous Systems, 56(9), 738–750.
Yuan, Y. X., Li, Z. J., Zhao, T., & Gan, D. (2020). DMP-based motion generation for a walking exoskeleton robot using reinforcement learning. IEEE Transactions on Industrial Electronics, 67(5), 3830–3839.
Long, Y., Du, Z. J., Cong, L., Wang, W. D., Zhang, Z. M., & Dong, W. (2017). Active disturbance rejection control based human gait tracking for lower extremity rehabilitation exoskeleton. ISA Transactions, 67, 389–397.
Gao, Z. Q. (2003). Scaling and bandwidth-parameterization based controller tuning. The 2003 American Control Conference, Denver, USA, 4989–4996.
Acknowledgements
We are grateful to the Natural Science Foundation of Guangdong Province (2020A1515110121) and the Fundamental Research Funds for the Central Universities (N2129002) for all support provided to realize this project.
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Long, Y., Peng, Y. Design and Control of a Quasi-direct Drive Actuated Knee Exoskeleton. J Bionic Eng 19, 678–687 (2022). https://doi.org/10.1007/s42235-022-00168-2
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DOI: https://doi.org/10.1007/s42235-022-00168-2