Abstract
Sensitivity Amplification Control (SAC) algorithm was first proposed in the augmentation application of the Berkeley Lower Extremity Exoskeleton (BLEEX). Since the SAC algorithm can greatly reduce the complexity of exoskeleton system, it is widely used in human augmentation applications. Nevertheless, the performance of the SAC algorithm depends on the accuracy of dynamic model parameters. In this paper, we propose a novel Model-based control with Interaction Predicting (MIP) strategy to lower dependency on the accurate dynamic model of the exoskeleton. The MIP consists of an interaction predictor and a model-based controller. The interaction predictor can predict motion trajectories of the pilot and substitute for the pilot to drive the exoskeleton through an impedance model. In proposed strategy, the model-based controller not only amplify the forces initiated by the interaction predictor, but more importantly the forces imposed by the pilot to correct the errors between the predictive motion trajectory and the intended motion trajectory of the pilot. Illustrative simulations and experimental results are presented to demonstrate the efficiency of the proposed strategy. Additionally, the comparisons with traditional model-based control algorithm are also presented to demonstrate the efficiency and superiority of the proposed control strategy for lowering dependency on dynamic models.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Calzado, J., Lindsay, A., Chen, C., Samuels, G., Olszewska, J.: SAMI: Interactive, multi-sense robot architecture. In: IEEE 22nd International Conference on Intelligent Engineering Systems (INES), pp. 317–322 (2018)
Chen, Q., Cheng, H., Yue, C., Huang, R., Guo, H.: Step length adaptation for walking assistance. In: IEEE International Conference on Mechatronics and Automation (ICMA), pp. 644–650 (2017)
Chen, Q., Cheng, H., Yue, C., Huang, R., Guo, H.: Dynamic balance gait for walking assistance exoskeleton. Applied Bionics and Biomechanics, pp. 1–10 (2018)
Ding, Y., Galiana, I., Siviy, C., Panizzolo, F.A., Walsh, C.: IMU-based iterative control for hip extension assistance with a soft exosuit. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3501–3508 (2016)
Ghan, J., Kazerooni, H.: System identification for the Berkeley Lower Extremity Exoskeleton (BLEEX). In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3477–3484 (2006)
Ghan, J., Steger, R., Kazerooni, H.: Control and system identification for the Berkeley Lower Extremity Exoskeleton (BLEEX). Adv. Robot. 20(9), 989–1014 (2006)
Huang, L., Steger, R.R., Kazerooni, H.: Hybrid control of the Berkeley Lower Extremity Exoskeleton (BLEEX). In: International Mechanical Engineering Congress and Exposition, pp. 1429–1436 (2005)
Huang, R., Cheng, H., Chen, Q., Tran, H.T., Lin, X.: Interactive learning for sensitivity factors of a human-powered augmentation lower wxoskeleton. In: IEEE International Conference on Intelligent Robots and Systems (IROS), pp. 6409–6415 (2015)
Huang, R., Cheng, H., Guo, H., Chen, Q., Lin, X.: Hierarchical interactive learning for a human-powered augmentation lower exoskeleton. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 257–263 (2016)
Huang, R., Cheng, H., Guo, H., Lin, X., Chen, Q., Sun, F.: Learning cooperative primitives with physical human-robot interaction for a HUman-Powered Lower EXoskeleton. In: IEEE International Conference on Intelligent Robots and Systems (IROS), pp. 5355–5360 (2016)
Huang, R., Cheng, H., Guo, H., Lin, X., Zhang, J.: Hierarchical learning control with physical human-exoskeleton interaction. Inform. Sci. 432, 584–595 (2018)
Ijspeert, A.J., Nakanishi, J., Schaal, S.: Learning rhythmic movements by demonstration using nonlinear oscillators. In: IEEE International Conference on Intelligent Robots and Systems (IROS), vol. 3, pp 958–963 (2002)
Kazerooni, H., Chu, A., Steger, R.: That which does not stabilize, will only make us stronger. Int. J Robotics Res. 26(1), 75–89 (2007)
Kazerooni, H., Racine, J.L., Huang, L., Steger, R.: On the control of the Berkeley Lower Extremity Exoskeleton (BLEEX). In: IEEE International Conference on Robotics and Automation (ICRA), pp. 4353–4360 (2005)
Kazerooni, H., Steger, R.: The Berkeley Lower Extremity Exoskeleton. Journal of Dynamic Systems, Measurement and Control 128(1), 14–25 (2006)
Li, Z., Ma, W., Yin, Z., Guo, H.: Tracking control of time-varying knee exoskeleton disturbed by interaction torque. ISA Trans. 71, 458–466 (2017)
Ng, A.Y., Coates, A., Diel, M., Ganapathi, V., Schulte, J., Tse, B., Berger, E., Liang, E.: Autonomous inverted helicopter flight via reinforcement learning. In: Experimental Robotics IX, pp 363–372. Springer (2006)
Nguyen-Tuong, D., Peters, J.R., Seeger, M.: Local Gaussian process regression for real time online model learning. In: Advances in Neural Information Processing Systems, pp. 1193–1200 (2009)
Olszewska, J.I., Houghtaling, M., Goncalves, P.J., Fabiano, N., Haidegger, T., Carbonera, J.L., Patterson, W.R., Ragavan, S.V., Fiorini, S.R., Prestes, E.: Robotic standard development life cycle in action. Journal of Intelligent & Robotic Systems, pp. 1–13 (2019)
Schaal, S., Atkeson, C.G.: Constructive incremental learning from only local information. Neural Comput. 10(8), 2047–2084 (1998)
Steger, R., Kim, S.H., Kazerooni, H.: Control scheme and networked control architecture for the Berkeley Lower Extremity Exoskeleton (BLEEX). In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3469–3476 (2006)
Tran, H.T., Cheng, H., Lin, X., Duong, M.K., Huang, R.: The relationship between physical human-exoskeleton interaction and dynamic factors: using a learning approach for control applications. Science China Information Sciences 57(12), 1–13 (2014)
Tutsoy, O.: CPG based RL algorithm learns to control of a humanoid robot leg. Int. J. Robot. Autom. 30(2), 1–7 (2015)
Walsh, C.J., Paluska, D., Pasch, K., Grand, W., Valiente, A., Herr, H.: Development of a lightweight, underactuated exoskeleton for load-carrying augmentation. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3485–3491 (2006)
Wang, Y., Gao, F., Doyle, F.J. III: Survey on iterative learning control, repetitive control, and run-to-run control. J. Process. Control. 19(10), 1589–1600 (2009)
Winter, D.A.: Biomechanics and Motor Control of Human Movement. Wiley, Hoboken (2009)
Acknowledgements
This work was made possible by support from the National Key Research and Development Program of China (No. 2017YFB1302300), National Natural Science Foundation of China (NSFC) (No. 6150020696, 61503060), Sichuan Science and Technology Major Projects of New Generation Artificial Intelligence (No. 2018GZDZX0037) and the Fundamental Research Funds for the Central Universities (No. ZYGX2015J148).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Song, G., Huang, R., Qiu, J. et al. Model-based Control with Interaction Predicting for Human-coupled Lower Exoskeleton Systems. J Intell Robot Syst 100, 389–400 (2020). https://doi.org/10.1007/s10846-020-01200-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-020-01200-5