Abstract
Problem statement: For the organization of feedback in the control system of the exoskeleton, information-measuring modules, sensors are essential elements. They allow monitoring the state of the system, to obtain information about the environment, objects of manipulation. Sensors are necessary elements of the master devices that allow evaluating the control signals of the operator. In this paper we propose our algorithm based on mathematical model of human skeletal muscle. Purpose: The movement of the exoskeleton with low speed is necessary to perform any technological operations and it requires increased accuracy of the desired movement. This is especially important when holding or moving heavy cargo or fragile objects. The mode of movement at high speeds allows operator to move quickly the links of the exoskeleton to the desired position in space. This mode is essential for application in situations where frequent changes of direction of movement are taking place and high speeds are required. A feature of this mode is the requirement for a short transition time of the position and speed of the links of the exoskeleton. Results: The algorithm for recognizing the desired action of the operator and selecting the desired mode of operation of the exoskeleton with the adjustment of the characteristics of the task generator was proposed. To obtain reliable experimental data SEMS system was used. The simulation shows that this algorithm improves the quality of control of the exoskeleton drive, using different control formation laws for the corresponding tasks. Practical significance: The field of exoskeleton devices application is determined by the scientific and technical tasks assigned to such systems. The use of exoskeletons is relevant in emergency situations where they are performing tasks related to the movement of heavy loads, ammunition suspension and the implementation of power support while debris removing, repair of agricultural machinery. The carried out researches allows revealing requirements to quality of drive system control of the exoskeleton device applied for any human activity. Various modes of operation of the exoskeleton device were proposed. Each mode should meet the requirements of operations that the operator should perform in the exoskeleton.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gradetsky, V., Ermolov, I., Knyazkov, M., Semenov, E., Sukhanov, A.: The influence of various factors on the control of the exoskeleton. In Interactive Collaborative Robotics, proc. of the 3rd International Conference ICR 2018, pp. 60–70. Springer, Switzerland, AG 2018 Printforce, The Netherlands (2018)
Gradetsky, V., Ermolov, I., Knyazkov, M., Semenov, E., Sukhanov, A: The dynamic model of operator-exoskeleton interaction. In Interactive Collaborative Robotics, proc. of the 3rd International Conference ICR 2018, pp. 52–59. Springer, Switzerland, AG 2018 Printforce, The Netherlands (2018)
Gradetsky, V., Ermolov, I., Knyazkov ,M., Sukhanov, A.: Generalized approach to bilateral control for EMG driven exoskeleton. In Conference Volume 113, 2017, 12th International Scientific-Technical Conference on Electromechanics and Robotics, volume 113 of Zavalishin’s Readings, pp. 1–5 (2017)
Ermolov, I.L., Sukhanov, A.N., Knyaz’kov, M.M., Kryukova, A.A., Kryuchkov, B.I., Usov, V.M.: A sensory control and orientation system of an exoskeleton.In: Saint Petersburg International Conference on Integrated Navigation Systems, icons 2015—Proceedings, vol. 22, pp. 181–185 (2015)
Wilkie, D.R.: The mechanical properties of muscle. British Med. Bull. vol. 12 (1956)
Gasser, H.S., Hill, A.V.: The dynamics of muscle contraction. Proc. R. Soc. Lond. B 96, 398–437 (1924)
Physiology of muscular activity, labor and sports, L., (Manual of physiology); Hill, A.: Mechanics of muscle contraction (1969)
Ito, K.: EMG pattern classification for a prosthetic forearm with three degrees of freedom. In: Ito, K., Tsuji, T., Kato, A., Ito, M. (eds.) IEEE International Workshop on Robot and Human Communication, pp. 69–74 (1992)
DiCicco, M.: Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand. In: DiCicco, M., Lucas, L., Matsuoka, Y. (eds.) Proceedings of the 2004 IEEE International Conference on Robotics and Automation, New Orleans, LA, pp. 1622–1627 (Apr 2004)
De Luca, C.J., De Luca, C.J.: Surface Electromyography: Detection and Recording. DelSys Incorporated, p. 10 (2002)
Kuribayashi, K.: A discrimination system using neural networks for EMG-control prostheses-Integral type of EMG signal processing. In: Kuribayashi, K., Shimizu, S., Okimura, K., Taniguchi, T.: Proceedings of the 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1750–1755 (1993)
Abbott, V.S., Wilkie, D.R.: The relation between velocity of shortening and the tension-length curve of skeletal muscle. J. Physiol. vol. 120 (1953)
Haeufle, D.F.B., Grimmer, S., Seyfarth, A.: A 2010 the role of intrinsic muscle properties for stable hopping—stability is achieved by the force–velocity relation. Bioinspir. Biomim. 5, 016004. https://doi.org/10.1088/1748-3182/5/1/016004
Zajac, F.E., Gordon, M.E.: Determining muscle’s force and action in multi-articular movement. Exerc. Sport Sci. Rev. 17, 187–230 (1989); Zajac, F.E.: Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. CRC Critical Rev. Biomed. Eng. 17, 359–411 (1989)
Vladimir, R.: Neuromodulation: action potential modeling. Master of Science Thesis in Biomedical Engineering, p. 130 (2014)
Samuel, A.: Active muscle control in human body model simulations. Master’s Thesis in Automotive Engineering, CHALMERS, Applied Mechanics, Master’s Thesis 2013, 62, 64 (2013)
Novoselov, V.S.: On mathematical models of molecular contraction of skeletal muscles. Vestnik SPbGU. Ser. 10. 3, 88–96 (in Russian) (2016)
Sancho-Bru, J.L., Pérez-González, A., Mora, M.C., León, B.E., Vergara, M., Iserte, J.L., RodrÃguez-Cervantes, P.J., Morales, A.: Towards a realistic and self-contained biomechanical model of the hand (2011)
Acknowledgements
The present work was supported by the Ministry of Science and Higher Education within the framework of the Russian State Assignment under contract No. AAAA-A17-117021310384-9.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Gradetsky, V.G., Ermolov, I.L., Knyazkov, M.M., Semenov, E.A., Sukhanov, A.N. (2020). Switching Operation Modes Algorithm for the Exoskeleton Device. In: Gorodetskiy, A., Tarasova, I. (eds) Smart Electromechanical Systems. Studies in Systems, Decision and Control, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-030-32710-1_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-32710-1_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-32709-5
Online ISBN: 978-3-030-32710-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)