Nothing Special   »   [go: up one dir, main page]
Skip to main content

Advertisement

Springer Nature Link
Log in

On-line Walking Speed Control in Human-Powered Exoskeleton Systems Based on Dual Reaction Force Sensors

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

On-line walking speed control in human-powered exoskeleton systems is a big challenge, the translations of human intention to increase or decrease walking speed in maneuverable human exoskeleton systems is still complex field. In this paper, we propose a novel sensing technique to control the walking speed of the system according to the pilot intentions and to minimize the interaction force. We introduce a new sensing technology “Dual Reaction Force (DRF)” sensors, and explain the methodology of using it in the investigation of walking speed changing intentions. The force signals mismatch successfully applied to control the walking speed of the exoskeleton system according to the pilot intentions. Typical issues on the implementation of the sensory system are experimentally validated on flat terrain walking trails. We developed an adaptive trajectory frequency control algorithm to control the walking speed of HUman-powered Augmentation Lower Exoskeleton (HUALEX) within the human wearer intended speed. Based on the mismatch of DRF sensors, we proposed a new control methodology for walking speed control. Human intention recognition and identification through an sensorized footboard and smart shoe is achieved successfully in this work, the new term heel contact time H C T is main feedback signal for the control algorithm. From the experimental walking trails we found that, the H C T during flat walking ranges from 0.69±0.05 sec and 0.41±0.07 sec while walking speed varies between 1m/s and 2.5m/s. The proposed algorithm used an Adaptive Central Pattern Generators (ACPGs) applied to control joint trajectory frequency, the different walking speeds associated with different functioning of human body CPGs frequency. We validated the proposed control algorithm by simulations on single Degree of Freedom (1-DoF) exoskeleton platform, the simulation results show the efficiency and validated that the proposed control algorithm will provides a good walking speed control for the HUALEX exoskeleton system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Tonietti, G., Schiavi, R., Bicchi, A.: Design and Control of a Variable Stiffness Actuator for Safe and Fast Physical Human-Robot Interaction. International Conference on Robotics and Automation, 526–531 (2005)

  2. Hogan, N.: Impedance Control: An Approach to Manipulation. American Control Conference, 304–313 (1984)

  3. Miller, L.M., Rosen, J.: Comparison of Multi-Sensor Admittance Control in Joint Space and Task Space for a Seven Degree of Freedom Upper Limb Exoskeleton In: Proceedings of the 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, pp. 70–75 (2010)

  4. Okunev, V., Nierhoff, T., Hirche, S.: Human-preference-based Control Design: Adaptive Robot Admittance Control for Physical Human-Robot Interaction. The 21st IEEE International Symposium on Robot and Human Interactive Communication, 443–448 (2012)

  5. Lee, B.K., Lee, H.D., Lee, J.y., Shin, K., Han, J.S., Han, C.S.: Development of Dynamic Model-based Controller for Upper Limb Exoskeleton Robot. 2012 IEEE International Conference on Robotics and Automation, 3173–3178 (2012)

  6. Yu, W., Rosen, J., Li, X.: PID Admittance Control for an Upper Limb Exoskeleton. American Control Conference, 1124–1129 (2011)

  7. Augugliaro, F., D’Andrea, R.: Admittance Control for Physical Human-Quadrocopter Interaction. European Control Conference, 1805–1810 (2013)

  8. Oda, M., Zhu, C., Suzuki, M., Luo, X., Watanabe, H., Yan, Y.: Admittance Based Control of Wheelchair Typed Omnidirectional Robot for Walking Support and Power Assistance. 19th IEEE International Symposium on Robot and Human Interactive Communication, 159–164 (2010)

  9. Tran, H.T., Cheng, H., Duong, M.K., Zheng, H.: Fuuzy-based Impedance Regulation for Control of the Coupled Human-Exoskeleton System. IEEE International Conference on Robotics and Biomimetics, 986–992 (2014)

  10. Tran, H.T., Cheng, H., Lin, X., Huang, R.: The Relationship between Physical Human-Exoskeleton Interaction and Dynamic Factors: Using a Learning Approach for Control Applications. Science China Information Science 12, 57 (2014)

    Google Scholar 

  11. Keller, T.S., Weisberger, A.M., Ray, J.L., Hasan, S.S., Shiavi, R.G., Spengler, D.M.: Relationship between vertical ground reaction force and speed during walking, slow jogging, and running. Clin. Biomech. 11(5), 253–259 (1996)

    Article  Google Scholar 

  12. Amor, H.B., Neumann, G., Kamthe, S., Kroemer, O., Peters, J.: Interaction Primitives for Human-Robot Cooperation Tasks In: IEEE International Conference on Robotics and Automation (ICRA), pp. 2831–2837 (2014)

  13. Ikemoto, S., Amor, H.B., Minato, T., Jung, B., Ishiguro, H.: Physical HumanÜRobot Interaction: Mutual Learning and Adaptation. IEEE Robot. Autom. Mag. 19(4), 24–35 (2012)

    Article  Google Scholar 

  14. De Rossi, S.M.M., Lenzi, T., Vitiello, N., Donati, M., Persichetti, A., Giovacchini, F., Vecchi, F., Carrozza, M.C.: Development of an in-shoe pressure-sensitive device for gait analysis In: 33rd Annual International Conference of the IEEE EMBS, pp. 5637–5640 (2011)

  15. Liu, T., Inoue, Y., Shibata, K.: A Wearable Ground Reaction Force Sensor System and Its Application to the Measurement of Extrinsic Gait Variability. Sensors 10, 10240–10255 (2010)

    Article  Google Scholar 

  16. Hassan, M., Kadone, H., Suzuki, K., Sankai, Y.: Wearable Gait Measurement System with an Instrumented Cane for Exoskeleton Control. Sensors 14, 1705–1722 (2014)

    Article  Google Scholar 

  17. Kazerooni, H., Chu, A., Steger, R.: That Which Does Not Stabilize, Will Only Make Us Stronger. Int. J. Robot. Res. 26(75), 75–89 (2007)

    Article  MATH  Google Scholar 

  18. Crea, S., Donati, M., De Rossi, S.M.M., Oddo, C.M., Vitiello, N.: A Wireless Flexible Sensorized Insole for Gait Analysis. Sensors 14, 1073–1093 (2014)

    Article  Google Scholar 

  19. Righetti, L., Ijspeert, A.J.: Programmable Central Pattern Generators: an application to biped locomotion control In: Proceedings of the 2006 IEEE International Conference on Robotics and Automation, pp. 1585–1590 (2006)

  20. Liu, C., Chen, Y., Zhang, J., Chen, Q.: CPG Driven Locomotion Control of Quadruped Robot. IEEE International Conference on Systems, Man, and Cybernetics, 2368–2373 (2009)

  21. Righetti, L., Buchli, J., Ijspeert, A.: Dynamic hebbian learning in adaptive frequency oscillators. Physica D: Nonlinear Phenomena 216(2), 269–281 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  22. Kazerooni, H., Steger, R., Huang, L.: Hybrid Control of the Berkeley Lower Extremity Exoskeleton (BLEEX). Int. J. Robot. Res. 25(5-6), 561–573 (2006)

    Article  Google Scholar 

  23. Lee, S., Sankai, Y.: Power Assist Control for Walking Aid with HAL-3 Based on EMG and Impedance Adjustment around Knee Joint. International Conference on Intelligent Robots and Systems, 1499–1504 (2002)

  24. Yang, Z., Zhu, Y., Yang, X., Zhang, Y.: Impedance control of exoskeleton suit based on adaptive rbf neural network In: International conference on intelligent human-machine systems and cybernetics, pp. 182–96187 (2009)

  25. Harischandra, N., Knuesel, J., Kozlov, A., Bicanski, A., Cabelguen, J.M., Ijspeert, A., Ekeberg, O.: Sensory feedback play sasignificant role in generating walking gait and in gait transition in salamanders a simulation study. Neurorobotics 5, 1–13 (2011)

    Google Scholar 

  26. Sankai, Y.: HAL: Hybrid Assistive Limb Based on Cybernics. Robot. Res. 66, 25–34 (2011)

    Article  Google Scholar 

  27. Suzuki, K., Kawamura, Y., Hayashi, T., Sakurai, T., Hasegawa, Y., Sankai, Y.: Intention-Based Walking Support for Paraplegia Patient In: IEEE International Conference on Systems, Man and Cybernetics, pp. 2707–2713 (2005)

  28. Bortole, M.: Design and Control of a Robotic Exoskeleton for Gait Rehabilitation. Master thesis,Universidad de Madrid, Spain,Madrid (2013)

    Google Scholar 

  29. Yoon, J., ParkEmail, H.n, Damiano, D.L.: A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation. J. Neuroeng. Rehabil. 9(62), 1–13 (2012)

    Google Scholar 

  30. Yu, H., Wang, D., Yang, C., Lee, K.: A Walking Monitoring Shoe System for Simultaneous Plantar-force Measurement and Gait-phase Detection In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 207–212 (2010)

  31. Forner-Cordero, A., Koopman, H.J.F.M., van der Helm, F.C.T.: Inverse dynamics calculations during gait with restricted ground reaction force information from pressure insoles. Gait Posture 23(2), 189–199 (2006)

  32. Mondal, S., Nandy, A., Verma, C., Shukla, S., Saxena, N., Chakraborty, P., Nandi, G.C.: Modeling a Central Pattern Generator to Generate the Biped Locomotion of a Bipedal Robot Using Rayleigh Oscillators. Communications in Computer and Information Science 168, 289–300 (2011)

    Article  Google Scholar 

  33. Jiaqi, Z., Masayoshi, T., Qijun, C., Chengju, L.: Dynamic Walking of AIBO with Hopf Oscillators. Chinese Journal of Mechanical Engineering 24(4), 612–617 (2011)

    Article  Google Scholar 

  34. Inada, H., Ihii, K.: A Bipedal Walk Using Central Pattern Generator (CPG). Brain Science and Engineering, Kyushu Institute of Technology,Japn 1269, 185–6188 (2004)

    Google Scholar 

  35. Tsuchiya, K., Aoi, S., Tsujita, K.: Locomotion Control of a Biped Locomotion Robot using Nonlinear Oscillators, IEEE/RSJ Intl. Conference on Intelligent Robots and Systems, 1745–1750 (2003)

  36. Arena, P., Fortuna, L., Branciforter, M.: Realization of a Reaction-Diffusion CNN Algorithm for Locomotion Control in an Hexapode Robot. J. VLSI Sig. Proc. 23, 267–280 (1999)

    Article  Google Scholar 

  37. Pinto, C., Machado, J.A.T.: Forced van der Pol oscillator of complex order. J. Vib. Control. 18 (14), 2201–2209 (2011). ENOC, Rome, Italy, 2011

    Article  Google Scholar 

  38. Righetti, L., Ijspeert, A.J.: Programmable Central Pattern Generators: an application to biped locomotion control In: IEEE International Conference on Robotics and Automation, pp. 1585–1590 (2006)

  39. Kadaba, M.P., Ramakrishnan, H.K., Wootten, M.E., Gainey, J., Gorton, G., Cochran, G.V.B.: Repeatability of kinematic, kinetic, and electromyographic data in normal adult gait. J. Orthop. Res. 7, 849–860 (1989)

    Article  Google Scholar 

  40. Grieve, D.W.: Gait Patterns and the Speed of Walking. Biomed. Eng. 3, 119–122 (1968)

    Google Scholar 

  41. Kuo, A.D.: A simple model predicts the step length-speed relationship in human walking. J. Biomed. Eng. 123, 264–269 (2001)

    Google Scholar 

  42. Isakov, E., Burger, H., Krajnik, J., Grgoric, M., Marincek, C.: Influence of speed on gait parameters and on symmetry in transtibial amputees. Prosthetics Orthot. Int. 20, 153–158 (1996)

    Google Scholar 

  43. Cook, T.M., Farrell, K.P., Carey, I.A., Gibbs, l.M., Wiger, G.E.: Effects of Restricted Knee Flexion and Walking Speed on the Vertical Ground Reaction Force During Gait. J. Orthop. Sports Phys. Ther. 25(4), 236–244 (1997)

    Article  Google Scholar 

  44. Chang, H.S., Fu, M.C., Hu, J.q., Marcus, S.I.: Simulation-based Algorithms for Markov Decision Processes. Springer-Verlag, London Limited (2007)

    Book  MATH  Google Scholar 

  45. Khasraghi, M.M., Sefidkouhi, M.A.G., Valipour, M.: Simulation of open- and closed-end border irrigation systems using SIRMOD. Archives Of Agronomy And Soil Science 61(7), 929–941 (2015)

    Article  Google Scholar 

  46. Valipour, M., Sefidkouhi, M.A.G., Eslamian, S.: Surface irrigation simulation models: a review. Int. J. Hydrology Science and Technology 5(1), 51–70 (2015)

    Article  Google Scholar 

  47. Valipour, M., Banihabib, M.E., Behbahani, S.M.R.: Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir. J. Hydrol. 476(7), 433–441 (2013)

    Article  Google Scholar 

  48. Valipour, M.: Optimization of neural networks for precipitation analysis in a humid region to detect drought and wet year alarms. Meteorol. Appl. 23(1), 91–100 (2016)

    Article  Google Scholar 

  49. Valipour, M.: Sprinkle and Trickle Irrigation System Design Using Tapered Pipes for Pressure Loss Adjusting. J. Agric. Sci. 4(12), 125–133 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Robotics, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China

    Abusabah I. A. Ahmed, Hong Cheng, Zhang Liangwei, Mugahid Omer & Xichuan Lin

  2. Department of Electrical and Computer Engineering, Karary University, Khartoum, 12304, Sudan

    Abusabah I. A. Ahmed

Authors
  1. Abusabah I. A. Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hong Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhang Liangwei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mugahid Omer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xichuan Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abusabah I. A. Ahmed.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

I. A. Ahmed, A., Cheng, H., Liangwei, Z. et al. On-line Walking Speed Control in Human-Powered Exoskeleton Systems Based on Dual Reaction Force Sensors. J Intell Robot Syst 87, 59–80 (2017). https://doi.org/10.1007/s10846-017-0491-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-017-0491-z

Keywords

Search

Navigation