Skip to main content
SpringerLink
Log in

Virtual model control of lower extremity exoskeleton for load carriage inspired by human behavior

  • Published:
Autonomous Robots Aims and scope Submit manuscript

Abstract

The most significant feature of the exoskeleton system, which distinguishes it from other robotic systems, is the symbiotic relationship between the exoskeleton and the wearer. For perfect symbiotic relationship, the exoskeleton should be able to exactly detect the wearer’s intention to move. Existing methods by which lower extremity exoskeletons can detect human intentions are highly dependent on additional sensor systems or accurate dynamic models. In this paper, we propose a novel method for detecting human intention inspired by human behavior, and a control method that utilizes it. We define human intention as the tendency of humans to maintain a statically stable posture and minimize joint torques when supporting payloads. The control method reduces the computational requirements and simplifies the exoskeleton sensor system compared to existing methods. The experimentally measured ground reaction force was used to indirectly estimate the effects of our method on the wearer. The results suggest that the proposed method reduces the load acting on the wearer during locomotion under loaded conditions, and results in a portion of his body weight being supported by the exoskeleton when he is in an uncomfortable position.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Aguirre-Ollinger, G., Colgate, J. E., Peshkin, M. A., & Goswami, A. (2011). Design of an active one-degree-of-freedom lower-limb exoskeleton with inertia compensation. International Journal of Robotics Research, 30(4), 486–499.

    Google Scholar 

  • Browning, R. C., Modica, J. R., Kram, R., & Goswami, A. (2007). The effects of adding mass to the legs on the energetics and biomechanics of walking. Medicine & Science in Sports & Exercise, 39(3), 515–525.

    Article  Google Scholar 

  • Chiu, S. L. (1988). Task compatibility of manipulator postures. International Journal of Robotics Research, 7(5), 13–21.

    Article  Google Scholar 

  • Cram, J. R., & Kasman, G. S. (2010). The basics of surface electromyography. In E. Criswell (Ed.), Cram’s introduction to surface electromyography (2nd ed.). London: Jones & Bartlett Publishers.

    Google Scholar 

  • Dollar, A., & Herr, H. (2008). Lower extremity exoskeletons and active orthoses: Challenges and state-of-the-art. IEEE Transactions on Robotics, 24(1), 144–158.

    Article  Google Scholar 

  • Donelan, J. M., Kram, R., & Kuo, A. D. (2001). Mechanical and metabolic determinants of the preferred step width in human walking. Proceedings of the Royal Society of London Series B: Biological Sciences, 268(1480), 1985–1992.

    Article  Google Scholar 

  • Donelan, J. M., Kram, R., & Kuo, A. D. (2002). Mechanical work for step-to-step transitions is a major determinant of the metabolic cost of human walking. Journal of Experimental Biology, 205(23), 3717–3727.

    Google Scholar 

  • Geyer, H., Seyfarth, A., & Blickhan, R. (2006). Compliant leg behaviour explains basic dynamics of walking and running. Proceedings of the Royal Society of London Series B: Biological Sciences, 273(1603), 2861–2867.

    Article  Google Scholar 

  • Gottschall, J. S., & Kram, R. (2005). Energy cost and muscular activity required for leg swing during walking. Journal of Applied Physiology, 99(1), 23–30.

    Article  Google Scholar 

  • Grabowski, A., Farley, C. T., & Kram, R. (2005). Independent metabolic costs of supporting body weight and accelerating body mass during walking. Journal of Applied Physiology, 98(2), 579–583.

    Article  Google Scholar 

  • Grabowski, A. M. (2010). Metabolic and biomechanical effects of velocity and weight support using a lower-body positive pressure device during walking. Archives of Physical Medicine and Rehabilitation, 91(6), 951–957.

    Article  Google Scholar 

  • Guizzo, E., & Goldstein, H. (2005). The rise of the body bots. IEEE Spectrum, 42(10), 50–56.

    Article  Google Scholar 

  • Hayashi, T., Kawamoto, H., & Sankai, Y. (2005). Control method of robot suit hal working as operator’s muscle using biological and dynamical information. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 3063–3068).

  • He, H., & Kiguchi, K. (2007). A study on emg-based control of exoskeleton robots for human lower-limb motion assist. Proceedings of the International Special Topic Conference on Information Technology Application in Biomedicine (pp. 292–295).

  • Kawamoto, H., Kanbe, S., & Sankai, Y. (2003a). Power assist method for hal-3 estimating operator’s intention based on motion information. Proceedings of the IEEE International Workshop on Robot and Human Interactive Communication (pp. 67–72).

  • Kawamoto, H., Lee, S., Kanbe, S., & Sankai, Y. (2003b). Power assist method for hal-3 using emg-based feedback controller. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (pp. 1648–1653).

  • Kazerooni, H., Racine, J., Huang, L., & Steger, R. (2005). On the control of the berkeley lower extremity exoskeleton (bleex). Proceedings of the IEEE International Conference on Robotics and Automation (pp. 4353–4360).

  • Kazerooni, H., Steger, R., & Huang, L. (2006). Hybrid control of the berkeley lower extremity exoskeleton (bleex). International Journal of Robotics Research, 25(5–6), 561–573.

    Article  Google Scholar 

  • Kuo, A. D. (2007). The six determinants of gait and the inverted pendulum analogy: A dynamic walking perspective. Human Movement Science, 26(4), 617–656.

    Article  Google Scholar 

  • Lee, J., Kim, H., Jang, J., & Park, S. (2012). Development of semi-active hydraulic system and its application to human assist devices. Proceedings of the International Symposium on Robotics (pp. 1082–1087).

  • Low, K., Liu, X., Yu, H. (2005). Development of ntu wearable exoskeleton system for assistive technologies. Proceedings of the IEEE International Conference on Mechatronics and Automation (pp. 1099–1106).

  • Neptune, R., Zajac, F., & Kautz, S. (2004a). Muscle force redistributes segmental power for body progression during walking. Gait & Posture, 19(2), 194–205.

    Article  Google Scholar 

  • Neptune, R. R., Zajac, F. E., & Kautz, S. A. (2004b). Muscle mechanical work requirements during normal walking: The energetic cost of raising the body’s center-of-mass is significant. Journal of Biomechanics, 37(6), 817–825.

    Article  Google Scholar 

  • Park, S. J., Park, S. C., Kim, J. H., & Kim, C. B. (1999). Biomechanical parameters on body segments of Korean adults. International Journal of Industrial Ergonomics, 23(1), 23–31.

    Article  Google Scholar 

  • Royer, T. D., Martin, P. E., et al. (2005). Manipulations of leg mass and moment of inertia: Effects on energy cost of walking. Medicine & Science in Sports & Exercise, 37(4), 649–656.

    Article  Google Scholar 

  • Shih, C. L. (1996). The dynamics and control of a biped walking robot with seven degrees of freedom. Journal of Dynamic Systems, Measurement, and Control, 118(4), 683–690.

    Article  MATH  Google Scholar 

  • Soule, R. G., & Goldman, R. F. (1969). Energy cost of loads carried on the head, hands, or feet. Journal of Applied Physiology, 27(5), 687–690.

    Google Scholar 

  • Soule, R. G., Pandolf, K. B., & Goldman, R. F. (1978). Energy expenditure of heavy load carriage. Ergonomics, 21(5), 373–381.

    Article  Google Scholar 

  • Umberger, B. R. (2010). Stance and swing phase costs in human walking. Journal of The Royal Society Interface, 7(50), 1329–1340.

    Article  Google Scholar 

  • Walsh, C., Pasch, K., Herr, H. (2006). An autonomous, underactuated exoskeleton for load-carrying augmentation. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1410–1415).

  • Walsh, C., Endo, K., & Herr, H. (2007). A quasi-passive leg exoskeleton for load-carrying augmentation. International Journal of Humanoid Robotics, 4(3), 487–506.

    Article  Google Scholar 

  • Whittle, M. W. (2007). Gait analysis: An introduction (4th ed.). Oxford: Butterworth-Heinemann.

    Google Scholar 

  • Zarrugh, M., & Radcliffe, C. (1978). Predicting metabolic cost of level walking. European Journal of Applied Physiology and Occupational Physiology, 38(3), 215–223.

    Article  Google Scholar 

Download references

Acknowledgments

This work was partially supported by the Industrial Strategic technology development program (No. 10035431, Development of Wearable Robot for Industrial Labor Support) funded by the Ministry of Trade, Industry and Energy (MI, Korea) and partially supported by the Ministry of Knowledge Economy (MKE, Korea), under the Advanced Robot Manipulation Research Center support program supervised by National IT Industry Promotion Agency (NIPA), NIPA-2013-H1502-13-1001.

Author information

Authors and Affiliations

  1. Department of Intelligent Robot Engineering, University of Science and Technology (UST), Ansan, Gyeonggi-do, Republic of Korea

    Jong-won Lee

  2. Advanced Robotics Laboratory, Department of Mechatronics Engineering, Hanyang University, Ansan, Gyeonggi-do, Republic of Korea

    Hyogon Kim

  3. Robotics R&BD Group, Korea Institute of Industrial Technology (KITECH), Ansan, Gyeonggi-do, Republic of Korea

    Jaeho Jang & Sangdeok Park

Authors
  1. Jong-won Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hyogon Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaeho Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sangdeok Park
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sangdeok Park.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, Jw., Kim, H., Jang, J. et al. Virtual model control of lower extremity exoskeleton for load carriage inspired by human behavior. Auton Robot 38, 211–223 (2015). https://doi.org/10.1007/s10514-014-9404-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10514-014-9404-1

Keywords

Search

Navigation