Skip to main content

Advertisement

Springer Nature Link
Log in

Scale Force Control of an Exoskeleton for Human Performance Augmentation

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

Abstract

Exoskeletons for human performance augmentation have been widely applied in many environments, ranging from military, industry, to construction. For load-carrying augmentation exoskeletons, one of the key issues is to control the human-robot interaction (HRI) force. This paper firstly proposes a unified framework for scale force control (SFC) of human-bearing augmentation exoskeleton (HBAE) and robot-bearing augmentation exoskeleton (RBAE). Furthermore, a mid-level SFC method was proposed, in the light of both cognitive and physical HRIs (cHRI and pHRI). On this basis, a hybrid low-level controller was designed for load-carrying exoskeletons (LCEs). Finally, the proposed method was simulated on an LCE. The simulation results demonstrate the effectiveness of our SFC approach: the pilot is always provided with an arbitrary scaled-down interaction force, regardless of the load state.

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.

Code or Data Availability

The code is available from the corresponding author on reasonable request.

References

  1. Tucker MR, Olivier J, Pagel Aet al. Control strategies for active lower extremity prosthetics and orthotics: a review. J Neuroeng Rehabiln 2015; 12(1): 1

  2. Rupal, B.S., Rafique, S., Singla, A., et al.: Lower-limb exoskeletons: research trends and regulatory guidelines in medical and non-medical applications. Int. J. Adv. Robot. Syst. 14(6), 1729881417743554 (2017)

    Article  Google Scholar 

  3. Herr, H.: Exoskeletons and orthoses: classification, design challenges and future directions. J Neuroeng Rehabil. 6(1), 21 (2009)

    Article  Google Scholar 

  4. Gilbert K and Callan P. Hardiman i prototype. General Electric Company, Schenectady, NY, GE Tech Rep S-68-1081 1968

  5. Raab, K., Krakow, K., Tripp, F., Jung, M.: Effects of training with the rewalk exoskeleton on quality of life in incomplete spinal cord injury: a single case study. Spinal Cord Series Cases. 2, 15025 (2016)

    Article  Google Scholar 

  6. Tsukahara, A., Hasegawa, Y., Eguchi, K., Sankai, Y.: Restoration of gait for spinal cord injury patients using hal with intention estimator for preferable swing speed. IEEE Trans Neural Syst Rehabil Eng. 23(2), 308–318 (2014)

    Article  Google Scholar 

  7. Baunsgaard, C.B., Nissen, U.V., Brust, A.K., et al.: Gait training after spinal cord injury: safety, feasibility and gait function following 8 weeks of training with the exoskeletons from ekso bionics. Spinal Cord. 56(2), 106–116 (2018)

    Article  Google Scholar 

  8. Zoss, A.B., Kazerooni, H., Chu, A.: Biomechanical design of the Berkeley lower extremity exoskeleton (bleex). IEEE/ASME Trans Mech. 11(2), 128–138 (2006)

    Article  Google Scholar 

  9. Yang, Z., Gu, W.: Zhang J Et al. Springer, Force control theory and method of human load carrying exoskeleton suit (2017)

    Google Scholar 

  10. Fontana, M., Vertechy, R., Marcheschi, S., Salsedo, F., Bergamasco, M.: The body extender: a full-body exoskeleton for the transport and handling of heavy loads. IEEE Robotics Auto Magaz. 21(4), 34–44 (2014)

    Article  Google Scholar 

  11. Cornwall W. In Pursuit of the Perfect Power Suit, 2015

  12. Dollar, A.M., Herr, H.: Lower extremity exoskeletons and active orthoses: challenges and state-of-the-art. IEEE Trans. Robot. 24(1), 144–158 (2008)

    Article  Google Scholar 

  13. Pons, J.L.: Wearable Robots: Biomechatronic Exoskeletons. John Wiley & Sons (2008)

    Book  Google Scholar 

  14. Lee, H.D., Lee, B.K., Kim, W.S., Han, J.S., Shin, K.S., Han, C.S.: Human–robot cooperation control based on a dynamic model of an upper limb exoskeleton for human power amplification. Mechatronics. 24(2), 168–176 (2014)

    Article  Google Scholar 

  15. Hong, M.B., Shin, Y.J., Wang, J.H.: Novel three-DOF ankle mechanism for lower-limb exoskeleton: kinematic analysis and design of passive-type ankle module. IEEE/RSJ Int Conf Intell Robots Syst. 504–509 (2014)

  16. Kim, J., Shin, M., Ahn, D.H., Son, B.J., Kim, S., Kim, D.Y., et al.: Design of a knee exoskeleton using foot pressure and knee torque sensors. Int J Adv Robot Syst. 12(2), 101–112 (2015)

    Google Scholar 

  17. Walsh, C.J., Endo, K., Herr, H.: A quasipassive leg exoskeleton for load-carrying augmentation. Int J Human Robot. 4, 487–506 (2007)

    Article  Google Scholar 

  18. Walsh, C.J., Paluska, D., Pasch, K., Grand, W., Valiente, A., Herr, H.: Development of a lightweight, underactuated exoskeleton for load-carrying augmentation. IEEE Int Conf Robot Autom. 3485–3491 (2006)

  19. Kim, H., Seo, C., Shin, Y.J., Kim, J., Kang, Y.S.: Locomotion control strategy of hydraulic lower extremity exoskeleton robot. IEEE Int Conf Advanc Intell Mechatron. 577–582 (2015)

  20. Lee, H., Lee, B., Kim, W., Han, J.: Human-robot cooperation control based on a dynamic model of an upper limb exoskeleton for human power amplification. Mechatronics. 24, 168–176 (2014)

    Article  Google Scholar 

  21. Hussain, S., Xie, S.Q., Jamwal, P.K.: Adaptive impedance control of a robotic orthosis for gait rehabilitation. IEEE Trans Syst Man Cybern Part B Cybern. 43, 1025–1034 (2013)

    Google Scholar 

  22. Koopman, B., Van Asseldonk, E.H.F., Van Der, K.H.: Selective control of gait subtasks in robotic gait training: foot clearance support in stroke survivors with a powered exoskeleton. J Neuroeng Rehabil. 10, 1–10 (2013)

    Article  Google Scholar 

  23. Al-Shuka HF and Song R. On low-level control strategies of lower extremity exoskeletons with power augmentation. In 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI). IEEE, pp. 63–68

  24. Chen, S., Chen, Z., Yao, B., Zhu, X., Zhu, S., Wang, Q., Song, Y.: Adaptive robust cascade force control of 1-dof hydraulic exoskeleton for human performance augmentation. IEEE/ASME Trans Mechatronics. 22(2), 589–600 (2016)

    Article  Google Scholar 

  25. Chen, S., Chen, Z., Yao, B.: Precision cascade force control of multi-dof hydraulic leg exoskeleton. IEEE Access. 6, 8574–8583 (2018)

    Article  Google Scholar 

  26. Li, Z., Su, C.Y., Wang, L., Chen, Z., Chai, T.: Nonlinear disturbance observerbased control design for a robotic exoskeleton incorporating fuzzy approximation. IEEE Trans. Ind. Electron. 62(9), 5763–5775 (2015)

    Article  Google Scholar 

  27. Lee, S., Sankai, Y.: Virtual impedance adjustment in unconstrained motion for an exoskeletal robot assisting the lower limb. Adv. Robot. 19(7), 773–795 (2005)

    Article  Google Scholar 

  28. Yang Z, Zhu Y, Yang X et al. Impedance control of exoskeleton suit based on adaptive rbf neural network. In 2009 International Conference on Intelligent Human-Machine Systems and Cybernetics, volume 1. IEEE, pp. 182–187

  29. Tran, H.T., Cheng, H., Rui, H., Lin, X.C., Duong, M.K., Chen, Q.M.: Evaluation of a fuzzy-based impedance control strategy on a powered lower exoskeleton. Int. J. Soc. Robot. 8(1), 103–123 (2016)

    Article  Google Scholar 

  30. Aguirre-Ollinger G, Colgate JE, Peshkin MA et al. Activeimpedance control of a lower-limb assistive exoskeleton. In 2007 IEEE 10th international conference on rehabilitation robotics. IEEE, pp. 188–195

  31. Lenzi, T., Carrozza, M.C., Agrawal, S.K.: Powered hip exoskeletons can reduce the user’s hip and ankle muscle activations during walking. IEEE Trans Neural Syst Rehab Eng. 21(6), 938–948 (2013)

    Article  Google Scholar 

  32. Boaventura T, Hammer L and Buchli J. Interaction force estimation for transparency control on wearable robots using a kalman filter. In Converging clinical and engineering research on neurorehabilitation II. Springer, 2017. pp. 489–493

  33. Masud, N., Smith, C., Isaksson, M.: Disturbance observer based dynamic load torque compensator for assistive exoskeletons. Mechatronics. 54, 78–93 (2018)

    Article  Google Scholar 

  34. Brahmi, B., Saad, M., Lam, J.T.A.T., Luna, C.O., Archambault, P.S., Rahman, M.H.: Adaptive control of a 7-dof exoskeleton robot with uncertainties on kinematics and dynamics. Eur. J. Control. 42, 77–87 (2018)

    Article  MathSciNet  Google Scholar 

  35. Ka, D.M., Hong, C., Toan, T.H., Qiu, J.: Minimizing humanexoskeleton interaction force by using global fast sliding mode control. Int. J. Control. Autom. Syst. 14(4), 1064–1073 (2016)

    Article  Google Scholar 

  36. Mao, Y., Jin, X., Dutta, G.G., et al.: Human movement training with a cable driven arm exoskeleton (carex). IEEE Trans Neural Syst Rehabil Eng. 23(1), 84–92 (2014)

    Article  Google Scholar 

  37. Beil J, Perner G and Asfour T. Design and control of the lower limb exoskeleton kit-exo-1. In 2015 IEEE International Conference on Rehabilitation Robotics (ICORR). IEEE, pp. 119–124

  38. Perry, J.C., Rosen, J., Burns, S.: Upper-limb powered exoskeleton design. IEEE/ASME Trans Mechatron. 12(4), 408–417 (2007)

    Article  Google Scholar 

  39. Rocon E, Ruiz A, Raya R et al. Human-robot physical interaction. Wearable Robots: Biomechatronic Exoskeletons 2008: 127–163

  40. Schiele, A., van der Helm, F.C.: Influence of attachment pressure and kinematic configuration on phri with wearable robots. Appl Bionics Biomech. 6(2), 157–173 (2009)

    Article  Google Scholar 

  41. Jinqing, H., Lulin, Y.: The discrete form of tracking differentiator. J Syst Sci Math Sci. 3, (1999)

  42. Seth, A., Hicks, J.L., Uchida, T.K., Habib, A., Dembia, C.L., Dunne, J.J., Ong, C.F., DeMers, M.S., Rajagopal, A., Millard, M., Hamner, S.R., Arnold, E.M., Yong, J.R., Lakshmikanth, S.K., Sherman, M.A., Ku, J.P., Delp, S.L.: Opensim: simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement. PLoS Comput. Biol. 14(7), e1006223 (2018)

    Article  Google Scholar 

  43. Anderson, F.C., Pandy, M.G.: Dynamic optimization of human walking. J. Biomech. Eng. 123(5), 381–390 (2001)

    Article  Google Scholar 

Download references

Funding

This work was supported by the National Natural Science Foundation of China (Grant number: 61903131 and 71904047) (Lin Lang, Chunbaixue Yang), and China Postdoctoral Science Foundation (Grant number: 2020 M683715) (Lin Lang).

Author information

Authors and Affiliations

  1. National University of Defense Technology, Changsha, 410072, China

    Lin Lang, Junhao Xiao, Huimin Lu & Zongtan Zhou

  2. Hunan University of Finance and Economics, Changsha, 410000, China

    Lin Lang & Chunbaixue Yang

  3. CNNP Liaoning Nuclear Power Co., Ltd., Changsha, China

    Yunshu Sun

Authors
  1. Lin Lang
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Junhao Xiao
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Yunshu Sun
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Huimin Lu
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Zongtan Zhou
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Chunbaixue Yang
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Lin Lang: Coding and writing

Junhao Xiao: Coding and writing

Yunshu Sun: English writing

Huimin Lu: Review and editing

Zongtan Zhou: Investigation, as well as review and editing

Chunbaixue Yang: Review and editing

Corresponding author

Correspondence to Junhao Xiao.

Ethics declarations

Ethics Approval

Not applicable

Consent to Participate

The authors consent to participate in this work.

Consent for Publication

The authors consent to publish this work.

Conflict of Interest

The authors declare that they have no conflicts of interest to report regarding the present study.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lang, L., Xiao, J., Sun, Y. et al. Scale Force Control of an Exoskeleton for Human Performance Augmentation. J Intell Robot Syst 106, 22 (2022). https://doi.org/10.1007/s10846-022-01611-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10846-022-01611-6

Keywords