Skip to main content
Log in

Locomotion Stability Analysis of Lower Extremity Augmentation Device

  • Published:
Journal of Bionic Engineering Aims and scope Submit manuscript

Abstract

Stability is of great significance in the theoretical framework of biped locomotion. Real-time control and walking patterns planning are on the premise that the robot works in the stable condition. In this paper, we address the crucial issue of the locomotion stability based on the modified Poincare return map and the hybrid automata. Not akin to the traditional stability criteria, i.e., the Zero Moment Point (ZMP) and the Center of Mass (CoM), the modified Poincare return map is more appropriate for both dynamic walking and non-periodic walking. Moreover, a novel high-level reinforcement learning methodology, so-called active PI2 CMA-ES, is proposed in this paper to plan the exoskeleton locomotion. The proposed learning methodology demonstrates that the locomotion of the exoskeleton is asymptotically stable according to the modified Poincare return map criterion. Finally, the proposed learning methodology is tested by the Lower Extremity Augmentation Device (LEAD) and its effectiveness is verified by the experiments.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Tsukahara A, Kawanishi R, Hasegawa Y, Sankai Y. Sit-to-stand and stand-to-sit transfer support for complete paraplegic patients with robot suit HAL. Advanced Robotics, 2010, 24, 1615–1638.

    Article  Google Scholar 

  2. Aguirre-Ollinger G, Colgate J E, Peshkin M A, Goswami A. Active-impedance control of a lower-limb assistive exoskeleton. IEEE 10th International Conference Rehabilitation Robotics, Noordwijk, Netherlands, 2007, 188–195.

  3. Wang L, Du Z, Dong W, Shen Y, Zhao G. Intrinsic sensing and evolving internal model control of compact elastic module for a lower extremity exoskeleton. Sensors, 2018, 18, 909.

    Article  Google Scholar 

  4. Tran H T, Cheng H, Duong M K, Zheng H. Fuzzy-based impedance regulation for control of the coupled human-exoskeleton system. IEEE International Conference on Robotics and Biomimetics, Bali, Indonesia, 2014, 986–992.

  5. Wang L K, Chen C F, Li Z Y, Dong W, Du Z J, Shen Y, Zhao G Y. High precision data-driven force control of compact elastic module for a lower extremity augmentation device. Journal of Bionic Engineering, 2018, 15, 805–819.

    Article  Google Scholar 

  6. Talaty M, Esquenazi A, Briceno J E. Differentiating ability in users of the ReWalk TM powered exoskeleton: An analysis of walking kinematics. IEEE International Conference on Rehabilitation Robotics, Seattle, WA, USA, 2013, 1–5.

  7. Hayashi T, Kawamoto H, Sankai Y. Control method of robot suit HAL working as operator’s muscle using biological and dynamical information. IEEE/RSJ International Conference on Intelligent Robots and Systems, Edmonton, Alta., Canada, 2005, 3063–3068.

  8. Huang L, Steger R R, Kazerooni H. Hybrid control of the berkeley lower extremity exoskeleton (BLEEX). ASME International Mechanical Engineering Congress and Exposition. Orlando, Florida, USA, 2005, 1429–1436.

  9. Kazerooni H, Racine J L, Huang L, Steger R. On the control of the berkeley lower extremity exoskeleton (BLEEX). Robotics and automation. Proceedings of the IEEE International Conference, Barcelona, Spain, 2005, 4353–4360.

  10. Long Y, Du Z J, Chen C F, Wang W D, He L, Mao X W, Xu G Q, Zhao G Y, Li X Q, Dong W. Development and analysis of an electrically actuated lower extremity assistive exoskeleton. Journal of Bionic Engineering, 2017, 14, 272–283.

    Article  Google Scholar 

  11. Wang L K, Du Z J, Dong W, Shen Y, Zhao G Y. Hierarchical human machine interaction learning for a lower extremity augmentation device. International Journal of Social Robotics, 2018, 1–17.

  12. Pransky J. The Pransky interview: Russ Angold, co-founder and president of Ekso™ Labs. Industrial Robot: An International Journal, 2014, 41, 329–334.

    Article  Google Scholar 

  13. Wehner M, Quinlivan B, Aubin P M, Martinez-Villalpando E, Baumann M, Stirling L, Walsh C. A lightweight soft exosuit for gait assistance. IEEE International Conference Robotics and Automation. Karlsruhe, Germany, 2013, 3363–3369.

  14. Vukobratović M, Borovac B. Zero-moment point–thirty five years of its life. International Journal of Humanoid Robotics, 2004, 1, 157–173.

    Article  Google Scholar 

  15. Aphiratsakun N, Chairungsarpsook K, Parnichkun M. ZMP based gait generation of AIT’s Leg Exoskeleton. The 2nd International Conference on Computer and Automation Engineering (ICCAE), Singapore, 2010, 886–890.

  16. Barbareschi G, Richards R, Thornton M, Carlson T, Holloway C. Statically vs dynamically balanced gait: Analysis of a robotic exoskeleton compared with a human. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, Italy, 2015, 6728–6731.

  17. Benbrahim H, Franklin J A. Biped dynamic walking using reinforcement learning. Robotics and Autonomous Systems, 1997, 22, 283–302.

    Article  Google Scholar 

  18. Wang L K, Du Z J, Dong W, Shen Y, Zhao G Y. Probabilistic sensitivity amplification control for lower extremity exoskeleton. Applied Sciences, 2018, 8, 525.

    Article  Google Scholar 

  19. Veneman J F. Safety standardization of wearable robots— The need for testing methods. In González-Vargas J, Ibáñez J, Contreras-Vidal J L, van der Kooij H eds., Wearable Robotics: Challenges and Trends, 2017, 189–193.

  20. Lenzi T, De Rossi S M M, Vitiello N, Carrozza M C. Intention-based EMG control for powered exoskeletons. IEEE Transactions on Biomedical Engineering, 2012, 59, 2180–2190.

    Article  Google Scholar 

  21. Ghan J, Steger R, Kazerooni H. Control and system identification for the Berkeley lower extremity exoskeleton (BLEEX). Advanced Robotics, 2006, 20, 989–1014.

    Article  Google Scholar 

  22. Jung C. Poincaré map for scattering states. Journal of Physics A: Mathematical and General, 1986, 19, 1345.

    Article  MathSciNet  MATH  Google Scholar 

  23. Uustal H. Prosthetics and orthotics. In Cooper G ed., Essential Physical Medicine and Rehabilitation, 2006, 101–118.

  24. Rose J, Gamble J G. Human Walking, 3rd ed, Lippnicott Williams & Wilkins, Philadelphia, USA, 2006.

    Google Scholar 

  25. Czerniecki J M. Rehabilitation in limb deficiency. 1. Gait and motion analysis. Archives of Physical Medicine and Rehabilitation, 1996, 77, S3–S8.

  26. Ijspeert A J, Nakanishi J, Hoffmann H, Pastor P, Schaal S. Dynamical movement primitives: Learning attractor models for motor behaviors. Neural Computation, 2013, 25, 328–373.

    Article  MathSciNet  MATH  Google Scholar 

  27. Pastor P, Kalakrishnan M, Meier F, Stulp F, Buchli J, Theodorou E, Schaal S. From dynamic movement primitives to associative skill memories. Robotics and Autonomous Systems, 2013, 61, 351–361.

    Article  Google Scholar 

  28. Bucher D, Haspel G, Golowasch J, Nadim F. Central pattern generators. eLS, 2000.

    Google Scholar 

  29. Ijspeert A J. Central pattern generators for locomotion control in animals and robots: A review. Neural Networks, 2008, 21, 642–653.

    Article  Google Scholar 

  30. Henzinger T A. The theory of hybrid automata. In Inan M K, Kurshan R P eds., Verification of Digital and Hybrid Systems, Springer, Berlin, Heidelberg, Germany, 2000, 265–292.

  31. Lygeros J, Johansson K H, Simic S N, Zhang J, Sastry S S. Dynamical properties of hybrid automata. IEEE Transactions on Automatic Control, 2003, 48, 2–17.

    Article  MathSciNet  MATH  Google Scholar 

  32. Nersesov S G, Chellaboina V, Haddad W M. A generalization of Poincaré’s theorem to hybrid and impulsive dynamical systems. American Control Conference, Anchorage, AK, USA, 2002, 1240–1245.

  33. Lyapunov A M. The general problem of the stability of motion. International Journal of Control, 1992, 55, 531–534.

    Article  MathSciNet  Google Scholar 

  34. Parks P C. AM Lyapunov’s stability theory—100 years on. IMA Journal of Mathematical Control and Information, 1992, 9, 275–303.

    Article  MathSciNet  MATH  Google Scholar 

  35. Sastry S. Nonlinear Systems: Analysis, Stability, and Control. Springer Science & Business Media, 2013.

    Google Scholar 

  36. Friedland B. Control System Design: An Introduction to State-space Methods, Dover Publications, Germany, 2012.

    MATH  Google Scholar 

  37. Slotine J J E, Li W. Applied Nonlinear Control, Pearson Education, NJ, USA, 1991.

    MATH  Google Scholar 

  38. Grizzle J W, Abba G, Plestan F. Asymptotically stable walking for biped robots: Analysis via systems with impulse effects. IEEE Transactions on Automatic Control, 2001, 46, 51–64.

    Article  MathSciNet  MATH  Google Scholar 

  39. Chevallereau C, Grizzle J W, Shih C L. Asymptotically stable walking of a five-link underactuated 3-D bipedal robot. IEEE Transactions on Robotics, 2009, 25, 37–50.

    Article  Google Scholar 

  40. Fu C, Wang J, Huang Y, Chen K. Section-map stability criterion for biped robots part I: Theory. International Conference on Mechatronics and Automation, Harbin, China, 2007, 1529–1534.

  41. Kappen H J. Path integrals and symmetry breaking for optimal control theory. Journal of Statistical Mechanics: Theory and Experiment, 2005, 11011.

  42. Theodorou E, Buchli J, Schaal S. A generalized path integral control approach to reinforcement learning. Journal of Machine Learning Research, 2010, 11, 3137–3181.

    MathSciNet  MATH  Google Scholar 

  43. Arnold D V, Hansen N. Active covariance matrix adaptation for the (1+1)-CMA-ES. Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, Portland, USA, 2010, 285–392.

  44. Arnold D V, Hansen N. A (1+1)-CMA-ES for constrained optimisation. Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, Philadelphia, USA, 2012, 297–304.

  45. Hansen N. The CMA evolution strategy: A tutorial. arXiv preprint arXiv:1604.00772, 2016, 2005, 1–39.

    Google Scholar 

Download references

Acknowledgement

Part of this work was supported by the National Science Foundation of China under Grant No. 51521003.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yi Shen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, L., Chen, C., Dong, W. et al. Locomotion Stability Analysis of Lower Extremity Augmentation Device. J Bionic Eng 16, 99–114 (2019). https://doi.org/10.1007/s42235-019-0010-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42235-019-0010-y

Keywords

Navigation