Hostname: page-component-7b7567c8c-2rsb6 Total loading time: 0 Render date: 2026-11-12T19:50:06.281Z Has data issue: false hasContentIssue false
  • English
  • Français

A walking control strategy combining global sensory reflex and leg synchronization

Published online by Cambridge University Press:  31 July 2014

Chenglong Fu,
Jianmei Wang,
Ken Chen,
Zhangguo Yu and
Qiang Huang
Chenglong Fu*
Affiliation:
State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, ChinaDepartment of Mechanical Engineering, Tsinghua University, Beijing 100084, China
Jianmei Wang
Affiliation:
State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
Ken Chen
Affiliation:
State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, ChinaDepartment of Mechanical Engineering, Tsinghua University, Beijing 100084, China
Zhangguo Yu
Affiliation:
Key Laboratory of Biomimetic Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
Qiang Huang
Affiliation:
Key Laboratory of Biomimetic Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
*
*Corresponding author. E-mail: fcl@tsinghua.edu.cn
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

Biped walking can be regarded as a global limit cycle whose stability is difficult to verify by only local sensory feedback. This paper presents a control strategy combining global sensory reflex and leg synchronization. The inverted pendulum angle is utilized as global motion feedback to ensure global stability, and joint synchronization between legs is designed to stabilize bifurcations. The proposed strategy can achieve a stable gait and stabilize bifurcations. The robustness of this approach was evaluated against external disturbances. Walking experiments of a biped actuated by pneumatic muscles were conducted to confirm the validity of the proposed method. Instead of tracking predetermined trajectories, this method uses sensory reflexes to activate motor neurons and coincides with the biological idea wherein inessential degrees-of-freedom are barely controlled rather than strictly controlled.

Keywords

Biped locomotionWalking controlGlobal sensory reflexLeg synchronization

Information

Type
Articles
Information
Robotica , Volume 34 , Issue 5: RAAD , May 2016, pp. 973 - 994
Copyright
Copyright © Cambridge University Press 2014 

References

1.Lim, H., Yamamoto, Y. and Takanishi, A., “Control to Realize Human-Like Walking of a Biped Humanoid Robot,” Proceedings of the IEEE Conference on System, Man and Cybernetics, Nashville, TN, USA (Oct. 2000) pp. 3271–3276.Google Scholar
2.Fu, C. and Chen, K., “Gait synthesis and sensory control of stair climbing for a humanoid robot,” IEEE Trans. Ind. Electron. 55 (5), 2111–2120 (2008).Google Scholar
3.Reichert, H., Neurobiologie (Thieme Georg Verlag, Stuttgart, Germany, 2000).Google Scholar
4.Matsuoka, K., “Sustained oscillations generated by mutually inhibiting neurons with adaption,” Biol. Cybern. 52 (6), 367–376 (1985).Google Scholar
5.Taga, G., Yamaguchi, Y. and Shimizu, H., “Self-organized control in bipedal locomotion by neural oscillators in unpredictable environment,” Biol. Cybern. 65, 147–159 (1991).CrossRefGoogle ScholarPubMed
6.Righetti, L. and Ijspeert, A. J., “Programmable Central Pattern Generators: An Application to Biped Locomotion Control,” Proceedings of the IEEE Conference on Robotics Automation, Orlando, FL, USA (May 2006), pp. 1585–1590.Google Scholar
7.Fu, C., Tan, F. and Chen, K., “A simple walking strategy for biped walking based on an intermittent sinusoidal oscillator,” Robotica 28 (6), 869–884 (2010).CrossRefGoogle Scholar
8.Clarac, F., Cattaert, D. and Ray, D. L., “Central control components of a ‘simple’ stretch reflex,” Trends Neurosci. 23 (5), 199–208 (2000).Google Scholar
9.Cruse, H. and Warnecke, H., “Coordination of the legs of a slow-walking cat,” Exp. Brain Res. 89 (1), 147–156 (1992).Google Scholar
10.Cruse, H., Kindermann, T. and Schumm, M., “Walknet – a biologically inspired network to control six-legged walking,” Neural Netw. 11 (7), 1435–1447 (1998).Google Scholar
11.Zaier, R. and Nagashima, F., “Motion Pattern Generator and Reflex System for Humanoid Robots,” Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, Beijing, China (Oct. 2006), pp. 840–845.Google Scholar
12.Boone, G. and Hodgins, J., “Slipping and tripping reflexes for bipedal robots,” Auton. Robots 4 (3), 259–271 (1997).Google Scholar
13.Funabashi, H., Takeda, Y., Itoh, S. and Higuchi, M., “Disturbance compensating control of a biped walking machine based on reflex motions,” JSME Int. J. 44 (3), 724–730 (2001).Google Scholar
14.Geng, T., Porr, B. and Worgotter, F., “Fast biped walking with a sensor-driven neuronal controller and real-time online learning,” Int. J. Robot. Res. 25 (3), 243–259 (2006).CrossRefGoogle Scholar
15.Manoonpong, P., Geng, T., Kulvicius, T., Porr, B. and Worgotter, F., “Adaptive, fast walking in a biped robot under neuronal control and learning,” PLos Comput. Biol. 3 (7), 1305–1320 (2007).Google Scholar
16.Grizzle, J. W., Abba, G. and Plestan, F., “Asymptotically stable walking for biped robots: Analysis via systems with impulse effects,” IEEE Trans. Autom. Control 46 (1), 51–64 (2001).Google Scholar
17.Westervelt, E. R., Buche, G. and Grizzle, J. W., “Experimental validation of a framework for the design of controllers that induce stable walking in planar bipeds,” Int. J. Robot. Res. 23 (6), 1–24 (2004).CrossRefGoogle Scholar
18.Harata, Y., Asano, F., Taji, K. and Uno, Y., “Parametric excitation-based inverse bending gait generation,” Robotica 29 (6), 831–841 (2011).Google Scholar
19.Harata, Y., Asano, F., Luo, Z.-W., Taji, K. and Uno, Y., “Biped gait generation based on parametric excitation by knee-joint actuation,” Robotica 27 (6), 1063–1073 (2009).CrossRefGoogle Scholar
20.Hurmuzlu, Y. and Marghitu, D. B., “Rigid body collisions of planar kinematic chains with multiple contact points,” Int. J. Robot. Res. 13 (1), 82–92 (1994).Google Scholar
21.McGeer, T., “Passive Walking with Knees,” Proceedings of the IEEE Conference on Robotics and Automation, Cincinnati, OH, USA (May 1990), pp. 1640–1645.Google Scholar
22.Collins, S. H., Wisse, M. and Ruina, A., “A three-dimensional passive-dynamic walking robot with two legs and knees,” Int. J. Robot. Res. 20 (2), 607–615 (2001).Google Scholar
23.Sinnet, R. W. and Ames, A. D., “2D Bipedal Walking with Knees and Feet: A Hybrid Control Approach,” Proceedings of the IEEE Conference on Decision and Control, Shanghai, China (Dec. 2009), pp. 3200–3207.Google Scholar
24.Ono, K., Furuichi, T. and Takahashi, R., “Self-excited walking of a biped mechanism with feet,” Int. J. Robot. Res. 23 (1), 55–68 (2004).Google Scholar
25.Thuilot, B., Goswami, A. and Espiau, B., “Bifurcation and Chaos in a Simple Passive Bipedal Gait,” Proceedings of the IEEE Conference on Robotics Automation, Albuquerque, NM, USA (Apr. 1997), pp. 792–798.Google Scholar
26.Wisse, M., Schwab, A. L., vd Linde, R. Q. and vd Helm, F. C. T., “How to keep from falling forward: Elementary swing leg action for passive dynamic walkers,” IEEE Trans. Robot. 21 (3), 393–401 (2005).CrossRefGoogle Scholar
27.McGeer, T., “Passive dynamic walking,” Int. J. Robot. Res. 9 (2), 62–82 (1990).Google Scholar
28.Wadden, T. and Ekeberg, O., “A neuro-mechanical model of legged locomotion: Single leg control,” Biol. Cybern. 79 (2), 161–173 (1998).Google Scholar
29.Fu, C., Shuai, M., Huang, Y., Wang, J. and Chen, K., “Parametric Walking Patterns and Optimum Atlases for Underactuated Biped Robots,” Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, Beijing, China (Oct. 2006), pp. 342–347.Google Scholar