Hostname: page-component-6898cfcb55-zkb6p Total loading time: 0 Render date: 2026-11-11T08:17:56.016Z Has data issue: false hasContentIssue false
  • English
  • Français

A force-resisting balance control strategy for a walking biped robot under an unknown, continuous force

Published online by Cambridge University Press:  03 December 2014

Yeoun-Jae Kim,
Joon-Yong Lee and
Ju-Jang Lee
Yeoun-Jae Kim
Affiliation:
Robotics Program, Korea Advanced Science and Technology, Euseong-Gu Daehak-Ro 291, Daejeon, Korea. E-mail: lethkim@kaist.ac.kr
Joon-Yong Lee*
Affiliation:
Department of Genetics Development and Cell Biology, Iowa State University, Ames, Iowa 50011, USA
Ju-Jang Lee
Affiliation:
Electrical Engineering, Korea Advanced Science and Technology, Euseong-Gu Daehak-Ro 291, Daejeon, Korea. E-mail: jjlee@ee.kaist.ac.kr
*
*Corresponding author. E-mail: junyoni@gmail.com
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.

In this paper, we propose and examine a force-resisting balance control strategy for a walking biped robot under the application of a sudden unknown, continuous force. We assume that the external force is acting on the pelvis of a walking biped robot and that the external force in the z-direction is negligible compared to the external forces in the x- and y-directions. The main control strategy involves moving the zero moment point (ZMP) of the walking robot to the center of the robot's sole resisting the externally applied force. This strategy is divided into three steps. The first step is to detect an abnormal situation in which an unknown continuous force is applied by examining the position of the ZMP. The second step is to move the ZMP of the robot to the center of the sole resisting the external force. The third step is to have the biped robot convert from single support phase (SSP) to double support phase (DSP) for an increased force-resisting capability. Computer simulations and experiments of the proposed methods are performed to benchmark the suggested control strategy.

Keywords

Biped robotInverted pendulum modelBalance controlContinuous force

Information

Type
Articles
Information
Robotica , Volume 34 , Issue 7 , July 2016, pp. 1495 - 1516
Copyright
Copyright © Cambridge University Press 2014 

References

1.Vukobratovic, M. and Borovac, B., “Zero moment point: Thirty five years of its life,” Int. J. Humanoid Robot 1 (1), 157–173 (2004).CrossRefGoogle Scholar
2.McGeer, T., “Passive dynamic walking,” Int. J. Robot. Res. 9 (2), 62–82 (1990).Google Scholar
3.Geng, T. and Gan, J. Q., “Planar biped walking with an equilibrium point controller and state machines,” IEEE/ASME Trans. Mechatronics 15 (2), 253–260 (2010).CrossRefGoogle Scholar
4.Berenguer, F. J. and Monasterio-Huelin, F. M., “Zappa, a quasi-passive biped walking robot with a tail: Modeling, behavior, and kinematic estimation using accelerometers,” IEEE Trans. Indust. Electron. 55 (9), 3281–3289 (2010).Google Scholar
5.Sato, T., Sakaino, S. and Ohnishi, K., “Real-time walking trajectory generation method with three-mass models at constant body height for three-dimensional biped robots,” IEEE Trans. Indust. Electron. 58 (2), 376–383 (2011).Google Scholar
6.Goswami, D. and Vadakkepat, P., “Planar bipedal jumping gaits with stable landing,” IEEE Trans. Robot. 25 (5), 1030–1046 (2009).CrossRefGoogle Scholar
7.Kajita, S., Nagasaki, T., Kaneko, K. and Hirukawa, H., “ZMP-based biped running control,” IEEE Robot. Autom. Mag. 14 (2), 63–72 (2007).Google Scholar
8.Huang, Q.et al., “Balance Control of a Biped Robot Combining Off-line Pattern with Real-time Modification,” Proceedings of the 2000 IEEE International Conference on Robotics and Automation (2000) pp. 3346–3352.Google Scholar
9.Hemani, H. and Camana, P., “Nonlinear feedback in simple locomotion systems,” IEEE Trans. Autom. Control 21 (6), 855–860 (1976).Google Scholar
10.Horak, F. and Nashner, L., “Central programming of postural movements: Adaptation to altered support-surface configurations,” J. Neurophysiol. 55 (6), 1369–1381 (1986).Google Scholar
11.Nenchev, D. N. and Nishio, A., “Ankle and hip strategies for balance recovery of a biped subjected to an impact,” Robotica 26 (5), 643–653 (2008).Google Scholar
12.Stephens, B., “Integral Control of Humanoid Balance,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2007) pp. 4020–4027.Google Scholar
13.Goddard, R., Hemami, H. and Weimer, F., “Biped side step in the frontal plane,” IEEE Trans. Autom. Control 28 (2), 179–187 (1983).Google Scholar
14.Winter, D., “Human balance and posture control during standing and walking,” Gait Posture 3 (4), 193–214 (1995).CrossRefGoogle Scholar
15.Deng-Peng, X. and Xu, L., “Multiple balance strategies for humanoid standing control,” Acta Autom. Sin. 37 (2), 228–233 (2011).Google Scholar
16.Stephens, B., “Humanoid Push Recovery,” Proceedings of the 7th IEEE-RAS International Conference on Humanoid Robots (2007) pp. 589–595.Google Scholar
17.Pratt, J. E., Carff, J., Drakunov, S. and Goswami, A., “Capture Point: A Step Toward Humanoid Push Recovery,” Proceedings of the IEEE-RAS International Conference on Humanoid Robots (2006) pp. 200–207.Google Scholar
18.Motoi, N., Ikebe, M. and Ohnishi, K., “Real-time gait planning for pushing motion of humanoid robot,” IEEE Trans. Indust. Inform. 3 (2), 154–163 (2007).Google Scholar
19.Harada, K., Kajita, S., Kanehiro, F., Fujiwara, K., Kaneko, K., Yokoi, K. and Hirukawa, H., “Walking motion for pushing manipulation by a humanoid robot,” J. Robot. Soc. Japan. 22 (3), 392–399 (2004).Google Scholar
20.Komura, T., Leung, H., Kudoh, S. and Kuffner, J., “A Feedback Controller for Biped Humanoids that can Counteract Large Perturbation during Gait,” Proceedings of the 2005 IEEE International Conference Robotics and Automation (ICRA) (2005) pp. 1989–1995.Google Scholar
21.Yasin, A., Huang, Q., Xu, Q. and Ahang, W., “Biped Robot Push Detection and Recovery,” Proceedings of the IEEE International Conference on Information and Automation (2012) pp. 993–998.Google Scholar
22.Yi, S. J., Zhang, B. T., Hong, D. and Lee, D. D., “Learning Full Body Push Recovery Control for Small Humanoid Robots,” Proceedings of the IEEE International Conference on Robotics and Automation (2011) pp. 2047–2052.Google Scholar
23.Yi, S. J., Zhang, B. T., Hong, D. and Lee, D. D., “Online Learning of a Full Body Push Recovery Controller for Omnidirectional Walking,” Proceedings of the 11th IEEE-RAS International Conference on Humanoid Robots (2011) pp. 1–6.Google Scholar
24.Li, T. S., Su, Y. T., Liu, S. H., Hu, J. J. and Chen, C. C., “Dynamic balance control for biped robot walking using sensor fusion, Kalman Filter, and Fuzzy logic,” IEEE Trans. Indust. Electron. 59 (11), 4394–4408 (2012).Google Scholar
25.Kim, Y. J., Lee, J. Y. and Lee, J. J., “A Balance Control Strategy of A Walking Biped Robot in An Externally Applied Force,” Proceeding of the IEEE International Conference on Information and Automation (2012) pp. 572–577.Google Scholar
26.Demura, K., “practice! easy! robot simulation,” Morikita 2007.Google Scholar
27.Kim, Y. J., Lee, J. Y. and Lee, J. J., “Bipedal Walking Trajectory Generation Using Tchebychev Method,” Proceedings of the International Conference on Mechatronics and Informatics (2011) pp. 34–42.Google Scholar
28.Kajita, S., Kanehiko, F., Kaneko, K., Yokoi, K. and Hirukawa, H., “The 3D Linear Inverted Pendulum Mode: A Simple Modeling for a Biped Walking Pattern Generation,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (2001) pp. 239–246.Google Scholar
29.Sugihara, T. and Nakamura, Y., “Whole-body Cooperative Balancing of Humanoid Robot Using COG Jacobian,” Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems (2002) pp. 2575–2580.Google Scholar