Skip to main content
    • Aa
    • Aa

A uniform biped gait generator with offline optimization and online adjustable parameters

  • Lin Yang (a1), Chee-Meng Chew (a1), Teresa Zielinska (a2) and Aun-Neow Poo (a1)

This paper presents the Genetic Algorithm Optimized Fourier Series Formulation (GAOFSF) method for stable gait generation in bipedal locomotion. It uses a Truncated Fourier Series (TFS) formulation with its coefficients determined and optimized by Genetic Algorithm. The GAOFSF method can generate human-like stable gaits for walking on flat terrains as well as on slopes in a uniform way. Through the adjustment of only a single or two parameters, the step length and stride-frequency can easily be adjusted online, and slopes of different gradients are accommodated. Dynamic simulations show the robustness of the GAOFSF, with stable gaits achieved even if the step length and stride frequency are adjusted by significant amounts. With its ease of adjustments to accommodate different gait requirements, the approach lends itself readily for control of walking on a rough terrain and in the presence of external perturbations.

Corresponding author
*Corresponding author. Email:
Hide All
1.Atienza R. O. and M. Ang, Jr.A flexible control architecture for mobile robots: an application for a walking robot,” J. Intell. Robot. Syst. 30, 2948 2001.
2.Chew C. M. and Pratt G. A., “Dynamic bipedal walking assisted by learning,” Robotica 20, 477491 2002.
3.Kajita S., Matsumoto O. and Saigo M., “Real-Time 3D Walking Pattern Generation for a Biped Robot With Telescopic Legs,” Proceedings of the IEEE International Conference on Robotics and Automation, 3, 22992306, Seoul, Korea May 21–26, 2001.
4.Hirukawa H., Kajita S., Kanehiro F., Kaneko K. and Isozumi T., “The human-size humanoid robot that can walk, lie down and get up,” Int. J. Robot. Res. 24 (9), 755769 2005
5.Nakanishi J., Morimoto J., Endo G., Cheng G., Schaal S. and Kawato M., “Learning from demonstration and adaptation of biped locomotion,” Robot. Autonom. Syst. 47, 7991 2004.
6.Williamson M. M., “Neural control of rhythmic arm movements,” Neural Netw. 11, 13791394 1998.
7.Dutra M. S., Filho A. C. de P. and Romano V. F., “Modeling of a bipedal locomotor using coupled nonlinear oscillators of Van der Pol,” Biol. Cybern. 88 (4), 286292 2004.
8.Fukuoka Y., Kimura H. and Cohen A. H., “Adaptive dynamic walking of a quadruped robot on irregular terrain based on biological concepts,” Int. J. Robot. Res. 22 (3–4), 187202 Mar.–Apr. 2003.
9.Miyakoshi S., Yamakita M. and Furuta K., “Juggling Control Using Neural Oscillators,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems 1994 pp. 1186–1193.
10.Kotosaka S. and Schaal S., “Synchronized Robot Drumming by Neural Oscillator,” Journal of the Robotics Society of Japan 19 (1), 116123 2001.
11.Khoukhi A., “Neural based RSPN multi-agent strategy for biped motion control,” Robotica 19, 611617 2001.
12.Taga G., Yamaguchi Y. and Shimizu H., “Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment,” Biol. Cybern. 65, 147159 1991.
13.Matsuoka K., “Sustaned oscillations generated by mutually inhibiting neurons with adaptation,” Biol. Cybern. 52, 367376 1985.
14.Vukobratovic M., Borovac B., Surla D. and Stokic D., Biped Locomotion—Dynamics, Stability, Control and Application (Springer-Verlag, London, UK, 1990).
15.Sardain P. and Bessonnet G., “Forces acting on a biped robot. Center of pressure—zero moment point,” IEEE Trans. Syst., Man, Cybern.—part A: systems and humans 34 (5), 630637 2004.
16.Goswami A., “Postural stability of biped robots and the foot-rotation indicator (FRI) point,” Int. J. Robot. Res. 18 (6), 523533 1999.
17.Lum H. K., Zribi M. and Soh Y. C., “Planning and control of a biped robot,” Int. J. Eng. Sci. 37, 13191349 1999.
18.Chevallereau C. and Aoustin Y., “Optimal reference trajectories for walking and running of a biped robot,” Robotica 19, 557569 2001.
19.Takanishi A., Lim H., Tsuda M. and Kato I., “Realization of Dynamic Biped Walking Stabilized by Trunk Motion on a Saggitally Uneven Surface,” Proceedings of the IEEE International Workshop on Intelligent Robots and Systems, Ibaraki, Japan 1990 pp. 323–330.
20.Ogura Y. et al. , “A Novel Method of Biped Walking Pattern Generation With Predetermined Knee Joint Motion,” Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems 3, 28312836 2004.
21.Lim H.-O. and Takanishi A., “Compensatory motion control for a biped walking robot,” Robotica 23, 111 2005.
22.Michalewicz Z., “Genetic algorithms + data structures = evolution programs,” AI Series (Springer-Verlag, New York, 1994.
23.“Biomechanics of motion,” CISM Courses and Lectures 263, 79–129 1980.
24.Perry, MD J., Gait Analysis: Normal and Pathological Function (McGraw Hill, New York, 1992 pp. 556.
25.Shih C. L., “Gait synthesis for a biped robot,” Robotica 15, 599607 1997.
26.Park J. H., “Fuzzy-logic zero-moment-point trajectory generation for reduced trunk motion of biped robots,” Fuzzy Sets Syst. 134, 189203 2003.
27.Arakawa T. and Fukuda T., “Natural Motion Generation of Biped Locomotion Robot Using Hierarchical Trajectory Generation,” Proceedings of the 1997 IEEE International Conference on Robotics and Automations 1997 pp. 211–216.
28.Mu X. and Wu Q., “Synthesis of a complete sagittal gait cycle for a five-link biped robot,” Robotica 21, 581587 2003.
29.Users Guide for Yobotics! (Yobotics, Inc., Boston, MA, 2000–2003.
30.Lalash M. L., Control of Human Movement (Human Kinetics Publishers, USA, 1994.
31.Ogura Y., Aikawa H., Shimomura K., Kondo H., Morishima A., Lim H. and Takanish A., “Development of a New Humanoid Robot to Realize Various Walking Pattern Using Waist Motions,” Springer CISM Courses and Lectures: Robotic Design, Dynamics, and Control 487, 279286. Warsaw, Poland 2006.
32.Nagasaki T., Kajita S., Yokoi K., Kaneko K. and Tanie K., “Running Pattern Generation and Its Evaluation Using a Realistic Humanoid Model,” Proceedings of the 2003 IEEE International Conference on Robotics and Automation, Taipet, Taiwan 2003 pp. 14–19.
33.Poo A. N., Ang, Jr M. H., Teo C. L. and Li Q., “Performance of a neuro-model-based robot controller: adaptability and noise rejection,” Intell. Syst. Eng. 1 (1), 5062 1992.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

  • ISSN: 0263-5747
  • EISSN: 1469-8668
  • URL: /core/journals/robotica
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 0
Total number of PDF views: 17 *
Loading metrics...

Abstract views

Total abstract views: 150 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 21st October 2017. This data will be updated every 24 hours.