Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31106
Lower energy Gait Pattern Generation in 5-Link Biped Robot Using Image Processing

Authors: Byounghyun Kim, Youngjoon Han, Hernsoo Hahn


The purpose of this study is to find natural gait of biped robot such as human being by analyzing the COG (Center Of Gravity) trajectory of human being's gait. It is discovered that human beings gait naturally maintain the stability and use the minimum energy. This paper intends to find the natural gait pattern of biped robot using the minimum energy as well as maintaining the stability by analyzing the human's gait pattern that is measured from gait image on the sagittal plane and COG trajectory on the frontal plane. It is not possible to apply the torques of human's articulation to those of biped robot's because they have different degrees of freedom. Nonetheless, human and 5-link biped robots are similar in kinematics. For this, we generate gait pattern of the 5-link biped robot by using the GA algorithm of adaptation gait pattern which utilize the human's ZMP (Zero Moment Point) and torque of all articulation that are measured from human's gait pattern. The algorithm proposed creates biped robot's fluent gait pattern as that of human being's and to minimize energy consumption because the gait pattern of the 5-link biped robot model is modeled after consideration about the torque of human's each articulation on the sagittal plane and ZMP trajectory on the frontal plane. This paper demonstrate that the algorithm proposed is superior by evaluating 2 kinds of the 5-link biped robot applied to each gait patterns generated both in the general way using inverse kinematics and in the special way in which by considering visuality and efficiency.

Keywords: gait pattern, COG (Center OfGravity), ZMP (Zero Moment Point)

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1616


[1] L. Magdalena, "Learning Gait Patterns for the Fuzzy Synthesis of Biped Walk," IEEE IFCIS, pp.248-250, 1994.
[2] Q. Huang, "Planning Walking Patterns for a Biped Robot," IEEE ICRA Vol. 17, pp. 280-289, 2001.
[3] L. Endo, "Co-evolution of Morphology and Walking Pattern of Biped Humanoid Robot using Evolutionary Computation-Evolutionary Designing Method and its Evaluation," IEEE IROS, Vol. 1, pp. 340-345, 2003.
[4] M. Vukobratobic and D. Juricic, "Contribution to the Synthesis of Biped Gait," IEEE Trans. Bio-Med. Eng, Vol. 1, pp. 1-6, 1996.
[5] S. Kajita, F. Kanehiro, K. Kaneko, k. Yokoi and H. Hirukawa, "The 3D Linear Inverted Pendulum Mode : A simple modeling for a biped walking pattern generation," Proc. of the 2001 IEEE/RSJ, Vol. 1, pp. 239-246, 2001.
[6] Q. Huang, K. Shuuji, N. Koyachi, K. Kaneko, K. Yokoi, H. Arai, K. Komoriya and K. Tanie, "A High Stability, Smooth Walking pattern for a Biped Robot," IEEE ICRA, pp. 65-71, 1999.
[7] Arbulu, "ZMP Human Measure System," IEEE Climbing-Walking Robots, pp. 433-440, 2006.
[8] M. Morisawa, S. kajita, K. Kaneko and K. Harada, "Pattern Generation of Biped Walking Constrained on Parametric Surface," IEEE ICRA, pp. 2405-2410, 2005.
[9] Y. Hasegawa, "Trajectory Generation for Biped Locomotion Robot," Mechatronics, Vol. 10, pp. 67-89, 2000.
[10] A. Borghese, L. Bianchi and F. Lacquaniti, "Kinematic determinants of Human Locomotion," Journal of Physiology, pp. 863-879, 1996.
[11] Xiuping Mu and Qiong Wu, "A Complete dynamics model of five-link bipedal walking," Proceeding of american control Conference, pp. 4926-4931, 2003.
[12] Xiuping Mu and Qiong Wu, "Development of a complete dynamic model of a planar five-link biped and sliding mode control of its locomotion during the double support phase," Int. Journal of control, Vol. 77, no. 8, pp. 789-799, 2004.
[13] S. Kajita and K. Tani, "Study of Dynamic Biped Locomotion on Rugged Terrain," ICAR, Vol. 1, pp.741-746, 1991.