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Design and similarity evaluation on humanoid motion based on human motion capture

Published online by Cambridge University Press:  28 August 2009

Qiang Huang,
Zhangguo Yu,
Weimin Zhang,
Wei Xu and
Xuechao Chen
Qiang Huang*
Affiliation:
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, 5 Nandajie, Zhongguancun, Haidian, Beijing, China
Zhangguo Yu
Affiliation:
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, 5 Nandajie, Zhongguancun, Haidian, Beijing, China
Weimin Zhang
Affiliation:
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, 5 Nandajie, Zhongguancun, Haidian, Beijing, China
Wei Xu
Affiliation:
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, 5 Nandajie, Zhongguancun, Haidian, Beijing, China
Xuechao Chen
Affiliation:
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, 5 Nandajie, Zhongguancun, Haidian, Beijing, China
*
*Corresponding author. E-mail: qhuang@bit.edu.cn
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Summary

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This paper explores the design of humanoid complicated dynamic motion based on human motion capture. Captured human data must be adapted for the humanoid robot because its kinematics and dynamics mechanisms differ from those of the human actor. It is expected that humanoid movements are highly similar to those of the human actor. First, the kinematics constraints, including ground contact conditions, are formulated. Second, the similarity evaluation on the humanoid motion based on both the spatial and temporal factors compared with the human motion is proposed. Third, the method to obtain humanoid motion with high similarity is presented. Finally, the effectiveness of the proposed method is confirmed by simulations and experiments of our developed humanoid robot “sword” motion performance.

Keywords

Humanoid robotSimilarity evaluationMotion captureDynamic stabilityKinematics constraint

Information

Type
Article
Information
Robotica , Volume 28 , Issue 5 , September 2010, pp. 737 - 745
Copyright
Copyright © Cambridge University Press 2009

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