NDLI: The Use of BSN for Whole Body Motion Training for a Humanoid Robot

Content Provider	IEEE Xplore Digital Library
Author	Teachasrisaksakul, K. Zhiqiang Zhang Guang-Zhong Yang
Copyright Year	2014
Description	Author affiliation: Hamlyn Centre, Imperial Coll. London, London, UK (Teachasrisaksakul, K.; Zhiqiang Zhang; Guang-Zhong Yang)
Abstract	Sensor based motion capture system enables motion analysis with applications ranging from entertainment, healthcare and robotics. It can provide an intuitive interface for human to provide motion training and control a humanoid robot. In this paper, we propose a novel framework for the imitation of human motion for a humanoid robot. In the proposed framework, human motion data is directly captured from a wireless, wearable motion capture platform (Biomotion+). The reconstructed posture is then converted into joint angle trajectories. Due to the structural differences between the joints of the robot and those of the human, the trajectories are then optimized to satisfy the mechanical constraints of the robot and to maintain appropriate balance. To validate the proposed framework, different motion trajectories were verified. The results demonstrate the stability and effectiveness of the proposed framework to reproduce realistic human motion for a humanoid robot and the potential for a tele-rehabilitation application. The proposed framework offers a new way of imitating human motion for a humanoid robot.
Starting Page	45
Ending Page	51
File Size	448833
Page Count	7
File Format	PDF
e-ISBN	9781479949595
DOI	10.1109/BSN.2014.12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-16
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Humanoid robots Trajectory Joints Optimization Foot
Content Type	Text
Resource Type	Article

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