Abstract
Understanding the basis of human movement and reproducing it in robotic environments is a compelling challenge that has engaged a multidisciplinary audience. In addressing this challenge, an important initial step involves reconstructing motion from experimental motion capture data. To this end we propose a new algorithm to reconstruct human motion from motion capture data through direct control of captured marker trajectories. This algorithm is based on a task/posture decomposition and prioritized control approach. This approach ensures smooth tracking of desired marker trajectories as well as the extraction of joint angles in real-time without the need for inverse kinematics. It also provides flexibility over traditional inverse kinematic approaches. Our algorithm was validated on a sequence of tai chi motions. The results demonstrate the efficacy of the direct marker control approach for motion reconstruction from experimental marker data.
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Demircan, E., Sentis, L., De Sapio, V., Khatib, O. (2008). Human Motion Reconstruction by Direct Control of Marker Trajectories. In: Lenarčič, J., Wenger, P. (eds) Advances in Robot Kinematics: Analysis and Design. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8600-7_28
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DOI: https://doi.org/10.1007/978-1-4020-8600-7_28
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-8599-4
Online ISBN: 978-1-4020-8600-7
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