Human Motion Reconstruction by Direct Control of Marker Trajectories
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.
Key wordshuman motion synthesis operational space formulation task/posture decomposition prioritization marker space
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