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Optimization-based Motion Retargeting Integrating Spatial and Dynamic Constraints

Thomas Moulard 1 Eiichi Yoshida 1 Shin'Ichiro Nakaoka 2
2 Humanoid Research Group
AIST - National Institute of Advanced Industrial Science and Technology
Abstract : In this paper, we present an optimization-based retargeting method for precise reproduction of captured human motions by a humanoid robot. We take into account two important aspects of retargeting simultaneously: spatial relationship and robot dynamics model. The former takes care of the spatial relationship between the body parts based on "interaction mesh" to follow the human motion in a natural manner, whereas the latter adapts the resulting motion in such a way that the dynamic constraints such as torque limit or dynamic balance are being satisfied. We have integrated the interaction mesh and the dynamic constraints in a unified optimization framework, which is advantageous for generation of natural motions by a humanoid robot compared to previous work that performs those processes separately. We have validated the basic effectiveness of the proposed method with a sequence of postures converted from captured human data to a humanoid robot.
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https://hal.archives-ouvertes.fr/hal-00908568
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Submitted on : Monday, November 25, 2013 - 8:48:02 AM
Last modification on : Thursday, January 11, 2018 - 6:21:02 AM
Long-term archiving on: : Wednesday, February 26, 2014 - 4:23:53 AM

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Thomas Moulard, Eiichi Yoshida, Shin'Ichiro Nakaoka. Optimization-based Motion Retargeting Integrating Spatial and Dynamic Constraints. The 44th Symposium on Robotics, Oct 2013, Seoul, South Korea. ⟨hal-00908568⟩

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