2012
RSS
RSS 2012
Affine trajectory deformation for redundant manipulators
Abstract
We propose a new method to smoothly deform trajectories of redundant manipulators in order to deal with unforeseen perturbations or to retarget captured motions into new environments. This method is based on the recently-developed affine deformation framework, which offers such advantages as closed-form solutions, one-step computation and no trajectory re-integration. Satisfaction of inequality constraints and dynamics optimization are seamlessly integrated into the framework. Applications of the method to interactive motion editing and motion transfer to humanoid robots are presented. Building on these developments, we offer a brief discussion of the concept of redundancy from the viewpoint of group theory.
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Interdisciplinary Bridge
— Computer Science and Mathematics & Optimization
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Keyword Pioneer
— motion retargeting
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio