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http://dx.doi.org/10.15701/kcgs.2017.23.3.105

On-line Trajectory Optimization Based on Automatic Time Warping  

Han, Daseong (Handong Global University)
Noh, Junyong (KAIST)
Shin, Joseph S. (Handong Global University)
Publication Information
Journal of the Korea Computer Graphics Society / v.23, no.3, 2017 , pp. 105-113 More about this Journal
Abstract
This paper presents a novel on-line trajectory optimization framework based on automatic time warping, which performs the time warping of a reference motion while optimizing character motion control. Unlike existing physics-based character animation methods where sampling times for a reference motion are uniform or fixed during optimization in general, our method considers the change of sampling times on top of the dynamics of character motion in the same optimization, which allows the character to effectively respond to external pushes with optimal time warping. In order to do so, we formulate an optimal control problem which takes into account both the full-body dynamics and the change of sampling time for a reference motion, and present a model predictive control framework that produces an optimal control policy for character motion and sampling time by repeatedly solving the problem for a fixed-span time window while shifting it along the time axis. Our experimental results show the robustness of our framework to external perturbations and the effectiveness on rhythmic motion synthesis in accordance with a given piece of background music.
Keywords
Physics-based; Character Animation; Motion Control; Time Warping;
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