Task-driven Posture Optimization for Virtual Characters
Mingxing Liu, Alain Micaelli, Paul Evrard, Adrien Escande
Symposium on Computer Animation, July 2012, pp. 155--164.
Abstract: This paper presents a generic approach to find optimal postures, including contact positions, for manipulation tasks. It can be used in either the preparation for a task, or the evaluation of the feasibility of a task during planning stages. With such an approach, an animator can control a virtual character from a high level by just specifying a task, such as moving an object along a desired path to a desired position; the animator does not need to manually find suitable postures for the task. For each task, an optimization problem is solved, which considers not only geometric and kinematic constraints, but also force and moment constraints. The optimized postures allow the virtual character to apply manipulation forces as strongly as possible, and meanwhile to avoid foot slipping. Moreover, potential perturbation forces can be taken into account in the optimization to make postures more robust. The realism of our approach is demonstrated with different types of manipulation tasks.
Article URL: http://dx.doi.org/10.2312/SCA/SCA12/155-164
BibTeX format:
@inproceedings{Liu:2012:TPO,
  author = {Mingxing Liu and Alain Micaelli and Paul Evrard and Adrien Escande},
  title = {Task-driven Posture Optimization for Virtual Characters},
  booktitle = {Symposium on Computer Animation},
  pages = {155--164},
  month = jul,
  year = {2012},
}
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