Sampling-based contact-rich motion control

Human motions are the product of internal and external forces, but these forces are very difficult to measure in a general setting. Given a motion capture trajectory, we propose a method to reconstruct its open-loop control and the implicit contact forces. The method employs a strategy based on randomized sampling of the control within user-specified bounds, coupled with forward dynamics simulation. Sampling-based techniques are well suited to this task because of their lack of dependence on derivatives, which are difficult to estimate in contact-rich scenarios. They are also easy to parallelize, which we exploit in our implementation on a compute cluster. We demonstrate reconstruction of a diverse set of captured motions, including walking, running, and contact rich tasks such as rolls and kip-up jumps. We further show how the method can be applied to physically based motion transformation and retargeting, physically plausible motion variations, and referencetrajectory-free idling...

• Type: Conference
• Year: 2010
• Where: SIGGRAPH
• Authors: Libin Liu, KangKang Yin, Michiel van de Panne, Tianjia Shao, Weiwei Xu
• Keywords: Computer Graphics, Human Motions, Implicit Contact Forces, Motion Capture Trajectory, SIGGRAPH 2010