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CGV: Small: Simulation Motion Capture of Dexterous Manipulation

CGV: Small: Simulation Motion Capture of Dexterous Manipulation
CGV:小:灵巧操作的模拟动作捕捉
批准号:
1218182
负责人:
Nancy Pollard
金额:
$49.98万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-08-01 至 2016-07-31

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中文摘要
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英文摘要
This research involves novel techniques for capturing natural human manipulation actions in all of their complexity. Consider how we prepare food, pick up and use a common tool such as a wrench, or plant a flower. We would like to learn from human examples of such complex actions, so that we can portray convincing graphical renditions of human characters for applications ranging from education, training, and entertainment to exposition and scientific study. Broader impact includes use of databases and the capture tool developed as part of this research for development of dexterous robotic manipulation, design of prosthetics, and understanding of human grasping and manipulation. The visual nature and appeal of this research makes it especially suited for mentoring of undergraduates and women, as well as for outreach to spark interest in science for K-12 students.Traditional and established approaches to motion capture, such as optical approaches, cannot handle the complex, detailed, high degree of freedom interactions that must be observed to capture dexterous manipulation actions. The alternative pursued in this research is simulation motion capture, where a user interacts with and guides a running simulation. Enabling technologies include (1) real-time simulation of a skeleton driven deformable hand in close interaction with simulated objects, (2) novel control algorithms and interface techniques to allow direct control of such simulations, (3) a new language for segmentation and control law development, based on user actions during the simulation, and (4) novel manipulation objective functions learned from direct observation of human actions. Benefits of simulation capture over current capture technologies include little or no postprocessing, precise representation of contact forces, fast trial and error, ability to make use of a variety of means for control, and ability to use a variety of input devices. The resulting capture system will be inexpensive and broady accessible.
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Convergence Accelerator Track M: Bio-Inspired Design of Robot Hands for Use-Driven Dexterity
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