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Volume 26 Issue 7 - Publication Date: 1 July 2007
 
Recognizing Assembly Tasks Through Human Demonstration
 
J. Takamatsu, K. Ogawara Institute of Industrial Science the University of Tokyo, Japan, H. Kimura Graduate School of Information Systems the University of Electro-Communications Tokyo, Japan, and K. Ikeuchi Graduate School of Interdisciplinary Information Studies the University of Tokyo, Japan
 
As one of the methods for reducing the work of programming, the Learning-from-Observation (LFO) paradigm has been heavily promoted. This paradigm requires the programmer only to perform a task in front of a robot and does not require expertise. In this paper, the LFO paradigm is applied to assembly tasks by two rigid polyhedral objects. A method is proposed for recognizing these tasks as a sequence of movement primitives from noise-contaminated data obtained by a conventional 6 degree-of-freedom (DOF) object-tracking system. The system is implemented on a robot with a real-time stereo vision system and dual arms with dexterous hands, and its effectiveness is demonstrated.
 
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