Recognizing Assembly Tasks Through Human Demonstration

Authors:
Jun Takamatsu;Koichi Ogawara;Hiroshi Kimura;Katsushi Ikeuchi
Affiliations:
Institute of Industrial Science the University of TokyoTokyo, Japan, j-taka,ogawara}@cvl.iis.u-tokyo.ac.jp;Institute of Industrial Science the University of TokyoTokyo, Japan, j-taka,ogawara}@cvl.iis.u-tokyo.ac.jp;Graduate School of Information Systems the Universityof Electro-Communications Tokyo, Japan;Graduate School of Interdisciplinary Information Studiesthe University of Tokyo Tokyo, Japan
Venue:
International Journal of Robotics Research
Year:
2007

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Abstract

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.