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2008
IEEE

Motion recognition and generation by combining reference-point-dependent probabilistic models

10 years 4 months ago
Motion recognition and generation by combining reference-point-dependent probabilistic models
— This paper presents a method to recognize and generate sequential motions for object manipulation such as placing one object on another or rotating it. Motions are learned using reference-point-dependent probabilistic models, which are then transformed to the same coordinate system and combined for motion recognition/generation. We conducted physical experiments in which a user demonstrated the manipulation of puppets and toys, and obtained a recognition accuracy of 63% for the sequential motions. Furthermore, the results of motion generation experiments performed with a robot arm are presented.
Komei Sugiura, Naoto Iwahashi
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where IROS
Authors Komei Sugiura, Naoto Iwahashi
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