By Topic

Humanoid Robot's Autonomous Acquisition of Proto-Symbols through Motion Segmentation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Takano, W. ; Dept. of Mechano-Informatics, Tokyo Univ. ; Nakamura, Y.

Mimesis is the theory that human intelligence originated in the interactive communication of motion recognition and generation through imitation. A mimesis model has been proposed using hidden Markov models (HMMs), which represent proto symbols. In our previous system, the user had to manually divided a sequence of motion into segments in order to embed each segment as an HMM. Automatic segmentation is essential for a system to autonomously learn and develop through imitation. In this paper, we propose an automatic motion segmentation method utilizing correlation among movements for a short time period. In addition, we show that it is possible to acquire proto symbols by providing the automatically segmented motion patterns with the mimesis system

Published in:

Humanoid Robots, 2006 6th IEEE-RAS International Conference on

Date of Conference:

4-6 Dec. 2006