By Topic

Learning task sequences from scratch: applications to the control of tools and toys by a humanoid robot

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
$33 $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

1 Author(s)
A. M. Arsenio ; CSAIL, MIT, USA

The goal of this work is to build perceptual and motor control systems for a humanoid robot, starting from an infant's early ability for detecting repetitive or abruptly varying world events from human-robot interactions, and walking developmentally towards robust perception and learning. This work presents strategies for learning task sequences from human-robot interaction cues. Demonstration by human teachers facilitates robot learning to recognize new objects, such as tools or toys, and their functionality. Self-exploration of the world extends the robot's knowledge concerning object properties. Multi-modal percepts are then acquired and recognized by robotic manipulation of toys and tools.

Published in:

Control Applications, 2004. Proceedings of the 2004 IEEE International Conference on  (Volume:1 )

Date of Conference:

2-4 Sept. 2004