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An active stereo vision-based learning approach for robotic tracking, fixating and grasping control

Xiao, Nan-Feng and Nahavandi, Saeid 2002, An active stereo vision-based learning approach for robotic tracking, fixating and grasping control, in IEEE ICIT' 02 : 2002 IEEE International Conference on Industrial Technology : productivity reincarnation through robotics & automation : 11-14 December 2002, Shangri-La Hotel, Bangkok, Thailand, IEEE Xplore, Piscataway, N.J., pp. 584-587.

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Title An active stereo vision-based learning approach for robotic tracking, fixating and grasping control
Author(s) Xiao, Nan-Feng
Nahavandi, Saeid
Conference name IEEE International Conference on Industrial Technology (2002 : Bangkok, Thailand)
Conference location Bangkok, Thailand
Conference dates 11-14 December 2002
Title of proceedings IEEE ICIT' 02 : 2002 IEEE International Conference on Industrial Technology : productivity reincarnation through robotics & automation : 11-14 December 2002, Shangri-La Hotel, Bangkok, Thailand
Editor(s) Parnichkun, Manukid
Publication date 2002
Start page 584
End page 587
Publisher IEEE Xplore
Place of publication Piscataway, N.J.
Summary In this paper, an active stereo vision-based learning approach is proposed for a robot to track, fixate and grasp an object in unknown environments. First, the functional mapping relationships between the joint angles of the active stereo vision system and the spatial representations of the object are derived and expressed in a three-dimensional workspace frame. Next, the self-adaptive resonance theory-based neural networks and the feedforward neural networks are used to learn the mapping relationships in a self-organized way. Then, the approach is verified by simulation using the models of an active stereo vision system which is installed in the end-effector of a robot. Finally, the simulation results confirm the effectiveness of the present approach.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 0780376579
9780780376571
Language eng
Field of Research 080101 Adaptive Agents and Intelligent Robotics
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2002, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30004850

Document type: Conference Paper
Collections: School of Engineering and Technology
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