NDLI: The "feature CMAC": a neural-network-based vision system for robotic control

Content Provider	IEEE Xplore Digital Library
Author	Carusone, J. D'Eleuterio, G.M.T.
Copyright Year	1998
Description	Author affiliation: Inst. for Aerosp. Studies, Toronto Univ., Downsview, Ont., Canada (Carusone, J.)
Abstract	A strategy for locating and grasping a target object in an unknown position using a robotic manipulator equipped with a CCD camera is described. Low-level trajectory and joint control during the grasping operation is handled by the manipulator's conventional motion controller using target-pose data provided by an artificial-neural-network-based vision system. The feature CMAC is a self-organizing neural network that efficiently transforms images of a target into estimates of its location and orientation. The approach emulates biological systems in that it begins with simple image features (e.g., corners) and successively combines them to form more complex features in order to determine object position. Knowledge of camera parameters, camera position and object models is not required since that information is incorporated into the network during a training procedure wherein the target is viewed in a series of known poses. The manipulator is used to generate the training images autonomously. No training of connection weights is required; instead, training serves only to define the network topology which requires just one pass through the training images. Experiments validating the effectiveness of the strategy on an industrial robotic workcell are presented.
Starting Page	2959
Ending Page	2964
File Size	761762
Page Count	6
File Format	PDF
ISBN	078034300X
ISSN	10504729
DOI	10.1109/ROBOT.1998.680745
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-05-20
Publisher Place	Belgium
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Industrial training Manipulators Cameras Motion control Control systems Artificial neural networks Charge coupled devices Robot vision systems Charge-coupled image sensors Trajectory
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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