DocumentCode
3260740
Title
A machine learning algorithm for automated assembly
Author
Vaaler, Erik G. ; Seering, Warren P.
Author_Institution
A.I. Lab., MIT, Cambridge, MA, USA
fYear
1991
fDate
9-11 Apr 1991
Firstpage
2231
Abstract
A primary source of difficulty in automated assembly is the uncertainty in the relative position of the parts being assembled. This study focuses on a machine learning approach for solving the problem. Force sensor information, responses to recent moves and results from previous assemblies are used to generate a set of production rules. These rules govern the motion of the robot during the assembly process
Keywords
assembling; industrial robots; learning systems; position measurement; process computer control; automated assembly; machine learning algorithm; position measurement; process computer control; production rules; Force measurement; Force sensors; Information resources; Logic; Machine learning algorithms; Production; Robot sensing systems; Robotic assembly; Robotics and automation; Torque measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation, 1991. Proceedings., 1991 IEEE International Conference on
Conference_Location
Sacramento, CA
Print_ISBN
0-8186-2163-X
Type
conf
DOI
10.1109/ROBOT.1991.131962
Filename
131962
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