Title :
A machine learning algorithm for automated assembly
Author :
Vaaler, Erik G. ; Seering, Warren P.
Author_Institution :
A.I. Lab., MIT, Cambridge, MA, USA
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;
Conference_Titel :
Robotics and Automation, 1991. Proceedings., 1991 IEEE International Conference on
Conference_Location :
Sacramento, CA
Print_ISBN :
0-8186-2163-X
DOI :
10.1109/ROBOT.1991.131962
