DocumentCode :
3453169
Title :
Multi-sensor integration system based on fuzzy inference and neural network for industrial application
Author :
Fukuda, Toshio ; Shimojima, Koji ; Arai, Fumihito ; Matsuura, Hideo
Author_Institution :
Dept. of Mech. Eng., Nagoya Univ., Japan
fYear :
1992
fDate :
8-12 Mar 1992
Firstpage :
907
Lastpage :
914
Abstract :
The authors deal with a multi-sensor system applied to an unknown curved metal surface cutting robot system. The measurements were performed by sensors set on an array of the tip of a five axis manipulator. The sensor array is carried to the target surface by moving the manipulator. The manipulator approaches the surface by using sensor outputs. To approach the work fast, the system should use long measurement range sensors. For precise cutting and a fast approach, the system should use both high accuracy sensors and long measurement range sensors. To use these sensors effectively, the multi-sensor integration system was based on neural network and fuzzy inference techniques. As a result, the system can consider the angle between the sensors and the object. The proposed system was shown to be effective through extensive experiments
Keywords :
cutting; fuzzy set theory; industrial robots; inference mechanisms; manufacturing computer control; neural nets; sensor fusion; curved metal surface cutting robot system; five axis manipulator; fuzzy inference; long measurement range sensors; multisensor system; neural network; sensor array; Fuzzy neural networks; Fuzzy systems; Manipulators; Manufacturing systems; Neural networks; Performance evaluation; Robot sensing systems; Robotics and automation; Sensor arrays; Sensor systems; Shape measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1992., IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0236-2
Type :
conf
DOI :
10.1109/FUZZY.1992.258778
Filename :
258778
Link To Document :
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