DocumentCode :
2518504
Title :
Model based robot vision
Author :
Groen, F.C.A. ; Antonissen, P.P.J. ; Weller, G.A.
Author_Institution :
Fac. of Math. & Comput. Sci., Amsterdam Univ., Netherlands
fYear :
1993
fDate :
18-20 May 1993
Firstpage :
584
Lastpage :
588
Abstract :
A robust methodology is presented for sensing and data processing to recognize industrial objects in a scene. The method is based upon an extension of the logical sensor concept. Each module of the sensing system is equipped with tests on its results to verify the correctness of the operation. If these tests are not successful, corrective action is taken. This is realized by adjustment of the module parameters or incorporation of another module in the processing. The modules and tests to recognize industrial objects in an image are described. The robustness of the method for noise and shading is demonstrated and compared with a conventional approach
Keywords :
industrial robots; intelligent sensors; object recognition; robot vision; robust control; Cranfield benchmark; correctness; data processing; industrial objects; logical sensor; model based robot vision; module parameters; noise; object recognition; robustness; shading; Image sensors; Layout; Robot sensing systems; Robot vision systems; Robustness; Sensor phenomena and characterization; Sensor systems; Sensor systems and applications; Testing; Transducers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1993. IMTC/93. Conference Record., IEEE
Conference_Location :
Irvine, CA
Print_ISBN :
0-7803-1229-5
Type :
conf
DOI :
10.1109/IMTC.1993.382575
Filename :
382575
Link To Document :
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