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