DocumentCode :
2118274
Title :
Vision-based bin-picking: recognition and localization of multiple complex objects using simple visual cues
Author :
Rahardja, Krisnawan ; Kosaka, Akio
Author_Institution :
Robot Vision Lab., Purdue Univ., West Lafayette, IN, USA
Volume :
3
fYear :
1996
fDate :
4-8 Nov 1996
Firstpage :
1448
Abstract :
Vision-based bin-picking is increasingly more difficult as the complexity of target objects increases. We propose an efficient solution where complex objects are sufficiently represented by simple features/cues; thus invariance to object complexity is established. The region extraction algorithm utilized in our approach is capable of providing the focus of attention to the simple cues as a trigger toward recognition and pose estimation. Successful bin-picking experiments of industrial objects using stereo vision tools are presented
Keywords :
image recognition; image segmentation; manipulators; materials handling; object recognition; robot vision; stereo image processing; bin-picking experiments; industrial objects; multiple complex object localization; object complexity invariance; object recognition; pose estimation; region extraction algorithm; stereo vision tools; vision-based bin-picking; Alternators; Focusing; Image recognition; Laboratories; Layout; Metals industry; Robot vision systems; Shape; Stereo vision; Target recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems '96, IROS 96, Proceedings of the 1996 IEEE/RSJ International Conference on
Conference_Location :
Osaka
Print_ISBN :
0-7803-3213-X
Type :
conf
DOI :
10.1109/IROS.1996.569005
Filename :
569005
Link To Document :
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