DocumentCode :
1260183
Title :
A fusion toolbox for sensor data fusion in industrial recycling
Author :
Karlsson, Björn ; Järrhed, Jan-Ove ; Wide, Peter
Author_Institution :
Dept. of Phys. & Meas. Technol., Linkoping Inst. of Technol., Sweden
Volume :
51
Issue :
1
fYear :
2002
fDate :
2/1/2002 12:00:00 AM
Firstpage :
144
Lastpage :
149
Abstract :
Information from different sensors can be fused in various ways. It is often difficult to choose the most suitable method for solving a fusion problem. In a measurement situation, the measured signal is often corrupted by disturbances (noise, etc.). It is, therefore, meaningless to compare crisp values without the corresponding uncertainty intervals. This paper describes a toolbox including nine different fusing methods. All methods are applied on training data, and the most suitable method is then used for solving the real fusion problem. In the example, fusion is performed on data for classification in an industrial recycling operation. The data is from different vision systems and an eddy current system. The fusion methods included in the toolbox are fuzzy logic with triangular and Gaussian shaped membership functions, fuzzy measures with triangular and Gaussian shapes, Bayes´ statistics, artificial neural networks, multivariate analysis (PCA), a knowledge-based system, and a neurofuzzy system
Keywords :
Bayes methods; eddy currents; fuzzy logic; fuzzy neural nets; measurement uncertainty; recycling; robot vision; sensor fusion; Bayes´ statistics; Gaussian shaped membership functions; disturbances; eddy current system; fusion toolbox; fuzzy logic; industrial recycling; knowledge-based system; measured signal; measurement situation; multivariate analysis; neurofuzzy system; robot vision; sensor data fusion; triangular shaped membership functions; uncertainty intervals; vision systems; Eddy currents; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Machine vision; Noise measurement; Recycling; Sensor fusion; Shape measurement; Training data;
fLanguage :
English
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9456
Type :
jour
DOI :
10.1109/19.989918
Filename :
989918
Link To Document :
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