Title :
Data fusion using the expected output membership function
Author :
Choi, Jongbae ; Dickerson, Julie A.
Author_Institution :
Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA
Abstract :
Fuzzy set methods can be used for data fusion of uncertain sensor data. The expected output membership function (EOMF) method computes a fusability measure based on the sensor uncertainty. The EOMF is the expected fuzzy output based on the input data and the system parameters. The most likely position of the EOMF occurs when the weighted average of the intersections of the fuzzified sensor inputs with the proposed EOMF is maximum. An example from a robotics system which combines the output of ten sensors shows the effectiveness of the EOMF method in comparison with other sensor fusion methods
Keywords :
fuzzy set theory; sensor fusion; data fusion; expected fuzzy output; expected output membership function; fusability measure; fuzzy set methods; robotics system; sensor uncertainty; uncertain sensor data; Fuzzy sets; Fuzzy systems; Gaussian noise; Neural networks; Robot sensing systems; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Statistical analysis; Uncertainty;
Conference_Titel :
Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4863-X
DOI :
10.1109/FUZZY.1998.686332