DocumentCode
2647250
Title
Adaptive sensor models
Author
Van Dam, Joris W M ; Krose, Ben J A ; Groen, Franciscus C A
Author_Institution
Fac. of Math., Amsterdam Univ., Netherlands
fYear
1996
fDate
8-11 Dec 1996
Firstpage
705
Lastpage
712
Abstract
In this paper we consider the conversion of sensor data to a probabilistic representation of the environment (occupancy grid). We introduce a neural network which learns these conversions. The conversion of sensor data remains adaptive to changes in either the sensor or its environment. To place this work in a broader context we describe the architecture of our sensor data fusion system in which these conversions are applied. We also introduce the PDOP: a rule for fusing occupancy grids in this system
Keywords
adaptive systems; mobile robots; neural nets; probability; sensor fusion; PDOP; adaptive sensor models; autonomous mobile robot; data conversion; neural network; occupancy grid fusion; probabilistic representation; sensor data fusion system; Computer science; Mathematical model; Mathematics; Mobile robots; Neural networks; Robot sensing systems; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Multisensor Fusion and Integration for Intelligent Systems, 1996. IEEE/SICE/RSJ International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-3700-X
Type
conf
DOI
10.1109/MFI.1996.572306
Filename
572306
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