Adaptive human sensor model in sensor networks

Kaupp, Tobias, Makarenko, Alexei, Ramos, Fabio, Upcroft, Ben, Williams, Stefan and Durrant-Whyte, Hugh (2005). Adaptive human sensor model in sensor networks. In: , 2005 7th International Conference on Information Fusion (FUSION). 7th International Conference on Information Fusion, Philadelphia, U.S., (748-755). 25-28 July, 2005.


Author Kaupp, Tobias
Makarenko, Alexei
Ramos, Fabio
Upcroft, Ben
Williams, Stefan
Durrant-Whyte, Hugh
Title of paper Adaptive human sensor model in sensor networks
Conference Paper Type Fully Published Paper
Conference name 7th International Conference on Information Fusion    (ERA 2010 Rank C)
DOI 10.1109/ICIF.2005.1591929
Conference location Philadelphia, U.S.
Conference dates 25-28 July, 2005
Proceedings title 2005 7th International Conference on Information Fusion (FUSION)
Place published New York, U.S.
Publisher IEEE
Publication date 2005
Volume number 1
ISBN 0-7803-9286-8
Start page 748
End page 755
Total pages 8
Language eng
Abstract/Summary This paper presents the design of a probabilistic model of human perception as an integral part of a decentralized data fusion system. The system consists of a team of human operators and robotic platforms, together forming a heterogenous sensor network. Human operators are regarded as information sources submitting raw observations. The observations are converted into a probabilistic representation suitable for fusion with the system's belief. The conversion is performed by a Human Sensor Model (HSM). The initial HSM is built offline based on an average of multiple human subjects conducting a calibration experiment. Since individual human operators may vary in their performance an online adaptation of the HSM is required. The network estimate is used for adaptation because the true feature state is unknown at runtime. Results of an outdoor calibration experiment using range and bearing observations are presented. Simulations show the feasibility of efficient online adaptation.
Subjects 0801 Artificial Intelligence and Image Processing
Keyword Sensor network
Data fusion
Human-network interaction
User modeling
Sensor model adaptation
Q-Index Code E1

Document type: Conference Paper
Sub-type: Fully Published Paper
Collections: Excellence in Research Australia (ERA) - Collection
School of Mechanical & Mining Engineering Publications
 
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Created: Mon, 18 Jan 2010, 16:00:04 EST by Tara Johnson on behalf of Faculty Of Engineering, Architecture & Info Tech