---
abstract: |-
More and more fields of applied computer
science involve fusion of multiple data sources, such as sensor
readings or model decision. However incompleteness of the
models prevent the programmer from having an absolute
precision over their variables. Therefore bayesian framework
can be adequate for such a process as it allows handling of
uncertainty.We will be interested in the ability to express any
fusion process as a product, for it can lead to reduction of
complexity in time and space. We study in this paper various
fusion schemes and propose to add a consistency variable to
justify the use of a product to compute distribution over the
fused variable. We will then show application of this new
fusion process to localization of a mobile robot and obstacle
avoidance.
altloc:
- http://www-laplace.imag.fr/publications/Rayons/Pradalier03b.pdf
chapter: ~
commentary: ~
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confdates: 2003
conference: IEEE-RSJ Int. Conf. on Intelligent Robots and Systems (IROS)
confloc: 'Las Vegas, USA'
contact_email: ~
creators_id: []
creators_name:
- family: Pradalier
given: C
honourific: ''
lineage: ''
- family: Colas
given: F
honourific: ''
lineage: ''
- family: Bessiere
given: P
honourific: ''
lineage: ''
date: 2003
date_type: published
datestamp: 2004-08-10
department: ~
dir: disk0/00/00/37/59
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eprint_status: archive
eprintid: 3759
fileinfo: /style/images/fileicons/application_pdf.png;/3759/1/Pradalier03b.pdf
full_text_status: public
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keywords: ~
lastmod: 2011-03-11 08:55:40
latitude: ~
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metadata_visibility: show
note: ~
number: ~
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pubdom: TRUE
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refereed: FALSE
referencetext: ~
relation_type: []
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reportno: ~
rev_number: 12
series: ~
source: ~
status_changed: 2007-09-12 16:53:21
subjects:
- comp-sci-robot
succeeds: ~
suggestions: ~
sword_depositor: ~
sword_slug: ~
thesistype: ~
title: 'Expressing Bayesian Fusion as a Product of Distributions: Application in Robotics'
type: confpaper
userid: 4357
volume: ~