---
abstract: |-
  A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. Carsense is a European project whose purpose is to develop such a new sensing system. It will combine different sensors (laser, radar and video) and will rely on the fusion of the information coming from these sensors in order to achieve better accuracy, robustness and an increase of the information content. This paper demonstrates the interest of using
  probabilistic reasoning techniques to address this challenging multi-sensor data fusion problem. The approach used is called Bayesian Programming. It is a general approach based on an implementation of the Bayesian theory. It was introduced rst to design robot control programs but its scope of application is much broader and it can be used whenever one has to deal with problems involving uncertain or incomplete knowledge.
altloc:
  - http://www-laplace.imag.fr/publications/Rayons/Coue03a.pdf
chapter: ~
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confdates: 2003
conference: Int. Conf. on RoboticsApplications (ICRA)
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contact_email: ~
creators_id: []
creators_name:
  - family: Coue
    given: C
    honourific: ''
    lineage: ''
  - family: Fraichard
    given: T
    honourific: ''
    lineage: ''
  - family: Bessiere
    given: P
    honourific: ''
    lineage: ''
  - family: Mazer
    given: E
    honourific: ''
    lineage: ''
date: 2003
date_type: published
datestamp: 2004-08-10
department: ~
dir: disk0/00/00/37/53
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eprintid: 3753
fileinfo: /style/images/fileicons/application_pdf.png;/3753/1/Coue03a.pdf
full_text_status: public
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keywords: 'Bayesian reasonning, multi-sensor target tracking, data-fusion'
lastmod: 2011-03-11 08:55:39
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rev_number: 12
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status_changed: 2007-09-12 16:53:15
subjects:
  - comp-sci-robot
succeeds: ~
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title: Using Bayesian Programming for Multisensor Multi-Target Tracking in Automative Applications
type: confpaper
userid: 4357
volume: ~
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