creators_name: Koike, C
creators_name: Pradalier, C
creators_name: Bessiere, P
creators_name: Mazer, E
type: confpaper
datestamp: 2004-08-10
lastmod: 2011-03-11 08:55:39
metadata_visibility: show
title: Obstacle Avoidance and Proscriptive Bayesian Programming
ispublished: pub
subjects: comp-sci-robot
full_text_status: public
keywords: Bayesian programming, Obstacle avoidance, Command fusion
abstract: Unexpected events and not modeled properties of the robot environment are some of
the challenges presented by situated robotics research field. Collision avoidance is a basic security
requirement and this paper proposes a probabilistic approach called Bayesian Programming, which
aims to deal with the uncertainty, imprecision and incompleteness of the information handled to
solve the obstacle avoidance problem. Some examples illustrate the process of embodying the
programmer preliminary knowledge into a Bayesian program and experimental results of these
examples implementation in an electrical vehicle are described and commented. A video illustration
of the developed experiments can be found at http://www.inrialpes.fr/sharp/pub/laplace
date: 2003
date_type: published
refereed: FALSE
citation:   Koike, C and Pradalier, C and Bessiere, P and Mazer, E  (2003) Obstacle Avoidance and Proscriptive Bayesian Programming.  [Conference Paper]     
document_url: http://cogprints.org/3756/1/Koike03.pdf