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La carte bayésienne : un modèle probabiliste hiérarchique pour la navigation en robotique mobile

Julien Diard 1 
1 E-MOTION - Geometry and Probability for Motion and Action
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes
Abstract : What is a map? What is its utility? What is a location, a behaviour? What
are navigation, localization and prediction for a mobile robot facing a
given task?

These questions have neither unique nor straightforward answer to this day,
and are still the core of numerous research domains.

Robotics, for instance, aim at answering them for creating successful
sensori-motor artefacts. Cognitive sciences use these questions as
intermediate goals on the road to understanding living beings, their skills,
and furthermore, their intelligence.

Our study lies between these two domains. We first study classical
probabilistic approaches (Markov localization, POMDPs, HMMs, etc.), then
some biomimetic approaches (Berthoz, Franz, Kuipers). We analyze their
respective advantages and drawbacks in light of a general formalism for
robot programming based on bayesian inference (BRP).

We propose a new probabilistic formalism for modelling the interaction
between a robot and its environment: the Bayesian map.

In this framework, defining a map is done by specifying a particular
probability distribution. Some of the questions above then amount to solving
inference problems.

We define operators for putting maps together, so that "hierarchies of maps"
and incremental development play a central role in our formalism, as in
biomimetic approaches. By using the bayesian formalism, we also benefit both
from a unified means of dealing with uncertainties, and from clear and
rigorous mathematical foundations. Our formalism is illustrated by
experiments that have been implemented on a Koala mobile robot.
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Submitted on : Thursday, January 29, 2004 - 11:04:49 AM
Last modification on : Friday, March 25, 2022 - 11:10:36 AM
Long-term archiving on: : Friday, April 2, 2010 - 7:10:16 PM


  • HAL Id : tel-00004369, version 1



Julien Diard. La carte bayésienne : un modèle probabiliste hiérarchique pour la navigation en robotique mobile. Interface homme-machine [cs.HC]. Institut National Polytechnique de Grenoble - INPG, 2003. Français. ⟨tel-00004369⟩



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