TY - GEN
ID - cogprints3756
UR - http://cogprints.org/3756/
A1 - Koike, C
A1 - Pradalier, C
A1 - Bessiere, P
A1 - Mazer, E
TI - Obstacle Avoidance and Proscriptive Bayesian Programming
Y1 - 2003///
N2 - 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
AV - public
KW - Bayesian programming
KW - Obstacle avoidance
KW - Command fusion
ER -