Bayesian Programming and Hierarchical Learning in Robotics - Archive ouverte HAL
Communication Dans Un Congrès Année : 2000

Bayesian Programming and Hierarchical Learning in Robotics

Julien Diard

Résumé

This paper presents a new robotic programming environment based on the probability calculus. We show how reactive behaviours, like obstacle avoidance, contour following, or even light following, can be programmed and learned by a Khepera robot with our system. We further demonstrate that behaviours can be combined either by programmation or learning. A homing behaviour is thus obtained by combining obstacle avoidance and light following.

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Dates et versions

hal-00019361 , version 1 (11-09-2006)

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  • HAL Id : hal-00019361 , version 1

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Julien Diard, Olivier Lebeltel. Bayesian Programming and Hierarchical Learning in Robotics. 2000, 10p. ⟨hal-00019361⟩

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