Autonomous Robot Controller Using Bitwise GIBBS Sampling

Abstract : In the present paper we describe a bio-inspired non von Neumann controller for a simple sensorimotor robotic system. This controller uses a bitwise version of the Gibbs sampling algorithm to select commands so the robot can adapt its course of action and avoid perceived obstacles in the environment. The VHDL specification of the circuit implementation of this controller is based on stochastic computation to perform Bayesian inference at a low energy cost. We show that the proposed unconventional architecture allows to successfully carry out the obstacle avoidance task and to address scalability issues observed in previous works.
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Communication dans un congrès
15th IEEE International Conference on COGNITIVE INFORMATICS & COGNITIVE COMPUTING, Aug 2016, Calgary, Canada
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Contributeur : Dominique Vaufreydaz <>
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Dernière modification le : mercredi 11 avril 2018 - 01:56:04
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Rémi Canillas, Raphael Laurent, Marvin Faix, Dominique Vaufreydaz, Emmanuel Mazer. Autonomous Robot Controller Using Bitwise GIBBS Sampling. 15th IEEE International Conference on COGNITIVE INFORMATICS & COGNITIVE COMPUTING, Aug 2016, Calgary, Canada. 〈hal-01316568〉

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