Scaling up a Boltzmann machine model of hippocampus with visual features for mobile robots
Saul, A., Prescott, T.J. and Fox, C.W.
(2011)
Scaling up a Boltzmann machine model of hippocampus with visual features for mobile robots.
In:
Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on.
2011 IEEE International Conference on Robotics and Biomimetics, December 7-11, 2011, Phucket, Thailand.
IEEE
, pp. 835-840.
ISBN 978-1-4577-2136-6
Abstract
Previous papers [4], [5] have described a detailed mapping between biological hippocampal navigation and a temporal restricted Boltzmann machine [20] with unitary coherent particle filtering. These models have focused on the biological structures and used simplified microworlds in implemented examples. As a first step in scaling the model up towards practical bio-inspired robotic navigation, we present new results with the model applied to real world visual data, though still limited by a discretized configuration space. To extract useful features from visual input we apply the SURF transform followed by a new lamellae-based winner-take-all Dentate Gyrus. This new visual processing stream allows the navigation system to function without the need for a simplifying data assumption of the previous models, and brings the hippocampal model closer to being a practical robotic navigation system.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)