Multimodal Active Exploration using a Bayesian Approach

J.F. Ferreira, J.A. Prado, J. Lobo, and J. Dias (Portugal)


Active Perception, Multisensory, Bayesian, Bioinspired,Exploration, Realtime.


In this text, we use a Bayesian framework for active multimodal perception of 3D structure and motion — which, while not strictly neuromimetic, finds its roots in the role of the dorsal perceptual pathway of the human brain — to implement a strategy of active exploration based on entropy. The computational models described in this text support a robotic implementation of multimodal active perception to be used in real-world applications, such as human-machine interaction or mobile robot navigation.

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