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AMOUSE Résumé de rapport

Project ID: IST-2000-28127
Financé au titre de: FP5-IST
Pays: Germany

Experiments on motor categorization and forward models

We investigated numerous strategies for active sensing in distance estimation and shape recognition, and tested these in robot experiments. We found that the integration of motor signals (whisker protraction) and sensory signals (whisker deflection) provides useful information for above-mentioned tasks. Sensorimotor loops for the repositioning of the mobile robot with respect to the object were developed.

We also used an integrated sensorimotor architecture based on reciprocal cross-modal coupling, and highlighted cognitive abilities that spontaneously arose in tactile discrimination task and predictive reafference cancellation (forward models). The AMOUSE robot of partner 2 was used to collect naturalistic stimuli. The robot is equipped with 12 whiskers (6 on each side in two rows of 3 whiskers each) and a camera pointing to a hyperbolic overhead mirror.

The whisker tips are located within the visual field. While the robot explores the environment, we record the 360-degree view around the robot and the simultaneous whisker deflections. Using this bimodal sensory input dataset we train networks to optimise for sparseness or stability of the output layer. We thereby generalize the learning algorithms (developed by partner 4) that where successfully used to explain e.g. viewpoint invariance in the visual system and the emergence of whisker representations for texture discrimination in the somato-sensory system to learn multi-modal representations.

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Ralf MOELLER, (Head of Unit)
Tél.: +49-0521-1065272
Fax: +49-0521-1066440