A biologically plausible robot attention model, based on space and time

In this work we describe a biological inspired approach to robot attention, developed on the basis of experiments aimed to map human visual search onto robot behaviour, allowing particularly for depth as a further feature in the attention model. By means of a purposely-designed machine we studied fixation zones elicited from scanning paths that were performed during a task driven wandering of subjects’ gaze over a cluttered scene. Hence, we defined preference criteria and a utility function accounting for the optimization of visual endeavours. This function would allow a robot to select meaningful spots without the need to process the whole scene.

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