A Biologically Inspired Architecture for Visual Self-location
Self-location—recognizing one’s surroundings and reliably keeping track of current position relative to a known environment—is a fundamental cognitive skill for entities biological and artificial alike. At a minimum, it requires the ability to match current sensory (mainly visual) inputs to memories of previously visited places, and to correlate perceptual changes to physical movement. Both tasks are complicated by variations such as light source changes and the presence of moving obstacles. This article presents the Difference Image Correspondence Hierarchy (DICH), a biologically inspired architecture for enabling self-location in mobile robots. Experiments demonstrate DICH works effectively despite varying environment conditions.
KeywordsMobile Robot Difference Image Cosine Similarity Shift Vector Walk Away
This research work was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grant 201799/2012-0).
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