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| Hauptseite > Publikationsdatenbank > Finding the gap: neuromorphic motion-vision in dense environments |
| Journal Article | FZJ-2024-01289 |
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2024
Nature Publishing Group UK
[London]
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Please use a persistent id in citations: doi:10.1038/s41467-024-45063-y doi:10.34734/FZJ-2024-01289
Abstract: Animals have evolved mechanisms to travel safely and efficiently within different habitats. On a journey in dense terrains animals avoid collisions andcross narrow passages while controlling an overall course. Multiple hypotheses target how animals solve challenges faced during such travel. Here weshow that a single mechanism enables safe and efficient travel. We developed arobot inspired by insects. It has remarkable capabilities to travel in denseterrain, avoiding collisions, crossing gaps and selecting safe passages. Thesecapabilities are accomplished by a neuromorphic network steering the robottoward regions of low apparent motion. Our system leverages knowledgeabout vision processing and obstacle avoidance in insects. Our resultsdemonstrate how insects might safely travel through diverse habitats. Weanticipate our system to be a working hypothesis to study insects’ travels indense terrains. Furthermore, it illustrates that we can design novel hardwaresystems by understanding the underlying mechanisms driving behaviour.
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