Event-driven figure-ground organisation model for the humanoid robot iCub

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00381590" target="_blank" >RIV/68407700:21230/25:00381590 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1038/s41467-025-56904-9" target="_blank" >https://doi.org/10.1038/s41467-025-56904-9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41467-025-56904-9" target="_blank" >10.1038/s41467-025-56904-9</a>

Result language

angličtina

Original language name

Event-driven figure-ground organisation model for the humanoid robot iCub

Original language description

Figure-ground organisation is a perceptual grouping mechanism for detecting objects and boundaries, essential for an agent interacting with the environment. Current figure-ground segmentation methods rely on classical computer vision or deep learning, requiring extensive computational resources, especially during training. Inspired by the primate visual system, we developed a bio-inspired perception system for the neuromorphic robot iCub. The model uses a hierarchical, biologically plausible architecture and event-driven vision to distinguish foreground objects from the background. Unlike classical approaches, event-driven cameras reduce data redundancy and computation. The system has been qualitatively and quantitatively assessed in simulations and with event-driven cameras on iCub in various scenarios. It successfully segments items in diverse real-world settings, showing comparable results to its frame-based version on simple stimuli and the Berkeley Segmentation dataset. This model enhances hybrid systems, complementing conventional deep learning models by processing only relevant data in Regions of Interest (ROI), enabling low-latency autonomous robotic applications.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

R - Projekt Ramcoveho programu EK

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Nature Communications

ISSN

2041-1723

e-ISSN

2041-1723

Volume of the periodical

16

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

13

Pages from-to

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UT code for WoS article

001428299300004

EID of the result in the Scopus database

2-s2.0-85218493738