A neuromorphic electronic artist for robotic painting
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00389955" target="_blank" >RIV/68407700:21230/25:00389955 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1038/s41598-025-92081-x" target="_blank" >https://doi.org/10.1038/s41598-025-92081-x</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-025-92081-x" target="_blank" >10.1038/s41598-025-92081-x</a>
Alternative languages
Result language
angličtina
Original language name
A neuromorphic electronic artist for robotic painting
Original language description
Recent advances in deep learning have sparked interest in AI-generated art, including robot-assisted painting. Traditional painting machines use static images and offline processing without considering the dynamic nature of painting. Neuromorphic cameras, which capture light intensity changes through asynchronous events, and mixed-signal neuromorphic processors, which implement biologically plausible spiking neural networks, offer a promising alternative. In this work, we present a robotic painting system comprising a 6-DOF robotic arm, event-based input from a Dynamic Vision Sensor (DVS) camera and a neuromorphic processor to produce dynamic brushstrokes, and tactile feedback from a force-torque sensor to compensate for brush deformation. The system receives DVS events representing the desired brushstroke trajectory and maps these events onto the processor’s neurons to compute joint velocities in close-loop. The variability in the input’s noisy event streams and the processor’s analog circuits reproduces the heterogeneity of human brushstrokes. Tested in a real-world setting, the system successfully generated diverse physical brushstrokes. This network marks a first step towards a fully spiking robotic controller with ultra-low latency responsiveness, applicable to any robotic task requiring real-time closed-loop adaptive control.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific Reports
ISSN
2045-2322
e-ISSN
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Volume of the periodical
15
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
001503073900003
EID of the result in the Scopus database
2-s2.0-105007233376