All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • 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

  • 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

  • UT code for WoS article

    001503073900003

  • EID of the result in the Scopus database

    2-s2.0-105007233376