Unsupervised Discovery of Behavioral Primitives from Sensorimotor Dynamic Functional Connectivity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00387029" target="_blank" >RIV/68407700:21230/25:00387029 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/ICDL63968.2025.11204389" target="_blank" >https://doi.org/10.1109/ICDL63968.2025.11204389</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICDL63968.2025.11204389" target="_blank" >10.1109/ICDL63968.2025.11204389</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Unsupervised Discovery of Behavioral Primitives from Sensorimotor Dynamic Functional Connectivity

Popis výsledku v původním jazyce

The movements of both animals and robots give rise to streams of high-dimensional motor and sensory information. Imagine the brain of a newborn or the controller of a baby humanoid robot trying to make sense of unprocessed sensorimotor time series. Here, we present a framework for studying the dynamic functional connectivity between the multimodal sensory signals of a robotic agent to uncover an underlying structure. Using instantaneous mutual information, we capture the time-varying functional connectivity (FC) between proprioceptive, tactile, and visual signals, revealing the sensorimotor relationships. Using an infinite relational model, we identified sensorimotor modules and their evolving connectivity. To further interpret these dynamic interactions, we employed non-negative matrix factorization, which decomposed the connectivity patterns into additive factors and their corresponding temporal coefficients. These factors can be considered the agent’s motion primitives or movement synergies that the agent can use to make sense of its sensorimotor space and later for behavior selection. In the future, the method can be deployed in robot learning as well as in the analysis of human movement trajectories or brain signals.

Název v anglickém jazyce

Unsupervised Discovery of Behavioral Primitives from Sensorimotor Dynamic Functional Connectivity

Popis výsledku anglicky

The movements of both animals and robots give rise to streams of high-dimensional motor and sensory information. Imagine the brain of a newborn or the controller of a baby humanoid robot trying to make sense of unprocessed sensorimotor time series. Here, we present a framework for studying the dynamic functional connectivity between the multimodal sensory signals of a robotic agent to uncover an underlying structure. Using instantaneous mutual information, we capture the time-varying functional connectivity (FC) between proprioceptive, tactile, and visual signals, revealing the sensorimotor relationships. Using an infinite relational model, we identified sensorimotor modules and their evolving connectivity. To further interpret these dynamic interactions, we employed non-negative matrix factorization, which decomposed the connectivity patterns into additive factors and their corresponding temporal coefficients. These factors can be considered the agent’s motion primitives or movement synergies that the agent can use to make sense of its sensorimotor space and later for behavior selection. In the future, the method can be deployed in robot learning as well as in the analysis of human movement trajectories or brain signals.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název statě ve sborníku

2025 IEEE International Conference on Development and Learning (ICDL)

ISBN

979-8-3315-4343-3

ISSN

—

e-ISSN

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Počet stran výsledku

8

Strana od-do

—

Název nakladatele

IEEE Conference Publications

Místo vydání

Piscataway

Místo konání akce

Praha

Datum konání akce

16. 9. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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