Interpretable Active Inference Gait Control Learning

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00388320" target="_blank" >RIV/68407700:21230/25:00388320 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICRA55743.2025.11128724" target="_blank" >https://doi.org/10.1109/ICRA55743.2025.11128724</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICRA55743.2025.11128724" target="_blank" >10.1109/ICRA55743.2025.11128724</a>

Result language
angličtina
Original language name
Interpretable Active Inference Gait Control Learning
Original language description
Sustaining the gait locomotion in an adversarial environment requires the robot to react to novel experiences adaptively. In Free Energy Principle (FEP), the behavioral reaction is driven by the discrepancy between observation and prediction. Although, for legged robot gait locomotion, the prediction of gait dynamics is challenging as the consequences non-linearly depend on the activity history, the animal gait is robust, adapting to severe motion disruptions seemingly instantly. In biomimetic robotics, the Central Pattern Generator (CPG) relaxes the general dynamics of body-environment interaction to the stable and repetitive dynamics of gait. Based on these observations, we propose self-learning of the gait dynamics model and FEP framework that infers state estimation and gait control. The proposed method is experimentally evaluated on a real hexapod walking robot with 18 controllable degrees of freedom. The robot learns the gait dynamics model indoors and then deploys it in outdoor navigation under various adversarial scenarios. Results show that the developed interpretable gait controller exhibits complex and real-time adaptive behavior when it encounters unknown situations.
Czech name
—
Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2025 IEEE International Conference on Robotics and Automation (ICRA)
ISBN
979-8-3315-4139-2
ISSN
1050-4729
e-ISSN
1050-4729
Number of pages
7
Pages from-to
9630-9636
Publisher name
IEEE Industrial Electronic Society
Place of publication
Vienna
Event location
Atlanta
Event date
May 19, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001614845800364

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