Vision-Based Modeling and Control of Dynamical Systems Using Deep Learning
Authors
Tomoya YOSHIOKA, Yusuke SASAKI, Haohui JIA, Takashi MATSUBARA
Abstract
Not available
Citation
- Journal: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
- Year: 2026
- Volume: E109.A
- Issue: 5
- Pages: 1042–1045
- Publisher: Institute of Electronics, Information and Communications Engineers (IEICE)
- DOI: 10.1587/transfun.2025eal2064
BibTeX
@article{YOSHIOKA_2026,
title={{Vision-Based Modeling and Control of Dynamical Systems Using Deep Learning}},
volume={E109.A},
ISSN={1745-1337},
DOI={10.1587/transfun.2025eal2064},
number={5},
journal={IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences},
publisher={Institute of Electronics, Information and Communications Engineers (IEICE)},
author={YOSHIOKA, Tomoya and SASAKI, Yusuke and JIA, Haohui and MATSUBARA, Takashi},
year={2026},
pages={1042--1045}
}References
- Böttcher L, Antulov-Fantulin N, Asikis T (2022) AI Pontryagin or how artificial neural networks learn to control dynamical systems. Nat Commun 13(1). https://doi.org/10.1038/s41467-021-27590- – 10.1038/s41467-021-27590-0
- Todorov E, Erez T, Tassa Y (2012) MuJoCo: A physics engine for model-based control. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems 5026–503 – 10.1109/iros.2012.6386109
- Jaques M, Burke M, Hospedales T (2021) NewtonianVAE: Proportional Control and Goal Identification from Pixels via Physical Latent Spaces. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 4452–446 – 10.1109/cvpr46437.2021.00443