Dataset for "Learning Visually Interpretable Oscillator Networks for Soft Continuum Robots from Video"
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This dataset was used to learn visually interpretable oscillator networks in "Learning Visually Interpretable Oscillator Networks for Soft Continuum Robots from Video" (DOI: https://doi.org/10.48550/arXiv.2511.18322). Please cite this paper when using the dataset. The implementation of the visually interpretable oscillator networks and their training is published as a GitHub repository (https://github.com/UThenrik/visual_oscillators_for_SCR).The dataset includes:Pressure and video raw data of a soft pneumatic robot during dynamic planar movements based on step and oscillatory inputsData processing script for data loading, synchronization, subsampling and croppingProcessed data used for training of networks in the paper
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Publication Details
Subfield
Computer Vision and Pattern Recognition
Field
Computer Science
Domain
Physical Sciences
Confidence Score
57%
Source
Scholar Data Model