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TORSO-21 Dataset: Typical Objects in RoboCup Soccer 2021

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RoboCup 2021: Robot World Cup XXIV (RoboCup 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13132))

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Abstract

We present a dataset specifically designed to be used as a benchmark to compare vision systems in the RoboCup Humanoid Soccer domain. The dataset is composed of a collection of images taken in various real-world locations as well as a collection of simulated images. It enables comparing vision approaches with a meaningful and expressive metric. The contributions of this paper consist of providing a comprehensive and annotated dataset, an overview of the recent approaches to vision in RoboCup, methods to generate vision training data in a simulated environment, and an approach to increase the variety of a dataset by automatically selecting a diverse set of images from a larger pool. Additionally, we provide a baseline of YOLOv4 and YOLOv4-tiny on this dataset.

All authors contributed equally.

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Notes

  1. 1.

    https://humanoid.robocup.org/hl-2021/v-hsc/ (last accessed: 2021/06/14)

  2. 2.

    https://github.com/noctrog/conv-vae (last accessed: 2021/06/14)

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Acknowledgments

Thanks to all individuals and teams that provided data and labels or helped to develop and host the ImageTagger.

This research was partially funded by the Ministry of Science, Research and Equalities of Hamburg as well as the German Research Foundation (DFG) and the National Science Foundation of China (NSFC) in project Crossmodal Learning, TRR-169.

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Authors and Affiliations

  1. Hamburg Bit-Bots, Department of Informatics, Universität Hamburg, Vogt-Kölln-Straße 30, 22527, Hamburg, Germany

    Marc Bestmann, Timon Engelke, Niklas Fiedler, Jasper Güldenstein, Jan Gutsche, Jonas Hagge & Florian Vahl

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  1. Marc Bestmann
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Correspondence to Florian Vahl .

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Editors and Affiliations

  1. LAAS-CNRS/ANITI, Toulouse, France

    Rachid Alami

  2. The University of Texas at Austin, Austin, TX, USA

    Joydeep Biswas

  3. University of Washington, Seattle, WA, USA

    Maya Cakmak

  4. Western Sydney University, Penrith, NSW, Australia

    Oliver Obst

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Bestmann, M. et al. (2022). TORSO-21 Dataset: Typical Objects in RoboCup Soccer 2021. In: Alami, R., Biswas, J., Cakmak, M., Obst, O. (eds) RoboCup 2021: Robot World Cup XXIV. RoboCup 2021. Lecture Notes in Computer Science(), vol 13132. Springer, Cham. https://doi.org/10.1007/978-3-030-98682-7_6

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  • DOI: https://doi.org/10.1007/978-3-030-98682-7_6

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