Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper

Egor Davydenko; Ivan Khokhlov; Vladimir Litvinenko; Ilya Ryakin; Ilya Osokin; Azer Babaev

Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper

Robotics 2021-10-19 v1 Artificial Intelligence Computer Vision and Pattern Recognition

Authors: Egor Davydenko , Ivan Khokhlov , Vladimir Litvinenko , Ilya Ryakin , Ilya Osokin , Azer Babaev

Abstract

This article is devoted to the features that were under development between RoboCup 2019 Sydney and RoboCup 2021 Worldwide. These features include vision-related matters, such as detection and localization, mechanical and algorithmic novelties. Since the competition was held virtually, the simulation-specific features are also considered in the article. We give an overview of the approaches that were tried out along with the analysis of their preconditions, perspectives and the evaluation of their performance.

Keywords

robocup humanoid robots kidsize vision localization simulation robotics

Cite

@article{arxiv.2110.08377,
  title  = {Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper},
  author = {Egor Davydenko and Ivan Khokhlov and Vladimir Litvinenko and Ilya Ryakin and Ilya Osokin and Azer Babaev},
  journal= {arXiv preprint arXiv:2110.08377},
  year   = {2021}
}

Comments

15 pages, 10 figures

Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper

Abstract

Keywords

Cite

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