# Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper

arXiv: https://arxiv.org/abs/2110.08377 · HTML: https://mlsanity.com/paper/2110.08377/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 7 references that are in the map.
- First posted on arXiv 15 Oct 2021.

## Builds on (most cited first, 2 of 2)

- [Tiny-YOLO object detection supplemented with geometrical data](https://mlsanity.com/paper/2008.02170/) (2020)
- [Planning to Score a Goal in Robotic Football with Heuristic Search](https://mlsanity.com/paper/2008.00851/) (2020)

## Built on by (most cited first, 1 of 1)

- [Multi-Agent Reinforcement Learning and Real-Time Decision-Making in Robotic Soccer for Virtual Environments](https://mlsanity.com/paper/2512.03166/) (2025)

## Abstract (arXiv)

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.