# Bold Hearts Team Description for RoboCup 2019 (Humanoid Kid Size League)

Source: [Bold Hearts Team Description for RoboCup 2019 (Humanoid Kid Size League)](<https://www.sota2.com/research/paper/68fa65a91e209131cea0bbb9>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:32:37.817Z

Authors: Marcus M. Scheunemann, Sander G. van Dijk, Rebecca Miko, Daniel Barry, George M. Evans, Alessandra Rossi, Daniel Polani

Published: 2019-04-22T21:10:25.000Z

## Abstract

We participated in the RoboCup 2018 competition in Montreal with our newly developed BoldBot based on the Darwin-OP and mostly self-printed custom parts. This paper is about the lessons learnt from that competition and further developments for the RoboCup 2019 competition. Firstly, we briefly introduce the team along with an overview of past achievements. We then present a simple, standalone 2D simulator we use for simplifying the entry for new members with making basic RoboCup concepts quickly accessible. We describe our approach for semantic-segmentation for our vision used in the 2018 competition, which replaced the lookup-table (LUT) implementation we had before. We also discuss the extra structural support we plan to add to the printed parts of the BoldBot and our transition to ROS 2 as our new middleware. Lastly, we will present a collection of open-source contributions of our team.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1904.10066>)

[PDF](<https://arxiv.org/pdf/1904.10066.pdf>)