  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.
