Detecting which pixels in the image belong to the playing field can make it easier and safer to detect other objects such as field lines, other robots and the ball. The field in RoboCup is green. So one way to recognize the field is to classify the pixels by their color, i.e. to recognize if they are green. However, this green detection depends strongly on the lighting and is also susceptible to shadows cast by the robots themselves.
The task of this seminar project is to compare the green detection of 4 different RoboCup SPL teams. For this purpose the algorithms be implemented in Python and evaluated afterwards. A data set will be provided for this purpose.
Based on the comparison, an own solution can be developed. For example, with DNN's for semantic segmentation.
Relevant publications and theses:
- B-Human Teamreport: https://github.com/bhuman/BHumanCodeRelease/raw/master/CodeRelease2019.pdf
- NaoTH Teamreport: https://www2.informatik.hu-berlin.de/~naoth/docs/publications/technical/naoth-report19.pdf
- HTWK Leipzig Teamreport: http://robocup.imn.htwk-leipzig.de/documents/TRR_2018.pdf
- Hulks Hamburg Teamreport: https://hulks.de/_files/TRR_2019.pdf
Information about Nao Team Humboldt
RoboCup Regeln: https://cdn.robocup.org/spl/wp/2021/01/SPL-Rules-2021.pdf
Public Github: https://github.com/BerlinUnited
Internal Gitlab: https://scm.cms.hu-berlin.de/berlinunited
Source code of other RoboCup SPL teams
Public NaoTH Repo: https://github.com/BerlinUnited/NaoTH
Public Nao Devils Repo: https://github.com/NaoDevils/CodeRelease
Public B-human Repo: https://github.com/bhuman/BHumanCodeRelease
rUNSWift: https://github.com/UNSWComputing/rUNSWift-2019-release Hulks: https://github.com/HULKs/HULKsCodeRelease
Publication lists of other teams
Possibly work of other teams can be helpful:
B-Human Abschlussarbeiten: https://b-human.de/theses-en.html
B-Human Publikationen: https://b-human.de/publications-en.html
Supervision and technical support: Heinrich Mellmann
Work in the lab necessary: possibly
Own PC necessary: yes