Contribution

We are happy to welcome contributions of any kind. As we experienced many challenges with setting up and stabilizing our choice for algorithms, we look forward to contributions that help to improve our provided SLAM tutorials, the usability of our dataset, and benchmark. This includes, but is not limited to:

• Benchmark of your algorithm on our data
• Dockerfiles
• Configuration files for the presented SLAM algorithms
• Suggestions to Improving our dataset

Please feel free to raise an issue or open a discussion on our Github