The Symphony Lake Dataset consists of 121 visual surveys of a lakeshore over more than three years in Metz, France. Unique from roadway datasets, it adds breadth to a
space at a time when larger and more diverse datasets are needed to train data hungry machine learning methods. Over 5 million images from
an unmanned surface vehicle capture the unstructured, natural environment as it evolved over time. Significant variation in appearance
is present on time scales of weeks, seasons, and years. Success in this space may demonstrate advancements in perception, SLAM, and environment monitoring.
The data presented in this page includes the results of our 2D multi-session SLAM research using the 2D LIDAR data combined with ICP
The archive below includes three types of data: the map point clouds in a CSV format compatible with LibPointMatcher, the boat trajectories and a PNG image for each survey, similar to the one below.
© 2019 DREAM Lab – Georgia Institute of Technology Lorraine