Into the dirt: Datasets of sewer networks with aerial and ground platforms

This paper presents an unprecedented set of data in a challenging underground environment: the visitable sewers of Barcelona. To the best of our knowledge, this is the first data set involving ground and aerial robots in such scenario: the sewer inspection autonomous robot (SIAR) ground robot and the autonomous robot for sewer inspection aerial platform. These platforms captured data from a great variety of sensors, including sequences of red green blue-depth (RGB-D) images with their onboard cameras. The set consists of 14 logs of experiments that were obtained in more than 10 different days and in four different locations. The complete length of the experiments in the data set exceeds 5 km. In addition, we provide the users with a partial ground-truth and baselines of the localization of the platforms, which can be used for testing their localization and simultaneous localization and mapping (SLAM) algorithms. We also provide details on the setup and execution of each mission and a partial labeling of the elements found in the sewers. All the data were recorded by using the rosbag tool from robot operating system framework. Our goal is to make the data available to the scientific community as a benchmark to test localization, SLAM and classification algorithms in underground environments. The data set are available at .

Automated summary

This paper presents a unique dataset collected in the visitable sewers of Barcelona, involving ground and aerial robots. The dataset includes a variety of sensor data, with experiments exceeding 5 km in length. Users can utilize this dataset for testing localization, SLAM, and classification algorithms in underground environments.