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

Alejo Teissière, DavidFrançois Chataigner,Daniel Serrano,Merino, LuisCaballero, Fernando2026-01-202026-01-202021Alejo D, Chataigner F, Serrano D, Merino L, Caballero F. Into the dirt: Datasets of sewer networks with aerial and ground platforms. J Field Robotics. 2021; 38: 105–120. https://doi.org/10.1002/rob.2197610.1002/rob.21976https://hdl.handle.net/10433/25692Ministerio de Ciencia, Innovación y Universidades. Grant Number: RTI2018-100847-B-C22 Agència per a la Competitivitat de l'Empresa FP7 Information and Communication Technologies. Grant Number: 601116 Ministerio de Ciencia e Innovación. Grant Number: FJCI-2015-25700This paper presents an unprecedented set of data in a challenging undergroundenvironment: the visitable sewers of Barcelona. To the best of our knowledge, this isthe first data set involving ground and aerial robots in such scenario: the sewerinspection autonomous robot (SIAR) ground robot and the autonomous robot forsewer inspection aerial platform. These platforms captured data from a great varietyof sensors, including sequences of red green blue‐depth (RGB‐D) images with theironboard cameras. The set consists of 14 logs of experiments that were obtained inmore than 10 different days and in four different locations. The complete length ofthe experiments in the data set exceeds 5 km. In addition, we provide the users witha partial ground‐truth and baselines of the localization of the platforms, which canbe used for testing their localization and simultaneous localization and mapping(SLAM) algorithms. We also provide details on the setup and execution of eachmission and a partial labeling of the elements found in the sewers. All the data wererecorded by using the rosbag tool from robot operating system framework. Our goalis to make the data available to the scientific community as a benchmark to testlocalization, SLAM and classification algorithms in underground environments. Thedata set are available at https://robotics.upo.es/datasets/echord.application/pdfenAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Field roboticsSewer inspectionInto the dirt: Datasets of sewer networks with aerial and ground platformsjournal articleopen access