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 https://robotics.upo.es/datasets/echord.

中文翻译：

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陷入泥土：具有空中和地面平台的下水道网络数据集

本文提供了一个充满挑战的地下环境中前所未有的数据集：巴塞罗那可访问的下水道。据我们所知，这是在这种情况下涉及地面和空中机器人的第一个数据集：下水道检查自治机器人（SIAR）地面机器人和下水道检查空中平台自治机器人。这些平台从各种各样的传感器捕获数据，包括使用车载摄像头拍摄的红色，绿色，蓝色深度（RGB-D）图像序列。该组包含14个实验日志，这些日志是在10多个不同的日期和四个不同的位置获得的。数据集中实验的全长超过5 km。此外，我们为用户提供了平台本地化的部分基础和基线，可用于测试其定位以及同时定位和映射（SLAM）算法。我们还提供有关每个任务的设置和执行的详细信息，以及下水道中所含元素的部分标签。使用机器人操作系统框架中的rosbag工具记录了所有数据。我们的目标是将数据提供给科学界，作为在地下环境中测试定位，SLAM和分类算法的基准。数据集位于https://robotics.upo.es/datasets/echord。我们的目标是将数据提供给科学界，作为在地下环境中测试定位，SLAM和分类算法的基准。数据集位于https://robotics.upo.es/datasets/echord。我们的目标是将数据提供给科学界，作为在地下环境中测试定位，SLAM和分类算法的基准。数据集位于https://robotics.upo.es/datasets/echord。