Litcius/Paper detail

Dataset collection from a SubT environment

Anton Koval, Samuel Karlsson, Sina Sharif Mansouri, Christoforos Kanellakis, Ilias Tevetzidis, Jakub Haluška, Ali‐akbar Agha‐mohammadi, George Nikolakopoulos

2022Robotics and Autonomous Systems21 citationsDOIOpen Access PDF

Abstract

This article presents a dataset collected from the subterranean (SubT) environment with a current state-of-the-art sensors required for autonomous navigation. The dataset includes sensor measurements collected with RGB, RGB-D, event-based and thermal cameras, 2D and 3D lidars, inertial measurement unit (IMU), and ultra wideband (UWB) positioning systems which are mounted on the mobile robot. The overall sensor setup will be referred further in the article as a data collection platform. The dataset contains synchronized raw data measurements from all the sensors in the robot operating system (ROS) message format and video feeds collected with action and 360 cameras. A detailed description of the sensors embedded into the data collection platform and a data collection process are introduced. The collected dataset is aimed for evaluating navigation, localization and mapping algorithms in SubT environments. This article is accompanied with the public release of all collected datasets from the SubT environment. Link: Dataset

Topics & Concepts

Computer scienceInertial measurement unitData collectionRGB color modelArtificial intelligenceReal-time computingProcess (computing)Simultaneous localization and mappingEvent (particle physics)Computer visionRobotMobile robotMathematicsPhysicsQuantum mechanicsOperating systemStatisticsRobotics and Sensor-Based LocalizationRobotics and Automated SystemsIndoor and Outdoor Localization Technologies