Multimodal Dataset from Harsh Sub-Terranean Environment with Aerosol Particles for Frontier Exploration

本数据集名为‘Multimodal Dataset from Harsh Sub-Terranean Environment with Aerosol Particles for Frontier Exploration’，由吕勒奥理工大学的机器人与人工智能团队创建。该数据集包含来自恶劣地下环境的多模态数据，特别是在存在气溶胶颗粒的情况下。数据集内容包括来自多种传感器（如雷达、激光雷达、红外摄像机）的同步原始数据测量，旨在支持地下环境中的自主导航和定位算法。创建过程中，数据集通过ROS格式记录，确保数据的可评估性和算法开发的便利性。该数据集主要应用于地下环境的前沿探索，特别是在视觉退化条件下，如黑暗和气溶胶颗粒影响下的自主导航和障碍物检测。

This dataset is named 'Multimodal Dataset from Harsh Sub-Terranean Environment with Aerosol Particles for Frontier Exploration', and it is developed by the Robotics and Artificial Intelligence Team at Luleå University of Technology. This dataset contains multimodal data collected from harsh subterranean environments, specifically under conditions with aerosol particles. It includes synchronized raw sensor measurements from various sensors such as radar, LiDAR, and infrared cameras, which is designed to support autonomous navigation and positioning algorithms for subterranean environments. All data within the dataset was recorded in ROS format during its creation to ensure data evaluability and ease of algorithm development. This dataset is primarily utilized for frontier exploration of subterranean environments, especially for autonomous navigation and obstacle detection under visually degraded conditions such as darkness and interference from aerosol particles.