LIBRE: LiDAR Benchmarking and Reference

LIBRE数据集是由名古屋大学未来社会创新研究所创建的，包含10种不同LiDAR传感器的数据，覆盖多种制造商、型号和激光配置。数据集内容包括静态目标、恶劣天气和动态交通三种环境下的数据，旨在为自动驾驶车辆和机器人相关软件的开发和调优提供支持。数据集创建过程中，研究人员在不同环境和配置下独立捕捉了每种传感器的数据，包括在控制环境中的静态目标测量、恶劣天气条件下的移动车辆测量以及公共城市道路上的动态交通对象捕捉。LIBRE数据集的应用领域主要集中在自动驾驶车辆和机器人技术，旨在解决LiDAR感知算法在不同环境下的性能评估和优化问题。

The LIBRE dataset was developed by the Institute of Future Social Innovation at Nagoya University. It encompasses data from 10 distinct LiDAR sensors, spanning various manufacturers, models, and laser configurations. The dataset includes data collected under three core environmental scenarios: static targets, adverse weather conditions, and dynamic traffic situations, with the aim of supporting the development and tuning of software for autonomous vehicles and robotics. During the dataset construction process, researchers independently collected data for each sensor across diverse environments and configurations, including static target measurements in controlled environments, moving vehicle measurements under adverse weather conditions, and dynamic traffic object captures on public urban roads. The primary application domains of the LIBRE dataset are autonomous vehicles and robotics, targeting the resolution of performance evaluation and optimization issues for LiDAR perception algorithms across different environments.