UTBM Robocar Dataset

UTBM Robocar Dataset是由法国贝尔福-蒙贝利亚尔技术大学开发的多传感器自动驾驶数据集。该数据集包含多种传感器数据，如摄像头、激光雷达、雷达等，旨在支持自动驾驶车辆的环境感知和定位研究。数据集涵盖城市和郊区环境，捕捉了日常和季节变化，特别适合长期自动驾驶研究。创建过程中，数据集利用ROS系统进行数据处理和同步，提供了车辆定位的地面真实轨迹。该数据集的应用领域包括自动驾驶车辆的感知、定位、路径规划和决策制定，旨在解决自动驾驶车辆在复杂环境中的安全导航问题。

UTBM Robocar Dataset is a multi-sensor autonomous driving dataset developed by the University of Technology of Belfort-Montbéliard (UTBM) in France. It includes multiple sensor modalities such as cameras, LiDAR, radar and others, and is designed to support research on environmental perception and positioning of autonomous vehicles. The dataset covers urban and suburban environments, captures daily and seasonal changes, and is particularly suitable for long-term autonomous driving research. During the dataset construction, the ROS (Robot Operating System) was employed for data processing and synchronization, and ground-truth vehicle positioning trajectories are provided. The application domains of this dataset cover perception, positioning, path planning and decision-making for autonomous vehicles, with the goal of addressing safe navigation challenges for autonomous vehicles in complex environments.