Adverse Weather Kitti 360

New Dataset: Adverse Weather-Augmented Kitti 360 This dataset enhances the KITTI 360 dataset by adding simulated snow, rain, and fog effects to the original clear-weather scans captured by the Velodyne HDL-64 LiDAR sensor. This allows researchers to evaluate their algorithms for tasks like lidar odometry, SLAM, navigation, and 3D object detection under challenging weather conditions. Scenarios: 9 long-term driving sequences with post-processed GNSS/IMU ground truth localization data. Data per Scan: Points include x, y, z coordinates, intensity, ring/channel information, and a normalized azimuth angle representing time. Weather Masks: Each scan includes a mask that identifies points affected by simulated weather (signal attenuation). Augmented Scans: Three compressed versions (rain, fog, and snow) are provided for each scenario, encoded as binary float32. Original Scans: Downloadable from the KITTI-360 dataset. Data Access: A C++/Python code example demonstrates how to read the data format. This dataset provides a valuable resource for researchers developing robust algorithms that function effectively in adverse weather conditions.

新型数据集：恶劣天气增强型KITTI 360
本数据集对KITTI 360数据集进行增强：针对Velodyne HDL-64激光雷达传感器采集的原始晴朗天气点云扫描数据，添加了模拟降雪、降雨及雾霭效果。这使得研究人员能够在复杂天气条件下，针对激光雷达里程计、同步定位与地图构建（Simultaneous Localization and Mapping，SLAM）、导航及三维目标检测等任务，对其算法开展性能评估。
场景设置：共包含9段长期驾驶序列，配套经过后处理的全球导航卫星系统（Global Navigation Satellite System，GNSS）与惯性测量单元（Inertial Measurement Unit，IMU）真值定位数据。
单帧点云数据：点云包含x、y、z坐标、反射强度、环/通道信息，以及用于表征时间的归一化方位角。
天气掩码：每帧点云均附带掩码，用于标记受模拟天气影响（即信号衰减）的点。
增强型点云：针对每个场景，均提供三种压缩后的增强版本（降雨、雾霭及降雪），编码格式为二进制float32。
原始点云：可从KITTI-360数据集下载。
数据获取：附带C++/Python代码示例，演示如何读取该数据集的格式。
本数据集可为开发在恶劣天气条件下仍能稳定运行的鲁棒算法的研究人员提供宝贵的研究资源。

搜集汇总

背景与挑战

背景概述

该数据集是基于KITTI 360数据集扩展的，通过添加模拟的雪、雨和雾效果，增强了原始晴朗天气下的激光雷达扫描数据，旨在帮助研究人员评估算法在恶劣天气条件下的性能，如激光雷达里程计和3D物体检测。它包含9个驾驶序列，每个扫描点提供详细的空间和强度信息，并附带天气掩码以标识受模拟天气影响的点，为开发鲁棒算法提供了宝贵资源。