GIO_dataset

Name: GIO_dataset
Creator: Wang, Yusheng
Published: 2026-04-17T17:24:44+08:00

IEEE2026-04-17 收录

里程计研究

自动驾驶定位

数据链接：

https://ieee-dataport.org/documents/giodataset 数据链接链接失效反馈

官方服务：

资源简介：

This is the dataset for 'A General Lightweight Odometry Framework for Intelligent Vehicles' See https://github.com/YushengWHU/GIO_dataset for detailed introduction.

提供机构：

Wang, Yusheng

MagneticPillars++: Efficient LiDAR Odometry Via Deep Frame-To-Keyframe Point Cloud Registration

点云注册

里程计研究

Downstream applications for point cloud registration, like LiDAR Odometry, often conduct Iterative Closest Points (ICP) in the initial frame-to-frame matching and/or subsequent map refinement. However

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Oxford Radar RobotCar Dataset

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里程计研究

Oxford Radar RobotCar 数据集是 Oxford RobotCar 数据集的雷达扩展。它已使用来自 Navtech CTS350-X 毫米波 FMCW 雷达和 Dual Velodyne HDL-32E LIDAR 的数据进行扩展，该雷达具有优化的地面实况雷达里程计，可在英国牛津周围行驶 280 公里（除了原始牛津 RobotCar 中的所有传感器）数据集）。

OpenXLab40

Interactive maps for the visualization of ESRIUM automated driving tests with various EGNSS localization solutions

自动驾驶定位

EGNSS定位测试

In order to make the test results available to a broader audience in an easy manner, we have generated interactive maps. These maps are attached to this report and can be viewed in a web-browser. Due

NIAID Data Ecosystem30

Perth-WA Localization Dataset in 3D Point Cloud Maps

点云定位

自动驾驶定位

Another major contribution of this work is Perth-WA dataset that provides 6DoF annotations for localization. The data comprises a LiDAR map of 4km square region of Perth Central Business District (CBD

DataCite Commons2023-02-28 更新90

Kitti_odom.zip

无人地面车辆

里程计研究

This is the experimental code of A novel 3D liDAR feature learning approach for uncrewed ground vehicle odometry

Figshare2024-05-06 更新30