Ford

我们提供了一个基于改装的福特F-250皮卡的自主地面车辆试验台收集的数据集。该车辆配备了专业 (Applanix POS LV) 和消费者 (Xsens mti-g) 惯性测量单元 (IMU)，Velodyne 3D-lidar扫描仪，两个推扫帚前视Riegl激光雷达和一个Point Grey Ladybug3全向摄像机系统。在这里，我们提供了来自安装在车辆上的这些传感器的时间记录数据，这些数据是在2009年11月到12月期间在福特研究园区和密歇根州迪尔伯恩市中心驾驶车辆时收集的。这些数据集中的车辆路径轨迹包含几个大型和小型环路闭合，这对于测试各种最先进的计算机视觉和SLAM (同时定位和映射) 算法应该是有用的。数据集的大小很大 (约100 GB)，因此在下载数据集之前，请确保您有足够的带宽。

We present a dataset collected from an autonomous ground vehicle testbed based on a modified Ford F-250 pickup truck. This vehicle is equipped with professional (Applanix POS LV) and consumer-grade (Xsens mti-g) inertial measurement units (IMUs), a Velodyne 3D lidar scanner, two push-broom forward-looking Riegl LiDARs, and a Point Grey Ladybug3 omnidirectional camera system. Herein, we provide time-stamped data from these sensors mounted on the vehicle, collected during driving sessions at the Ford Research Campus and downtown Dearborn, Michigan, between November and December 2009. The vehicle path trajectories within this dataset contain several large and small loop closures, which should be useful for testing a variety of state-of-the-art computer vision and SLAM (Simultaneous Localization and Mapping) algorithms. The dataset has a large file size (approximately 100 GB), so please ensure you have sufficient bandwidth before downloading it.

搜集汇总

背景与挑战

背景概述

Ford数据集是一个自动驾驶数据集，基于改装的福特F-250皮卡测试平台，搭载了专业和消费级IMU、激光雷达及全向摄像机等传感器。数据于2009年11月至12月在福特研究园区和迪尔伯恩市中心收集，包含多个环路闭合路径，适用于计算机视觉和SLAM算法测试，总大小约100GB。