The Obstacle Detection and Avoidance Dataset for Drones

We introduce the Obstacle Detection and Avoidance Dataset for Drones, aiming at providing raw data obtained in a real indoor environment with sensors adapted for aerial robotics. Our micro air vehicle (MAV) is equipped with the following sensors: (i) an event-based camera, the dynamic performance of which make it optimized for drone applications; (ii) a standard RGB camera; (iii) a 24-GHz radar sensor to enhance multi-sensory solutions; and (iv) a 6-axes IMU. The ground truth position and attitude are provided by the OptiTrack motion capture system. The resulting dataset consists in more than 1350 samples obtained in four distinct conditions (one or two obstacles, full or dim light). It is intended for benchmarking algorithmic and neural solutions for obstacle detection and avoidance with UAVs, but also course estimation and therefore autonomous navigation. For further information, please visit: https://github.com/tudelft/ODA_Dataset

本研究提出面向无人机的障碍物检测与避障数据集（Obstacle Detection and Avoidance Dataset for Drones），旨在提供适配空中机器人的传感器在真实室内环境中采集的原始数据。本研究所使用的微型飞行器（micro air vehicle, MAV）搭载了以下传感器：(i) 事件相机（event-based camera），其动态性能使其适配无人机应用场景；(ii) 标准RGB相机；(iii) 24GHz雷达传感器，用于优化多传感融合方案；(iv) 六轴惯性测量单元（6-axes IMU）。数据集的地面真值位置与姿态由OptiTrack动作捕捉系统提供。最终构建的数据集包含超过1350条样本，采集自四种不同工况：单障碍物或双障碍物环境、全光照或弱光照条件。本数据集可用于无人机（Unmanned Aerial Vehicle, UAV）的障碍物检测与避障算法、神经网络方案的基准评测，同时也可用于航迹估计及自主导航相关研究。如需获取更多信息，请访问：https://github.com/tudelft/ODA_Dataset

搜集汇总

背景与挑战

背景概述

该数据集名为'The Obstacle Detection and Avoidance Dataset for Drones'，旨在为无人机提供室内环境下的多传感器原始数据，包括事件相机、RGB相机、雷达传感器和IMU等设备采集的1350多个样本，适用于无人机避障算法和自主导航的基准测试。数据集采用CC0许可，由4TU.ResearchData发布。