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首页> 外文期刊>The International journal of robotics research >Complex urban dataset with multi-level sensors from highly diverse urban environments
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Complex urban dataset with multi-level sensors from highly diverse urban environments

机译：复杂的城市数据集，具有来自高度多样化的城市环境的多级传感器

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摘要

The high diversity of urban environments, at both the inter and intra levels, poses challenges for robotics research. Such challenges include discrepancies in urban features between cities and the deterioration of sensor measurements within a city. With such diversity in consideration, this paper aims to provide Light Detection and Ranging (LiDAR) and image data acquired in complex urban environments. In contrast to existing datasets, the presented dataset encapsulates various complex urban features and addresses the major issues of complex urban areas, such as unreliable and sporadic Global Positioning System (GPS) data, multi-lane roads, complex building structures, and the abundance of highly dynamic objects. This paper provides two types of LiDAR sensor data (2D and 3D) as well as navigation sensor data with commercial-level accuracy and high-level accuracy. In addition, two levels of sensor data are provided for the purpose of assisting in the complete validation of algorithms using consumer-grade sensors. A forward-facing stereo camera was utilized to capture visual images of the environment and the position information of the vehicle that was estimated through simultaneous localization mapping (SLAM) are offered as a baseline. This paper presents 3D map data generated by the SLAM algorithm in the LASer (LAS) format for a wide array of research purposes, and a file player and a data viewer have been made available via the Github webpage to allow researchers to conveniently utilize the data in a Robot Operating System (ROS) environment. The provided file player is capable of sequentially publishing large quantities of data, similar to the rosbag player. The dataset in its entirety can be found at http://irap.kaist.ac.kr/dataset..
机译：城市环境的高度多样性，介绍了机器人研究的挑战。这些挑战包括城市之间城市特征的差异和城市内传感器测量的恶化。考虑到这种多样性，本文旨在提供在复杂的城市环境中获得的光检测和测距（LIDAR）和图像数据。与现有数据集相比，所呈现的数据集封装了各种复杂的城市特征，并解决了复杂的城市地区的主要问题，例如不可靠，零星的全球定位系统（GPS）数据，多车道道路，复杂建筑结构以及丰富高度动态的物体。本文提供了两种类型的LIDAR传感器数据（2D和3D）以及具有商业级精度和高电平精度的导航传感器数据。此外，提供了两种级别的传感器数据，以辅助使用消费者级传感器的完全验证算法。用于捕获面向前部的立体相机来捕获环境的视觉图像和通过同时定位映射（SLAM）估计的车辆的位置信息作为基线。本文介绍了激光（LAS）格式中的SLAM算法生成的3D地图数据，用于广泛的研究目的，以及通过GitHub网页提供文件播放器和数据查看器，以允许研究人员方便地利用数据在机器人操作系统（ROS）环境中。提供的文件播放器能够顺序地发布大量数据，类似于ROSBAG播放器。可以全身的数据集在http://irap.kaist.ac.kr/dataset上找到..

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  • 来源
    《The International journal of robotics research》 |2019年第6期|642-657|共16页
  • 作者

    Jeong Jinyong; Cho Younggun; Shin Young-Sik; Roh Hyunchul; Kim Ayoung;

  • 作者单位

    Korea Adv Inst Sci & Technol Dept Civil & Environm Engn 291 Daehak Ro Daejeon 34141 South Korea;

    Korea Adv Inst Sci & Technol Dept Civil & Environm Engn 291 Daehak Ro Daejeon 34141 South Korea;

    Korea Adv Inst Sci & Technol Dept Civil & Environm Engn 291 Daehak Ro Daejeon 34141 South Korea;

    Dyphi Co Daejeon South Korea;

    Korea Adv Inst Sci & Technol Dept Civil & Environm Engn 291 Daehak Ro Daejeon 34141 South Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Dataset; urban; LiDARs; cameras; SLAM;

    机译：数据集;城市;Lidars;相机;猛击;

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