YUTO MMS: A comprehensive SLAM dataset for urban mobile mapping with tilted LiDAR and panoramic camera integration

Yiujia Zhang, SeyedMostafa Ahmadi, Jungwon Kang, Zahra Arjmandi, Gunho Sohn
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Abstract

The York University Teledyne Optech (YUTO) Mobile Mapping System (MMS) Dataset, encompassing four sequences totaling 20.1 km, was thoroughly assembled through two data collection expeditions on August 12, 2020, and June 21, 2019. Acquisitions were performed using a uniquely equipped vehicle, fortified with a panoramic camera, a tilted LiDAR, a Global Positioning System (GPS), and an Inertial Measurement Unit (IMU), journeying through two strategic locations: the York University Keele Campus in Toronto and the Teledyne Optech headquarters in City of Vaughan, Canada. This paper not only delineates the comprehensive overview of the YUTO MMS dataset, delving into aspects such as the collection procedure, sensor configuration, synchronization, data structure and format but also presents a robust benchmark of prevailing Simultaneous Localization and Mapping (SLAM) systems. By subjecting them to analysis utilizing the introduced dataset, this research lays a foundational baseline for ensuing studies, thereby contributing to advancements and enhancements in the SLAM-integrated mobile mapping system. The dataset can be downloaded from: https://ausmlab.github.io/yutomms/ .
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YUTO MMS:集成倾斜激光雷达和全景相机的城市移动制图综合 SLAM 数据集
约克大学 Teledyne Optech(YUTO)移动测绘系统(MMS)数据集包括四个序列,总长 20.1 公里,分别于 2020 年 8 月 12 日和 2019 年 6 月 21 日通过两次数据采集考察彻底完成。采集工作由一辆配备了全景相机、倾斜式激光雷达、全球定位系统(GPS)和惯性测量单元(IMU)的独特车辆完成,途经两个战略要地:位于多伦多的约克大学基尔校区和位于加拿大沃恩市的 Teledyne Optech 总部。本文不仅全面概述了 YUTO MMS 数据集,深入探讨了收集程序、传感器配置、同步、数据结构和格式等方面的问题,而且还为当前的同步定位和绘图(SLAM)系统提供了一个强大的基准。通过利用引入的数据集对其进行分析,本研究为后续研究奠定了基础,从而有助于推进和改进集成 SLAM 的移动测绘系统。数据集可从以下网址下载: https://ausmlab.github.io/yutomms/ 。
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