Zhang Yiujia, Ahmadi SeyedMostafa, Kang Jungwon, Arjmandi Zahra, Sohn Gunho
Department of Earth and Space Science and Engineering, Lassonde School of Engineering, York University, Toronto, ON, Canada.
School of Instrument Science and Engineering, Southeast University, Nanjing, China.
Int J Rob Res. 2025 Jan;44(1):3-21. doi: 10.1177/02783649241261079. Epub 2024 Jun 13.
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/.
约克大学Teledyne Optech（YUTO）移动测绘系统（MMS）数据集包含四个序列，总长20.1公里，是通过2020年8月12日和2019年6月21日的两次数据采集考察全面汇编而成的。采集工作使用了一辆独特装备的车辆，配备了全景相机、倾斜激光雷达、全球定位系统（GPS）和惯性测量单元（IMU），行驶经过两个战略地点：加拿大多伦多的约克大学基尔校区和加拿大旺市的Teledyne Optech总部。本文不仅阐述了YUTO MMS数据集的全面概述，深入探讨了采集程序、传感器配置、同步、数据结构和格式等方面，还给出了主流同时定位与地图构建（SLAM）系统的强大基准测试。通过使用引入的数据集对它们进行分析，本研究为后续研究奠定了基础基线，从而有助于推动集成SLAM的移动测绘系统的进步与改进。该数据集可从以下网址下载：https://ausmlab.github.io/yutomms/ 。
