ConSLAM: SLAM的建设数据集

IF 4.7 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
M. Trzeciak, K. Pluta, Yasmin Fathy, Lucio Alcalde, Stanley Chee, Antony Bromley, I. Brilakis, P. Alliez
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引用次数: 2

摘要

本文介绍了在建筑工地定期收集的数据集。数据集13旨在评估移动扫描仪或au-14自主机器人使用的SLAM算法的性能。它包括使用地面激光扫描仪收集的建筑工地的地面真实扫描,以及五个空间注册和时间同步图像序列,激光雷达扫描和来自我们的原型手持扫描仪的惯性数据。我们17还通过将连续的激光雷达扫描注册到地面真值扫描来恢复移动扫描仪的地面真值轨迹,并展示了如何使用一个流行的软件包19来自动测量SLAM算法对我们轨迹的准确性。据我们所知,这是第一个可公开访问的数据集,由建筑工地定期收集的连续数据组成。22
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ConSLAM: Construction Data Set for SLAM
12 This paper presents a dataset collected periodically on a construction site. The dataset 13 aims to evaluate the performance of SLAM algorithms used by mobile scanners or au-14 tonomous robots. It includes ground-truth scans of a construction site collected using a ter-15 restrial laser scanner along with five sequences of spatially registered and time-synchronized 16 images, LiDAR scans and inertial data coming from our prototypical hand-held scanner. We 17 also recover the ground-truth trajectory of the mobile scanner by registering the sequential 18 LiDAR scans to the ground-truth scans and show how to use a popular software package 19 to measure the accuracy of SLAM algorithms against our trajectory automatically. To the 20 best of our knowledge, this is the first publicly accessible dataset consisting of periodically 21 collected sequential data on a construction site. 22
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来源期刊
Journal of Computing in Civil Engineering
Journal of Computing in Civil Engineering 工程技术-工程:土木
CiteScore
11.90
自引率
7.20%
发文量
58
审稿时长
6 months
期刊介绍: The Journal of Computing in Civil Engineering serves as a resource to researchers, practitioners, and students on advances and innovative ideas in computing as applicable to the engineering profession. Many such ideas emerge from recent developments in computer science, information science, computer engineering, knowledge engineering, and other technical fields. Some examples are innovations in artificial intelligence, parallel processing, distributed computing, graphics and imaging, and information technology. The journal publishes research, implementation, and applications in cross-disciplinary areas including software, such as new programming languages, database-management systems, computer-aided design systems, and expert systems; hardware for robotics, bar coding, remote sensing, data mining, and knowledge acquisition; and strategic issues such as the management of computing resources, implementation strategies, and organizational impacts.
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