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ConSLAM: Periodically Collected Real-World Construction Dataset for SLAM and Progress Monitoring

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Peer-reviewed

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Conference Object

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Authors

Pluta, Kacper 
Fathy, Yasmin 
Alcalde, Lucio 
Chee, Stanley 

Abstract

Hand-held scanners are progressively adopted to workflows on con- struction sites. Yet, they suffer from accuracy problems, preventing them from deployment for demanding use cases. In this paper, we present a real-world dataset collected periodically on a construction site to measure the accuracy of SLAM algorithms that mobile scanners utilize. The dataset contains time-synchronised and spatially registered images and LiDAR scans, inertial data and professional ground-truth scans. To the best of our knowledge, this is the first publicly available dataset which reflects the periodic need of scanning construction sites with the aim of accurate progress monitoring using a hand-held scanner.

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European Conference on Computer Vision Workshops 2022

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Sponsorship
BP, GeoSLAM, Laing O’Rourke, Topcon, Trimble, EU Horizon 2020 BIM2TWIN: Optimal Construction Management & Production Control project under an agreement No. 958398.