Abstract
The integration of robot vision techniques, specifically focused on 3D reconstruction, assumes paramount significance in the construction sector, serving as a key enabler for fulfilling the imperative digitalization prerequisites inherent to the principles of Industry 4.0. This study proposes a real-time 3D reconstruction pipeline, based on common algorithms, that utilizes both RGB and depth information. Specifically, it delves into a comprehensive evaluation of InfiniTAM [5] and introduces a novel pipeline, that involves the integration of InfiniTAM with either ORB-SLAM3 [1] or RTAB-Map [3], aiming to enhance the accuracy of 3D surface reconstruction, especially in the context of robotic operations. The insights derived from this study facilitate the implementation of a robust 3D reconstruction methodology applicable to the construction industry.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Campos, C., Elvira, R., Rodríguez, J.J.G., Montiel, J.M.M., Tardós, J.D.: ORB-SLAM3: an accurate open-source library for visual, visual-inertial and multi-map SLAM. CoRR abs/2007.11898 (2020)
Hong, K., Wang, H., Yuan, B.: Inspection-NeRF: rendering multi-type local images for dam surface inspection task using climbing robot and neural radiance field. Buildings 13(1) (2023)
Labbé, M., Michaud, F.: RTAB-map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation: LabbÉ and michaud. J. Field Robot. 36 (2018)
Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: NeRF: representing scenes as neural radiance fields for view synthesis (2020)
Prisacariu, V.A., et al.: InfiniTAM v3: a framework for large-scale 3D reconstruction with loop closure. CoRR abs/1708.00783 (2017)
Shang, Z., Shen, Z.: Real-time 3D reconstruction on construction site using visual SLAM and UAV (2018)
Hachisuka, S., Tono, A., fisher, M.: Harbingers of NeRF-to-BIM: a case study of semantic segmentation on building structure with neural radiance fields (2023)
Yeh, C.H., Lin, M.H.: Robust 3D reconstruction using HDR-based slam. IEEE Access 9, 16568–16581 (2021)
Zhao, S., et al.: Application and development of autonomous robots in concrete construction: challenges and opportunities application of unmanned aerial vehicle. Drones 6(12), 424 (2022)
Acknowledgment
This work has been supported by the EU Horizon Europe funded project “RobetArme” under the GA No: 101058731. We extend our gratitude to Christiansen & Essenbaek A/S (CEAS) for providing access to their mock-up construction site premises for data acquisition.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Katsatos, D., Alexiou, D., Kontodina, T., Kostavelis, I., Giakoumis, D., Tzovaras, D. (2024). Real-Time 3D Reconstruction Adapted for Robotic Applications in Construction Sites. In: Secchi, C., Marconi, L. (eds) European Robotics Forum 2024. ERF 2024. Springer Proceedings in Advanced Robotics, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-031-76424-0_44
Download citation
DOI: https://doi.org/10.1007/978-3-031-76424-0_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-76423-3
Online ISBN: 978-3-031-76424-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)