Publications / 2024 Proceedings of the 41st ISARC, Lille, France

Towards autonomous shotcrete construction: semantic 3D reconstruction for concrete deposition using stereo vision and deep learning

Patrick Schmidt, Dimitrios Katsatos, Dimitrios Alexiou, Ioannis Kostavelis, Dimitrios Giakoumis, Dimitrios Tzovaras, Lazaros Nalpantidis
Pages 896-903 (2024 Proceedings of the 41st ISARC, Lille, France, ISBN 978-0-6458322-1-1, ISSN 2413-5844)
Abstract:

The adoption of autonomous systems is a foreseeable necessity in the construction sector due to work hazards and labor shortages. This paper presents a semantic 3D understanding module that creates 3D models of construction sites with highlighted regions of interest for shotcrete application. The approach uses YOLOv8m-seg and SiamMask for robust semantic segmentation together with RTAB-Map and InfiniTAM for visual odometry and 3D reconstruction. Our method is the first step towards a novel, autonomous robot for shotcrete spraying and finishing. The effectiveness of our approach is shown on a mock-up construction site and provides evidence for the applicability of robotic construction.

Keywords: Construction Robotics, 3D Reconstruction, Semantic Segmentation, Shotcrete Automation