Reality-Capture Technologies for Automated Quality-Control During Construction 3D Printing (2023-06)¶
Martin Michael, Banijamali Kasra,
Contribution - Proceedings of the ASCE International Conference on Computing in Civil Engineering 2023
Abstract
A low-cost 2D LiDAR sensor and a near real-time data processing algorithm are used in this study to capture the as-built geometry of the freshly printed layers for inline and automated inspection. The accuracy of the proposed system is evaluated under different conditions and layer dimensions. Based on the obtained results, significant improvements were observed after a statistical approach was used for outlier detection and elimination. Maximum error values of less than 1.1 mm were achieved for inline layer width and height measurements using the proposed approach.
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5 References
- Barjuei Erfan, Courteille Eric, Rangeard Damien, Marie F. et al. (2022-07)
Real-Time Vision-Based Control of Industrial Manipulators for Layer-Width Setting in Concrete 3D Printing Applications - Davtalab Omid, Kazemian Ali, Yuan Xiao, Khoshnevis Behrokh (2020-10)
Automated Inspection in Robotic Additive Manufacturing Using Deep Learning for Layer Deformation Detection - Kazemian Ali, Yuan Xiao, Cochran Evan, Khoshnevis Behrokh (2017-04)
Cementitious Materials for Construction-Scale 3D Printing:
Laboratory Testing of Fresh Printing Mixture - Kazemian Ali, Yuan Xiao, Davtalab Omid, Khoshnevis Behrokh (2019-01)
Computer-Vision for Real-Time Extrusion-Quality-Monitoring and Control in Robotic Construction - Nair Sooraj, Sant Gaurav, Neithalath Narayanan (2021-11)
Mathematical Morphology-Based Point-Cloud-Analysis-Techniques for Geometry-Assessment of 3D Printed Concrete Elements
6 Citations
- Banijamali Kasra, Martin Michael, Mascarenas David, Kazemian Ali (2025-11)
Automated Inspection in Robotic 3D Printing:
In-Process Geometrical Measurements Using Structured Light Machine Vision - Cai Yilin, Hartell Julie, Aryal Ashrant (2025-07)
Real-Time Multimodal Sensing System for Additive Construction by Extrusion:
Integrating Thermal, Depth and RGB Data - Banijamali Kasra, Dempsey Mary, Chen Jianhua, Kazemian Ali (2025-02)
Machine Learning Approach to Predict the Early-Age Flexural Strength of Sensor-Embedded 3D-Printed Structures - Martin Michael, Banijamali Kasra, Gilbert Hunter, Mascarenas David et al. (2024-09)
LiDAR-Based Real-Time Geometrical Inspection for Large-Scale Additive Manufacturing - Banijamali Kasra, Vosoughi Payam, Arce Gabriel, Noorvand Hassan et al. (2024-08)
Automated Strength Monitoring of 3D Printed Structures via Embedded Sensors - Giwa Ilerioluwa, Dempsey Mary, Fiske Michael, Kazemian Ali (2024-06)
3D Printed Sulfur-Regolith Concrete Performance Evaluation for Waterless Extraterrestrial Robotic Construction
BibTeX
@inproceedings{mart_bani_kaze.2023.RCTfAQCDC3P,
author = "Michael Martin and Kasra Banijamali and Ali Kazemian",
title = "Reality-Capture Technologies for Automated Quality-Control During Construction 3D Printing",
doi = "10.1061/9780784485224.044",
year = "2023",
booktitle = "Proceedings of the ASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics",
editor = "Yelda Turkan and Joseph Louis and Fernanda Leite and Semiha Ergan",
}
Formatted Citation
M. Martin, K. Banijamali and A. Kazemian, “Reality-Capture Technologies for Automated Quality-Control During Construction 3D Printing”, in Proceedings of the ASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics, 2023. doi: 10.1061/9780784485224.044.
Martin, Michael, Kasra Banijamali, and Ali Kazemian. “Reality-Capture Technologies for Automated Quality-Control During Construction 3D Printing”. In Proceedings of the ASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics, edited by Yelda Turkan, Joseph Louis, Fernanda Leite, and Semiha Ergan, 2023. https://doi.org/10.1061/9780784485224.044.