Ground-Level Surface Reconstruction and Soil Volume Estimation in Construction Sites Using Marching Cubes Method
Accurate environmental sensing is pivotal for advancing automation in construction, particularly in autonomous excavation. Precise 3D representations of complex and dynamic site geometries is essential for obstacle detection, progress monitoring, and safe operation. However, existing sensing techniq...
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MDPI AG
2025-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/13/7595 |
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| author | Fattah Hanafi Sheikhha Jaho Seo Hanmin Lee |
| author_facet | Fattah Hanafi Sheikhha Jaho Seo Hanmin Lee |
| author_sort | Fattah Hanafi Sheikhha |
| collection | DOAJ |
| description | Accurate environmental sensing is pivotal for advancing automation in construction, particularly in autonomous excavation. Precise 3D representations of complex and dynamic site geometries is essential for obstacle detection, progress monitoring, and safe operation. However, existing sensing techniques often struggle with capturing irregular surfaces and incomplete data in real-time, leading to significant challenges in practical deployment. To address these gaps, we present a novel framework integrating curve approximation, surface reconstruction, and marching cubes algorithm to transform raw sensor data into a detailed and computationally efficient soil surface representation. Our approach improves site modeling accuracy, paving the way for reliable and efficient construction automation. This paper enhances sensory data quality using surface reconstruction techniques, followed by the marching cubes algorithm to generate an accurate and flexible 3D soil model. This model facilitates rapid estimation of soil volume, weight, and shape, offering an efficient approach for environmental analysis and decision-making in automated systems. Experimental validation demonstrated the effectiveness of the proposed method, achieving relative errors of 4.92% and 1.42% across two excavation cycles. Additionally, the marching cubes algorithm completed volume estimation in just 0.05 s, confirming the approach’s accuracy and suitability for real-time applications in dynamic construction environments. |
| format | Article |
| id | doaj-art-9309e6bd8e2c443bae9e784fedc786a8 |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-9309e6bd8e2c443bae9e784fedc786a82025-08-20T03:16:41ZengMDPI AGApplied Sciences2076-34172025-07-011513759510.3390/app15137595Ground-Level Surface Reconstruction and Soil Volume Estimation in Construction Sites Using Marching Cubes MethodFattah Hanafi Sheikhha0Jaho Seo1Hanmin Lee2Department of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, CanadaDepartment of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, CanadaDepartment of Industrial Machinery DX, Korea Institute of Machinery and Materials, Daejeon 305343, Republic of KoreaAccurate environmental sensing is pivotal for advancing automation in construction, particularly in autonomous excavation. Precise 3D representations of complex and dynamic site geometries is essential for obstacle detection, progress monitoring, and safe operation. However, existing sensing techniques often struggle with capturing irregular surfaces and incomplete data in real-time, leading to significant challenges in practical deployment. To address these gaps, we present a novel framework integrating curve approximation, surface reconstruction, and marching cubes algorithm to transform raw sensor data into a detailed and computationally efficient soil surface representation. Our approach improves site modeling accuracy, paving the way for reliable and efficient construction automation. This paper enhances sensory data quality using surface reconstruction techniques, followed by the marching cubes algorithm to generate an accurate and flexible 3D soil model. This model facilitates rapid estimation of soil volume, weight, and shape, offering an efficient approach for environmental analysis and decision-making in automated systems. Experimental validation demonstrated the effectiveness of the proposed method, achieving relative errors of 4.92% and 1.42% across two excavation cycles. Additionally, the marching cubes algorithm completed volume estimation in just 0.05 s, confirming the approach’s accuracy and suitability for real-time applications in dynamic construction environments.https://www.mdpi.com/2076-3417/15/13/7595surface reconstructionmarching cubessensingautonomous excavationconstruction site |
| spellingShingle | Fattah Hanafi Sheikhha Jaho Seo Hanmin Lee Ground-Level Surface Reconstruction and Soil Volume Estimation in Construction Sites Using Marching Cubes Method Applied Sciences surface reconstruction marching cubes sensing autonomous excavation construction site |
| title | Ground-Level Surface Reconstruction and Soil Volume Estimation in Construction Sites Using Marching Cubes Method |
| title_full | Ground-Level Surface Reconstruction and Soil Volume Estimation in Construction Sites Using Marching Cubes Method |
| title_fullStr | Ground-Level Surface Reconstruction and Soil Volume Estimation in Construction Sites Using Marching Cubes Method |
| title_full_unstemmed | Ground-Level Surface Reconstruction and Soil Volume Estimation in Construction Sites Using Marching Cubes Method |
| title_short | Ground-Level Surface Reconstruction and Soil Volume Estimation in Construction Sites Using Marching Cubes Method |
| title_sort | ground level surface reconstruction and soil volume estimation in construction sites using marching cubes method |
| topic | surface reconstruction marching cubes sensing autonomous excavation construction site |
| url | https://www.mdpi.com/2076-3417/15/13/7595 |
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