Abdalwhab, Abdalwhab, Imran, Ali, Heydarian, Sina, Iordanova, Ivanka et St-Onge, David.
2025.
« Are open-vocabulary models ready for detection of MEP elements on construction sites ».
In 42nd International Symposium on Automation and Robotics in Construction (Montreal, QC, Canada, July 28-31, 2025)
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Résumé
The construction industry has long explored robotics and computer vision, yet their deployment on construction sites remains very limited. These technologies have the potential to revolutionize traditionalworkflows by enhancing accuracy, efficiency, and safety in construction management. Ground robots equipped with advanced vision systems could automate tasks such as monitoring mechanical, electrical, and plumbing (MEP) systems. The present research evaluates the applicability of open-vocabulary vision-language models compared to fine-tuned, lightweight, closed-set object detectors for detecting MEP components using a mobile ground robotic platform. A dataset collected with cameras mounted on a ground robot was manually annotated and analyzed to compare model performance. The results demonstrate that, despite the versatility of vision-language models, fine-tuned lightweight models still largely outperform them in specialized environments and for domain-specific tasks.
| Type de document: | Compte rendu de conférence |
|---|---|
| Professeur: | Professeur Iordanova, Ivanka St-Onge, David |
| Affiliation: | Génie de la construction, Génie mécanique |
| Date de dépôt: | 10 juill. 2025 20:24 |
| Dernière modification: | 01 août 2025 04:00 |
| URI: | https://espace2.etsmtl.ca/id/eprint/31135 |
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