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Intuitive BIM-aided robotic navigation and assets localization with semantic user interfaces

Rafael Gomes Braga, Muhammad Owais Tahir, Sina Karimi, Ulrich Dah-Achinanon, Ivanka Iordanova et David St-Onge

Article de revue (2025)

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Abstract

Introduction: The deployment of mobile robots on construction sites has gained increasing attention from both academic research and industry due to labor shortages and the demand for more efficient project management. However, integrating robotic systems into dynamic and hazardous construction environments remains challenging. Key obstacles include reliance on extensive on-site infrastructure, limited adaptability, and a disconnect between system capabilities and field operators' needs.

Methods: This study introduces a comprehensive, modular robotic platform designed for construction site navigation and asset localization. The system incorporates Building Information Modeling (BIM)-based semantic navigation, active Ultra-Wideband (UWB) beacon tracking for precise equipment detection, and a cascade navigation stack that integrates global BIM layouts with real-time local sensing. Additionally, a user-centric graphical user interface (GUI) was developed to enable intuitive control for non-expert operators, improving field usability.

Results: The platform was validated through real-world deployments and simulations, demonstrating reliable navigation in complex layouts and high localization accuracy. A user study was conducted, confirming improved task efficiency and reduced cognitive load for operators.

Discussion: The results indicate that the proposed system provides a scalable, infrastructure-light solution for construction site robotics. By bridging the gap between advanced robotic technologies and practical deployment, this work contributes to the development of more adaptable and user-friendly robotic solutions for construction environments.

Mots clés

Département: Département de génie informatique et génie logiciel
Organismes subventionnaires: Mitacs and Pomerleau Construction, NSERC
Numéro de subvention: RGPIN-2020-06121
URL de PolyPublie: https://publications.polymtl.ca/63392/
Titre de la revue: Frontiers in Robotics and AI (vol. 12)
Maison d'édition: Frontiers Media
DOI: 10.3389/frobt.2025.1548684
URL officielle: https://www.frontiersin.org/journals/robotics-and-...
Date du dépôt: 18 mars 2025 15:30
Dernière modification: 15 nov. 2025 12:01
Citer en APA 7: Gomes Braga, R., Tahir, M. O., Karimi, S., Dah-Achinanon, U., Iordanova, I., & St-Onge, D. (2025). Intuitive BIM-aided robotic navigation and assets localization with semantic user interfaces. Frontiers in Robotics and AI, 12, 16 pages. https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1548684/abstract

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