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Prototyping Fully Autonomous Bridge Visual Inspection based on mobile robots with visual recognition capabilities

 Prototyping Fully Autonomous Bridge Visual Inspection based on mobile robots with visual recognition capabilities
Autor(en): , ,
Beitrag für IABSE Congress: Beyond Structural Engineering in a Changing World, San José, Cost Rica, 25-27 Seotember 2024, veröffentlicht in , S. 969-976
DOI: 10.2749/sanjose.2024.0969
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This research discusses the technical roadmap and prototype development for replacing the human inspectors for bridge visual inspection by autonomous robots. The envisioned mobile robotic system fi...
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Bibliografische Angaben

Autor(en): (ZJU-UIUC Institute, Zhejiang University, Haining, Zhejiang, China.)
(ZJU-UIUC Institute, Zhejiang University, Haining, Zhejiang, China.)
(ZJU-UIUC Institute, Zhejiang University, Haining, Zhejiang, China.)
Medium: Tagungsbeitrag
Sprache(n): Englisch
Tagung: IABSE Congress: Beyond Structural Engineering in a Changing World, San José, Cost Rica, 25-27 Seotember 2024
Veröffentlicht in:
Seite(n): 969-976 Anzahl der Seiten (im PDF): 8
Seite(n): 969-976
Anzahl der Seiten (im PDF): 8
DOI: 10.2749/sanjose.2024.0969
Abstrakt:

This research discusses the technical roadmap and prototype development for replacing the human inspectors for bridge visual inspection by autonomous robots. The envisioned mobile robotic system first navigates and collects high-quality image data of critical structural components based on its own visual recognition of the bridge inspection scenes. The collected data is further post-processed to provide information about structural conditions. Preliminary results in structural component recognition and navigation planning steps are presented. Then, ongoing work to integrate those subsystems into a prototype autonomous system in the laboratory environment is discussed. Finally, the challenges that need to be addressed to realize such a complex autonomous system that performs tasks in the field environment are discussed. This work will motivate further investigations to accelerate the ongoing transformation in autonomous structural inspection.

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