An Edge-Computing UAV Architecture for GPS-Denied Structural Inspection in Reinforced-Concrete Environments: A Prototype-Based Proof-of-Concept Evaluation

While there are evident advantages to deploying UAVs for structural inspection applications within reinforced-concrete structures where human access may be hazardous or restricted, UAV deployment is still inhibited within structures due to a lack of GPS, payload and power limitations, signal attenuation, limited transmission opportunities, and low bandwidth for communication. Within the confines of the present project, a low-cost two-layer six-rotor architecture was developed; a single Pixhawk PX4 manages stabilized flight, while a Raspberry Pi 4 manages mission-level operations. The complete prototype integrated a relative-pose/nearby-object estimator, hybrid 433 MHz and Wi-Fi/MQTT communications, avionics-side energy management, mission continuity via SQLite, and human-in-the-loop fail-safe support. Prototype experiments revealed reduced horizontal drift compared to both tested comparison configurations, continued operation under constrained communication conditions, and a 62.0% reduction in avionics-side power consumption, excluding propulsion. This was followed by a complementary PX4–Gazebo evaluation probing horizontal and vertical proximity responses, six-sector LiDAR processing, and stale-data watchdog functionality. Across 45 repeated simulation runs and 3000 retained sector-level observations, no simulated collisions occurred during the horizontal-approach, vertical-proximity, or watchdog tests. No false sector assignments were observed, and the overall mean absolute error was 0.0285 m. From this limited demonstration, the architecture appears satisfactory at the prototype and simulated-subsystem levels. Further physical testing will be needed prior to operational deployment.

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Publication Details

Journal
Drones
Published
2026-09-04
DOI
https://doi.org/10.3390/drones10090678
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

An Edge-Computing UAV Architecture for GPS-Denied Structural Inspection in Reinforced-Concrete Environments: A Prototype-Based Proof-of-Concept Evaluation

Aytuğ Boyacı, Anıl Sezgin, Nihal Arda AKYILDIZ, Mustafa Ulaş et al.
Drones
UAV Applications and Optimization
article

An Edge-Computing UAV Architecture for GPS-Denied Structural Inspection in Reinforced-Concrete Environments: A Prototype-Based Proof-of-Concept Evaluation

Aytuğ Boyacı, Anıl Sezgin, Nihal Arda AKYILDIZ, Mustafa Ulaş, Betül BEKTAŞ EKİCİ, Merve Açıkgenç Ulaş, Hakan Güler, Nuray Beyza Avcı, Görkem Gök
article en

Abstract

While there are evident advantages to deploying UAVs for structural inspection applications within reinforced-concrete structures where human access may be hazardous or restricted, UAV deployment is still inhibited within structures due to a lack of GPS, payload and power limitations, signal attenuation, limited transmission opportunities, and low bandwidth for communication. Within the confines of the present project, a low-cost two-layer six-rotor architecture was developed; a single Pixhawk PX4 manages stabilized flight, while a Raspberry Pi 4 manages mission-level operations. The complete prototype integrated a relative-pose/nearby-object estimator, hybrid 433 MHz and Wi-Fi/MQTT communications, avionics-side energy management, mission continuity via SQLite, and human-in-the-loop fail-safe support. Prototype experiments revealed reduced horizontal drift compared to both tested comparison configurations, continued operation under constrained communication conditions, and a 62.0% reduction in avionics-side power consumption, excluding propulsion. This was followed by a complementary PX4–Gazebo evaluation probing horizontal and vertical proximity responses, six-sector LiDAR processing, and stale-data watchdog functionality. Across 45 repeated simulation runs and 3000 retained sector-level observations, no simulated collisions occurred during the horizontal-approach, vertical-proximity, or watchdog tests. No false sector assignments were observed, and the overall mean absolute error was 0.0285 m. From this limited demonstration, the architecture appears satisfactory at the prototype and simulated-subsystem levels. Further physical testing will be needed prior to operational deployment.

DronesVol. 10(9)
University of Turku (FI), Teknoloji Arastirma ve Gelistirme Endustriyel Urunler Bilisim Teknolojileri San Tic (TR), Artificial Intelligence in Medicine (Canada) (CA), Istanbul Arel University (TR), Turkish Air Force Academy (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Affordable and clean energy
Openalex Percentile: Top 7%
UAV Applications and Optimization
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