A Multi-Layer Resilient Architecture for Autonomous Quadcopter-Based Bridge Inspection Under Environmental Uncertainties

This paper presents a multi-layer architecture designed to enhance the reliable autonomous flight of single and multiple quadcopters in simulation. The architecture leverages concepts inspired by the resilient spacecraft executive to hierarchically organize trajectory planning and flight control and integrates an extended Simplex framework that employs multiple candidate algorithms to provide safety assurance at each layer, with a supervisory program that adapts Simplex behavior based on system states and environmental conditions to enable high-level mission management. The approach is evaluated in bridge-inspection simulations under environmental uncertainties, including varying wind conditions and obstacles. Across multiple operating configurations and Monte Carlo simulation runs, the architecture achieves high coverage rates; notably, under high-wind conditions, it reduces average trajectory deviation by 66.2%. The results demonstrate proactive safety through graceful degradation in both trajectory planning and flight control under stress and off-nominal conditions.

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Publication Details

Journal
Drones
Published
2026-02-15
DOI
https://doi.org/10.3390/drones10020136
Primary Topic
Space Satellite Systems and Control
Type
article
Field-Weighted Citation Impact
0.00
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article

A Multi-Layer Resilient Architecture for Autonomous Quadcopter-Based Bridge Inspection Under Environmental Uncertainties

Zhenyu Shi, Donghoon Kim
Drones
Space Satellite Systems and Control
article

A Multi-Layer Resilient Architecture for Autonomous Quadcopter-Based Bridge Inspection Under Environmental Uncertainties

Zhenyu Shi, Donghoon Kim
article en

Abstract

This paper presents a multi-layer architecture designed to enhance the reliable autonomous flight of single and multiple quadcopters in simulation. The architecture leverages concepts inspired by the resilient spacecraft executive to hierarchically organize trajectory planning and flight control and integrates an extended Simplex framework that employs multiple candidate algorithms to provide safety assurance at each layer, with a supervisory program that adapts Simplex behavior based on system states and environmental conditions to enable high-level mission management. The approach is evaluated in bridge-inspection simulations under environmental uncertainties, including varying wind conditions and obstacles. Across multiple operating configurations and Monte Carlo simulation runs, the architecture achieves high coverage rates; notably, under high-wind conditions, it reduces average trajectory deviation by 66.2%. The results demonstrate proactive safety through graceful degradation in both trajectory planning and flight control under stress and off-nominal conditions.

DronesVol. 10(2)
University of Cincinnati (US)
Affordable and clean energy
Openalex Percentile: Top 55%
Space Satellite Systems and Control
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A Multi-Layer Resilient Architecture for Autonomous Quadcopter-Based Bridge Inspection Under Environmental Uncertainties — Zhenyu Shi, Donghoon Kim · Drones (2026) | TGRS Research Map | TGRS