Optimized structural inspection path planning for automated unmanned aerial systems
Year: 2024
Type: article
Abstract: Automation in Unmanned Aerial Systems (UAS)-based structural inspections has gained significant traction given the scale and complexity of infrastructure. A core problem in UAS-based inspection is electing an optimal flight path to achieve the mission objectives while minimizing flight time. This paper presents an effective two-stage method that guarantees coverage as a constraint to ensure damage detectability, while minimizing path length as an objective. A genetic algorithm first determines viewpoint positions, and a greedy algorithm calculates the camera poses, as opposed to directly optimizing all degrees of freedom (DOF) simultaneously. A sensitivity analysis demonstrates the range of applicability and superiority of this formulation over direct 5-DOF optimization by at least 30 % shorter path length. Applied examples, including focused and partial space inspections, are also presented, demonstrating the flexibility of the proposed method to meet real-world requirements. The results highlight the feasibility of the approach and contribute to incorporating automation into UAS-based structural inspections. • A two-stage optimization for bridge inspection path planning was proposed. • The proposed method outperforms direct 5DOF optimization baseline. • Sensitivity of the proposed method to hyperparameters was studied. • Practical considerations can be seamlessly integrated into the method.
Source: Automation in Construction
Authors: Yuxiang Zhao, Benhao Lu, Mohamad Alipour
Institution: University of Illinois Urbana-Champaign
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,850
Funder: Nvidia
OpenAlex ID: W4402532316
