  Unmanned Aerial Systems (UAS) have gained significant traction for their
application in infrastructure inspections. However, considering the enormous
scale and complex nature of infrastructure, automation is essential for
improving the efficiency and quality of inspection operations. One of the core
problems in this regard is electing an optimal automated flight path that can
achieve the mission objectives while minimizing flight time. This paper
presents an effective formulation for the path planning problem in the context
of structural inspections. Coverage is guaranteed as a constraint to ensure
damage detectability and path length is minimized as an objective, thus
maximizing efficiency while ensuring inspection quality. A two-stage algorithm
is then devised to solve the path planning problem, composed of a genetic
algorithm for determining the positions of viewpoints and a greedy algorithm
for calculating the poses. A comprehensive sensitivity analysis is conducted to
demonstrate the proposed algorithm's effectiveness and range of applicability.
Applied examples of the algorithm, including partial space inspection with
no-fly zones and focused inspection, are also presented, demonstrating the
flexibility of the proposed method to meet real-world structural inspection
requirements. In conclusion, the results of this study highlight the
feasibility of the proposed approach and establish the groundwork for
incorporating automation into UAS-based structural inspection mission planning.
