UAS-based Automated Structural Inspection Path Planning via Visual Data Analytics and Optimization

TL;DR

This paper introduces a novel two-stage optimization algorithm for planning UAS flight paths in structural inspections, balancing coverage, efficiency, and inspection quality through genetic and greedy algorithms.

Contribution

It presents a new formulation and a two-stage algorithm combining genetic and greedy methods for optimal UAS inspection path planning, considering real-world constraints.

Findings

Effective path planning with coverage guarantees

Demonstrated flexibility in complex inspection scenarios

Validated approach through comprehensive sensitivity analysis

Abstract

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.