Liu, Jiucai  ORCID: https://orcid.org/0009-0001-7056-8983, Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133, Wang, Dalei, Chai, Chengzhang ORCID: https://orcid.org/0000-0001-6911-8048 and Dong, Yiqing
2025.
Semantic-PolygonGraph driven context-aware coverage path planning for infrastructure visual inspection.
Advanced Engineering Informatics
68
(Part A)
, 103580.
10.1016/j.aei.2025.103580
|
Preview |
PDF
- Accepted Post-Print Version
Available under License Creative Commons Attribution No Derivatives. Download (6MB) | Preview |
Abstract
Automatic infrastructure visual inspection using Unmanned Aerial Vehicles (UAVs) enhances efficiency and safety. However, existing approaches lack context-aware path planning capabilities, often leading to redundant inspections without focus. To address this limitation, this study introduces a novel infrastructure inspection paradigm that integrates 3D coverage path planning (3D-CPP), real-time data interpretation, and inspection information management, to generate and refine 3D-CPP progressively based on recorded information and real-time observation. The proposed paradigm consists of two main components. First, a graph-based information management system named Semantic-PolygonGraph is developed to incorporate static information from Industry Foundation Classes (IFC) alongside dynamically accumulated inspection data. Second, leveraging this structured representation, a progressive 3D-CPP method is proposed to generates an adaptive inspection path that dynamically refines itself based on task requirements, historical records, and real-time observations, prioritizing regions exhibiting superficial damage. To evaluate the effectiveness of the proposed paradigm, this study introduces a data quality assessment metric to quantify the trade-off between inspection cost and data quality. Simulated case studies demonstrate that the proposed approach improves data quality with limited increase of inspection costs, highlighting its potential for long-term infrastructure maintenance.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Engineering |
| Publisher: | Elsevier |
| ISSN: | 1474-0346 |
| Date of First Compliant Deposit: | 4 July 2025 |
| Date of Acceptance: | 20 June 2025 |
| Last Modified: | 03 Jul 2026 01:45 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/179552 |
Actions (repository staff only)
 |
Edit Item |
Altmetric
Altmetric