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Keypoint-Based Geometric Anomaly Analysis Method for Antennas Using an EO Sensor Mounted on an Unmanned Vehicle

무인이동체 탑재 EO 센서를 활용한 키포인트 기반 안테나 기하학적 이상 분석 기법

  • Yusun Ahn (Electronics and Telecommunications Research Institute, Defense & Safety Intelligence Research Section) ;
  • ihun Jeon (Electronics and Telecommunications Research Institute, Defense & Safety Intelligence Research Section) ;
  • Kangbok Lee (Electronics and Telecommunications Research Institute, Defense & Safety Intelligence Research Section)
  • 안유선 (한국전자통신연구원 국방안전지능화연구실) ;
  • 전지훈 (한국전자통신연구원 국방안전지능화연구실) ;
  • 이강복 (한국전자통신연구원 국방안전지능화연구실)
  • Received : 2025.08.20
  • Accepted : 2025.10.23
  • Published : 2025.12.05

Abstract

This study proposes a keypoint-based structural anomaly analysis system using Electro-Optical(EO) sensors mounted on unmanned ground vehicles. Unlike conventional object detection approaches, which struggle to interpret fine-grained structural deviations, the proposed method extracts keypoints of components and evaluates their geometric relationships-such as relative height ratios and tilt angles-to assess structural integrity. A three-stage pipeline consisting of object detection, keypoint detection, and post-processing validation is implemented. Experiments under various rotated conditions (0°, 90°, 135°, and 180°) show that the proposed method achieves error rates below 0.5 %, significantly outperforming conventional bounding box-based methods, which show over 50 % error. The system also demonstrates strong robustness against occlusion, viewpoint variation, and partial visibility. These results highlight the system's potential for real-time autonomous diagnostics, predictive maintenance, and quantitative evidence-based monitoring in dynamic field environments.

Keywords

Acknowledgement

본 연구는 대한민국 정부(산업통상자원부 및 방위사업청) 재원으로 민군협력진흥원에서 수행하는 민군 기술협력사업의 연구비 지원으로 수행되었습니다. (과제번호 23-CM-TC-13)

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