Automated Multi-Camera Inspection System for Aircraft

Authors

  • Mark David Rice Institute for Infocomm Research (I2R), A*STAR
  • Gu Ying Institute for Infocomm Research (I2R), A*STAR
  • Kelvin Wei Lim Institute for Infocomm Research (I2R), A*STAR
  • Qing Yu Hoo Institute for Infocomm Research (I2R), A*STAR
  • Liyuan Li Institute for Infocomm Research (I2R), A*STAR
  • Lee Jue Ying Institute for Infocomm Research (I2R), A*STAR
  • Jacky Jie Wei Tan Institute for Infocomm Research (I2R), A*STAR
  • Lai Xing Ng Institute for Infocomm Research (I2R), A*STAR
  • Jamie Ng Institute for Infocomm Research (I2R), A*STAR

DOI:

https://doi.org/10.1609/aaai.v40i48.42378

Abstract

In this paper, we present the development of an automated visual inspection system designed to detect defects on the upper surface of an aircraft airframe. Specifically, the system employs a multi-camera PTZ (Pan-Tilt-Zoom) set-up to capture and process images from designated regions. Custom developed software manages path planning and camera localization, while a hybrid-AI framework is integrated to identify various defect types, including missing and damaged components. The demonstration highlights the system’s detection capabilities and prototype functionalities using a large aircraft model, supported by a user interface to monitor progress and visualize results. To help validate this work, performance evaluations were conducted using selected multimodal and object detection models.

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Published

2026-03-14

How to Cite

Rice, M. D., Ying, G., Lim, K. W., Hoo, Q. Y., Li, L., Ying, L. J., … Ng, J. (2026). Automated Multi-Camera Inspection System for Aircraft. Proceedings of the AAAI Conference on Artificial Intelligence, 40(48), 41676–41678. https://doi.org/10.1609/aaai.v40i48.42378