LiDAR-Assisted UAV Stereo Vision Detection in Railway Freight Transport Measurement
Author:
Li Jiale,Zhou Wei,Gong Wei,Lu Zhaijun,Yan Hongkai,Wei Wanhui,Wang Zhixin,Shen Chao,Pang Jiahong
Abstract
Identifying and detecting the loading size of heavy-duty railway freight cars is crucial in modern railway freight transportation. Due to contactless and high-precision characteristics, light detection and ranging-assisted unmanned aerial vehicle stereo vision detection is significant for ensuring out-of-gauge freight transportation security. However, the precision of unmanned aerial vehicle flight altitude control and feature point mismatch significantly impact stereo matching, thus affecting the accuracy of railway freight measurement. In this regard, the altitude holding control strategy equipped with a laser sensor and SURF_rBRIEF image feature extraction and matching algorithm are proposed in this article for railway freight car loading size measurement. Moreover, an image segmentation technique is used to quickly locate and dismantle critical parts of freight cars to achieve a rapid 2-dimension reconstruction of freight car contours and out-of-gauge detection. The robustness of stereo matching has been demonstrated by external field experiment. The precision analysis and fast out-of-gauge judgment confirm the measurement accuracy and applicability.
Funder
the Special Heavy Load Topic of Science and Technology Research and Development Plan of China Railway Taiyuan Bureau Group Co., Ltd
the Fundamental Research Funds for the Central Universities of Central South University
the Postgraduate Scientific Research Innovation Project of Hunan Province
the National Key R&D Program of China
Subject
Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering
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