Automatic Detection and Measurement Method for Road Block on UGVs

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초록

Deep excavation in urban areas has the potential to cause significant economic and human losses by damaging adjacent structures. Prior to such damage, deformation may occur in the sidewalk or road nearest to the construction site. Accurate measurement of deformation levels is crucial for assessing stability in such scenarios, but existing techniques face challenges in achieving precise measurements. In this paper, we propose a novel approach for detecting and measuring block joints using laser sensor data. Our method consists of two key steps: detection and measurement based on laser sensor data. In the detection stage, the proposed method constructs dynamic frames from line data from laser sensor that contain depth information and utilizes these frames to detect block objects. Furthermore, in the measurement stage, it employs a clustering based measurement, called CPLF (Clustered Piecewise Linear Fitting). We built its prototype implementation on an Unmanned Ground Vehicle (UGV) equipped with a laser sensor and performed measurements to quantify its run-time performance. The implementation results show that our proposed approach yields more accurate results within a 1 mm of error.1 © 2023 Owner/Author.

키워드

3D Laser SensorBlock Joint DetectionLine DataSidewalk Block
제목
Automatic Detection and Measurement Method for Road Block on UGVs
저자
Shin, JiwooKim, SeoyeonKim, TaesikJung, Jinman
DOI
10.1145/3599957.3606247
발행일
2023
유형
Conference paper
저널명
2023 Research in Adaptive and Convergent Systems RACS 2023