LIDAR, 360° scanning, crack detection, point‑cloud processing, infrastructure inspection, deep learning, non‑destructive evaluation. 1. Introduction Crack detection is a cornerstone of structural health monitoring (SHM) for civil engineering assets. Early identification enables timely maintenance, extending service life and preventing catastrophic failures. Traditional inspection techniques—handheld visual surveys, hammer probing, or 2‑D photogrammetry—suffer from several drawbacks:
A. Smith¹, B. Lee², C. Martínez³, D. Khan⁴ lidar360 crack
| Limitation | Conventional Method | 360° LIDAR Approach | |------------|--------------------|---------------------| | | Limited to line‑of‑sight, often requires multiple passes | Whole‑scene capture in a single scan | | Subjectivity | Dependent on inspector experience | Objective geometric measurements | | Speed | Hours to days for large structures | Minutes per scan (≤ 5 min) | | Environmental constraints | Poor lighting, weather sensitivity | Independent of illumination; works in low‑light | | Data richness | 2‑D images only | 3‑D geometry + intensity + RGB (when fused) | Lee², C
¹ Department of Civil Engineering, University of X ² Center for Robotics and Perception, Institute Y ³ Department of Computer Science, University Z ⁴ National Laboratory for Infrastructure Safety weather sensitivity | Independent of illumination
360° LIDAR‑Based Crack Detection and Characterisation for Infrastructure Inspection
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