Automated method improves dimensional accuracy in retaining grid frame structures, enhancing safety over manual inspections.
• End-to-end automated as-built management of retaining grid frame structures. • Segmentation, cross-sectioning and dimension extraction performed on point clouds. • Field test on a 60 m curved slope achieved 0.02 m mean dimensional error. • Method reached F1 = 0.92 for slope surface detection on TLS and HLS datasets. • Replaces hazardous rope-work with safe remote point-cloud inspection. Extreme weather and earthquakes are boosting demand for slope protection on steep terrain. Retaining grid frame structures—lattice-type concrete grids—must be surveyed precisely, yet rope-work-based manual measurements are labour-intensive and hazardous. This paper presents an as-built management method that (1) separates grid frame and slope surfaces in point cloud data, (2) creates cross-sections, and (3) outputs width, height and frame center distance for every frame. Tests on a 60 m curved site in Fukushima showed mean dimensional error of 0.02 m, satisfying the Japanese guideline tolerances (±0.10 m for frame center distance and ± 0.03 m for both width and height), and an F1-score of 0.92 for slope surface detection with reliable rope removal. The workflow lowers field labour, enhances safety.
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Umehara et al. (2026) studied this question.
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