LiDAR-based real-time geometrical inspection for large-scale additive manufacturing

This study proposes an automated real-time inspection methodology using 2D LiDAR for construction-scale additive manufacturing, aimed at prompt defect detection and preventing excessive layer deformations during the robotic fabrication process. Two new data processing algorithms are designed, implemented, and compared with benchmark data to conduct a comprehensive analysis. The proposed inspection module is integrated into the concrete printing machine, eliminating the need for an additional inspection robot—an important consideration for fabrication operations in outdoor and remote environments. Based on the quantitative data from a systematic experimental program, the proposed Variable Standard Deviation (VSD) algorithm continuously performs extrudate width and height measurements with an average error of less than 1.2 mm and maximum error values under 1.33 mm when data collection cycles longer than 1 s are adopted. The findings of this study also provide new insights into the influence of the data collection cycle, extrudate size and number of layers, and extruder traversal speed on the performance of the proposed scanning system.