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Intelligent risk-identification Algorithm with Vision and 3D LiDAR Patterns at Damaged Buildings

Intelligent Automation & Soft Computing 2023年第5期36卷 2315-2331页

作者： Dahyeon Kim Jiyoung Min Yongwoo Song Chulsu Kim Junho Ahn Computer Information Technology Korea National University of TransportationChungju27469Korea Department of Railway Vehicle System Engineering Korea National University of TransportationUiwang16106Korea

Existingﬁreﬁghting robots are focused on simple storage orﬁre sup-pression outside buildings rather than detection or *** a large number of robots using expensive equipment is *** study aims to increase the efﬁciency of search and rescue operations and the safety ofﬁreﬁgh-ters by detecting and identifying the disaster site by recognizing collapsed areas,obstacles,and rescuers on-site.A fusion algorithm combining a camera and three-dimension light detection and ranging(3D LiDAR)is proposed to detect and loca-lize the interiors of disaster *** algorithm detects obstacles by analyzingﬂoor segmentation and edge patterns using a mask regional convolutional neural network(mask R-CNN)features model based on the visual data collected from a parallelly connected camera and 3D *** as objects are detected using you only look once version 4(YOLOv4)in the image data to localize persons requiring *** point cloud data based on 3D LiDAR cluster the objects using the density-based spatial clustering of applications with noise(DBSCAN)clustering algorithm and estimate the distance to the actual object using the center point of the clustering *** proposed artiﬁcial intelligence(AI)algorithm was veriﬁed based on individual sensors using a sensor-mounted robot in an actual building to detectﬂoor surfaces,atypical obstacles,and persons requiring ***,the fused AI algorithm was comparatively veriﬁed.

关键词： Three-dimension light detection and ranging vision risk identiﬁcation damaged building robot

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