Intelligent Risk-Identification Algorithm with Vision and 3D LiDAR Patterns at Damaged Buildings  

作　　者：Dahyeon Kim Jiyoung Min Yongwoo Song Chulsu Kim Junho Ahn 

机构地区：[1]Computer Information Technology,Korea National University of Transportation,Chungju,27469,Korea [2]Department of Railway Vehicle System Engineering,Korea National University of Transportation,Uiwang,16106,Korea

出　　处：《Intelligent Automation & Soft Computing》2023年第5期2315-2331,共17页智能自动化与软计算（英文）

基　　金：supported by Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education(No.2020R1I1A3068274),Received by Junho Ahn.https://www.nrf.re.kr/;supported by the Korea Agency for Infrastructure Technology Advancement(KAIA)by the Ministry of Land,Infrastructure and Transport under Grant(No.22QPWO-C152223-04),Received by Chulsu Kim.https://www.kaia.re.kr/.

摘　　要：Existingfirefighting robots are focused on simple storage orfire sup-pression outside buildings rather than detection or recognition.Utilizing a large number of robots using expensive equipment is challenging.This 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 sites.The 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 LiDAR.People as objects are detected using you only look once version 4(YOLOv4)in the image data to localize persons requiring rescue.The 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 result.The 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 rescue.Accordingly,the fused AI algorithm was comparatively verified.

关 键 词：Three-dimension light detection and ranging VISION risk identification damaged building robot 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]