Location estimation of autonomous driving robot and 3D tunnel mapping in underground mines using pattern matched LiDAR sequential images

作     者：Heonmoo Kim Yosoon Choi Heonmoo Kim;Yosoon Choi

作者机构：Department of Energy Resources EngineeringPukyong National UniversityBusan 48513Republic of Korea 

出 版 物：《International Journal of Mining Science and Technology》 (矿业科学技术学报（英文版）)

年 卷 期：2021年第31卷第5期

页      面：779-788页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0810[工学-信息与通信工程] 080202[工学-机械电子工程] 081105[工学-导航、制导与控制] 0804[工学-仪器科学与技术] 0816[工学-测绘科学与技术] 081001[工学-通信与信息系统] 0802[工学-机械工程] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

基　　金：supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2021R1A2C1011216) 

主　　题：Pattern matching Location estimation Autonomous driving robot 3D tunnel mapping Underground mine 

摘      要：In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine *** autonomous driving robot continuously detects the wall of the tunnel in the horizontal direction using the light detection and ranging(Li DAR)sensor and performs pattern matching by recognizing the shape of the tunnel *** proposed method was designed to measure the heading of the robot by fusion with the inertial measurement units sensor according to the pattern matching accuracy;it is combined with the encoder sensor to estimate the location of the *** addition,when the robot is driving,the vertical direction of the underground mine is scanned through the vertical Li DAR sensor and stacked to create a 3D map of the underground *** performance of the proposed method was superior to that of previous studies;the mean absolute error achieved was 0.08 m for the X-Y axes.A root mean square error of 0.05 m^(2)was achieved by comparing the tunnel section maps that were created by the autonomous driving robot to those of manual surveying.