###### Abstract  
In this study, we compared the accuracy of three location estimation methods of an autonomous driving robot for underground mines: an inertial measurement unit with encoder (IMU + encoder) sensors, Light Detecting and Ranging with encoder (LiDAR + encoder) sensors, and IMU with LiDAR and encoder (IMU + LiDAR + encoder) sensors. An accuracy comparison experiment was conducted in an indoor laboratory composed of four sections (X-change, X-Y change, X-Z change, and Y-change sections) that simulated an underground mine. The robot's location was estimated using each of the three location estimation methods as the autonomous driving robot moved, and the results accuracy was analyzed by comparing the estimated location with the robot's actual location. From the results of the indoor experiments, the average estimation error of the IMU + LiDAR + encoder sensors was approximately 0.09 m, that of the IMU + encoder was 0.19 m, and that of the LiDAR + encoder was 0.81 m. In a field experiment, the average error of the IMU + LiDAR + encoder was approximately 0.11 m, that of the IMU + encoder was 0.17 m, and that of the LiDAR + encoder was 0.70 m. In conclusion, the IMU + LiDAR + encoder method, which uses three types of sensors, showed the highest accuracy in estimating the location of autonomous robots in an underground mine. s +
Footnote †: journal: Medical  
and mapping experiments on abandoned mines. [PERSON] and [PERSON] [10] developed an autonomous driving robot capable of route planning, and obstacle detection in the underground mine environment. They performed mapping work for underground mine tunnels. [PERSON] et al. [11] developed an autonomous driving robot, \"Barney\", equipped with a rotating LiDAR sensor, and performed 2D and 3D mapping work on underground mines. Studies have also been conducted to transport ores using autonomous driving vehicles in underground mines [12; 13]. [PERSON] et al. [14] developed an autonomous driving loader for underground mines using radio frequency identification technology (RFID) and the fuzzy logic algorithm. [PERSON] et al. [15] developed Load-Haul-Dump equipment capable of autonomous driving in underground mines, and conducted experiments on the feasibility of application to sites. Mobile Tronics [16] developed an autonomous driving train called the \"VirtuRail\" that transport ores from underground mines without rail tracks. VirtuRail utilizes sensors such as LiDAR, RFID, and radio detection and ranging to measure the distance to the tunnel wall and is autonomously driven by maintaining a constant distance from the wall. Additionally, studies have been conducted for exploration and environmental surveys of underground mines using the autonomous driving robot [17; 18]. [PERSON] et al. [19] developed the autonomous driving robot \"MSRBOTS\", for investigating safety accidents in the mines. The MSRBOTS is equipped with infrared sensors, environmental measuring sensors, and camera sensors, which make it possible to safely explore areas that are dangerous for humans to access. [PERSON] et al. [20] developed a system that could measure environmental factors such as temperature, humidity, and gas concentration in underground mines, and transmit the results remotely using an autonomous driving robot. [PERSON] and [PERSON] [21; 22] developed a LiDAR sensor-based autonomous driving robot and conducted driving performance experiments in an indoor laboratory, and field tests in underground mines. Essentially, autonomous driving technology in the mining industry is used in various ways, including tunnel mapping, ore transportation, and environment exploration. To efficiently apply autonomous driving technology to the mining industry, it is necessary to detect the surrounding environment using sensors, as well as estimate the location of the robot accurately. The application of autonomous driving robots (tunnel mapping, ore transport, and environmental exploration) in underground mine environments can only be effective when the robot's location is accurately determined.