# Development of Autonomous Driving Patrol Robot for Improving Underground Mine Safety
## 5 Discussion  
The robot system developed in this study was compared with the mobile robots in underground mines used in three previous studies (Table 4). The robot's localization function is essential in an underground mining environment in which GPS cannot be used. In two of the three comparison cases, the localization function was realized; however, in one study, the localization function was impossible because the operator controlled it remotely. In the two studies that achieved localization, one used multi-waypoint driving, and the other used one-way navigation via the wall-following method. To facilitate safe mine exploration, it is necessary to be able to explore the mine without requiring the worker to directly enter the tunnel. Therefore, the multi-waypoint navigation function must be used. Figure 14: Particle concentration map of the study area created using the measured data and GIS. Figure 13: Graph showing (**a**) particle concentration and (**b**) O\({}_{2}\) concentration in underground mine. Functions such as environmental monitoring and human detection are needed to detect hazard factors and recognize workers in dangerous areas. In the previous studies considered in this comparison, one involved environmental monitoring, and the other performed human detection; however, most functions were not performed simultaneously. Moreover, these studies did not use multi-waypoint navigation. Furthermore, these studies did not demonstrate the return of the robot to its origin. Therefore, these studies were limited because the mobile robots used at underground mine sites did not have safety-related functions when the robot's driving and returning functions were enabled, and studies with safety functions found that the robot's driving function was difficult to apply to an underground mine environment. In an underground mine, there are several roads to move to the mining and loading areas, and there are many intersections at the point where the roads are divided. Most underground mining sites include slope areas as they must reach deeper underground points for mining operations. Therefore, to utilize an autonomous robot in an actual underground mine environment, it is essential to verify and conduct an experiment not only on straight paths but also on intersections and slope areas. While other studies conducted field experiments on straight sections without intersections and slopes, this study conducted field experiments on intersections and slope areas, and as a result, stable driving performance was confirmed. In the case of an underground mine environment, since dust and gas are continuously generated due to repetitive blasting for mining, exploration for workers' safety must be performed periodically. If an unmanned autonomous driving robot is used instead of a human in the initial exploration after the blasting, safe exploration work can be performed. In addition, to explore underground mines safely using robots, the technology of autonomous driving to a specific point, along with an autonomous return to the starting point, is essential. In this study, an automated system was developed in which an autonomous robot returns to the starting point after performing autonomous exploration. By conducting field experiments on underground mines, it was possible to improve the possibility of using the robot system in actual work sites. The underground mining environment has rough roads designed to reach deeper areas while performing mining operations, as well as several roads made for different transport efficiencies. Therefore, a stable driving capability is essential for an autonomous robot to efficiently explore an underground mine site, especially when going down a slope or returning after exploration, and experiments must be conducted to verify this. Additionally, the robot should be able to drive and return along a planned route among several roads.