# Development of Autonomous Driving Patrol Robot for Improving Underground Mine Safety
###### Abstract  
To improve the working conditions in underground mines and eliminate the risk of human casualties, patrol robots that can operate autonomously are necessary. This study developed an autonomous patrol robot for underground mines and conducted field experiments at underground mine sites. The driving robot estimated its own location and autonomously operated via encoders, IMUs, and LiDAR sensors; it measured hazards using gas sensors, dust particle sensors, and thermal imaging cameras. The developed autonomous driving robot can perform waypoint-based path planning. It can also automatically return to the starting point after driving along waypoints sequentially. In addition, the robot acquires the dust and gas concentration levels along with thermal images and then combines them with location data to create an environmental map. The results of the field experiment conducted in an underground limestone mine in Korea are as follows. The O\({}_{2}\) concentration was maintained at a constant level of 15.7%; toxic gases such as H\({}_{2}\)S, CO, and LEL were not detected; and thermal imaging data showed that humans could be detected. The maximum dust concentration in the experimental area was measured to be about 0.01 mg/m\({}^{3}\), and the dust concentration was highly distributed in the 25-35 m section on the environmental map. This study is expected to improve the safety of work by exploring areas that are dangerous for humans to access using autonomous patrol robots and to improve productivity by automating exploration tasks. underground mine; patrol robot; autonomous driving; environmental monitoring; mine safety +
Footnote †: journal: Medical  
Several studies have been conducted on autonomous driving robots that can investigate the conditions of underground mines [23; 24; 25; 26; 27]. Autonomous driving robots were used for mapping to evaluate the stability of tunnels [28; 29; 30], and their own location estimation technologies were used to record the position of the robot where hazard factors were detected [31; 32; 33]. In addition, sensors that can measure the gas, temperature, and humidity conditions were installed on a robot to investigate the environmental characteristics of the tunnel [34; 35; 36]. [PERSON] et al. [37] developed a mobile robot capable of navigation, path planning, and mapping in underground mines and conducted a field experiment on abandoned mines. [PERSON] et al. [38] developed an autonomous driving robot that performed driving, exploration, and mapping in abandoned underground mines to investigate gas concentration and sinkage. [PERSON] and [PERSON] [36] analyzed and visualized environmental data obtained from an autonomous driving robot equipped with humidity and gas sensors in an underground mine. Previous studies that conducted autonomous exploration of underground mines using autonomous robots did not verify their performance in the case of intersections or slopes, as the experimental area consisted of straight lines. Furthermore, the robot's ability to return to its origin after driving to its destination was not verified. As autonomous exploration must be carried out periodically to ensure the safety of workers in underground mines, an automated system in which robots return to their origin after mine exploration is essential to improve safety and productivity. Therefore, the robot must be able to return to the starting point after sequentially traveling to several points designated by the user. In addition, a field test of an autonomous exploration system using an autonomous driving robot on an actual underground mine should be conducted to evaluate the effectiveness of autonomous driving robots in driving in areas such as intersections and slopes, as well as straight shafts. This study aims to develop an autonomous driving robot for the autonomous exploration of underground mines and to conduct field experiments in actual underground mine sites.