Towards the Deployment of an Autonomous Scaling Machine in Underground Mines

Abstract

Underground mines present inherently hazardous and complex environments, characterized by poor visibility, confined geometries, and uneven terrain. Autonomous machines offer a promising means to reduce human exposure in such conditions; however, their deployment is hindered by numerous challenges, including the absence of Global Navigation Satellite Systems (GNSS), sensor degradation, and the difficulty of maintaining reliable localization and situational awareness in such environments. This work presents the retrofitting of scaling machine for autonomous operation within an active mining site, detailing the sensor integration, system architecture and automation. We incorporate state-of-the-art mapping and localization algorithms, and leverage existing Wi-Fi access points to provide coarse global positioning within the mine. Experimental validation conducted on a live mining environment demonstrates the system's ability to maintain accurate localization and consistent mapping under real-world conditions.