There are many benefits for exploring and exploiting underground mines, but there are also significant risks and challenges. One such risk is the potential for accidents caused by the collapse of the pillars, and roofs which can be mitigated through inspections. However, these inspections can be costly and may put the safety of the inspectors at risk. To address this issue, this work presents Rhino, an autonomous robot that can navigate underground mine environments and generate 3D maps. These generated maps will allow mine workers to proactively respond to potential hazards and prevent accidents. The system being developed is a skid-steer, four-wheeled unmanned ground vehicle (UGV) that uses a LiDAR and IMU to perform long-duration autonomous navigation and generation of maps through a LIO-SAM framework. The system has been tested in different environments and terrains to ensure its robustness and ability to operate for extended periods of time while also generating 3D maps.

翻译：勘探和开发地下矿山具有诸多益处，但也伴随着重大风险与挑战。其中一种风险是由矿柱和顶板坍塌引发事故的可能性，而通过巡检可减轻此类风险。然而，这些巡检成本高昂，且可能危及巡检人员的安全。为解决此问题，本文提出了"犀牛"（Rhino）——一种能够在地下矿山环境中自主导航并生成三维地图的自主机器人。所生成的地图将使矿山工人能够主动应对潜在危险并预防事故。本系统是一台采用滑移转向的四轮无人地面车辆（UGV），通过激光雷达（LiDAR）和惯性测量单元（IMU），基于LIO-SAM框架实现长时间自主导航与地图生成。该系统已在不同环境和地形中进行了测试，以验证其鲁棒性、长时间运行能力及三维地图生成性能。