# Topological Navigation and Localization in
###### Abstract  
Mobile robots are no longer used exclusively in research laboratories and indoor controlled environments, but are now also used in dynamic industrial environments, including outdoor sites. Mining is one industry where robots and autonomous vehicles are increasingly used to increase the safety of the workers, as well as to augment the productivity, efficiency, and predictability of the processes. Since autonomous vehicles navigate inside tunnels in underground mines, this kind of navigation has different precision requirements than navigating in an open environment. When driving inside tunnels, it is not relevant to have accurate self-localization, but it is necessary for autonomous vehicles to be able to move safely through the tunnel and to make appropriate decisions at its intersections and access points in the tunnel. To address these needs, a topological navigation system for mining vehicles operating in tunnels is proposed and validated in this paper. This system was specially designed to be used by Load-Haul-Dump (LHD) vehicles, also known as scoop trans, operating in underground mines. In addition, a localization system, specifically designed to be used with the topological navigation system and its associated topological map, is also proposed. The proposed topological navigation and localization systems were validated using a commercial LHD during several months at a copper sub-level stoping mine located in the Coquimbo Region in the northern part of Chile. An important aspect to be addressed when working with heavy-duty machinery, such as LHDs, is the way in which automation systems are developed and tested. For this reason, the development and testing methodology, which includes the use of simulators, scale-models of LHDs, validation, and testing using a commercial LHD in test-fields, and its final validation in a mine, are described. autonomous navigation; topological mapping; field robotics; mining automation Article  
M. M.  
without doubt, a key factor, and has been the top priority of mining companies in recent years. This is true, especially, in underground mining operations with their hazardous environments in which workers are constantly exposed to the risks of rock falls, rock bursts, and mud rushes, and where the presence of dust in the air can result in a number of associated occupational diseases in the workers [1]. In an underground mine, autonomous vehicles navigate inside tunnels. This kind of navigation has different precision requirements from those where they are navigating in an open environment. First, tunnels are GNSS-denied environments and thus vehicles cannot use any GNSSs (Global Navigation Satellite Systems) to self-localize. Secondly, when driving inside tunnels, it is not relevant to have an accurate localization system, but it is essential to be able to move safely through the tunnel, and to make appropriate decisions at its intersections and access points. This is completely different from most robotic applications, where safe navigation requires an accurate determination of the robot's position and orientation at every moment. To address this need, a topological navigation system for mining vehicles operating in tunnels is proposed and validated in this paper. This system was specially designed to be used by Load-Haul-Dump (LHD) vehicles, also known as scopy trans, operating in underground mines. An LHD is a four-wheeled, center-articulated vehicle with a frontal bucket used to load and transport ore on the production levels of an underground mine (See Figure 1). These machines are a key component in the extraction of ore from underground mines because the ore extraction rate from the mine depends directly on the efficiency of the LHD. The proposed system permits a commercial LHD, which is a very large vehicle, to navigate inside tunnels that are just a couple of meters wider than the LHD. In addition, it allows bi-directional navigation and so-called _inversion_ maneuvers, both required in standard LHD operations inside productive sectors of underground mines.