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 trams, 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.
Highlights
The development of robotic applications has increased significantly in the last decade, and currently, robotic systems are being utilized for many purposes, in various environments
Mining is one industry in which autonomous vehicles have been in use for at least 13 years
The topological localization estimates the location of the LHD inside the TMM, as well as the distance between its current location and the closest AP/WP
Summary
The development of robotic applications has increased significantly in the last decade, and currently, robotic systems are being utilized for many purposes, in various environments. The use of autonomous mining equipment, mainly vehicles, is an important requirement in the whole mining industry This is because mining operations need to increase the safety of the workers, as well as to augment the productivity, efficiency, and predictability of the processes. LIDAR point clouds are stored at fixed positions inside each node (e.g., every 2 [m] in our current implementation) Each of these point clouds are built by joining the LIDAR scans acquired using the front-facing and the rear-facing LIDARs. a filtering process is applied: points colliding with the LHD’s body are removed, points that are located too far (>10 [m]) to the center of the LHD are removed, and the density of the point cloud is normalized.
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