The Husky unmanned ground vehicle (UGV) is being used to run autonomous sensor data in Chile’s mining industry in order to improve safety for operating teams and reduce manpower requirements in the dangerous mining environment.
The work is being carried out by the University of Chile’s Department of Electrical Engineering and the Advanced Mining Technology Center. The Husky is being used to solve registration problems with complex sensor data in the mines. By doing so, accurate and reliable sensing and automation will exist to enable improved safety and efficiency for tele-operated and autonomous mining activities.
The Autonomous Rock Surface Modelling and Mapping in Mines project was designed to collect motion characteristics from Husky and noise characteristics from radar (Acumine 2D scanning millimeter wave radar), laser (3D Riegle scanning laser range finder) and vision-based sensors to model open pit and underground mines. A millimetre wave radar was used to penetrate dust, and Speed-Up Robust Feature (SURF) detection was analysed to determine the applicability of information extraction from mapping and surface profiling in mines. Sensors were integrated using the Robot Operating System (ROS).
3D video footage and densely sampled data sets were successfully collected upon completing field tests and data is in the process of being submitted to the International Journal of Robotics Research. A leading mining company in Chile has expressed interest in the research; discussions are underway to determine how this technology can be integrated into their workforce.
Dr Martin Adams, Professor at the University of Chile, said: ‘Our project develops existing technologies so that terrain surface profile and mine mapping information can be extracted from noisy sensor data. Our Husky-based sensing system will contribute significantly to the success and efficiency in which future mining operations take place.’
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