Autonomous Robotic InSpEction (ARISE)
The modern world is dependent on the supply of mineral resources to provide the raw materials to meet, current and future needs for energy, manufacturing and construction industries and demands are increasing exponentially due to population growth, life expectancy and a more technologically-focused, digital world which requires sophisticated mineral products.
The mining industry is committed to operating safely and reducing accident numbers, and it is increasingly migrating underground as surface deposits are exhausted. The underground environment is challenging due to: high rock stress, high temperatures, poor communications with surface, restricted access and lack of access to satellite positioning systems.
The key risk in deep level mining is geotechnical because ground conditions are exacerbated by high stress at depth and the unpredictable nature of the blasting process on stress redistribution. It is essential to undertake disciplined geotechnical inspections of newly exposed rock after every blast, but it is well known that this process is dangerous, time-consuming and subject to human error.
ARISE aims to implement autonomous surveys of geotechnical conditions during the normally unproductive period immediately after the blast when workers vacate the mine due to post-blasting fumes and seismic risk. The robotic platform will be used to:
Survey roof conditions in newly-blasted areas;
Monitor material flow in orepasses and extraction points, particularly mapping ‘hangups’ that can block orepasses. Mapping hangups from below is extremely dangerous for people;
Accurately map areas in 3D for reconciliation and design verification.
ARISE will provide safety and financial benefits while not affecting the production cycle (operating in the shift change periods) and is therefore attractive for industrial roll-out.
The project will develop the ARISE system as a commercial product. The ARISE system is an inspection robot for mining environment. Existing or COTS components are used where applicable and development within this project only focuses on electronics (on-board-computer) and sensors (vision, LIDAR).
Sundance would develop the “ARISE-Kit” on-board computer and electronics to operate in harsh environments by using automotive graded parts. GMV will utilise its autonomy software but integrate a new set of visual sensing instruments using COTS cameras and develop an adjustable light array. MDA will loan an Obscurant-Penetrating (OPAL) LIDAR unit and aid in hardware and software integration activities. University of Exeter Camborne School of Mines will generate use cases and create risk assessment strategies that improve both safety and efficiency in underground production mining processes.