Increasing mine depth, a naturally hazardous environment, remains one of the key risks faced by mine owners and operators, irrespective if it is a surface or underground mine.
As advances in drone design and sensor development have helped to mitigate risks, improve production and reduce costs across the value chain, the next step or evolution of operating drones in mining has been to do it frequently, and at an acceptable cost underground.
While there have been some well publicized successes of drones being used in certain instances underground, the reality is that the complexity of flying underground safely, has made this a very limited field.
However, while flying underground is complex; it is not just a hardware challenge, but also a software and application development problem. In an environment, where technology and hardware solutions are increasingly capable of operating underground and able to perform tasks, the questions mine owners and drone operators have to consider is what tasks and what applications are the best fit? If we can answer these questions then we can do it frequently and at scale.
But, why is flying underground complex?
Underground environments pose many obstacles to flying drones. Confined spaces, obstacles, continued expansion; reduced visibility; air velocity; dust concentration; and lack of wireless communication systems make it a difficult task for an operator to fly a drone in underground working areas. Furthermore, access to unreachable and dangerous locations in underground mines is often impossible for a drone operator.
To operate underground, the preferred sensors are currently stereo cameras, ultrasonic sensors, laser range finders (LFRs) dual redundant IMUs, and infrared sensors.
Currently, we can identify several potential applications for underground mining operations. These include: Geotechnical Characterization, Rock Size Distribution, Gas Detection, Rescue Missions and the Mapping of Abandoned Mines.
Applications for Drones Underground
Rock mass data collections in underground openings requires the inspector(s) to survey the rock mass physically. The presence of personnel in unsupported areas such as open stope and newly blasted working faces endangers the safety of mining operators. To analyse the rock mass, imagery techniques such as photogrammetry and FLIR (forward-looking infrared) are used. Photogrammetry has also been proven to provide data for generating geological models, structural data for kinematic (the motion of points, bodies (objects), and systems of bodies (groups of objects) without considering the forces that cause them to move) and numerical analyses. In addition, FLIR imagery can be used to recognize areas of loose rock, which normally remain unnoticed until it becomes a hazard.
Rock Size Distribution Analysis in Underground Mines
The majority of underground hard rock mines use drilling and blasting methods for rock extraction. Assessment of rock size distribution after blasting is an important measurement for the next production phases (i.e., loading and hauling). There are some methods for rock size distribution analysis, including visual observation by an expert, sieve analysis, and image processing. Image analysis methods are fast and relatively accurate for rock fragmentation measurements.
Gas Detection in Underground Coal Mines
By applying a set of sensors to continuously measure atmospheric parameters and gas concentration enables a drone to be used for hazardous gas detection in underground coal mines, which can reliably asses and detect the likelihood of coal fires. However, during tests the flight time was limited to 10-15 minutes due to environmental conditions.
Mine Rescue Mission in Underground Mines
There have been multiple scenarios developed where a drone can provide the critical linkage between rescuers and trapped miners. In one promising scenario, an unmanned underground vehicle (UGV) and drone are paired to operate in a GPS denied environment. In this scenario, the UGV drives to the location, while scanning the area with LIDAR. The drone would then fly at the appropriate time and location to assess the collapsed area and attempt to identify a gap through the rockpile or soil.
Mapping of Abandoned Mines
Millions of abandoned mines worldwide pose multiple environmental, health, and safety threats to communities and current mining operations. From collapsing to methane leakage, illegal mining and more, the risks are endless, but to catalogue vast underground spaces manually is dangerous and an impossible task. Instead, we can use drones to provide a range of solutions such as gas detection, pillar mapping, mine shaft investigation, filling material calculation, rehabilitation and more.
It’s clear that drones have a role to play underground, but in a fluid and dynamic environment, whereby new obstacles are being created hourly, we need to develop solutions that are robust, and that can also operate independently which can mitigate risk and make operating underground feasible. We’ve seen a number of innovations in the last 12-months emerge, which do provide solutions to key challenges and the opportunity to scale. One of the most promising is Exyn’s AI drone platform, which reportedly can fly itself into newly excavated blasted areas or GPS denied without signal or pre-loaded maps. By fusing sensor data, the drone AI is able to map the space, which then allows it to follow its next steps determined by the mission director.
As mines inevitably deepen and we continue to prolong their lifespans; operating drones at an industrial scale underground will always remain a challenge. Despite the advances in sensors, cheaper and more robust drones, the challenge is not just hardware, it’s also linked to our imagination of what can we do and the creation of applications to make mining underground safer and more cost effective. As Nader Elm, Exyn’s CEO said, we have the iPhone, but we don’t have the Appstore.
Autonomous Industrial Drones Now Fly Anywhere By Themselves, Even Underground,
John Koetsier, Forbes, 24 September 2020
A Comprehensive Review of Applications of Drone Technology in the Mining Industry,
Javad Shahmoradi 1, Elaheh Talebi 2, Pedram Roghanchi 1 and Mostafa Hassanalian 3, June 2020