LiDAR technologies for survey grade data capture are now exploding across industries. The ability to collect extremely dense point cloud datasets with additional attributes, such as intensity, on each collected point are a real step forward for the spatial sciences. The market now has several commercially ready underground solutions that leverage on the power of LiDAR data capture techniques. Before we explore those, and the future that these sensors could unlock, let’s explore what LiDAR actually is…
A LiDAR (Light Detection And Ranging) sensor is a geospatial tool that sends a wave of light into its surrounding environment, and is therefore able to measure its surroundings. Similar to a traditional single point EDM (electronic distance measurer) seen in a total station or electronic tape measure, these use the simple rule: Distance = Speed x Time
The main point of difference is the density, speed and spread of data collection from the sensor head; the wave of light allows for returns from a far larger field of view than traditional EDM measures. Coupled with the ability to sense the intensity (as well as other parameters), allow for the processed point cloud to show more than just shape, but also changes in colour, surface texture and density.
What does this mean for underground mining?
Underground mining has always leveraged on survey and geological data sets to design and modify mining techniques as a project progresses. With the introduction of LiDAR into the underground environment, the data collected can create realistic “digital twins” of the working front and therefore generate improved volumetric calculations and geotechnical interpretation.
Below are some of the current tools that technical services teams could use to improve data collection that utilise LiDAR sensors.
Rock Mapper iPad app
Rock Mapper has featured on this website before, but only a few weeks back they outlined their latest updated release which utilises the iPad’s new LiDAR capabilities. This allows geologists to scan, photo, interpret and geo reference a recently fired cut with accuracy and ease.
The LiDAR ability of the new iPad is used by this app to great effect allowing close proximity scans of small areas in around 30 seconds. This would save time hand drawing or setting up mobile stationery scanners in situ within the busy mining cycle. The added bonus is then fully digitised interpretation at the face in a quicker time than traditional data capture and office processing. Saving time within the mining cycle (think hungry jumbo – chomping at the bit for meters!) but also in the office for the development geologist.
GeoSLAM ZEB handheld scanning system
This handheld LiDAR Scanner has proven use cases in the underground environment; particularly around face mapping, convergence inspection (geotechnical analysis) and stockpile data collection. The system can be walked around the mine by an operator and easily geo referenced. It is worth noting that a scanner like this will require post processing in the office, as unlike an unbuilt short range scanner (+/- 15m) as seen in the iPad, these puck sensors can collect data >100m. This allows far larger areas of the mine to be scanned and analysed, with improved data density and accuracy.
Emesent Hovermap underground autonomous drone system
The Hovermap system, developed here in Australia, has seen great commercial success in the past couple of years as its LiDAR based underground drone system delivers new datasets to underground mining teams.Similar to the GeoSlam ZEB it uses a collect and post process data collection method. The main point of difference is the autonomy of flight with the associated drone that the sensor is strapped onto. The ability to fly in areas deemed unsupported, or even beyond “Drilling Breakthrough” signs allows for massively improved data collection with much less impact on the mining cycle, all whilst removing operators from areas deemed hazardous.
The Future
The richness of data and the ability to map areas beyond human access in the underground environment has really disrupted expected data deliverables.In my opinion, there needs to be a period of consolidation over the next 12-18 months where technical service departments really use and realise the new data they are able to interpret. Areas that spring to mind would be:
- geotechnical analysis internal to stopes for structures and potential under/overbreak catalysts
- drilling QA/QC for drill and blast engineers who can now visualise with clarity underbreak areas as well as remaining drill hole strings
- engineering departments analysing down stream implications of much larger datasets and how they will be handled with their IT network
There have been talks of swarms of flying LiDAR systems within the underground mine to complete surveying and at the face data collection. Maybe in the near term we will be designing drone cuddy’s so we can keep them out of harm’s way as multiple machines tram past. For me, this isn’t where I see the LiDAR systems heading, rather the machines themselves having a sensor attached for ongoing data collection.
- A remote bogger for example could utilise a 2D ruggedised profile LiDAR Scanner on its cab and every two hours at the brow it could generate a scan to model the void and the remaining material in the draw cone.
- A jumbo could scale the face and then scan the heading once a rebog has been completed. This could then be used by the operator to calculate the best position for the incoming drill holes, against the mine design.
One thing is for sure, the future is here and science fiction seen in the likes of RoboCop and The Matrix is now being used daily across industries. What a fantastic time to be in the underground mining industry as it steps forward with transparency and accuracy into the digital era!
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LiDAR is changing the way survey is done underground — I have been to mines here in the US where they are using iPad Pros that come with built-in LiDAR — similar to what you mention in the article. The only downside at the moment on these iPads is the range — I’m sure it’ll get significantly better over the next couple of iterations — both Apple and Google are super good at miniaturizing and pushing technology boundaries.