Top two challenges with localisation in mining environments

Autonomous mining is growing in popularity, with examples of automated mining vehicles cropping up in mainstream media coverage. And the benefits seem obvious: by taking humans out of the mining process, safety and efficiency are both improved. But how do you ensure autonomous mining vehicle localisation is accurate in all environments? 

Up to now, much of the focus has been on open-pit mines, with two players dominating the autonomous mining equipment space: Caterpillar and Komatsu. As the popularity of autonomous mining equipment continues to grow, there will be plenty of room for new market entrants – provided they can build platforms that function to the right standard. That task, though, is complicated.

In this blog, we’re examining two major localisation challenges that autonomous mining trucks face – and discussing how they can be overcome, based on our experience supporting customers to create high-performing autonomous navigation systems. We’ll also be showcasing our new product, WayFinder, which is ideal for autonomous mining.

As with any autonomous vehicle, one of the most vital pieces of the system is the localisation solution. In one sense, its function is very simple: it tells the vehicle where it is, and how it’s positioned in the environment. But that information is used for several key functions: 

+ It ensures the robot can follow a path – and detect when it has deviated from the path.

+ It gives the robot vital information for obstacle avoidance, by enabling the robot to situate itself within a (usually pre-surveyed) map of its environment. 

+ Information such as pitch, roll, and heading can also be used to improve the safety of the vehicle by detecting if it might be at risk of tipping over. 

Many autonomous mining vehicle localisation solutions rely on a GNSS-aided inertial navigation system – also known as a GNSS/INS – for this data. In a mining environment, though, there are some unique challenges that a localisation solution will need to overcome. 

In open sky conditions, a GNSS/INS uses satellite data to establish its position, supported by the inertial measurement unit (IMU) it contains. Mines, however, are not always in open sky conditions. Even in open pit mines, there can be areas that mining trucks need to go where their view of the sky is obscured – and of course in underground mines no sky is visible at all. Without GNSS signal, the position the localisation solution reports can start to drift, affecting the performance of the robot.

Of course, you could choose to use a completely different localisation solution that doesn’t rely on GNSS at all. But most autonomous mining trucks will need to move between areas where GNSS signal is strong and weak or non-existent.  

The localisation solution you use needs to be able to transition seamlessly between those environments, so a solution adapted purely for GNSS-denied navigation might not perform as well as needed in open areas. This is especially true when you consider that many GNSS-denied solutions don’t perform as well over longer distances, which many autonomous mining trucks need to cover as they move around the mine. 

The solution: real-time sensor fusion for GNSS-denied navigation.

If you’re working in a GNSS-denied environment, arguably the best approach is to use additional sensors to provide localisation data that supports your main navigation output. It’s entirely possible to use data created by other sensors such as wheel speed, radar and cameras to prevent position drift in GNSS-denied spaces and accurately localise an autonomous platform.

Excitingly, it is now even possible to use LiDAR data to localise autonomous mining equipment and trucks in real time, even in underground mines. WayFinder, is designed to help you get accurate localisation data in GNSS-denied environments, and is a complete solution that functions with no additional hardware. It uses a unique sensor fusion technology called LiDAR Boost to convert LiDAR data, in real time, into localisation data that can be used for autonomous navigation. If the mine is mapped first using LiDAR, LiDAR Boost enables completely repeatable navigation by comparing data from the on-board LiDAR with the scan.

Using this solution, an autonomous mining truck or passenger transport vehicle can seamlessly navigate from its storage shed, into the mine and back again while maintaining cm-level position accuracy.

Learn more: LiDAR Boost closeup blog.

Autonomous mining vehicles shouldn’t be viewed solely as an expense – after all, they can improve safety and efficiency, delivering measurable returns on investment for mine operators. But that doesn’t mean they can cost the earth. To help your balance sheet, your localisation solution needs to deliver robust performance as economically as possible. 

That argument goes beyond the performance of the hardware itself, though that is obviously important. Other things to consider that affect the commercial viability of your localisation include: 

+ Import and export processes can be expensive and time-consuming, affecting your commercials when selling abroad. 

+ If your localisation solution is hard to integrate into the rest of your autonomous mining truck, you can rack up extra developer costs that could conceivably affect your overall product price. 

+ The effort involved in calibrating and configuring a localisation solution at scale could also affect your commercial viability when you operate at scale. 

The solution: look for solutions that punch above their weight and that have attractive commercial terms 

Fibre Optic Gyro (FOG) systems have always been seen as the most accurate navigation sensor available. They’re widely used in applications where only the most accurate position and orientation data will suffice. However, this additional accuracy comes with an additional cost meaning integrating them into a fleet of autonomous mining vehicles isn’t a realistic approach. 

However, advances in MEMS-based technology, through advanced algorithms and calibration techniques, drives more accuracy out of more economical parts. As a result, you can now achieve similar results with a MEMS GNSS/INS than a FOG GNSS/INS, while paying a fraction of the price. And, as we’ve already said, you can now boost that performance in GNSS-denied environments using WayFinder.

It’s also worth mentioning that OXTS technology is all ITAR-free, making it much easier and cheaper to export around the world. If you’re building autonomous mining equipment for sales overseas, that could make your life significantly easier.

If this blog has inspired you to rethink how you handle localisation in GNSS-denied environments, we’d love to talk with you about your project. We’re excited to work with vehicle manufacturers who could benefit from the GNSS-denied localisation capabilities of WayFinder; if that’s you, you can learn more about WayFinder here or alternatively complete the form below and a member of the team will be in touch to discuss whether WayFinder is a good fit for your project.