How Trimble is embracing and maximising mining autonomy


Australian Mining chats to Louis Nastro, Trimble’s senior director of technical and business solutions, off-road autonomy, about the rise of autonomy in mining and how the industrial technology company is harnessing the movement to improve safety and productivity in the sector.

While autonomous technology is becoming more and more prominent, it’s still a relatively new mainstream concept. In an era where safety and productivity is of the utmost importance, why should autonomy be embraced in mining?

The level of autonomy required by a particular client in a particular mining operation depends on a number of factors.

This could range from the age of equipment and skill level of operators to operating economics and whether the adoption of the technology will be rapid or completed in phases in order to acquire the right human/technical resources to operate and manage the equipment.

Whether the move toward autonomy is a phased evolution or consists of integrating specific autonomous tasks, there is no doubt that operational efficiencies can be realised.

Take autonomous mining trucks (AMTs) as an example of a fully automated process. There is a wealth of data over many years showing increased vehicle uptime, reduced operating costs, more predictable maintenance intervals, built-in safety measures, and operations that are both repeatable and reliable.

Louis Nastro

Comparatively, partially automated systems (e.g. operator assistance or remotely operated systems) can enable operators with less experience to perform otherwise complex tasks, or avoid mishaps and errors.

So, whether the goal of the autonomous mining operation is to improve safety, reduce costly maintenance slowdowns or increase productivity, the operator assistance technology can be adapted to support vehicles and suit the overall objectives of your mining operation.

And since autonomous technology can be added and then expanded upon incrementally as users move closer and closer to fully autonomous functionality, the flexibility is there to suit any level of need.

Trimble’s approach to autonomy is based on decades of innovation, intelligence and expertise. What separates Trimble’s autonomous solutions from the competition?

Our differentiation really starts at the inception of a project. We seek to understand detailed client requirements — not only as it pertains to the technology, but the business or productivity goals they wish to achieve through autonomous solutions.

Once we perform an initial scoping, we explore specifics of what the client requires on the machine and how we can integrate machine data into existing workflows, or even create a better one.

For example, onboard the machine we have multi-sensor data being used for real-time autonomous operation. We need to show clients how to utilise actionable data from that operation to boost productivity, and augment or even replace other processes to implement greater levels of autonomy through customised workflows.

Another key differentiator is time to deployment with rapid implementation of solutions in the field on a particular machine or machines. We leverage tools such as our autonomy development kit which allows our engineers to deploy with a dedicated toolset to achieve this.

This not only allows us to acquire a wealth of data, but collaboratively build the solution with the client so they see the benefits firsthand, as well as identify new ways to leverage the data to support other parts of the operation.

Trimble has become a market leader in autonomy within the agriculture, automotive and construction sectors. Could you elaborate on Trimble’s autonomous solutions for the mining sector?

Everything starts with reliable and repeatable positioning and orientation which is a hallmark of Trimble technology in the other application areas mentioned.

Clients are looking for the next evolution in precise positioning and orientation that addresses mining-specific challenges such as satellite accessibility in deep open pit mines.

This is where we can deploy our localisation solution which not only provides precise self-contained position estimation, but also has the capability to work with, and feed, corrections to the GNSS/inertial system acting as another source of observables.

This layered approach provides accuracy, repeatability and redundancy of measurements in the sensor fusion engine to help with positioning.

As more vehicles within the mining environment become autonomous and the interactions between them become more complex, different sensors may need to be implemented. Core data used for localisation with various sensors and aiding orchestration of complex tasks all comes from a precise estimation of where the vehicles are in all conditions.

The information we collect for localisation is a valuable tool for perceiving the mining environment. We can interpret a myriad of data points on every pass/interaction of that particular vehicle and use it to understand how machines, personnel and other vehicles are perceived in different weather/operational conditions within that particular mine.

The analysis of these results allows us to counsel clients as to sensor selection, placement, data transfer required to accomplish different tasks between machines and other vital parameters necessary for building not only individual localisation and perception systems, but also how we use our data platform to leverage the sensor output.

What can mining companies achieve from utilising Trimble’s autonomous solutions?

It starts with the approach outlined above, collaborating together to learn from real mine site experience. This allows mining companies to understand from the start the specific details of what the benefits will be and how it aligns to their strategic goals.

Deploying a dedicated team and acquiring data from the customer’s site allows us to be very flexible and generate results quickly, reducing the time from a proof of concept to prototype.

This applies not only to the machine itself but also how we can turn data into actionable insights for the client on how current workflows can be modified or transformed.

This is a critical part of introducing autonomous vehicle technology in a mining environment, as so much more data will be available. Knowing how to use it, and when, becomes even more critical in networked operations and more complex machine to machine interaction.

Whether the client chooses a gradual path to autonomy by introducing assistance mechanisms first, or they choose to automate a specific machine or workflow from inception, our approach allows for both to be accommodated.

What’s next for automation at Trimble? Any future developments that could benefit the mining industry?

We continue to evolve our industry platforms and data interpretation tools – not only for enhanced object detection such as vehicles or personnel in difficult environments, but also for deriving mining site specific intelligence.

Since each site is different, our goal is to stay ahead of client requirements with flexible solutions that can integrate more autonomous machines and/or processes faster through unique customisation to meet the needs of the site environment.

This involves constant development on our core software and staying up to date on the latest sensor technologies which we constantly test and validate.

For more on Trimble, head here.

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