Seeing the Forest Despite the Trees
Ideon Science Park
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Forest operators work alone, often in darkness. They use heavy machinery entirely on their own. When thinning a forest, a machine operator has to decide which trees to fell. ?Cognitively, it's a tough job to analyze and decide which trees to cut, says Lars Svensson , CEO and co-founder of NFA, Nordic Forestry Automation . NFA wants to make an operator’s job easier and has found a way. They use their innovative technology to automate parts of the operator's work.
The NFA team finds themselves at the forefront of technological advancements - in the forestry industry.
They aim to create sustainable and efficient solutions that benefit forest owners, operators - and the environment.
The team develops digital tools and precision forestry solutions based on sensor technique.
It all started with Lars Svensson’s idea about forestry automation. He’s got a PhD in Robotics from KTH Royal Institute of Technology in Stockholm and an MSc in Engineering Physics from Uppsala University.
His specialty is technology for autonomous vehicles, something he’s spent years developing. At KTH, Volvo, and Scania, he has also researched and worked with algorithms for motion planning and control.
When Lars did a research exchange in Berkeley, California, he got enlightened – academically as well as entrepreneurially.
–Growing a business started to appeal to me, he says. Halfway through my PhD, I started to get more and more interested in motion planning and control related to forestry management. I began to mull over a few ideas.
Firsthand Forest Experience
Growing up on a farm in Sweden, with family and friends in forestry Lars has tried small-scale forestry himself.
?I knew that motion planning and control technologies would develop forestry. I didn't know how, though. I figured that perhaps there’d be room for a startup working on automating certain parts. It hadn't quite reached the forestry industry yet, but I knew it would, soon.
The forest is an organic environment and forests also vary greatly.
According to Lars, advanced sensors, algorithms, and software come in handy in forest management.
?The so-called perception revolution* in AI represents a major milestone in the development of artificial intelligence. It has brought machines closer to human-like perception and understanding of the world around us.
Lars and his team use the same technology used in autonomous vehicles.
?Sensors used to be expensive, Lars says. But, with the rapid development, they have plummeted in price. To measure trees robustly and accurately, smart algorithms are useful.
Looking for Problems to Solve
In the early days of NFA, Lars Svensson and David Gillsj? , co-founders of NFA, developed a toolbox based on their knowledge of autonomous vehicles and AI.
?We wanted to see which challenges we could address using our technology, Lars says. We brainstormed in search of forest issues to take on and that we could address with our tools.
In the search for challenges –they knew they would find some– they got in touch with several large forest companies in Norrland, thanks to the so-called ‘forest technology cluster’.
? Looking at their respective value chains, we started investigating to see where sensors, automation, and AI could contribute; Lars explains. Could there be a value in the type of services we were envisioning?
The team got a few interesting suggestions to evaluate.
Understanding the Work Life of a Forest Machine Operator
NFA found the way forestry machine operators work interesting. They drive large, complex machines that kind of become extensions of their bodies.
?When thinning out the forest, you need to master forestry practices, Lars explains. These involve figuring out how many trees to sort out and which. To make these decisions, operators use intuition and experience.
Thinning means cutting down a subset of trees and not all of them. When thinning, an operator must concentrate and analyze the situation all the time, which is completely different from clear-cutting an entire forest.
?It's up to the operator to assess which trees to take down and which to keep, says Lars, as well how densely the trees ought to be spaced.
There is a clear and research-based specification that describes how to proceed. It details what density the remaining forest should have. Factors such as age, type of habitat, e.g. play a role.
But the tools that operators use today, require that they get out of their machines to measure, using an old-school optical tool.
?It only gives a rough image of a small portion of the forest. It doesn’t offer any further guidance, says Lars. It's the same tool that's been used since 1880.
The Missing Piece: an Image
?We concluded that tools, based on sensors, could make operators’ work much easier, says Lars.
The team came up with the idea of creating a digital representation of the area around the machine. Getting a big picture of the forest would make it easier for operators to plan their work.
Check it out: https://m.youtube.com/watch?v=KaE4eApplPU
?The digital representation of the forest surrounding the machine became a fundamental piece of the puzzle, says Lars.
NFA mounts a sensor on the forestry machine, which reads and creates a live image of the surroundings. The image describes the entire area of the forest near the machine.
The digital representation helps the machine operator sift through the forest and get the big picture.
Looking at a 3D version of the forest from a screen inside the machine gives the operator an overview that helps select which trees to take down to thin out the forest.
?In the next generation, says Lars, you will be able to point out specifically which individual trees to remove.
Forestry Requires Planning
Every forest needs a management strategy.
?When managing a forest, carbon balance and biological diversity also need to be considered, says Lars.
By now, it's well known that clear-cutting forestry practices are harmful to biodiversity. Since many initiatives today focus on carbon sequestration and biodiversity, forestry machine operators also need to implement management methods that can achieve such goals.
?Our solution helps the operator implement any strategy. We build tools for all operators to carry out any type of forest management.
According to Lars, the unique feature of the solution is a robust perception functionality* in a forest environment.
?It's the cornerstone of all autonomous systems, he says. Right now, we are working towards partial automation. We envision that much of the management will be fully automated in the near future.
The Next Steps
NFA has a few systems in the forest and works with early adopters, and customers looking to automate parts of their forestry management.
?We’re developing a pre-series of the sensor solution, being deployed in the field to initiate a data loop and capture data.
All the while developing and fine-tuning the solution, the team hence collects data to continuously improve processes.
?The data will also consist of feedback from operators. They’ll help us quantify the customer value, says Lars. We will learn how to better support them.
Data also serves as an added benefit: the collected data also gives customers a forest inventory.
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*Robust perception functionality in a forest environment means that a system or device can accurately and reliably sense and interpret its surroundings within a forested area. This involves being able to:
- Detect objects: Trees, undergrowth, trails, and potential obstacles.
- Determine distances: The system accurately measures the distance to objects in its environment.
- Recognize patterns: The system identifies specific tree species, recognizing forest types, or detecting changes in the environment.
- Handle varying conditions: Works well in different lighting conditions, weather, and terrain types.
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