AORO: The world's first autonomous forest machine

This article is based on our podcast episode released on 1 October 2024. [Listen to the full episode here].

In our last two articles, we've gradually explored how robots and drones are transforming our work in forests. This week, we continue our journey by focusing on a promising technology: the AORO platform. It's an autonomous forest machine that can navigate and perform tasks within the forest.

But is there substance to it? Or is it just another project that looks good in a controlled test environment but may struggle when introduced into real forests?

An ambitious collaboration between universities, forestry companies and technology firms

The AORO project was created in 2014 at Luleå University of Technology in Sweden as a collaboration between the university, forestry companies, and technology firms.

Their shared goal was to develop an autonomous forest machine that could safely and efficiently navigate the forest.

Jens, one of our podcast hosts, shares how he and Rasmus were involved in developing autonomous cleaning machines some years ago. The journey from prototype to market took several years.

So what can it actually do?

In our latest article, we covered BraSatt, which could plant trees on its own. But while BraSatt is designed to perform a single task, AORO is developed to perform several independent tasks in the forest, such as:

• Planning missions independently
• Navigating autonomously through various forest terrains
• Scanning for and recognising logs on the ground
• Collecting and moving logs using its hydraulic crane

Professor Pedro La Hera, who leads research at Luleå University of Technology, explains: 

"By utilising advanced technologies such as autonomous navigation and manipulation algorithms, the unmanned machine can not only harvest timber more efficiently but also to promote sustainable forestry."

Source: Woodcentral.com 

The technology driving AORO

AORO is an electric, remote-controlled forest machine designed to operate autonomously. It uses a large array of sensors, such as LiDAR, cameras and GPS, combined with artificial intelligence and machine learning to navigate and perform tasks in the forest.

LiDAR is a technology we've discussed several times before - and as Rasmus explains:

"LiDAR and camera technology form the backbone of the machine's navigation ability. LiDAR provides an accurate 3D image of the terrain, while the cameras identify specific objects. Getting these technologies to work together perfectly is an enormous challenge."

AORO’s sensors works so it can make decisions itself. For example, if a person gets too close it will turn it self off.

From laboratory to forest: Test phases and development

Since its inception in 2014, AORO has undergone extensive development. A milestone was reached in 2020 when the first field tests in real forest environments began. Here in 2024, the focus has shifted to advanced simulator tests with dynamometers, enabling faster and more controlled testing of the machine's complex systems.

A promising future: Potential benefits of AORO

There's no doubt that if we can bring autonomous forest machines into the forest safely and efficiently, there are enormous benefits to be gained - just as we've previously experienced in agriculture.

The benefits will include:

• Increased safety by removing humans from dangerous situations
• Possibility of 24/7 operation and significantly increased productivity
• Potential for more precise and sustainable forest management
• A possible solution to the shortage of skilled forest workers

However, an important point we always return to when discussing autonomous machines in forestry is that although full autonomy sounds appealing, human supervision will still be necessary. So the technology will likely be a supplement to humans in the forest rather than a replacement.

The challenges and limitations

Despite its enormous potential, the AORO project faces significant challenges. The forest's complexity makes autonomous navigation extremely demanding, and ensuring the machine can operate safely around humans and animals is crucial. Additionally, there are regulatory barriers to using autonomous machines in forests.

Rasmus emphasises a central issue: 

"Safety is absolutely crucial when we talk about autonomous machines in forestry. Unlike controlled factory environments, the forest is unpredictable. It requires robust safety systems that can handle all conceivable scenarios - and that's a huge challenge."

How’s the future looking for AORO?

The AORO project could potentially be a breakthrough for autonomous machines in forestry - especially considering how far they've already come in their testing phase.

Rasmus says he expects a gradual integration of autonomous functions in forest machines over the next decade, rather than an immediate transition to full automation.

And Jens adds: "It's easy to overestimate short-term results but underestimate long-term possibilities. We need to be realistic about the timeline for full implementation."

In our podcast, we'll keep you updated when there's more news about AORO. One thing is certain - we'll see many more projects of this type in the future.

If you want to read even more about AORO, you can learn more here:

• Autonomous Forestry Equipment
• AORO: Arctic Off-Road Robotics Lab
• World’s First AI Harvest Machine is Game Changer for Global Forests!
• New Tests on Autonomous Forest Machine Yield Promising Results