World’s First AI Harvest Machine is Game Changer for Global Forests!

The first-of-its-kind machine could drive rapid increases in forest health, certified forest area and timber harvest recovery.

Sun 11 Feb 24


Swedish scientists have designed the world’s first unmanned machine for autonomous forestry operations, a breakthrough in the push towards a fully automated forest management and production process.

It is the latest discovery by the Swedish University of Agricultural Sciences, which has spent decades pushing to transition from highly labour-intensive harvesting operated by skilled operators to improve productivity, reduce safety hazards and stimulate forest economies.

In recent years, the world’s largest forest machine manufacturers (including John Deere, Komatsu and others) have embraced basic automation technology into new machine prototypes to make control machines more intuitive for operators. However, those developments still revolve around skilled operators having complete autonomy over the machine controls.

Until now, the vast majority of fully autonomous testing has occurred in small to medium-sized lab tests, with forest-based testing challenged due to difficulties in the automation of outdoor robots.

The project utilises the AORO platform, designed at Luleå University of Technology in Sweden – footage courtesy of @aoro-arcticoff-roadrobotic705.

The new machine, known as the AORO platform, was fitted with computing hardware, exteroceptive sensors, an articulated swing stage suspension system, and a hydraulic crane, operating with autonomous navigation, log recognition, and, most notably, the motion control of the log movement.

The findings,  published in the Journal of Field Robotics, demonstrated for the first time that computer vision, autonomous navigation, and manipulator control algorithms can lead machines to safely, accurately, and efficiently pick up logs from the ground and maneuver through various forest terrains without human intervention.

In effect, it reduces the need for human labour, increasing productivity and reducing labour costs while minimising the environmental impact of timber harvesting.

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The sequence of steps followed by the fully automated machine is as follows (a) Planning the mission. (b) Autonomous navigation. (c) Scanning for logs. (d) Collecting logs. (Photo Credit: Swedish University of Agricultural Sciences)

According to lead researcher Pedro La Hera, autonomous forestry machines have the potential to address several short-, medium- and long-term environmental issues, as well as push for greater take up of certified and sustainable forest management.

“As demonstrated in this study, by embracing cutting-edge technologies like autonomous navigation and manipulation algorithms, the unmanned machine provides not only timber harvesting with greater efficiency but also promotes sustainable forestry,” Professor La Hera said.

Before adding that “automated operations can be highly accurate and effective regarding collateral damage to adjacent ecosystems, which helps us to be more ecologically friendly than we currently are.”

The push to fully automate forest harvesting comes as agricultural businesses increasingly turn to AI and machine learning to streamline processes and boost efficiency.

Last year, Wood Central revealed that up to 90% of workers in the forest-based economy will be subject to AI-driven automation over the coming decade.

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Goldman Sachs ‘ranked’ various industries from most impacted to least impacted. According to the research, up to 90% of agriculture will have between 10-49% of work duties replaced by AI. (Image credit: Goldman Sachs Global Investment Research)

In September 2018, the World Economic Forum (WEF) reported that “AI could be the game changer for the world’s forests.”

At the time, the WEF noted that forest management is an excellent example of how technology-first approaches can quickly deliver results.

“Predictive analytics and machine learning models,” the WEF said, are “helping scientists and authorities in different parts of the world in the quest for better forest management – this also includes restoring areas damaged by fires, logging, or clear-cutting.”

Nonetheless, whilst AI and drone-based technology are being embraced in forest monitoring, planting and the manufacturing process for timber and pulp, the harvesting process still has some time to go, according to the researchers.

“The development of automation technology for forest (harvesting) machinery is only starting to take place,” according to the researchers, who added “, Our initial results demonstrate the beginning of an unmanned machine with the ability to handle simplified work ahead.”


  • Jason Ross

    Jason Ross, publisher, is a 15-year professional in building and construction, connecting with more than 400 specifiers. A Gottstein Fellowship recipient, he is passionate about growing the market for wood-based information. Jason is Wood Central's in-house emcee and is available for corporate host and MC services.


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