Auto2 – Automation for Autonomous Terrain Mobility

In the transport and industry sectors, the development of autonomous machines has already come a long way. Now, Auto2 addresses the key conditions for enabling autonomous forest machines, which should improve the working environment of today’s forest machine operators and increase the sustainability in forestry. 

Femal at computer in foreground, machines cutting down trees in background. Illustration.
Illustration: SkogForsk


The vision of Auto2 is to develop the use of forest raw material as an alternative to fossil materials through increased automation in forest machines. This will help to strengthen Sweden’s world-leading position in the area of terrain machine equipment.

Increased automation allows for a safer and more attractive work environment, which should help attract a broader recruitment base, including both men and women. Moreover, optimisation and planning with the support of digital maps will help to reduce ground impact in sensitive areas and optimised routes will result in lower fuel consumption. The project focuses on three basic needs for enabling autonomous forest machines: AutoDrive (autonomous off-road driving), AutoSafety (security systems around autonomous machines) and AutoRemote (remote control of forest machines).

Addressing the question what is the most pressing issue going forward, Olle Gelin describes that “the most important to solve is safety systems for autonomous and remotely controlled machines. Without an approved and accepted security system, it is not possible to introduce larger automation functions”.

The project is financed by Vinnova and involves players from academia, the forestry sector and manufacturers of forest machines. Skogforsk (the Forestry Research Institute of Sweden) is the project owner and coordinates Auto2. The duration of the project is two years, running until December 2020.


Contact person:
Olle Gelin
+46 (0)70 376 68 80

Skogforsk – web site


House and tractor in background, arrows pointing at different network components. Illustration.
Illustration: SkogForsk