AutoPlant is a Vinnova-funded collaborative project between the parties Skogforsk, LTU, KTH, Bräcke, Skogstekniska klustret, SCA, Södra, Sveaskog, Holmen and StoraEnso.
Gentle soil preparation and planting. Photo: Linnea Hansson
The AutoPlant project is part of the initiative Challenge-driven Innovation, step 3 – implementation and runs from 29 January 2024 to 12 February 2026. Between 2021 and 2023, step 2 took place and Here you can read an article from the start-up of step 2 and here is a film that presents the project in one minute. The development during stage 2 has also been summarized in a scientific article. The project was presented at Sweden Innovation Days on 19 January 2022 (during the week for the global environmental goals at the World Expo in Dubai) and you can see that presentation here. In September 2022, field tests were carried out outside Bräcke and you can read more about these here. From there, it also became a new short film.
The forest is an important resource in a bio-based society as the forest raw material enables the phasing out of fossil products. Managing the forest requires sustainable methods with rapid establishment of seedlings and high growth. Today, it is difficult to find labor for the physically heavy manual planting and the plant survival rate is not high enough. The project’s goal is therefore to develop an autonomous soil preparation and planting system with high precision, low environmental impact and a good working environment.
In step 3, the focus is on scaling up the tests of the systems developed in step 2 so that they can be further developed into prototypes. A commercialisation plan will also be developed. The work includes: (WP1) Autonomous soil preparation and planting, (WP2) Perception, detection and quality measurement, (WP3) Gentle off-road driving, (WP4) Work environment and human machine interaction, (WP5) New forest quickly and better with reduced soil impact, and (WP6) Laws, regulations and lobbying.
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That’s a remarkable amount of work hours for a single machine, the Norcar 600 owned by Erkki Rinne is taken well care of, it even has the original Diesel engine.
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Kieran Anders is a forestry contractor working in the lake district. His work involves hand cutting and extracting timber using a skidder and tractor-trailer forwarder.
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It is not possible to eliminate chain shot, but there are simple steps that can be taken to reduce the risk.
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Arwel takes great pride in the fact that the mill has no waste whatsoever, “the peelings are used for children’s playgrounds, gardens and for farm animals in barns in the winter and the sawdust has multiple uses in gardens and farms as well.
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Timber hauliers need to encourage young blood in, and also look after the hauliers we have, we need make the sector a safe and positive place to work.
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The collaboration between the parties is further deepened in the strong consortium of researchers, manufacturers and users. This includes the entire chain from nursery to young forest, which is needed to solve the complex challenges that the project addresses. The value of a successful project is great if the system can increase plant survival and reduce soil impact. Increased growth creates better conditions for a bio-based society and more carbon dioxide is sequestered, which is positive for the climate. It would also increase Sweden’s competitiveness and contribute to maintaining a high reputation for Swedish forest technology.
The temporary control station during the field tests in Bräcke. Photo: Björn Edlund.
Publications
- Hansson et al. 2024: Autoplant – Autonomous Site Preparation and Tree Planting for a Sustainable Bioeconomy. Forest DOI: 10.3390/f15020263
- Semberg et al. 2024: Real-time target point identification and automated log grasping by a forwarder, using a single stereo camera for both object detection and boom-tip control T. Silva Fennica DOI: 10.14214/sf.23062
- Rossander & Lideskog 2023: Design and Implementation of a control system for an autonomous reforestation machine using finite state machines. Forest DOI: 10.3390/f14071340
- Li 2023: Vision based perception systems for unmanned forestry machines. PhD thesis, Luleå University of Technology
- Li & Lideskog 2021: Implementation of a system for real-time detection and localization of terrain objects on harvested forest land. Forest DOI: 10.3390/f12091142
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