CALamity Adapted HARvesting Innovation

Scientific Leader:
Project coordinator:
Lisa Jensen (Kuratorium für Waldarbeit und Forsttechnik e. V.)
Project leader:
Contact person:

CALAHARI is a vision for a robot-assisted, semi-autonomous timber harvesting process. The synthesis of the requirements analysis for successful implementation in the forestry industry and the assessment of the extent to which existing robotic solutions can be used consists of a concept for an automated timber harvesting process. Of particular interest in the concept to be presented is the safe work through radio-controlled forestry technology and the careful handling of the ecosystem in terms of soil degradation, noise pollution and CO2 footprint.

Duration: 01.11.2022 till 31.10.2023
Donee: German Research Center for Artificial Intelligence GmbH
Sponsor: Bundesministerium für Ernährung und Landwirtschaft
Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection
Grant number: Funded by: Federal Ministry of Food and Agriculture and the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection based on a resolution of the German Bundestag

Kuratorium für Waldarbeit und Forsttechnik e. V. (KWF); ANDREAS STIHL AG & Co. KG

Application Field: Agricultural Robotics
Assistance- and Rehabilitation Systems

Project details

Climate change is the greatest challenge facing modern forestry, with consequences in terms of calamities, stand vitality, biodiversity, supply of raw materials, water and oxygen. Cultivation risks in the future will be increasing drought on the one hand, but also other extreme weather events such as storms or heavy rain. Warm summers and mild winters also favour the growth of harmful organisms.
At the same time, forestry in Germany is still one of the sectors most prone to accidents. This is due in particular to the difficult terrain - block overlays, branches and tree trunks lying around, obstructions to visibility, slopes, uneven and sometimes strongly yielding ground. The movements of the foresters during logging with proximity to the sources of danger (saw chain and tree trunk) and not least the lack of visibility or even unpredictability are dangerous situations.

Harvesters and forwarders have brought an increase in work safety, but they also bring controversial consequences. In addition to physical and psychological phenomena of loneliness and severe fatigue due to a variety of stimuli, as well as posture problems among machine operators, the lasting soil compaction caused by the specific contact surface pressures of the machines should be mentioned in particular. This soil compaction has a demonstrably negative effect on the soil structure, and thus on the water and gas balance as well as the soil fauna and flora. Logging roads were introduced as a solution to the problem, but these areas are no longer available for timber production. Further attempts have been made to distribute the machine weight over a larger area and thus reduce the contact surface pressure. At the same time, the distances between the skid trails in many forestry operations are increasing from 20 to 30 or even 40 metres and more. These distances make the use of foresters obligatory again and thus combine the disadvantages of both labour forces (soil compaction by large machines and increased accident risks for foresters).

Against this background, the long-term vision of an automated logging system is to be initiated, in which the forester works outside the danger zone and remotely monitors a team of (partially) autonomous robots, communicates with them and carries out success control. The control of the systems is to be facilitated by the use of adapted AI methods and partial autonomy in order to relieve the forester physically and mentally. Furthermore, intelligent networking of the systems should enable a long-term database to be built up so that adapted control, analysis and forecasting of forest development are possible.

As a first step, a study is to be carried out in the CALAHARI project applied for here in order to develop and evaluate concepts for automated systems to support logging.

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