Research

The Lower Austrian cooperation project “Autonomous Drone Flight Along Forest Roads” aims to develop an autonomous drone solution that efficiently and safely flies along forest roads to collect real-time forestry data. With the help of advanced sensors, GPS and artificial intelligence, obstacles are detected and environmental conditions are analyzed to ensure safe and precise navigation. The drones support the monitoring and maintenance of forest roads by documenting road conditions, identifying potential hazards and optimizing the use of human resources. This project contributes to increasing efficiency and digitizing forestry.

In this project, novel scenarios are tested and evaluated, and work is done on how to bring "common sense" into robots. The approach followed is "human-in-the-loop", combining the advantages of human experts with the advantages of AI. Specifically, this project tests and evaluates deployment scenarios of robots in forestry technology and presents new deployment scenarios. The novelty of this approach allows us to explore basics in terms of requirements, challenges and future possibilities in dealing with such systems, thus paving the way for more advanced basic projects or applications. Specifically, this project is expected to result in a series of international publications and an infrastructure to research and test the fundamentals for the use of future AI technologies and to apply them in teaching. Finally, the emerging robot test park in Tulln – adjacent to the new House of Digitalization - may also generate broad interest in the topic. The research methodology follows a 3G pioneer research approach with agile human-centered design: generation 1 testing of existing technology, generation 2 adaptation of existing technology with low-cost means, generation 3 advanced adaptation that goes beyond the state of the art and is planned together with our partners in Canada and UK - world leading robotics institutes. The infrastructure funded by this proposal will serve existing projects and is intended to spur new, larger projects (e.g.,EU). Added values are planned on three levels: 1) for the international AI research community through publications, 2) for the state of Lower Austria through a) later practical usage possibilities, and b) as an important contribution to teaching and making AI education more attractive to young researchers to counteract the labor shortage in AI.

OptiForValue’s ultimate goal is to develop, test, and demonstrate high-value forest-based value chains based on efficient forest management and wood production and use, while supporting the economic, environmental, and socioeconomic sustainability principles. In addition, the project aims to increase the value, competitiveness, and sustainability of existing forest-based value chains, particularly in those regional forest-based value chains impacted or likely to be severely impacted by climate change in the following decades. The OptiForValue consortium, consisting of 7 companies and 12 R&D Organizations will accelerate the creation of at least four resilient, sustainable, and high-value forest-based regional value chains that will be the basis to transform other forest-based supply chains across Europe. The design and implementation of these high-value forest-based regional value chains will be built on cutting-edge scientific knowledge and participative engagement with relevant stakeholders in each region. These transformed high-value value chains will accelerate the transition to a more sustainable bioeconomy.