Infrastructure for the realistic testing of AI-supported robotic systems in challenging environments (e.g. forests) without a direct direct energy connection, for multiple use cases (e.g. monitoring/maintenance of forest roads) - human-robot teaming

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.