Artificial Wingman and Co-pilot 2

Purpose and goal:

This project explored the realms of machine learning applications within the domain of air combat, with a particular focus on future applications. Initially conceived as an exploration into fully autonomous systems, the focus shifted towards developing decision support mechanisms. This shift was motivated by the versatility of decision support, which can cater to the needs of both pilots and autonomous aircraft.

The research contributed to academic advancement in the field through a Ph.D. thesis and fostered industrial innovation. Expected results and effects:

Throughout the project, significant progress was made on the research front, including publications and presentations at the international conference ICUAS 2024. The articles form the basis for a Ph.D. thesis that shortly will be defended in public. An open-source Air Combat Beyond Visual Range was also developed to foster collaboration and facilitate experimentation within the research community.

Fighter pilots at Saab have given positive feedback on our ideas and results. We are considering implementing the decision support concept in Saab´s development environment. Approach and implementation:

The industrial Ph.D. student had a master´s degree in aeronautical engineering, but had to study machine learning from scratch for the research assignment. This has gone well, and he has produced several strong publications in the field and also written a Ph.D. thesis to be presented and defended in public. The Ph.D. student has developed a decision support tool to help operators in Beyond Visual Range (BVR) air combat scenarios assess the risks of different options and make decisions based on those. The results have been presented at a scientific conference.