Simulator Based mission optimization for swarm UAVs with Minimum Safety Distance Between Neighbors

View Video Presentation: https://doi.org/10.2514/6.2023-4453.vid The increasing prominence of Unmanned Aerial Vehicles (UAVs) in research has resulted in a heightened focus on their applications in both civilian and military sectors. As UAVs persist in playing an essential role in the future, understanding the minimum safety distances required for swarms during transportation between locations becomes crucial. Maintaining optimal safety distances is vital for preventing collisions and maximizing the efficient use of airspace. This paper investigates a Machine Learning (ML) approach to address this concern for fleets comprising ten or more swarm vehicles, employing a PX4/ROS/Gazebo-based digital simulation system framework to determine the minimum safety distance in various UAV transportation settings.