A Real-Time Aerial Imagery Collection, Mapping, and Remote Sensing Testbench for Uncrewed Missions

As uncrewed aerial systems continue to grow in popularity and importance, the long-term and scalable use of these systems for remote sensing and imagery data collection remains a valuable and achievable goal. To enable these systems at scale, real-time onboard imagery processing is required. To determine the feasibility of real-time remote sensing systems, many factors must be accounted for, including the ability of the sensing and processing algorithms to operate on and collect data from real-world scenes and deliver actionable intelligence to the data consumer. In this paper, a holistic simulation system based on ROS 2 and Gazebo is presented, which allows for real-time processing algorithms to be tested and proven for flight in an accurate and extensible way. By using ROS 2 and USU AggieAir's STARDOS platform, it is possible to show how the remote sensing system and onboard, real-time processing algorithms are applicable to the aerial remote sensing task (i.e. it can demonstrate feasibility for physical deployment based on accurate simulated data processing).