Cooperative Tracking of Moving Targets by a Team of Autonomous UAVs

This paper summarizes current work on theoretical and experimental cooperative tracking of moving targets by a team of UAVs. The Insitu Group is leading a diverse group of researchers to develop building block foundations for cooperative tracking. The building block algorithms have been maturing through the partners, and the team led by Insitu is now pulling the technologies together for demonstration and commercialization. The work reported here focuses on cooperative tracking using multiple UAVs, with the ability for one operator to control many UAVs which are tasked to 1) provide autonomous tracking of moving and evading targets, and 2) report to a centralized database (without operator attention): the position, position history, velocity vector of the target being tracked. Flock guidance algorithms have been developed and simulated to enable a flock of UAVs to track an evading vehicle. Algorithms have been demonstrated in simulation that: dynamically allocate tasks and compute near-optimal paths in real-time; minimize the probability that vehicles are destroyed due to collision or damage from threat; and accommodate moving targets, time-on-targets, and sequencing, as well as the effects of weather (especially wind) and terrain. Additionally geolocation estimation algorithms and software have been developed which exchange information among vehicles, process the information robustly and in real time, and have demonstrated that the joint accuracy is improved. Work has also focused on accurate probabilistic analysis of the estimates, especially considering variations across multiple vehicle sets of ScanEagle UAVs