The use of unmanned aerial vehicles (UAVs) for time critical tasks is becoming increasingly popular. Operators are expected to use information from these swarms to make real-time and informed decisions. Consequently, detecting and recognizing targets from video is extremely pivotal to the success of these systems. At greater altitudes or with more vehicles, this process becomes increasingly difficult and requires significant scrutiny from an operator. Hence, it is important to try and optimize the information passed between a UAV and the operator. In this work, we present a system that can be used to recreate high-fidelity environments as well as simulate the behavior and data of a UAV swarm. This simulation extends AirSim, a flight simulator plugin for Unreal Engine, to deploy fixedwing aircrafts and other vehicles for the use of conspicuity measurement and other visual salience studies. Through the use of this simulator, we showcase the effects that various factors can have on an operator’s target recognition including altitude, velocity, and conspicuity.

Katia Sycara (advisor)

Henny Admoni

Renos Zabounidis