Real-Time Trajectory Generation for Target Localization Using Micro Air Vehicles

This thesis presents an approach to near-optimal target localization for small and micro unmanned aerial vehicles using a family of pre-computed parameterized trajectories. These trajectories are pre-computed for a set of nominal target locations uniformly distributed over the sensor field of view and stored offline in a non-dimensionalized form. In the first part of this research, the trajectories are parameterized and stored as a sequence of turn-rate commands. In the second part of this research, the trajectories are parameterized and stored as a sequence of non-dimensional waypoints. Upon target detection, a trajectory corresponding to the nearest nominal target location is selected and dimensionalized. An onboard navigation controller follows the dimensionalized trajectory. Thus, trajectory generation occurs in near-constant time, which allows for fast adaptation as the target state estimate is refined. Non-dimensionalization of the trajectories with respect to relative vehicle speed, sensor range, and sensor update rate allows the same table to be used for various combinations of sensor package and vehicle or vehicle operating conditions.