Optimal UAV Path Planning for Tracking a Moving Ground Vehicle with a Gimbaled Camera

Abstract

This research develops a path planning algorithm that autonomously controls a UAV to provide convoy overwatch. The optimization algorithm determines the best path to y through developing a cost function that minimizes the control effort of the UAV and the deviation from a desired slant range. A heuristic-based algorithm was developed and implemented on the autopilot to approximate the optimal solution. In flight test, the UAV successfully tracked a moving ground vehicle by continually placing the UAV\u27s loiter point directly above the ground vehicle\u27s current location. This method was called the \follow-me mode and provided the baseline for real-world UAV convoy overwatch. The follow-me mode resulted in a cost function value that was 113 times greater than the optimal path. Through an in-depth analysis, the heuristic-based approach reduced this ratio down to only 7.5 times greater than the optimal path. The data collected shows tremendous promise for improving autonomous UAV performance through optimal control techniques