Online Border Patrol Guidance Algorithm for Unmanned Aerial Vehicles

Abstract

nding an online path planning algorithm for unmanned aerial vehicles (UAVs) in charge of autonomous border patrol is studied. As a Pursuit-Evasion game, the UAV is required to capture multiple trespassers on its own before any of them are able to reach a certain destination where they will be safe from capture. The problem formulation is based on Isaacs’ Target Guarding problem, but extended to the case of multiple evaders. Rapidly-exploring random trees (RRT), a sampling-based path planning method, are proposed as the solution to the research problem. Online RRT algorithms capable of producing trajectories within seconds are developed for the pursuer to capture 2 and 3 evaders. Simulations using the algorithms are carried out for various scenarios, including dierent pursuer-evader speed ratios and pursuer capture radius. The algorithms are demonstrated to generate trajectories that converge to the optimal solution produced by a nonlinear programming-based numerical optimal control solver.