A Real-time 3D Route Planner for Unmanned Air Vehicles

摘要

The ability of accurately and efficiently planning safe routes that achieve mission goals in a timely fashion is a requirement for many diverse applications, including military operations. Standard route planning algorithms usually generate a minimum cost route based on a predetermined cost function. Unfortunately, such a route may not represent a desirable solution for different military scenarios. In this paper, we present a 3D route planner for unmanned air vehicles based on Lagrange Programming Neural Networks (LPNN). Our approach can efficiently handle various constraints on the resultant route, such as minimum route leg length, maximum route length, maximum turning angle, maximum climbing/diving angle, minimum flight height, etc.