Three-dimensional Route Planning for Unmanned Aerial Vehicles in a Risk Environment

This paper introduces a new approach for three-dimensional flight path optimization for unmanned aerial vehicles. It considers the performance of the air vehicle as well as mission specific requirements including the avoidance of no-fly areas, risk reduction in threat environments by terrain following flight or terrain masking low-level flight, and other regulations such as fixed release and approach vectors at the start and destination locations. The focus of the approach is on a proper discretization of the airspace by a network which allows the application of standard algorithms of combinatorial optimization. In contrast to conventional discretizations by grids or grid-like graphs, our network is non-regular since created by some random process. Moreover, each path in the network corresponds to a twice continuously differentiable trajectory which obeys the kinematic restrictions of the air vehicle and which is feasible with respect to the operational requirements of the mission. With suitable costs defined on the edges of the network, a minimum-cost path calculation allows to identify a trajectory of shortest length, shortest flight time, minimum flight height, or minimum visibility from the ground. The latter objectives aim to minimize the probability of being detected by hostile forces, hence increasing the survivability of the air vehicle.