Enhanced Modified Voronoi Algorithm for UAV Path Planning and Obstacle Avoidance

Abstract

This paper presents an enhanced obstacle avoidance Voronoi algorithm for path planning and trajectory generation for unmanned aerial vehicles (UAVs). The proposed algorithm produces a flyable collision-free path through a series of obstacles/threats represented by cylindrical risk zones. A generalized model of the risk zones is formulated that can cover a wide diversity of real operational situations. This updated methodology produces a more predictable path grid with reduced computational overhead with respect to the original methodology by constructing the external path segments as tangent lines encircling the outer-most threat zones in the environment. The new methodology also improves the mechanism used to divert path segments away from obstacles. The result is a ready-to-use planner that can easily be implemented on-board UAVs. A model of the West Virginia University (WVU) YF-22 research aircraft implemented within the WVU UAV Simulation Environment is used to demonstrate the functionality of the proposed algorithm. The enhanced algorithm is compared with the original methodology to illustrate path generation and computational improvements.