UAS Collision Avoidance Algorithm Based on an Aggregate Collision Cone Approach

Abstract

A collision-avoidance (CA) algorithm is developed and implemented that is applicable to many different unmanned aerial systems (UAS), ranging from a single platform with the ability to perform all collision-avoidance functions independently to multiple vehicles performing functions as a cooperative group with collision-avoidance commands computed at a ground station. The algorithm leverages advances in several theoretical fields, including robotics, homing guidance, and airspace management, and considers several approaches to conflict detection and resolution, including the collision cone approach. The collision-avoidance system is exercised and tested by using operational hardware and platforms. Novel developments by using an aggregated collision cone approach allow each unmanned aircraft to detect and avoid collisions with two or more other aircraft simultaneously. The collision-avoidance system is implemented by using a miniature unmanned aircraft with an onboard autopilot. Various simulation and flight test cases are used to demonstrate the algorithm’s robustness to different collision encounters at various engagement angles. The flight test results are compared with ideal, software-in-the-loop, and hardware-in-the-loop tests. The results presented are the first known flight tests of two or more unmanned aircraft systems equipped with the same global, three-dimensional, geometric collision-avoidance system.