Optimization-based Path Planning for Separation Assurance on Small Unmanned Aircraft
This paper presents a time-based path planning optimizer for separation assurance for unmanned aircraft systems (UAS). Given Automatic Dependent Surveillance-Broadcast (ADS-B) as a sensor, intruder information such as position, velocity, and identification information is available at ranges on the order of 50 nautical miles. Such long-range intruder detection facilitates path planning for separation assurance, but also poses computational challenges. The time-based path optimizer presented in this paper provides a path-planning method that takes advantage of long-range ADS-B information and addresses the associated challenges. It is capable of long-range path planning and, due to the convex formulation, is computationally efficient enough to run successively for increased robustness. The ultimate result of this research is a convex, time-based path planner that is suitable for a detect- and-avoid solution on small UAS in the National Airspace System.