Initial designs for an automatic forced landing system for safer inclusion of small unmanned air vehicles into the national airspace

Abstract

Small unmanned air vehicles (UAVs) have unique advantages and limitations which will affect their safe inclusion into the national airspace system. In particular, challenges associated with emergency handling in beyond line of sight operations will be especially critical to address. This paper proposes initial designs for an autonomous decision system for UAVs to select emergency landing sites in a vehicle fault scenario. The overall design consists of two main components: pre-planning and realtime optimization. In the pre-planning component, the system uses offline information such as geographical and population data to generate landing loss maps over the operating environment, which can be used to constrain planning of flight routes to satisfy a bound on the expected landing loss under worst-case fault. In the real-time component, onboard sensor data is used to update a probabilistic risk assessment for potential landing areas allowing for refinement of the expected loss calculation and landing site selection at the time of a fault. The mathematical models and computational algorithms constituting these system components are based upon methodologies in optimal control and statistical inference. Simulation results are provided to demonstrate the application of the proposed algorithms in an example of quadrotor emergency landing over a section of UC Berkeley campus.