Safe landing planning for an energy-constrained multicopter

As Unmanned Aircraft Systems (UAS) become more prevalent and their commercial application in populated areas becomes technologically feasible, risk mitigation techniques must be developed to minimize the probability of harm to persons and property in the vicinity of the aircraft. This paper presents an algorithm to calculate a safe landing path for a small quadrotor UAS that experiences a low energy condition while flying over a populated area. This approach uses public databases of population distributions, structure locations, and terrain to create a cost map of the operating zone of the UAS offline. The UAS uses this data to quickly identify a safe landing path using an A* search algorithm. Simulation-based case studies are presented of a UAS operating within New York City to illustrate how different cost terms impact optimal path characteristics.