Simulation of a Fixed-wing UAV Forced Landing with Dynamic Path Planning

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Abstract

This paper describes the current status of a program to develop automated forced landing techniques for a fixed-wing Unmanned Aerial Vehicle (UAV). The paper outlines two dynamic path planning algorithms that were developed based on processes used by human pilots in forced landings. To evaluate the performances of these algorithms, a simulation environment was created using a non-linear 6 degree-of-freedom aircraft model. The simulation also modelled prevailing wind conditions which are a major factor in the forced landing planning process. Results from Monte Carlo testing demonstrate that the second algorithm was able to land the UAV inside the designated landing area with a success rate of 52%. This is twice the success rate of the first algorithm. The results of the Monte Carlo tests will serve as a benchmark for further refinements to the second algorithm,such that it can be implemented in an autonomous UAV forced landing system .