Optimization-Based Safety Analysis of Obstacle Avoidance Systems for Unmanned Aerial Vehicles

The integration of Unmanned Aerial Vehicles (UAVs) requires new methods to certify collision avoidance systems. This paper presents a safety clearance process for obstacle avoidance systems where worst case analysis is performed using optimization based approaches under all possible parameter variations. The clearance criterion for the UAV obstacle avoidance system is defined as the minimum distance from the aircraft to the obstacle during the collision avoidance manoeuvre. Local and global optimization based verification processes are developed to automatically search the worst combinations of the parameters and the worst-case distance between the UAV and an obstacle under all possible variations and uncertainties. Based on a simplified 4 Degree of Freedom (4DoF) kinematic and dynamic model of a UAV, the path planning and collision avoidance algorithms are developed in 3D. The artificial potential field method is chosen as a path planning and obstacle avoidance candidate technique for verification study as it is a simple and widely used method. Different optimisation algorithms are applied and compared in terms of the reliability and efficiency Keywords— Clearance process, Obstacle avoidance, Optimization, Potential field method, Unmanned Aerial Vehicle.