Autonomous Collision avoidance for Unmanned aerial systems

Unmanned Aerial System (UAS) applications are growing day by day and this will lead Unmanned Aerial Vehicle (UAV) in the close future to share the same airspace of manned aircraft.This implies the need for UAS to define precise safety standards compatible with operations standards for manned aviation. Among these standards the need for a Sense And Avoid (S&A) system to support and, when necessary, sub¬stitute the pilot in the detection and avoidance of hazardous situations (e.g. midair collision, controlled flight into terrain, flight path obstacles, and clouds). This thesis presents the work come out in the development of a S&A system taking into account collision risks scenarios with multiple moving and fixed threats. The conflict prediction is based on a straight projection of the threats state in the future. The approximations introduced by this approach have the advantage of high update frequency (1 Hz) of the estimated conflict geometry. This solution allows the algorithm to capture the trajectory changes of the threat or ownship. The resolution manoeuvre evaluation is based on a optimisation approach considering step command applied to the heading and altitude autopilots. The optimisation problem takes into account the UAV performances and aims to keep a predefined minimum separation distance between UAV and threats during the resolution manouvre. The Human-Machine Interface (HMI) of this algorithm is then embedded in a partial Ground Control Station (GCS) mock-up with some original concepts for the indication of the flight condition parameters and the indication of the resolution manoeuvre constraints. Simulations of the S&A algorithm in different critical scenarios are moreover in-cluded to show the algorithm capabilities. Finally, methodology and results of the tests and interviews with pilots regarding the proposed GCS partial layout are covered

Multiple Threats Sense and Avoid Algorithm for Static and Dynamic Obstacles

This paper presents a new computationally efficient S&A algorithm for implementation in real-time applications for UAV. Based on a simplified optimisation approach, the proposed algorithm aims to provide a reliable resolution manoeuvre (horizontal and vertical) for multiple threat scenarios which include both air and ground threats/obstacles. In presence of a conflict risk, the avoidance manoeuvre is defined as step variation in the heading angle or altitude variation of the autopilots command. This step command is optimised in order to keep a minimum distance of separation between the ownship and all threats during the overall manoeuvre. The algorithm computes the separation distance between the UAV and the threats by calculating the future trajectories at each time step of both the ownship and the threat, while always taking into account the ownship performance envelope constraints. The algorithms were validated in simulation, where the ground threats were derived from the ground elevation maps, while for the aerial threats the aircraft communicate their flight data through an ADS-B mode S transponder. The resolution manoeuvre optimisation technique takes about 0.1 second to compute. Hence enabling the algorithm to cope with any rapid changes in the aerial threat trajectory