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.

Marco Melega, Samuel Lazarus, Al Savvaris, Antonios Tsourdos (2015). Multiple Threats Sense and Avoid Algorithm for Static and Dynamic Obstacles. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 77(1), 215-228 [10.1007/s10846-014-0073-2].

Multiple Threats Sense and Avoid Algorithm for Static and Dynamic Obstacles

MELEGA, MARCO;
2015

Abstract

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.
2015
Marco Melega, Samuel Lazarus, Al Savvaris, Antonios Tsourdos (2015). Multiple Threats Sense and Avoid Algorithm for Static and Dynamic Obstacles. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 77(1), 215-228 [10.1007/s10846-014-0073-2].
Marco Melega;Samuel Lazarus;Al Savvaris;Antonios Tsourdos
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/399027
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