U nmanned aerial vehicles (UAVs) are acquiring an increased level of autonomy as more complex mission scenarios are envisioned [1]. For example, UAVs are being used for intelligence, surveillance, and reconnaissance missions as well as to assist humans in the detection and localization of wildfires [2], tracking of moving vehicles along roads [3], [4], and performing border patrol missions [5]. A critical component for networks of autonomous vehicles is the ability to detect and localize targets of interest in a dynamic and unknown environment. The success of these missions hinges on the ability of the algorithms to appropriately handle the uncertainty in the information of the dynamic environment and the ability to cope with the potentially large amounts of communicated data that will need to be broadcast to synchronize information across networks of vehicles. Because of their relative simplicity, centralized mission management algorithms have previously been developed to create a conflict-free task assignment (TA) across all vehicles. However, these algorithms are often slow to react to changes in the fleet and environment and require high bandwidth communication to ensure a consistent situational awareness (SA) from distributed sensors and also to transmit detailed plans back to those sensors. More recently, decentralized decision-making algorithms have been proposed [6]-[8] that reduce the amount of communication required between agents and improve the robustness and reactive ability of the overall system to bandwidth limitations and fleet, mission, and environmental variations. These methods focus on individual agents generating and maintaining their own SA and TA, relying on periodic intervehicle
After an actuator failure, the performance of an aircraft is degraded. If a fault detection and isolation system is available in the flight control system, the knowledge of the failure can be used to evaluate the new aircraft performance. Based thereon, a supervision system decides whether the mission can still be continued or if it should be aborted and have the aircraft redirected to the base station. In both cases, the aircraft should still be guided along a trajectory that is compatible with the new flying properties of the airplane. This paper focuses on an aileron failure and shows how the degraded flying performance can be evaluated and used to reconfigure the guidance system. Simulation results show that if the reduced performance due to the actuator failure is taken into account, the safety of the mission is improved.
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