Shared Control Between Adaptive Autopilots and Human Operators for Anomaly Mitigation

Abstract

Abstract As aerial vehicles become more autonomous, and guidance and navigation systems become increasingly network-centric, there is a need to consider a swift response to the growing forms of anomalies that may occur in these systems. We introduce a shared decision-making and control framework between a human operator and an adaptive autopilot, where the human operator plays a supervisory role and the adaptive autopilot retains the responsibility for low-level regulation and command tracking tasks. The human operator provides key inputs based on a higher-level perception of the anomaly, such as an increased lag in response to command inputs, which are then used by the adaptive autopilot in a suitable manner. The resulting shared control architecture is demonstrated on an unmanned aerial vehicle, whose actuators abruptly change from first-order to second-order due to an anomaly.