A computer processing system for optimising a sequence of aircraft at an airport is disclosed. The system comprises a module configured to receive flight plan data associated with a plurality of journeys between an origin and destination wherein each journey is associated with a different aircraft and wherein the flight plan data comprises flight schedule data associated with the plurality of different journeys; a second module coupled to the first module wherein the second module is configured to determine an aircraft taxi time, EXOT, based on the flight plan data; a third module coupled to the first module and the second module wherein the third module is configured to determine a target take-off time, TTOT, associated with each of the plurality of different journeys wherein the target take-off time is determined based on the taxi time, EXOT, and the flight plan data.

An in-flight risk management system includes an eye sensor, a seat sensor, and one or more in-flight risk management computers that perform operations including: obtaining history information for a flight crew member, obtaining flight information associated with a flight on which the flight crew member will be present, determining, based on the history information and the flight information, a predicted fatigue profile for the flight crew member, determining, based on the predicted fatigue profile for the crew member, one or more fatigue indicator profiles for the flight crew member, obtaining, from at least one of the eye sensor or seat sensor, one or more measured fatigue indicator values associated with the flight crew member, generating, based on the one or more measured fatigue indicator values, one or more updated fatigue indicator profiles, and generating, based on the one or more updated fatigue indicator profiles, an updated predicted fatigue profile.

Technology for operating an unmanned aerial vehicle (UAV) is disclosed herein that allows a drone to be flown along a computed spline, while also accommodating in-flight modifications. In various implementations, a UAV includes a flight control subsystem and an electromechanical subsystem. The flight control subsystem records keyframes during flight and computes a spline based on the keyframes. The flight control subsystem then saves the computed spline for playback, at which time the UAV automatically flies in accordance with the computed spline.

Systems and methods for terminal procedure prediction for flight planning include obtaining, at a processor, input data corresponding to an upcoming flight of an aircraft; obtaining, at the processor, predicted data corresponding to the upcoming flight; and processing, at the processor, the input data and the predicted data to obtain a terminal procedure prediction associated with the upcoming flight, the terminal procedure prediction at least partially based on flight plans of historical flights having conditions similar to the input data and the predicted data.

An example operation may provide receiving, at a server, one or more communications from a drone, determining the one or more communications identify a drone identifier and a current time, determining whether the one or more communications were received within a time window, assigning a token to the identified drone indicating the drone is active, and storing the token as a transaction in memory.

A method is provided for detecting and avoiding conflict along a current route of a robot. The method includes accessing a trajectory of the robot on the current route of the robot, and a predicted trajectory of a nearby moving object, and from the trajectory and predicted trajectory, detecting a conflict between the robot and the nearby moving object. Alternate routes for the robot are determined, each of which includes an alternative route segment offset from the current route, and a transition segment from the current route to the alternative route segment. Routes including the current and alternative routes are evaluated according to a cost metric, and a route from the routes is selected for use in at least one of guidance, navigation or control of the robot to avoid the conflict.

This disclosure relates to apparatuses, systems, and methods for controlling an aircraft. A computing system may identify a first command signal received via a flight control at a time point to control navigation of the aircraft through an environment. The computing system may attenuate the first command signal using a fade function over a time window relative to the time point to generate a second command signal. The computing system may input the second command signal to a model to generate predicted paths for the aircraft through the environment over the time window. The computing system may determine that at least one predicted path intersects with an obstacle in the environment during the time window. The computing system may generate a location to which to navigate the aircraft to avoid the obstacle. The computing system may perform an action to direct the aircraft to the location.

The method S200 can include: at an aircraft, receiving an audio utterance from air traffic control S210, converting the audio utterance to text, determining commands from the text using a question-and-answer model S240, and optionally controlling the aircraft based on the commands S250. The method functions to automatically interpret flight commands from the air traffic control (ATC) stream.

An information processing apparatus and corresponding information processing method performed by the information processing apparatus. The information processing apparatus includes a transceiver and a control circuit. The method includes: determining a number of flight vehicles within a predetermined region around exclusive controlled airspace; and transmitting one or more control signals to limit a number of flight vehicles that enter the exclusive controlled airspace, the exclusive controlled airspace including an area where the flight vehicles cannot report their own locations.

Systems and methods for defining a custom fix via a graphical user interface (GUI) for operation of an aircraft. The method includes uniquely sized and arranged custom fix dialog GUI windows that are displayed on an active avionic display, the custom fix dialog windows having preprogrammed arrangements of GUI objects. The GUI objects allow a user to select between custom airports or custom runways, and to select between create, edit, and store custom fix functions. The method decodes and sequences user input, as related to the displayed GUI objects. Embodiments keep track of required data fields for respective custom fixes, and store custom fix data in a custom database that is compatible with the navigation database and avionic display systems.