A system for navigating an aircraft in a hangar, having at least one optical sensor firmly connected to the aircraft. The sensor can be used to continuously capture surroundings contour data relative to the aircraft. A data processing apparatus, connected to the sensor, has a data memory storing reference data and can be used to determine an aircraft actual position by continuously matching captured surroundings contour data with the reference data and to identify a position deviation by comparing the determined actual position with a stored target position. Also, a method for navigating an aircraft in a hangar with such a system.

Provided are airplane trim systems and methods of controlling such systems. These systems utilize smaller portions of the stabilizer total travel range for takeoff trims, in comparison to other trim systems. A trim system described includes stabilizer and elevator, and these components are used together to achieved a takeoff total tail pitching moment. The elevator or, at least a portion of the elevator operating range, is available for flight control. As such, takeoff trim settings include stabilizer and elevator orientation settings. Addition of the elevator to control the takeoff tail pitching moment allows reducing the stabilizer total travel. The elevator orientation can be changed much faster than that of the stabilizer providing pilot more control.

The present invention relates generally to the operation of aircraft maneuvering with its landing gear in contact with a surface. Multiple electromagnetic-wave sensors measure, with respect to the surface, the aircraft's lateral and longitudinal translational velocities, as well as the aircraft's yaw rate. Icons representing the measured velocities and rotations are displayed to onboard or remotely-located pilots of such aircraft to make them aware of slipping, side sliding, moving rearward, and other uncommanded movements caused by: low friction surfaces, wind buffeting, rolling and pitching platforms, and other disturbances. Pilots can use the increased awareness of the aircraft's movements with respect to the surface to take corrective action to prevent accidents.

These capabilities can further be exploited to display icons representing the alignment of the aircraft with respect to a surface as opposed to alignment with respect to the horizon as is the present practice. Profiles of the surface along with distances between the aircraft and the surfaces which may have sloping topography, or which may be the surface of a moving platform are also displayed to the onboard or remotely-located pilot of aircraft that are landing, taking off, or hovering near a surface.

In various examples, live perception from sensors of a vehicle may be leveraged to generate potential paths for the vehicle to navigate an intersection in real-time or near real-time. For example, a deep neural network (DNN) may be trained to compute various outputssuch as heat maps corresponding to key points associated with the intersection, vector fields corresponding to directionality, heading, and offsets with respect to lanes, intensity maps corresponding to widths of lanes, and/or classifications corresponding to line segments of the intersection. The outputs may be decoded and/or otherwise post-processed to reconstruct an intersectionor key points corresponding theretoand to determine proposed or potential paths for navigating the vehicle through the intersection.

An aircraft includes a safe takeoff system that automatically and autonomously rejects a takeoff if actual measured acceleration deviates from calculations based on pre-flight parameters and the speed of the aircraft traveling down the runway is within a safe speed range to guarantee a successful low inertia rejected takeoff.

Embodiments are disclosed for a machine and process that include a computer code specially programmed for creating a runway extension speed for an aircraft taking off. The process may include sensing current location, current acceleration, and current speed, for the aircraft during takeoff roll; receiving, in a ROTTOWIRE, the current speed and the current acceleration for the aircraft; creating in the ROTTOWIRE an actual speed profile; creating, using a specially coded program in the ROTTOWIRE and the current acceleration, the runway extension speed via determining, for a current location of the aircraft, a distance from a departure end of the runway and a terminating distance required to terminate the takeoff to a stop of the aircraft on the runway, a distance until the aircraft reaches a designated height; and when the terminating distance equals the distance from the departure end of the runway; and presenting the runway extension speed.

An example method for predictive take-off rejection (TOR) of an aircraft includes receiving, at a computing device on the aircraft and at a time before the aircraft takes off for a current flight, outputs from a plurality of sensors positioned on the aircraft, comparing the outputs received from the plurality of sensors for the current flight to reference flight data, based on comparing the outputs received from the plurality of sensors for the current flight to the reference flight data the computing device making a determination of whether to initiate a TOR procedure before the aircraft reaches a takeoff speed on a runway, and based on determining to initiate the TOR procedure, the computing device sending a signal to a control device on the aircraft to initiate the TOR procedure.

To provide a safety device that, when a crosswind is present, allows an aircraft to more safely land on a runway in an airport. This safety device 10 for landing in a crosswind is designed for landing of an aircraft 1 on a runway 3 in a crosswind across the runway 3, and provided with a control unit 14 for controlling, when the nose cone 1T of the fuselage 8 of the aircraft 1 is directed windward, the orientation of the wheels of the aircraft 1 such that the wheels are oriented in the direction of travel of the aircraft 1.

Techniques for drone device control are provided. In one example, a computer-implemented method comprises: meeting, by a drone device operatively coupled to a processor, an aircraft at a first location; and guiding, by the drone device, the aircraft to a second location along a ground movement path selected from a plurality of ground movement paths associated with an airport. The guiding can comprise providing a direction indication to the aircraft; and monitoring a defined region around the aircraft for one or more hazards. The guiding can also comprise, in response to identifying a hazard from the one or more hazards related to the defined region around the aircraft, providing a hazard indication to the aircraft.

An example computing device may detect through a sensor that an aircraft started a particular phase of flight. The computing device may autonomously take independent actions on behalf of service operators to automatically allocate and assign resources to the aircraft based on availability of the resources and the flight phase of the aircraft. The computing device may thus trigger preparation of a particular service ahead of arrival of the aircraft, such that the associated service equipment is ready when the aircraft arrives at the gate.