A process and machine configured to predict and preempt an undesired load and/or bending moment on a part of a vehicle resulting from an exogenous or a control input. The machine may include a predictor with an algorithm for converting parameters from a state sensed upwind from the part into an estimated normal load on the part and a prediction, for a future time, of a normal load scaled for a weight of the aerospace vehicle. The machine may: produce, using a state upwind from the part on the aerospace vehicle and/or a maneuver input, a predicted state, load and bending moment on the part at a time in the future; derive a command preempting the part from experiencing the predicted load and bending moment; and actuate the command just prior to the part experiencing the predicted state, thereby alleviating the part from experiencing the predicted load and bending moment.

An aircraft is provided, including: at least one sensor for measuring a wind; actuators (motors, control surfaces, etc.); a data base embedded aboard the aircraft, the data base associating various values of wind measurement with various set points for the attention of the actuators. The aircraft furthermore includes a system of analysis and control, arranged so as, or programmed so as: to receive values of wind measurement originating from the at least one sensor; searching, inside the data base, for a correspondence of the wind measurement values originating from the at least one sensor, and determining (as a function of this search) the directives to be dispatched to the actuators, and dispatching these determined directives to the actuators.

The systems and methods described herein relate to fully or partially autonomous or remotely operated aerial pollination vehicles that use computer vision and artificial intelligence to automatically detect plants, orient the vehicle to a pollen dispensing position above each plant, and pollinate the individual plants.

An imaging system that includes a camera mounted on an aerial platform, for example a balloon, allows a user to increase the longevity of the camera's battery by remote control. A user may capture imagery at a time scale of interest and desired power consumption by adjusting parameters for image capture by the camera. A user may adjust a time to capture an image, a time to capture a video, or a number of cycles per time period to capture one or more images as the aerial platform moves in a region of interest to change power consumption for imaging. The system also provides imaging alignment to account for unwanted movement of the aerial platform when moved in the region of interest. Additionally, a mounting device is provided that is simple and inexpensive, and that allows a camera to remain positioned in a desired position relative to the ground.

Provided is an LGVF path-following controller including: an LGVF control unit that is provided with a heading angle command for a wing-fixed unmanned aerial vehicle and guidance commands from the outside, and is provided with a computed estimation disturbance speed from a nonlinear disturbance control unit; a heading angle computation control unit that computes a final heading angle of the wing-fixed unmanned aerial vehicle using a difference between the heading angle of the wing-fixed unmanned aerial vehicle, which is computed by the LGVF control unit, and a heading angle of the wing-fixed unmanned aerial vehicle in an ideal environment where a disturbance is not present; and a nonlinear disturbance control unit that computes the estimation disturbance speed using the final heading angle provided from the heading angle computation control unit and pieces of sensor data on the wing-fixed unmanned aerial vehicle, which are provided from a sensor.

In one embodiment, a navigation system may include at least one self-describing fiducial with a communication element to communicate navigation state estimation aiding information comprising a geographic position of the self-describing fiducial with respect to one or more coordinate systems and a first navigating object to receive navigation information from an exterior system, receive navigation state estimation aiding information from the self-describing fiducial, and compare the navigation information received from the exterior system to the navigation state estimation aiding information to improve navigation parameters of the first navigating object.

It is prevented that a communication relay apparatus in an upper airspace, which is suitable for constructing a three-dimensional network, falls by a strong wind. A communication relay apparatus is provided with a relay communication station that performs a radio communication with a terminal apparatus, and is capable of flying in an upper airspace by an autonomous control or an external control. This communication relay apparatus includes a flight control section that controls a flight of the communication relay apparatus based on flight control information determined so as to reduce an influence of a strong wind generated around the communication relay apparatus. The flight control information may include information for controlling at least one of a flight direction, velocity, altitude, attitude, flight route and flight pattern of the communication relay apparatus.

An aircraft is provided including an airframe, an extending tail, and a counter rotating, coaxial main rotor assembly including an upper rotor assembly and a lower rotor assembly. A translational thrust system positioned at the extending tail, the translational thrust system providing translational thrust to the airframe. A cockpit in the airframe, the cockpit including two seats and a single collective control input positioned between the two seats.

Using a set of airflow sensors disposed on an airfoil of an aircraft, first airflow data including an amount of airflow experienced at each airflow sensor at a first time is measured. Using a trained neural network model, the first airflow data is analyzed to determine an airflow state of the aircraft. In response to determining that the aircraft is in the abnormal airflow state, a control surface and a power unit of the aircraft are adjusted. Responsive to the adjusting, the aircraft is returned to the normal airflow state.

An apparatus for guiding an aircraft includes: an air velocity sensor disposed on the aircraft and configured to sense a speed and direction of a wind remote to the aircraft to provide remote wind speed and direction data; a flight control actuator coupled to a flight control device; and a flight controller communicably coupled to the air velocity sensor, the flight controller having an input section that receives the remote wind speed and direction data from the air velocity sensor, a processor configured to determine a magnitude and direction of the wind with respect to a planned flight route and to predict an influence acting on the aircraft due to the magnitude and direction of the wind with respect to the planned flight route, and an output section communicably coupled to the flight control actuator to provide a control signal that results in the aircraft counteracting the predicted influence.