A highly reliable and high-precision navigation and positioning method and system for UAV under GPS-DENIED conditions includes: obtaining measurements of inertial sensor and image of binocular camera, extracting and tracking point features of the image, and obtaining altitude value; calculating position and attitude of camera and depth of landmark point based on the parallax and baseline of the binocular camera; fusing the measurement data of the inertial sensor and the binocular camera, and optimizing the data to obtain high-precision position and attitude data; obtaining the altitude value of the ranging radar and performing four-degree-of-freedom position and attitude graph optimization after adding the detected keyframes when repeated occurrence of the UAV at the same location is detected; encapsulating optimized position and attitude data to form a pseudo-GPS signal, inputting the pseudo-GPS signal to the UAV for positioning.

Illustrative examples are provided of a process and machine configured to provide innovative technical solutions for: deriving a predicted trajectory for a vehicle; controlling a trajectory for a vehicle; and for reducing congestion in an Air Traffic Management system, via: a processor executing an algorithm specially programmed for: generating a baseline lateral profile for a baseline trajectory; subsequently generating a baseline vertical profile for the baseline trajectory; subsequently forming the baseline trajectory by merging the vertical profile with the baseline lateral profile; and using at least one of: a performance element, or a configuration element, from the baseline trajectory for deriving the predicted trajectory. The predicted trajectory is sent for use by a Flight Management System and/or an Air Traffic Management System.

Illustrative examples are provided of a process and machine configured to provide innovative technical solutions for: deriving a predicted trajectory for a vehicle; controlling a trajectory for a vehicle; and for reducing congestion in an Air Traffic Management system, via: a processor executing an algorithm specially programmed for: generating a baseline lateral profile for a baseline trajectory; subsequently generating a baseline vertical profile for the baseline trajectory; subsequently forming the baseline trajectory by merging the vertical profile with the baseline lateral profile; and using at least one of: a performance element, or a configuration element, from the baseline trajectory for deriving the predicted trajectory. The predicted trajectory is sent for use by a Flight Management System and/or an Air Traffic Management System.

An apparatus for guiding a transition between flight modes of an electric aircraft is illustrated. The apparatus comprises at least a sensor configured to detect a movement datum of the electric aircraft and a flight controller communicatively connected to the at least sensor, wherein the flight controller is configured to receive the movement datum from the at least a sensor, determine a current flight mode of the electric aircraft as a function of the movement datum, generate a guidance datum as a function of a change in flight mode and the movement datum, communicate the movement datum and the guidance datum to a pilot indicator in communication with the flight controller, and display the movement datum and the guidance datum using the pilot indicator.

An apparatus for guiding a transition between flight modes of an electric aircraft is illustrated. The apparatus comprises at least a sensor configured to detect a movement datum of the electric aircraft and a flight controller communicatively connected to the at least sensor, wherein the flight controller is configured to receive the movement datum from the at least a sensor, determine a current flight mode of the electric aircraft as a function of the movement datum, generate a guidance datum as a function of a change in flight mode and the movement datum, communicate the movement datum and the guidance datum to a pilot indicator in communication with the flight controller, and display the movement datum and the guidance datum using the pilot indicator.

The present invention is for an autonomous aerial vehicle that enables near real-time and offline data processing among heterogenous devices that are in unreliable or unconnected network service areas, wherein the heterogenous devices are associated with heavy industrial systems. The autonomous aerial vehicle may obtain data from a first physical asset, and segment the obtained data as suitable for a local area compute node and/or a cloud compute node. The autonomous aerial vehicle may identify a location associated with the one or more destination devices and may compute a flight path to the destination location. The aerial device may hereafter travel to the destination location and upload relevant data to the at least one destination upon arrival.

The present invention is for an autonomous aerial vehicle that enables near real-time and offline data processing among heterogenous devices that are in unreliable or unconnected network service areas, wherein the heterogenous devices are associated with heavy industrial systems. The autonomous aerial vehicle may obtain data from a first physical asset, and segment the obtained data as suitable for a local area compute node and/or a cloud compute node. The autonomous aerial vehicle may identify a location associated with the one or more destination devices and may compute a flight path to the destination location. The aerial device may hereafter travel to the destination location and upload relevant data to the at least one destination upon arrival.

The information processing device detects a feature existing in the peripheral area of a landing candidate place of the UAV 1, estimates a degree of influence on a landing due to downwardly-blowing wind generated during the landing of the UAV 1, hitting and bouncing off the feature, which is the degree of influence at the landing candidate place, and determines whether or not the landing candidate place is suitable for landing on the basis of the estimated degree of influence.

A method for managing a longitudinal position a follower aircraft following a leader aircraft by: obtaining a position and speed of the leader aircraft and a real longitudinal position and speed of the follower aircraft; determining a target longitudinal position of the follower aircraft with respect to the longitudinal position of the leader aircraft; calculating a difference between the target longitudinal position of the follower aircraft and the real longitudinal position of the follower aircraft; comparing the value of the difference with at least one predefined threshold; choosing a control law for controlling the speed of the follower aircraft, from among at least two separate control laws, on the basis of the comparison; and, applying the chosen control law so as to manage the real longitudinal position of the follower aircraft with respect to the position of the leader aircraft.

A method for managing a longitudinal position a follower aircraft following a leader aircraft by: obtaining a position and speed of the leader aircraft and a real longitudinal position and speed of the follower aircraft; determining a target longitudinal position of the follower aircraft with respect to the longitudinal position of the leader aircraft; calculating a difference between the target longitudinal position of the follower aircraft and the real longitudinal position of the follower aircraft; comparing the value of the difference with at least one predefined threshold; choosing a control law for controlling the speed of the follower aircraft, from among at least two separate control laws, on the basis of the comparison; and, applying the chosen control law so as to manage the real longitudinal position of the follower aircraft with respect to the position of the leader aircraft.