An emergency module may determine the occurrence of an autorotation condition for a rotary wing air vehicle controlled by a user. The emergency module may, responsive to determining the occurrence of the autorotation condition, control the air vehicle to enter into an autorotation. The emergency module may perform one or more non-user actions during the autorotation to assist the user with the autorotation. The emergency module may, while performing the one or more non-user actions during the autorotation, allow the user to maneuver the air vehicle by interacting one or more control interfaces of the air vehicle.

A control unit for an aircraft capable of hovering or for a flight simulation system of the aircraft is described; the control unit is programmed to: receive in input a plurality of data associated with equipment and/or kits actually installed or simulated on the aircraft and/or with the operating configuration of the equipment and/or kits; the equipment and/or kits causing a reduction of the actual or simulated forward velocity of the aircraft; store a table defining a correspondence between each datum and a respective value of a first signal associated with a value of maximum forward velocity of the aircraft; and display the lowest of the first signals.

This automatic takeoff/landing system for a vertical takeoff/landing aircraft comprises: a relative wind information acquisition unit that acquires the direction of relative wind at a moving object; and a control unit that executes takeoff/landing control to cause the vertical takeoff/landing aircraft to takeoff/land at a landing target point provided on the moving object. The control unit, during takeoff/landing of the vertical takeoff/landing aircraft, executes the takeoff/landing control on the basis of the direction of the relative wind acquired by the relative wind information acquisition unit, in a state in which the aircraft heading of the vertical takeoff/landing aircraft is caused to face the direction of the relative wind.

Example computer-implemented methods and systems for anomaly-sensing based multi-agent navigation are disclosed. One example computer-implemented method includes: receiving relative distance data specifying distance between at least one pair of agents of a plurality of agents, each of a first subset of the plurality of agents having an anomaly sensor subsystem; determining a set of relative pose vectors based at least in part on the relative distance data; receiving anomaly data from at least one anomaly sensor subsystem of one of the plurality of agents; obtaining pre-surveyed map data; determining global pose data of the plurality of agents based on the relative distance data and based on comparing the anomaly data to the pre-surveyed map data; and assigning a task to at least one of the plurality of agents based at least in part on a specialized operational capability of the at least one of the plurality of agents.

Embodiments of the disclosure provide for handover or roaming of unmanned vehicles and missions between ground control stations (GCSs) of the same or different ground control centers (GCCs). Some embodiments receive a control change indication indicative of reassignment of a vehicle associated with a first GCS that is associated with a first GCC. Some embodiments reassign the vehicle from a first GCS to a second GCS associated with the GCC to enable the second GCS to newly access data corresponding to the vehicle via the master control system to enable control of the vehicle. Some embodiments reassign the vehicle from a first GCC to a second GCC by copying data corresponding to the vehicle from the master control system of the first GCC to a second master control system of a second GCC to enable control of the vehicle via at least one GCS of the second GCC.

Provided are a system and device for controlling communication with clustered unmanned aerial vehicles (UAVs) and a storage medium on which a computer program is recorded. The system includes a server and a plurality of drone clusters configured to establish communication channels with the server and communicate with each other. Each of the plurality of drone clusters includes a master drone and slave drones configured to form a cluster with the master drone. To minimize the number of communication channels, a certain number of drone clusters are formed as the plurality of drone clusters with a master drone and a certain number of slave drones in each drone cluster.

A system and method for tilt dead reckoning is provided. The system and method allows an autopilot of an unmanned aerial vehicle (UAV) to perform dead reckoning with a hovering vehicle during GNSS signal loss by estimating the position and velocity of the vehicle based on its pitch and roll angles and known vehicle dynamics. The position and velocity are estimated using tables set up by a UAV integration engineer that provide the expected airspeed at given pitch and roll angles in steady state. This allows the UAV to attempt to follow waypoints when GNSS signal is lost without using any additional sensors.

An aircraft control system includes a target instruction value calculation unit configured to acquire a target instruction value to set an aircraft in a target state, a reference velocity calculation unit configured to input, to a reference model in which a reference velocity corresponding to a reference value of an aircraft velocity is set uniquely as an output value according to an input value, a value based on the target instruction value as the input value. A relative velocity calculation unit is configured to calculate a relative velocity of the aircraft to a target position. An estimated disturbance quantity calculation unit is configured to calculate an estimated disturbance quantity acting on the aircraft, based on a difference between the relative and reference velocities, and a correction target instruction value calculation unit is configured to correct the target instruction value, based on the estimated disturbance quantity calculated at a previous time.

The present invention provides methods and systems for remote operation of a vehicle with the capability to deal with communications jitter and intermittency. In particular, the methods and systems herein may safely predict a remote operator's intent (e.g., remote pilot) over long time scales, and up to the lost link timeout T.sub.LL.

The present relates to a method for operating a drone (1) navigating within an arena (18) delimited by boundaries (19), the navigation of the drone (1) in the arena (18) being ruled by a navigation program setting the navigation parameters of the drone (1) to ensure the drone (1) follows a calculated trajectory. The setting of the navigation parameters of the drone (1) in the navigation program depends on the object impacting the drone (1). The setting step comprises implementing a virtual impact setup in the navigation program for adjusting the navigation parameters of the drone (1) to an impact between the drone (1) and a virtual object, and implementing a real impact setup in the navigation program for adjusting the navigation parameters of the drone (1) to an impact between the drone (1) and a physical object.