System and method for determining distance in navigation of an electric aircraft is illustrated. The system and method comprise a sensor and a computing device. The sensor is configured to detect a surface and transmit at least a first signal and a first frequency and at least a second signal at a second frequency to a computing device, wherein the first signal and the second signal comprise a corresponding distance. The computing device is configured to receive a returned signal from the sensor, wherein the returned signal comprises an intermodulation product associated to the first signal and the second signal, detect an amplitude of the returned signal as a function of the frequency, identify a distance datum as a function of the amplitude and an amplitude threshold, determine an aircraft adjustment as a function of the distance datum, and transmit the distance datum and aircraft adjustment to a remote device.

A response system may be provided. The response system may include a security system and an autonomous drone. The security system includes a security sensor and a controller. The drone includes a processor, a memory in communication with the processor, and a drone sensor. The processor may be programmed to receive the deployment request from the security system, navigate to the one or more zones of the coverage area included in the deployment request, collect drone sensor data of the one or more zones of the coverage area using the at least one drone sensor, determine that an incident has occurred, and/or transmit the collected drone sensor data and incident verification to the security system, wherein, in response to receiving the collected drone sensor data and incident verification, the security system is configured to generate a command for responding to the incident.

A flight management system for unmanned aerial vehicles (UAVs), in which the UAV is equipped for cellular fourth generation (4G) flight control. The UAV carries on-board a 4G modem, an antenna connected to the modem for providing for downlink wireless RF. A computer is connected to the modem. A 4G infrastructure to support sending via uplink and receiving via downlink from and to the UAV. The infrastructure further includes 4G base stations capable of communicating with the UAV along its flight path. An antenna in the base station is capable of supporting a downlink to the UAV. A control centre accepts navigation related data from the uplink. In addition, the control centre further includes a connection to the 4G infrastructure for obtaining downlinked data. A computer for calculating location of the UAV using navigation data from the downlink.

A method for navigating an airborne device relative to a target comprises detecting, at an optical detector on the airborne device, an optical signal generated by one or more LEDs on the target. The method also comprises comparing, by a processor on the airborne device, the detected optical signal with a previously-detected optical signal. The method further comprises determining, by the processor based on the comparison, a change in location of at least one of the airborne device or the target. The method also comprises adjusting a position of the airborne device based on the determined change in location. The method also comprises predicting, by the processor, a movement of the target based on information indicative of at least one of a position, a rotation, an orientation, an acceleration, a velocity, or an altitude of the target, wherein the position of the airborne device is adjusted based on the predicted movement of the target. The method also comprises detecting an obstacle in a flight path associated with the airborne device and adjusting a position of the airborne device is further based, at least in part, on detected obstacle information.

A device for assisting the piloting of a rotorcraft in order to pilot a rotorcraft during an approach stage preceding a stage of landing on a rotorcraft landing area. Such a device includes in particular a camera for taking a plurality of images of the environment of the rotorcraft along a line of sight, looking at least along a forward direction Dx of the rotorcraft, and processor means for identifying in at least one image from among said plurality of images at least one looked-for landing area.

According to the present invention there is provided a drone (1) comprising one or more propellers (2) and one or more actuators (3) for actuating said one or more propellers (2) to generating a thrust force which enables the drone (1) to fly; a controller (4) which is configured such that it can control the flight of the drone (1), wherein the controller (4) comprises a memory (6) having stored therein a plurality of predefined sets of positions which define a virtual rail which can be used to guide the flight of the drone (1) so that the drone can avoid collision with an subject; and wherein the controller further comprises a mathematical model (7) of the drone; wherein the controller (4) is configured to control the flight of the drone by performing at least the following steps, (a) approximating lag error based on the position of the drone (1) measured by a sensor (5) and the virtual rail, wherein the lag error is the distance between a point along the virtual rail which is closest to the drone (1) and an estimate of said point along the virtual rail which is closest to the drone (1); (b) approximating a contour error based on the position of the drone (1) as measured by a sensor (5) and the virtual rail, wherein the contour error is the distance between a point along the virtual rail which is closest to the drone (1) and the position of the drone (1); (c) defining a cost function which comprises at least said approximation of the lag error and said approximation of the contour error; (d) minimizing the defined cost function, while also respecting at least limitations of the drone which are defined in said mathematical model, to determine a plurality of control inputs over a predefined time period into the future, and (e) applying the first control input only to the one or more actuators (3). There is further provided a corresponding method for controlling the flight of a drone.

Boundary information associated with a three-dimensional (3D) flying space is obtained, including a boundary of the 3D flying space. Location information associated with an aircraft is obtained, including a location of the aircraft. Information is presented based at least in part on the boundary information associated with the 3D flying space and the location information associated with the aircraft, including by presenting, in a display, the boundary of the 3D flying space and an avatar representing the aircraft at the location of the aircraft.

An air vehicle control system (1) and method for operation of one or more air vehicles, AVs, (2) flying along flight routes (FR) assigned to the air vehicles, AVs, (2) by said air control system (1) according to a calculated flight route plan, FRP, within a predefined airspace, wherein an air flight guarding control unit (3) integrated in the air vehicle, AV, (2) is adapted to intervene automatically with flight controls of the air vehicle, AV, (2) on the basis of a monitored flight status of the air vehicle, AV, (2) such that the air vehicle, AV, (2) is kept during a flight movement within three—dimensional confines or boundaries of the assigned flight route (FR) and collisions with other air vehicles, AVs, (2) or with other obstacles are avoided.

A vehicle control system includes at least one imaging device attached to a vehicle and that captures multiple images, and a control circuit that generates a composite image from the multiple images and displays the composite image on a display unit. The vehicle is operated according to a user operation on a portion of the display unit on which the composite image is being displayed.

A monitoring system for an aircraft uses sensors configured to sense objects around the aircraft to generate a recommendation that is ultimately used to determine a possible route that the aircraft can follow to avoid colliding with a sensed object. A first algorithm generates guidance to avoid encounters with sensed airborne aircrafts. A second algorithm generates guidance to avoid encounters with sensed non-aircraft airborne obstacles and ground obstacles. The second algorithm sends inhibiting information to the first algorithm in a feedback loop based on the position of sensed non-aircraft objects. The first algorithm considers this inhibiting information when generating avoidance guidance regarding airborne aircrafts.