Systems and methods are disclosed for transporting people using air vehicles.

A system for automated flight correction is an electric aircraft that includes an input control configured to receive a user input and generate a control datum as a function of the user input, at least a sensor connected to the electric aircraft that is configured to detect a status datum and transmit the status datum to a flight controller, a flight controller communicatively connected to the input control and the at least a sensor configured to receive the control datum from the input control, receive the status datum from the flight controller and determine a command datum as a function of the control datum and status datum, and an actuator connected to the flight controller configured to receive the command datum from the flight controller and command at least a flight component as a function of the command datum.

Techniques and systems are described for generating and using a sound localization model. A described technique includes obtaining for a building a sound sensor map indicating locations of first and second sound sensor devices in respective first and second rooms of the building; causing an autonomous device to navigate to the first room and to emit, during a time window, sound patterns at one or more frequencies within the first room; receiving sound data including first and second sound data respectively from the first and second sound sensor devices that are observed during the time window; and generating and storing a sound localization model based on the sound sensor map, autonomous device location information, and the received sound data, the model being configured to compensate for how sounds travels among rooms in at least a portion of the building such that an origin room of a sound source is identifiable.

Systems, devices, and methods for identifying a target aerial vehicle, deploying an interceptor aerial vehicle comprising at least one effector, maneuvering the interceptor aerial vehicle to a position to engage a target aerial vehicle, deploying the at least one effector to intercept the target aerial vehicle, and confirming that the target aerial vehicle has been intercepted.

A helicopter autopilot system includes an inner loop for attitude hold for the flight of the helicopter including a given level of redundancy applied to the inner loop. An outer loop is configured for providing a navigation function with respect to the flight of the helicopter including a different level of redundancy than the inner loop. An actuator provides a braking force on a linkage that serves to stabilize the flight of the helicopter during a power failure. The actuator is electromechanical and receives electrical drive signals to provide automatic flight control of the helicopter without requiring a hydraulic assistance system in the helicopter. The autopilot can operate the helicopter in a failed mode of the hydraulic assistance system. A number of flight modes are described with associated sensor inputs including rate based and true attitude modes.

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 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.

Systems and methods for obstacle detection and state information determination are provided. In some embodiments, a movable object may carry one or more imaging devices. The imaging devices may be arranged on the movable object so as to have a field of view oriented vertically relative to the movable object. The arrangement of the imaging device may complement or supplant existing arrangement schemes and provide efficient, multi-functional and cost-effective means of arranging imaging devices on movable objects.

A system and method for a providing a dynamic backhaul. In one example, the system includes a self-positionable wireless device (for example, a drone) including a dual-band radio configured to establish a wireless connection between the self-positionable wireless device and a wireless system. The dual-band radio initiates a narrowband wireless link with the wireless system via a first narrowband antenna of the self-positionable wireless device and a second narrowband antenna of the wireless system. A navigation system generates location, velocity and error estimate of the self-positionable wireless device. The location is transmitted to the wireless system using the narrowband wireless link. The self-positionable wireless device receives via the narrowband wireless link location, velocity and error estimate of the wireless system. The self-positionable wireless device establishes a directional broadband wireless link with the wireless system using the location, velocity and error estimate of the self-positionable wireless system and the wireless system.

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.