The present invention relates to a mobile security robot equipped with a micro flight device, which uses a camera mounted on the mobile security robot to patrol a predetermined area by the mobile security robot capable of autonomous driving and to patrol an area where the mobile security robot cannot move by the mounted micro flight device. Accordingly, there is an advantage in that it can efficiently patrol a much wider area compared to the patrol using only the mobile security robot.

The present disclosure is directed to systems and methods for trajectory and route planning including obstacle detection and avoidance for an aerial vehicle. For example, an aerial vehicle's flight control system may include a trajectory planner that may use short segments calculated using an iterative Dubins path to find a first path between a start point and an end point that does not avoid obstacles. Then the trajectory planner may use a rapidly exploring random tree algorithm that uses points along the first path as seed points to find a trajectory or route between the start point and end point that avoids known or detected obstacles.

A controller for an unmanned aerial vehicle (UAV) comprising an image capture means, the controller comprising: inputs arranged to receive: positional data relating to the UAV, a vehicle and a user device; image data captured by the image capture means; a processor arranged to process the received positional data to determine the relative locations of the UAV, vehicle and user device; an output arranged to output a control signal for controlling the UAV and to output an image signal comprising captured image data; wherein the processor is arranged to: generate the control signal for the UAV such that the image data captured by the image capture means comprises at least an image of an obscured portion of the vehicle that is obscured from a field of view of a user of the user device.

In some examples, an unmanned aerial vehicle (UAV) employs one or more image sensors to capture images of a scan target and may use distance information from the images for determining respective locations in three-dimensional (3D) space of a plurality of points of a 3D model representative of a surface of the scan target. The UAV may compare a first image with a second image to determine a difference between a current frame of reference position for the UAV and an estimate of an actual frame of reference position for the UAV. Further, based at least on the difference, the UAV may determine, while the UAV is in flight, an update to the 3D model including at least one of an updated location of at least one point in the 3D model, or a location of a new point in the 3D model.

A terrestrial acoustic sensor array for detecting and preventing airspace collision with an unmanned aerial vehicle (UAV) includes a plurality of ground-based acoustic sensor installations, each of the acoustic sensor installations including a sub-array of microphones. The terrestrial acoustic sensor array may further include a processor for detecting an aircraft based on sensor data collected from the microphones of at least one of the plurality of acoustic sensor installations and a network link for transmitting a signal based on the detection of the aircraft to a control system of the UAV.

A method is provided. An unmanned aerial vehicle (UAV) is operated. A position of the UAV is determined while in flight, and a nonce is generated. A Merkel root is generated based at least in part on a timestamp and the position of the UAV. A current block is calculated based at least in part on a previous block, the Merkel root, and the nonce, and the current block, the timestamp, the nonce, the prior block, and the position of the UAV are transmitted.

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.

In an embodiment, an optical sensor includes (i) a first lens array including a plurality of first lenses, (ii) a photodetector array including a plurality of photodetectors each aligned with a respective one of the plurality of first lenses, and (iii) a plurality of signal-modifying elements each aligned with a respective one of the plurality of first lenses. The plurality of signal-modifying elements includes (a) a first signal-modifying optical element having a first spatially-dependent transmission function, and (b) a second signal-modifying optical element having a second spatially-dependent transmission function differing from the first spatially-dependent transmission function.

A communication optimization system/method for mobile networks uses a server that generates waypoints based on a first communication network within a route to be travelled by an aerial vehicle, the aerial vehicle comprising a communication hub configured to communicate with at least one communication node, a communication hub controller configured control movement of a steerable antenna, and an aerial vehicle controller configured control movement of the aerial vehicle. The server then transmits the waypoints to the aerial vehicle controller; periodically monitors networks not connected to the communication hub; when a second communication network not connected to the communication hub satisfies a threshold, transmits causes the communication controller to steer the steerable antenna in a direction of the second communication network, further causing the communication hub to communicate and connect with the second communication network.

An unmanned aerial vehicle comprising at least one rotor motor. The rotor motor is powered by a micro hybrid generation system. The micro hybrid generator system comprises a rechargeable battery configured to provide power to the at least one rotor motor, a small engine configured to generate mechanical power, a generator motor coupled to the small engine and configured to generate AC power using the mechanical power generated by the small engine, a bridge rectifier configured to convert the AC power generated by the generator motor to DC power and provide the DC power to either or both the rechargeable battery and the at least one rotor motor, and an electronic control unit configured to control a throttle of the small engine based, at least in part, on a power demand of at least one load, the at least one load including the at least one rotor motor.