A route setting apparatus (10) includes a first acquisition unit (130) and a route setting unit (140). The first acquisition unit (130) acquires specification information that specifies a plurality of points. When setting the plurality of points, inspectors superimpose each of the plurality of points on an inspection target. The route setting unit (140) takes, as a flight route of an aircraft, a line connecting points acquired by moving the plurality of points indicated by the specification information in the same direction and for the same distance. For example, the route setting unit (140) sets a temporary flight route by connecting the plurality of points indicated by the specification information. Then, the route setting unit (140) sets a flight route by moving the temporary flight route.

The present invention relates to an armed unmanned aerial vehicle (“UAV”), an armed UAV control system, and methods of use thereof. In one form, the armed UAV includes: an elongate body, a pair opposed side rotor arm assemblies extending from the sides of the body, a tail rotor arm assembly extending from a rear end of the body, a weapons system including at least one firearm associated with the body, and a flight and targeting controller operatively associated with the side rotor arm assemblies and the tail rotor arm assembly. The controller configured to: determine at least a pitch angle and yaw angle required to strike a target with the weapons system, based on target information received; and selectively control operation of each rotor arm assembly for aiming the weapons system, based on at least the pitch angle and the yaw angle determined.

Boresight and lever arm calibration of cameras and scanners on UAVs or mobile platforms is performed by optimizing the flight/travel path of the UAV/platform relative to control points or tie points. The flight/travel paths account for the potential bias of boresight angles, lever arm and times delays to produce an accurate estimation of the orientation of these cameras/scanners relative to the GNSS/INS coordinate system of the UAV/platform.

An operations platform includes a structure configured to house and transport drones and a storage facility configured to store the drones within the structure. The operations platform includes a lift or conveyor configured to move the plurality of drones to/from a launching area. In some implementations, the operations platform may also include at least one robotic element configured to move the drones to and from the storage facility.

Systems and methods described herein relate to self-supervised learning of camera intrinsic parameters from a sequence of images. One embodiment produces a depth map from a current image frame captured by a camera; generates a point cloud from the depth map using a differentiable unprojection operation; produces a camera pose estimate from the current image frame and a context image frame; produces a warped point cloud based on the camera pose estimate; generates a warped image frame from the warped point cloud using a differentiable projection operation; compares the warped image frame with the context image frame to produce a self-supervised photometric loss; updates a set of estimated camera intrinsic parameters on a per-image-sequence basis using one or more gradients from the self-supervised photometric loss; and generates, based on a converged set of learned camera intrinsic parameters, a rectified image frame from an image frame captured by the camera.

A method of transporting cargo, a cargo transport system and an unmanned Wing In Ground Effect vessel (UWIG) for transporting the cargo. A wake up signal indicates assignment of a new delivery. The UWIG begins pre-flight, causes cargo to be transported to the UWIG, and causes the cargo loaded into UWIG storage compartments. Once loaded and the loaded UWIG is ready, the UWIG taxis, e.g., to the open sea. Environmentally sealed PAR thrust fans provide PAR thrust during takeoff. The UWIG flies to a delivery location where cargo is unloaded, and may be stored.

A UAV location management method for use with a flight management system is provided, where the method comprises providing a location for at least one unmanned aerial vehicle (UAV) for at least one of: landing, taking-off and loading, providing at least a first weight-sensitive UAV pad at the UAV location, assigning a gross weight limit to each UAV scheduled to take-off from the first weight-sensitive UAV pad, the gross weight limit being based on a safety factor and at least one of: (i) a characteristic of the UAV; (ii) a characteristic of a power source of the UAV; (iii) a scheduled flight path for the UAV; and (iv) a weather condition, monitoring a weight exerted on the first weight-sensitive UAV pad when the UAV is positioned on the UAV pad, and transmitting a halt-flight signal to the flight management system for the UAV where the weight exceeds the gross weight limit.

A computer implemented method in a communications network for determining location information about an actual location of a drone comprises obtaining (302) a reported location of the drone at a first time point and obtaining (304) a measurement of radio conditions between the drone and a node in the telecommunications network, at the first time point. The method then comprises predicting (306) radio conditions at one or more locations related to the reported location of the drone, and determining (308) the location information about the actual location of the drone based on the measured radio conditions and the predicted radio conditions.

Embodiments of the present invention are a trajectory tracking method and an unmanned aerial vehicle. The method is including an unmanned aerial vehicle body and a gimbal, and the unmanned aerial vehicle body being equipped with at least one visual sensor, and the method includes: obtaining a flight image acquired by the at least one visual sensor, the flight image including a to-be-tracked target; performing visual image processing on the flight image, to generate a gimbal rotation instruction and a path instruction; adjusting an angle of the gimbal according to the gimbal rotation instruction and a gimbal state parameter of the gimbal, to lock the to-be-tracked target; and controlling a motor speed of a flight motor of the unmanned aerial vehicle according to the path instruction and a flight state parameter of the unmanned aerial vehicle, to cause the unmanned aerial vehicle to track the to-be-tracked target according to the path instruction.

The present disclosure is directed to a method and apparatus for controlling the operation of aerial UEs. An example of the method may include: determining whether an aerial UE is in an autonomous mode or in a non-autonomous mode; determining the flight path information of the aerial UE; and reporting the flight path information of the aerial UE. When the aerial UE is in the autonomous mode, the flight path information is reported when a first reporting period expires or the path deviation of the aerial UE is larger than a deviation threshold. When the aerial UE is in the non-autonomous mode, the flight path information is reported when a second reporting period less than the first reporting period expires or when at least one of the flying direction and flying speed of the aerial UE changes. Embodiments of the present disclosure solve the technical problem concerning the control of the operation of aerial UEs based on various behaviors.