An unmanned aerial vehicle (UAV) having wings stowed against a fuselage of the UAV in a first arrangement is disclosed. Methods and systems for deploying the wings into a second arrangement are disclosed. For example, after a launch of the UAV, the UAV monitors for at least one pre-set condition. The at least one pre-condition being a pre-condition associated with deploying wings of the UAV into the second arrangement. Upon detecting the at least one pre-set condition, the wings of the UAV are deployed into a second arrangement. Deploying the wings comprises activating, in response to detecting the at least one pre-set condition associated with the UAV, a gearbox configured to transition the wings from the first arrangement to the second arrangement. Roll control may be maintained throughout launch and deployment.

A navigation program for an autonomous vehicle, the navigation program configured to: receive an initial model of an object to be inspected by the autonomous vehicle; identify an inspection target associated with the initial model of the object; and determine an inspection location for the autonomous vehicle from which inspection target is inspectable by an inspection system of the autonomous vehicle, wherein the initial model includes one or more convex shapes representing the object.

[Object] To provide a control device which enables a flight vehicle device to obtain a highly precise image. [Solution] Provided is the control device including an illuminating control unit configured to adjust a light amount of an illuminating device according to an inclination of a fuselage of a flight vehicle device that has an imaging device configured to photograph a photographing target and the illuminating device configured to illuminate the photographing target.

A method for determining residue coverage within a field after a harvesting operation may include receiving yield data associated with an estimated crop yield across a field and generating an estimated residue coverage map for the field based at least in part on the yield data. The method may further include receiving residue data associated with residue coverage across a surface of the field following the performance of a harvesting operation within the field. Additionally, the method may include generating an updated residue coverage map for the field based at least in part on the estimated residue coverage map and the residue data.

Target value detection for an unmanned aerial vehicle is described. The unmanned aerial vehicle includes a first transducer that transmits a first ultrasonic signal and receives a first ultrasonic response and a second transducer that transmits a second ultrasonic signal and receives a second ultrasonic response. The second transducer has a wider beam pattern than the first transducer. Determinations are made as to whether either or both of the first or second ultrasonic responses includes a target value within range areas associated with the respective beam patterns of the first and second transducers. A confidence value is generated based on the determinations. The target value is reflected from an object and the confidence value indicates a likelihood of a position of the unmanned aerial vehicle with respect to the object.

Embodiments of the present disclosure provide a gimbal control method. The method includes receiving a first position and a second position wherein the first position and the second position are touched positions of an operation interface of a terminal; determining a rotation angle of the gimbal based on the first position, the second position, and an attitude of the gimbal at the first position; and controlling rotation of the gimbal based on the rotation angle.

An unmanned aircraft includes: a sensor that includes at least a microphone that generates sound data; and a processor. The processor determines quality of a target sound using the sound data generated by the microphone, obtains a positional relationship between the unmanned aircraft and a sound source of the target sound using data generated by the sensor, and controls movement of the unmanned aircraft to control a distance between the unmanned aircraft and the sound source of the target sound, in accordance with the quality of the target sound and the positional relationship.

Disclosed herein is a method for an image analysis server to detect a change to a structure by using a drone. The method for an image analysis server to detect a change to a structure by using a drone includes: receiving images of a specific inspection target structure taken at different time points by a drone; detecting the difference between an image taken at a first time point and an image taken at a second time point based on the received images; and detecting a change to the inspection target structure via the detected difference, and generating a risk signal and then transmitting it to an administrator terminal.

Systems, devices, and methods for receiving image data; transferring the captured image data to a server having a processor and addressable memory via a network-connected computing device; storing the captured image data on the server; generating captured image metadata based on the stored captured image data; providing access to the captured image data and captured image metadata via an image management component; displaying, by the image management component, the captured image data; and filtering, by the image management component, the captured image data based on the generated captured image metadata.

Certain aspects of the present disclosure provide techniques for controlling at least one robot system. This includes offering control of a first robot to a first mobile application, indicating an available service offered by the first robot, and receiving instructions to perform the available service. This further includes delivering: (i) debris, (ii) dust, or (iii) cut grass to a stationary second garbage collection robot. A computing system maintains a device profile for the first robot, indicates the available service and a status of the first robot to the first mobile application, and is configured to update the first mobile application. The first robot is configured to drive while performing the available service and is controlled by at least one of: (i) a camera or (ii) a sensor, to avoid collision. The second robot is a stationary garbage collection robot configured to store the delivered debris, dust, or cut grass.