A control method is provided, including: obtaining a current altitude of an aircraft, and determining a preset horizontal deviation threshold corresponding to the current altitude; obtaining a current horizontal deviation, wherein the current horizontal deviation is a horizontal deviation between a landing position and a current position of the aircraft; and determining a landing strategy of the aircraft based at least in part on a comparison between the current horizontal deviation and the preset horizontal deviation threshold.

An information processing apparatus according to an embodiment of the present technology includes: a calculation unit. The calculation unit calculates a self-position of an own device that moves with a moving object, in accordance with a first movement state of a moving object and a second movement state of the own device, on a basis of first movement information relating to the moving object and second movement information relating to the own device. As a result, it is possible to improve detection accuracy. Further, it is possible to improve the accuracy and reliability of the self-position. Since no displacement of the self-position occurs even in a movement space, it is possible for a drone flying in the air to avoid collision with obstacles in the movement space.

A method for controlling an unmanned aerial vehicle using a control apparatus, comprises: executing a navigation process by: obtaining a live video moving image from a navigation camera device of the UAV; and generating a navigation display interface for display on a display device of the control apparatus, the navigation display interface comprising a plurality of navigation augmented reality display elements related to a determined waypoint superimposed over the live video moving image; and when the UAV reaches the determined waypoint, executing a precision landing process by: generating a precision landing display interface for display on the display device, the precision landing display interface comprising a plurality of precision landing AR display elements related to a landing target associated with the determined waypoint superimposed over the live video moving image obtained from a precision landing camera device of the UAV.

System and method are disclosed for multi-phase process of automated data capture for photogrammetry and 3D model building of an unknown object (311) in an unknown environment. Planner module (152) generates a flight plan (413) for a camera drone (110) to fly autonomously on a flight path along a virtual polygon grid (302) defined above the target object (311) during a survey phase. Model builder computer (153) receives a point cloud dataset (321) captured by LiDAR sensor on camera drone (301) during survey flight and constructs low resolution 3D mesh (331) of the target object (311). Planner module (152) generates a flight path (413) for camera drone inspection phase with virtual waypoints surrounding the target object (311) at a marginal distance from the surface defined by the low resolution 3D mesh (331). Model builder (153, 163) builds a high resolution 3D model (422) of the target object (311) using photogrammetry processing of high resolution images captured by camera drone (411, 412) during inspection phase.

A repellence system and method for repelling animals. The repellence system includes an imaging device arranged to generate image data from a surveillance area, one or more deterrence devices arranged to carry out deterrence actions for repelling animals and an repellence sub-system having one or more processors and memory storing instructions for execution by the one or more processors. The repellence sub-system being configured to receive image data of the surveillance area from the imaging device, detect an animal in the image data, identify animal species of the detected animal in the image data, provide species specific deterrence instructions to the one or more deterrence devices based on the identified animal species.

Example computer-implemented methods and systems for anomaly-sensing based multi-agent navigation are disclosed. One example computer-implemented method includes: receiving relative distance data specifying distance between at least one pair of agents of a plurality of agents, each of a subset of the plurality of agents having an anomaly sensor subsystem; receiving anomaly data from at least one anomaly sensor subsystem of one of the plurality of agents; obtaining pre-surveyed map data; and determining global pose data of the plurality of agents based on the relative distance data and based on comparing the anomaly data to the pre-surveyed map data.

The present disclosure is generally related to systems and methods for redundant communication in an aircraft. The system may include a primary connection, a secondary connection, and a tertiary connection. The system may include a computing device configured to receive at least a state datum and transmit the at least a state datum using at least a data connection of the plurality of data connections. The at least a network switch may be communicatively connected to the plurality of data connections and configured to select the at least a data connection from the plurality of data connections as a function of the at least a state datum.

A method for predictive fire control, comprising identifying a plurality of wildfire risk points on a power grid, calculating a route for an unmanned aerial vehicle (UAV) to intersect with a maximum number of points as a function of a range of the UAV, controlling the UAV to traverse the route, monitoring one or more sensors for an indication of a wildfire event and controlling the UAV to release a fire retardant on the fire.

Disclosed herein are system, method, and computer program product embodiments for locating, identifying, and tracking a known criminal, fugitive, missing person, and/or any other person of interest. An embodiment operates by deploying an unmanned aerial vehicle, determining the mode of operation of the UAV, operating the UAV in accordance with the mode of operation of the UAV, determining whether a subject has been detected, capturing a first voice sample associated with the subject, authenticating the identity of the subject, and transmitting the GPS location of the unmanned aerial vehicle to a computing device.

Disclosed is a system including a user device, a frame, a drone, and a server. The user device enables a user to aviate the drone that is adapted to be detachably coupled to the frame. The frame is further adapted to be detachably coupled to the one or more powerlines, and includes an X-ray unit configured to capture X-ray images of the one or more powerlines. The X-ray unit transmits the X-ray images to the user device and the user device further transmits the X-ray images to the server in a digital imaging and communication in non-destructive evaluation (DICONDE) format. The server detects one or more abnormalities in the one or more powerlines by processing the X-ray images using a picture archiving & communication system (PACS) and an ADR technique, and generates data and/or reports to be viewed by the user by way of the user device.