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.

Embodiments of the disclosure relate to the field of unmanned aerial vehicle (UAV) technologies, and specifically disclose an autonomous orbiting method and device and a UAV. The UAV includes a binocular camera assembly. The method includes: obtaining, through the binocular camera assembly, a target footage and an orbited object selected by a user from the target footage; obtaining a flying height of the UAV when obtaining the target footage; determining a spatial distance between the binocular camera assembly and the orbited object based on the target footage; detecting an optical axis direction of the binocular camera assembly in real time; and performing autonomous orbiting according to the flying height, the spatial distance and the optical axis direction of the binocular camera assembly detected in real time.

Embodiments of the disclosure relate to the field of unmanned aerial vehicle (UAV) technologies, and specifically disclose an autonomous orbiting method and device and a UAV. The UAV includes a binocular camera assembly. The method includes: obtaining, through the binocular camera assembly, a target footage and an orbited object selected by a user from the target footage; obtaining a flying height of the UAV when obtaining the target footage; determining a spatial distance between the binocular camera assembly and the orbited object based on the target footage; detecting an optical axis direction of the binocular camera assembly in real time; and performing autonomous orbiting according to the flying height, the spatial distance and the optical axis direction of the binocular camera assembly detected in real time.

In some examples, a first device includes multiple fixed first cameras and a movable second camera. A processor is configured to receive, from at least one of the fixed first cameras, a plurality of first images of an airspace corresponding to an area of operation of an unmanned aerial vehicle, and detect, based at least on the first images, a candidate object approaching or within the airspace. Based on detecting the candidate object, the processor controls a movable second camera to direct a field of view of the movable second camera toward the candidate object. Based on one or more second images from the movable second camera captured at a first location and one or more third images from a third camera captured at a second location, the processor may determine that the candidate object is an object of interest and perform at least one action.

A system for generating electrical energy, for instance at an agricultural site. The system includes at least one mobile robot, referred to as collecting robot and a plurality of mobile robots, referred to as producing robots. Each collect robot includes at least one input port adapted for coupling with an output port of a producing robot and an output port for outputting electrical energy received from each producing robot coupled with the collecting robot. Each producing robot includes a photovoltaic generator, at least one input port adapted for coupling with an output port of another producing robot, and at least one output port for outputting electrical energy generated by the producing robot and received from each other producing robot coupled with the producing robot.

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.

In one embodiment, the invention can be a system for monitoring a product, system including a transponder configured to attach to a product in a store; a drone comprising a camera, the drone configured to wirelessly communicate with the transponder; follow the transponder to maintain the wireless communication with the transponder; utilizing the camera, take a photograph or a video of the product to which the transponder is attached; and transmit a wireless alert signal upon an indication of an excessive separation between the drone and the transponder; and an employee device having a user interface, the user interface configured to display an alert when the drone sends the wireless alert signal.

A processor coupled to memory is configured to receive an identification of a geographical location associated with a target specified by a user remote from a vehicle. A machine learning model is utilized to generate a representation of at least a portion of an environment surrounding the vehicle using sensor data from one or more sensors of the vehicle. At least a portion of a path to a target location corresponding to the received geographical location is calculated using the generated representation of the at least portion of the environment surrounding the vehicle. At least one command is provided to automatically navigate the vehicle based on the determined path and updated sensor data from at least a portion of the one or more sensors of the vehicle.

A device and a method that prevent a tracking target tracked by a mobile device from deviating from a field of view at a fork, thereby enabling reliable tracking, are provided. When a control parameter determination unit of a mobile device cannot discriminate one of a plurality of routes constituting a fork that a tracking target selects and moves along, the control parameter determination unit calculates a goal position for bringing the tracking target within a viewing angle of the mobile device and a goal posture at the goal position, and generates a control parameter including the calculated goal position and goal posture. The control parameter determination unit calculates a position and posture that enable the tracking target to be within the viewing angle of the mobile device regardless of a route that the tracking target selects and moves along.

A device and a method that prevent a tracking target tracked by a mobile device from deviating from a field of view at a fork, thereby enabling reliable tracking, are provided. When a control parameter determination unit of a mobile device cannot discriminate one of a plurality of routes constituting a fork that a tracking target selects and moves along, the control parameter determination unit calculates a goal position for bringing the tracking target within a viewing angle of the mobile device and a goal posture at the goal position, and generates a control parameter including the calculated goal position and goal posture. The control parameter determination unit calculates a position and posture that enable the tracking target to be within the viewing angle of the mobile device regardless of a route that the tracking target selects and moves along.