The present disclosure provides a bird's-eye view data generating device including a memory; and at least one processor coupled to the memory.

The present disclosure provides a bird's-eye view data generating device including a memory; and at least one processor coupled to the memory.

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.

An autonomous robot drive assembly includes a plurality of drive units. The plurality of drive units may allow for movement and control of the autonomous robot drive. Each of the plurality of drive units are configured to be oriented independent of the other drive units. Each drive unit may include a plurality of independently operable driven wheels. Each drive unit may further include a drive unit coupling, allowing for the drive unit to rotate independently of other portions of the autonomous robot. The drive unit coupling may not be driven and may be configured to freely rotate.

An autonomous robot drive assembly includes a plurality of drive units. The plurality of drive units may allow for movement and control of the autonomous robot drive. Each of the plurality of drive units are configured to be oriented independent of the other drive units. Each drive unit may include a plurality of independently operable driven wheels. Each drive unit may further include a drive unit coupling, allowing for the drive unit to rotate independently of other portions of the autonomous robot. The drive unit coupling may not be driven and may be configured to freely rotate.

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 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.

A mobile body management device enables cost-effective execution of work that requires a mobile body. It includes an acceptance unit to receive work information specifying the application, time, and location. A determination unit compares this information with mobile body management data, considering storage location and availability, to select a mobile body that meets the criteria for executing the work. A control information generation unit generates instructions to control the movement of the selected mobile body based on the work application. These instructions are then transmitted to a mobile body control device to oversee the movement of the mobile body during the work. Overall, this device efficiently manages and utilizes mobile bodies for various tasks while maintaining low costs.

A mobile body management device enables cost-effective execution of work that requires a mobile body. It includes an acceptance unit to receive work information specifying the application, time, and location. A determination unit compares this information with mobile body management data, considering storage location and availability, to select a mobile body that meets the criteria for executing the work. A control information generation unit generates instructions to control the movement of the selected mobile body based on the work application. These instructions are then transmitted to a mobile body control device to oversee the movement of the mobile body during the work. Overall, this device efficiently manages and utilizes mobile bodies for various tasks while maintaining low costs.

Embodiments of the present disclosure may include a method for optimizing flight of an unmanned aerial vehicle (UAV) including a payload, the method including receiving one or more human-initiated flight instructions. Embodiments may also include determining a UAV context based at least in part on Inertial Measurement Unit (IMU) data from the UAV. Embodiments may also include receiving payload identification data. Embodiments may also include accessing a laden flight profile based at least in part on the payload identification data. Embodiments may also include determining one or more laden flight parameters. In some embodiments, the one or more laden flight parameters may be based at least in part on the one or more human-initiated flight instructions, the UAV context, and the laden flight profile.