Verizon Patent and Licensing Inc.

Skyward Io, Inc.

Dana Maher

Jonathan Evans

Matthew S Fanelli

Jared Nelson Muirhead

Eric B Miller

Eric T Ringer

Andrew McCollough

Jake Nylund

Chase Fiedler

Michael David Bergeron

Tariq Rashid

Shane Pierce Williams

David A Newell

Tera Lynn Schroeder

Daniel William McMillan

David Brian Rinaldi, Jr

An Aerial Robotics Network (ARN) Management Infrastructure (MI) (also referred to as ARNMI) that provides a mechanism for the management of aerobots.

Aerial robotics network management infrastructure

A device may include a memory and a processor. The device may receive, from a ground control station (GCS) associated with an unmanned aerial vehicle (UAV), credentials associated with a user. The device may determine whether the GCS has been registered and determine, in response to determining that the GCS has been registered, whether the UAV has been registered. The device may present, in response to determining that the UAV has been registered, a list of UAVs the user is authorized to operate and receive selection of a particular UAV from the list of UAVs. The device may facilitate operational activities of the particular UAV.

Registration and authentication of a drone, ground control station, and user for flights leveraging a wide area network

A method may include receiving an identifier (ID) from a first unmanned aerial vehicle (UAV) prior to a flight, storing the ID and receiving telemetry information from the first UAV during the flight. The method may also include storing the telemetry information, receiving a request from a user device for information associated with a first location and authenticating the user device. The method may further include determining whether at least one UAV is flying in an area associated with the first location and transmitting telemetry information associated with the at least one UAV, in response to determining that at least one UAV is flying in the area associated with the first location.

Unmanned aerial vehicle remote identification, command and control

A system described herein may provide a technique for the generation of one or more models indicating positions and/or attributes of objects within an environment, such as a warehouse, a facility, a data center, etc. The models may be generated by measuring radio frequency ('RF') metrics or other metrics within the environment over time. The environment may include mobile antenna apparatuses providing wireless coverage to wireless devices within the environment. The mobile antenna apparatuses may be moved within the environment based on the positions of objects within the environment (e.g., as indicated by the one or more models) and the positions of one or more wireless devices that connect to one or more of the mobile antenna apparatuses.

Systems and methods for autonomous spatial and beam configuration of antenna apparatus

An unmanned aerial vehicle (UAV) may include a communication interface and a pressure sensor configured to measure barometric pressure. The UAV may also include a processor configured to generate a request for elevation data and barometric pressure data and transmit, via the communication interface, the request to the at least one other device. The processor may also be configured to receive, from each of the at least one other device, elevation data and barometric pressure data, and estimate the elevation of the UAV based on the measured barometric pressure, the received elevation data and the received barometric pressure data.

Systems and methods for generating vertical positioning information for unmanned aerial vehicles

A device can receive information that identifies an airspace voxel that represents a three-dimensional portion of airspace during a particular time period. The device can associate one or more airspace parameters with the airspace voxel. The one or more airspace parameters can represent one or more conditions that relate to flight through the airspace voxel during the particular time period. The device can receive one or more flight parameters regarding a potential flight plan of an aircraft through a plurality of airspace voxels, including the airspace voxel, during the particular time period. The device can analyze the one or more flight parameters and a plurality of airspace parameters, associated with the plurality of airspace voxels, using one or more airspace rules. The device can output a recommendation regarding the potential flight plan based on analyzing the one or more flight parameters and the plurality of airspace parameters.

Flight plan recommendation based on analysis of airspace voxels

A device can be configured to receive map data from at least one map data provider, the map data including data points representing information regarding a space. The device can generate a first set of voxels based on the map data, the first set of voxels representing a first three-dimensional space that includes: at least a portion of the space represented by the map data, and voxel data corresponding to at least one of the data points. The device may also index the first set of voxels in a first index; generate a second set of voxels based on the first set of voxels, the second set of voxels representing a second three-dimensional space that is included in the first three-dimensional space; and index the second set of voxels in a second index.

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Portland, OR, United States of America

Dana Maher