Abstract: A system includes a storage facility configured to store drones. The system may also include at least one robotic element configured to move the drones to and from the storage facility and a conveyor configured to move the drones to a launching area. The at least one robotic element may include an articulating arm configured to move a first drone from the storage facility to the conveyor, in response to identifying that the first drone is selected for a flight.

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

Abstract: An operations platform includes a structure configured to house and transport drones and a storage facility configured to store the drones within the structure. The operations platform includes a lift or conveyor configured to move the plurality of drones to/from a launching area. In some implementations, the operations platform may also include at least one robotic element configured to move the drones to and from the storage facility.

Abstract: A device can be configured to receive flight data from an unmanned aerial vehicle (UAV), where the flight data indicates at least one of an identifier that identifies the UAV, a location of the UAV, an altitude of the UAV, a bearing of the UAV, or a speed of the UAV. The device can be further configured to convert at least a portion of the flight data from a first format to a second format; generate automatic dependent surveillance-broadcast (ADS-B) data based on the converted flight data; and perform an action associated with the ADS-B data.

Abstract: 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.

Abstract: 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.

Abstract: An operations platform includes a structure configured to house and transport drones and a storage facility configured to store the drones within the structure. The operations platform includes a lift or conveyor configured to move the plurality of drones to/from a launching area. In some implementations, the operations platform may also include at least one robotic element configured to move the drones to and from the storage facility.

Abstract: A system includes a storage facility configured to store drones. The system may also include at least one robotic element configured to move the drones to and from the storage facility and a conveyor configured to move the drones to a launching area. The at least one robotic element may include an articulating arm configured to move a first drone from the storage facility to the conveyor, in response to identifying that the first drone is selected for a flight.

Abstract: A device can be configured to receive flight data from an unmanned aerial vehicle (UAV), where the flight data indicates at least one of an identifier that identifies the UAV, a location of the UAV, an altitude of the UAV, a bearing of the UAV, or a speed of the UAV. The device can be further configured to convert at least a portion of the flight data from a first format to a second format; generate automatic dependent surveillance-broadcast (ADS-B) data based on the converted flight data; and perform an action associated with the ADS-B data.

Abstract: A device can be configured to receive flight data from an unmanned aerial vehicle (UAV), where the flight data indicates at least one of an identifier that identifies the UAV, a location of the UAV, an altitude of the UAV, a bearing of the UAV, or a speed of the UAV. The device can be further configured to convert at least a portion of the flight data from a first format to a second format; generate automatic dependent surveillance-broadcast (ADS-B) data based on the converted flight data; and perform an action associated with the ADS-B data.

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

Abstract: A device can be configured to receive flight data from an unmanned aerial vehicle (UAV), where the flight data indicates at least one of an identifier that identifies the UAV, a location of the UAV, an altitude of the UAV, a bearing of the UAV, or a speed of the UAV. The device can be further configured to convert at least a portion of the flight data from a first format to a second format; generate automatic dependent surveillance-broadcast (ADS-B) data based on the converted flight data; and perform an action associated with the ADS-B data.

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

Abstract: A device can be configured to receive flight data from an unmanned aerial vehicle (UAV), where the flight data indicates at least one of an identifier that identifies the UAV, a location of the UAV, an altitude of the UAV, a bearing of the UAV, or a speed of the UAV. The device can be further configured to convert at least a portion of the flight data from a first format to a second format; generate automatic dependent surveillance-broadcast (ADS-B) data based on the converted flight data; and perform an action associated with the ADS-B data.

Abstract: 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.

Abstract: A device can be configured to detect a physical connection with an unmanned aerial vehicle (UAV) flight controller through an interface. The device can identify a UAV identifier associated with the UAV flight controller and determine, based on the UAV identifier, an application programming interface (API) for communicating with the UAV flight controller. Using the API, the device can establish a communications link with the UAV flight controller and perform an action based on the communications link.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A device can be configured to receive flight data from an unmanned aerial vehicle (UAV), where the flight data indicates at least one of an identifier that identifies the UAV, a location of the UAV, an altitude of the UAV, a bearing of the UAV, or a speed of the UAV. The device can be further configured to convert at least a portion of the flight data from a first format to a second format; generate automatic dependent surveillance-broadcast (ADS-B) data based on the converted flight data; and perform an action associated with the ADS-B data.