Presented herein is a method and system for managing one or more missions of a vehicle. The apparatus includes one or more processors configured to control and manage flight missions and includes an active storage for executing a current mission, and a separate passive storage for subsequent missions. Subsequent missions are cued on the second storage to be validated and may be modified in view of additional information, prior to execution for maintaining positive control over the aircraft. The one or more processors are further configured to store a plurality of missions, including the current mission and a second mission, in a data store of a mission manager, each of the plurality of missions including a task graph having selected tasks to be completed for the mission, and a route map including a route for the vehicle to travel on the mission.

There is provided a method performed by a configuration unit, the configuration unit being communicatively coupled to a communication network and an Uncrewed Aerial System, UAS, the UAS including an Uncrewed Aerial Vehicle, UAV, and a UAV controller, UAV-C, the method comprising: receiving, for each of a plurality of UAV service suppliers, USS, information specifying a service area of that USS; obtaining UAS specific information, wherein the UAS specific information comprises a UAV registration area, a USS service requirement, or a combination thereof; and determining a mapping of the UAS specific information to one or more of the plurality of USSs based on the received USS information and the obtained UAS specific information.

A method and system for optimizing drone delivery efficiency. The method includes determining an optimal intermediate location for a UAV based on historical payload delivery data related to a payload carried by the UAV, wherein the distance between the optimal intermediate location and each of a group of potential recipient devices is less than a predetermined threshold; causing the UAV to navigate to the optimal intermediate location; sending, to each potential recipient device having a probability of requesting the payload carried by the UAV which exceeds a predetermined threshold, a notification indicating the payload carried by the unmanned aerial vehicle; receiving, from a first potential recipient device of the potential recipient devices, a request to deliver the payload; and causing the UAV to navigate from the optimal intermediate location to a location of the first potential recipient device when the request to deliver the payload is received.

An apparatus and a method of a wireless communication system, and a computer-readable storage medium are disclosed. The apparatus comprises a processing circuit. The processing circuit is configured to configure, directly or indirectly on the basis of one or more height thresholds for user equipment and a current height of the user equipment, operation of the user equipment. According to at least one aspect of the embodiments of the disclosure, configuring, on the basis of a height threshold, operation of a user equipment optimizes communication performance in an unmanned aerial vehicle communication scenario.

This application discloses a beacon for guiding landing of an unmanned aerial vehicle. The beacon includes at least three levels of patterns: one first-level pattern and at least one second-level pattern, where the at least one second-level pattern is superposed above the first-level pattern, and an area of the second-level pattern is less than that of the first-level pattern.

A system pairs a 5G-connected drone to a 5G-enabled user-controlled device. The system sets a predicted route for the 5G-connected drone to navigate. A portion of this route is indoors and matches an actual route of the user-controlled device. The system then causes the 5G-connected drone to commence navigating the predicted route. The system receives environmental data from the area surrounding the 5G-connected drone on the predicted route measured by a set of onboard sensors of the 5G-connected drone. Using the received environmental data and a deviation of the predicted route from the actual route traversed by the user-controlled device, the system determines that an alternate route for the 5G-connected drone exists and sets the alternate route. The system generates a notification based on the environmental data indicating hazards on the alternate route and transmits the notification over a 5G network to the user-controlled device.

Systems and methods provide a services architecture. An air mobility platform locally stores a native application at. The air mobility platform receives a first request for a first service and data identifying the first user as a priority user type or a non-priority user type. A second request for a second service and data related to the second user identifies the user type is received. The air mobility platform calculates a priority for the first request. If the priority for the first request exceeds the priority for the second request, a third party application is accessed for the first request. The air mobility platform submits the data related to the first request from the third party application to at least one of the first unmanned aerial vehicle or the first user.

The present disclosure provides a control system for controlling unmanned autonomous systems (UAS). The control system comprises of an application user system 102 to operate the UAS, an operating system 103, a virtual road system (VRS) 109 and a virtual packet 501. The virtual packet 501 created as a boundary around the UAS defined by application user system 102 or VRS 109. The operating system 103 includes a machine learning processing unit (MLPU) 104 configured for positioning the UAS, detecting collision within path of the virtual packet 901. The VRS 109 configured to generate a virtual roadway 902 using architecture for routing the UAS. The routing and controlling of UAS by the VRS 109 is based on request received from the MLPU 104, application zone packet parameters and actual position co-ordinates received from the MLPU 104.

Method and systems for situational awareness are disclosed. An example method includes receiving a first set of sensor data from a plurality of internal data sources that describes geospatial locations of objects within an airspace. The method also includes receiving event data from an external data source over a network describing publicly available information affecting the airspace. The method also includes receiving a second set of sensor data from another external data source operated by a user that describes the geospatial location of a user-operated object. The method also includes generating object metadata based on the first and second sets of sensor data and the event data. The method also includes streaming at least a subset of the object metadata to the computing device of the user. The object metadata is processed to generate a real-time three-dimensional rendering of the airspace, including the objects and the user-operated object.

A control device that includes a sensing unit that detects, from an image captured by a camera mounted in a drone, a guide light to be used for forming a corridor used by the drone, and identifies a position of the detected guide light, a calculation unit that calculates, according to positions of the drone and the guide light, a predicted arrival position of the drone and a control target position according to a positional relationship between the drone and the guide light at a control timing subsequent to a timing of capturing the image, a control condition generation unit that generates a control condition for a motor that drives a propeller of the drone according to the predicted arrival position and the control target position, and a control condition setting unit that sets the control condition for the motors of the drone.