A method for improving wireless communication for a drone swarm, the method comprising, at a computing system, receiving, from a plurality of drones of a drone swarm, data comprising radio frequency signal characteristics detected by the plurality of drones; generating a model of a radio frequency environment for the drone swarm based on the data received from the plurality of drones; and controlling at least one wireless communication system to improve wireless communication for the drone swarm based on the model of the radio frequency environment.

An example system includes a plurality of processor modules. Each of the plurality of processor modules is communicatively couplable to an autonomous system of a plurality of autonomous systems. Each of the processor modules includes an autonomous software defined network (A-SDN) data-plane communications controller. The system further includes a portable network controller including an A-SDN control-plane communications controller.

The present disclosure discloses a method for managing a UAV control operation that includes: periodically receiving a request for transmission of UAV assistance information from a network entity and establishing a radio resource control (RRC) connection with the network entity. In response to the received request, the method further includes determining a triggering of at least one event corresponding to an initiation of a UAV control operation and transmitting UAV assistance information to the network entity in an RRC connected state based on the determined triggering of the at least one event. The method further includes receiving a control message from the network entity in response to the transmitted UAV assistance information. The control message includes information related to an execution of the UAV control operation. Thereafter, the method further includes executing the UAV control operation based on the information included in the received control message.

The present invention provides an improved, autonomous unmanned aircraft vehicle (UAV) for harvesting or diluting fruit, and a control unit for coordinating flight and/or harvesting missions thereof, as well as a system and method for harvesting fruits.

A robotic vehicle management system for the control, optimization and distribution of robotic vehicles is presented in which vehicle operational data is recorded and used to model and optimize a vehicle's travel path. A process for receiving data from multiple vehicles is disclosed, wherein the recorded data is used in the optimization of control systems with regards to travel path, fuel savings, safety, and other considerations. The recorded data may be used to improve system operations or operations of individual vehicles. Methods and techniques are also provided for reading data from vehicle sensors, applying analysis techniques to this data, and uploading improved operational processes to one or more vehicles or to a fleet of vehicles. Adaptive controls, learning based controls, navigation system and other capabilities may be included for optimization and distribution by this discloses system and methods.

Systems and methods are disclosed to transport a common load attached by slings by two or more Vertical Take Off and Landing (VTOL) aircraft using synchronized maneuvering and load feedback control. In one embodiment, a system includes: a unit configured to direct the load operation with macro level commands input by a system operator; a unit, on each aircraft, configured to estimate its state; a unit configured to measure the sling load forces on each aircraft; a unit configured to release the load from the aircraft; a unit configured to allow all aircraft to share their load data and aircraft state data; a computing system on each aircraft with access to the shared data and the ability to control the aircraft control effectors and sling release mechanism; and a computing unit configured to execute a Guidance & Navigation system (or equivalent) and a Multi-Lift Autonomous Flight Control System (MLAFCS) with Multi-Lift Synchronized Maneuvering, Load Distribution Regulation, and Load Swing Feedback (or equivalent) on the aforementioned computing unit.

Systems and methods are provided for sample collection from one or more subjects using mobile sample collection devices.

A system for aircraft navigation is disclosed. The system comprises an aircraft traffic control (ATC) computing device configured to generate a navigation procedure including at least: a starting waypoint, an assigned vector, and four-dimensional (4D) trajectory information. A computing device on-board an aircraft is configured to: receive the navigation procedure via controller-pilot datalink communications (CPDLC), display the navigation procedure to a user of the aircraft, and responsive to the user of the aircraft selecting the navigation procedure, automatically control the aircraft based on the navigation procedure.

The present disclosure addresses the problem of UAVs pursuing a swarm of target UAVs. The target UAVs are flying together as a flock that are initially modeled as a circle having a time-varying radius or an arbitrarily-shaped swarm that may change in size. Guidance of the pursuing UAVs is developed based on a collision cone framework, wherein the pursuing UAVs cooperatively steer the velocity vector of any point in their convex hull, to intercept the target. Also, the problem of capturing a swarm of intruder UAVs using a net manipulated by a team of defense UAVs is disclosed. The intruder UAV swarm may be stationary, in motion, and even maneuver. Collision cones in 3-dimensional space are used to determine the strategy used by the net carrying UAVs to maneuver or manipulate the net in space in order to capture the intruders.

In an example, a method may assign a first drone of a drone network a first task, the first task may instruct the first drone to transport a first package to a first destination in a geographic area. The method may receive roadway traffic data for a plurality of roadway vehicles in the geographic area; determine, based on the roadway traffic data and during transit of the first package to the first destination by the first drone, to transfer the first package to a second drone in the drone network; and transfer the first package to the second drone in the drone network.