Abstract: An aircraft comprises an aircraft body, multiple battery packs positioned on the aircraft body, a load balancing circuit positioned on the aircraft body and connected to a battery power node, multiple motors positioned on the aircraft body and connected to the battery power node, and multiple bypass circuits positioned on the aircraft body. The load balancing circuit comprises multiple current delivery circuits. Each current delivery circuit is connected between one of the battery packs and the battery power node. Each of the bypass circuits is connected to the battery power node and one of the battery packs to provide a signal path from the battery power node to the respective battery pack that bypasses a respective current delivery circuit for regenerative current from one or more of the motors.

Abstract: An Unmanned Aerial Vehicle (UAV) payload includes an adaptive Software Defined Radio (SDR) interface that is configurable to communicate with two or more SDRs using two or more protocols, a UAV interface that is configured to communicate with the UAV and a control circuit connected to the adaptive SDR interface and to the UAV interface. The control circuit is configured to communicate with the adaptive SDR interface and with the UAV interface. The control circuit is configured to receive SDR data from the adaptive SDR interface, receive UAV flight data from the UAV interface and use the SDR data and the UAV flight data to generate Signal Intelligence (SIGINT) data regarding the one or more emitter.

Abstract: Techniques for an unmanned ariel vehicle (UAV) having a closed-loop controller that is gain scheduled based on a trained machine learning model. The closed-loop controller could be a PID controller. Real-time data pertaining to the motor being controlled is input to the trained machine learning model. Examples of the real-time data includes, but is not limited to, motor current, motor voltage, and an estimate of motor thrust. The trained machine learning model may also input an error term of the closed-loop controller. Tuning constants for the closed-loop controller are derived based on the prediction from the machine learning model. Gain scheduling for the closed-loop controller may thus be performed “online” while the UAV continues on its mission. Controller gain scheduling may be performed to account for changes in a payload carried by the UAV.

Abstract: A plug-and-play Hub that provides an intermediary between an Unmanned Aerial Vehicle (UAV) and peripheral electronic devices. The Hub has a power and data interface to the UAV and peripheral ports that allow the peripheral electronic devices to connect to the Hub. The peripheral ports provide power to the peripheral electronic devices and also allow data communication between the Hub and the peripheral electronic devices. The Hub may detect when a peripheral electronic device has been plugged into a peripheral port and access communication protocol information and voltage level information by way of the peripheral port. A Hub voltage converter receives power from the UAV and converts the UAV power source voltage to a voltage level that is suitable for the various peripheral electronic devices. The Hub has a data hub that mediates data communication between the UAV and the various peripheral electronic devices.

Abstract: An Unmanned Aerial Vehicle (UAV) mechanical release device includes a quick-release UAV-attachment mechanism to attach the UAV mechanical release device to a UAV and a payload latch mechanism to secure and release a drop-payload from the UAV mechanical release device. A latch actuator is connected to the payload latch mechanism to move the payload latch mechanism between a closed position and an open position to release the drop-payload.

Abstract: An Unmanned Aerial Vehicle (UAV) drop-plate includes a frame that extends along a plane. The frame includes a plurality of frame members separated by a plurality of openings that extend through the frame. Lugs are attached to the frame and are configured to extend along a direction perpendicular to the plane of the frame. Each lug is configured to engage with a corresponding engagement feature of a UAV Mechanical Release Device (MRD).

Abstract: A method of simulating a quadcopter includes recording camera output for one or more video cameras under constant conditions and subtracting a constant signal from the recorded camera output to obtain a camera noise recording. Simulated camera noise is generated from the camera noise recording and is added to a plurality of simulated camera outputs of a quadcopter simulator to generate noise-added simulated camera outputs. The noise-added simulated camera outputs are sent to an Artificial Intelligence (AI) controller coupled to the quadcopter simulator for the AI controller to use to pilot a simulated quadcopter of the quadcopter simulator.

Abstract: A method of simulating a quadcopter includes testing a plurality of quadcopter components at a plurality of operating conditions to generate one or more lookup tables for characteristics of the quadcopter components. The lookup tables are stored for quadcopter component simulation in a quadcopter simulator. When a simulated input value for a simulated quadcopter component is received in the simulator lookup table, entries corresponding to the simulated input value are read from the lookup table and simulated quadcopter component output is generated. Simulated quadcopter output to a flight controller is generated according to the simulated quadcopter component output from one or more entries of one or more lookup tables.

Abstract: A wireless power initiated test system can use an aircraft controller to automatically initiate a test sequence to determine status of systems of the aircraft, based on the detection of receipt of the wireless power at the aircraft. The detection of receipt of the wireless power at the aircraft can be based on the detection at a voltage regulator of the aircraft which is receiving the wireless power from a wireless power receiver of the aircraft. The system may also power the aircraft controller during the test sequence using the wireless power received. Such a system may quickly and efficiently initiate, power and perform a pre-flight test sequence to determine statuses of systems of the aircraft, such as during a competition or race of the aircraft. The system may apply to drones, as well as of other types of aircraft.

Abstract: An example of a drone includes a drone chassis, a plurality of motors attached to the drone chassis and a plurality of propellers coupled to the plurality of motors. The drone further includes a net assembly mounted to the drone chassis. The net assembly extends above the plurality of propellers. The net assembly including a bottom portion and a plurality of upright frame members that are mounted to the bottom portion by a plurality of articulating joints.

Abstract: An autonomous quadcopter has four motors, each motor coupled to a corresponding propeller and a flight controller coupled to the four motors to provide input to the four motors to control flight. The autonomous quadcopter also has a plurality of cameras and an Artificial Intelligence (AI) controller coupled to the plurality of cameras to receive input from the plurality of cameras, determine a flightpath for the autonomous quadcopter according to the input from the plurality of cameras, and provide commands to the flight controller to direct the flight controller to follow the flightpath.

Abstract: An example of a drone includes a drone chassis extending along a plane, a plurality of motors attached to the drone chassis and a plurality of propellers coupled to the plurality of motors. The drone includes net assembly mounted to the drone chassis. The net assembly includes a net enclosure rotatably mounted such that an outward facing opening of the enclosure is rotatable about an axis of rotation that is parallel to the drone chassis.

Abstract: A drone includes a drone chassis, a plurality of motors attached to the drone chassis, and a plurality of propellers coupled to the plurality of motors, the plurality of propellers extending above the drone chassis. A net assembly is mounted to the drone chassis. The net assembly extends above the plurality of propellers. The net assembly includes a frame and one or more portions of netting.

Abstract: An example of a drone includes a drone chassis, a plurality of motors attached to the drone chassis and a plurality of propellers coupled to the plurality of motors. The drone also includes a net assembly mounted above the drone chassis. The net assembly includes an enclosure and a hinged portion that extends upwards from the enclosure in an open position and folds down in a closed position.

Abstract: A method of debugging quadcopter piloting code includes coupling an Artificial Intelligence (AI) controller configured with AI piloting code to a workstation having a quadcopter simulator and initiating piloting of a simulated quadcopter of the quadcopter simulator by the AI piloting code of the AI controller. Operations of the quadcopter simulator are logged, and communications timestamped. Subsequently, in response to an AI piloting code event at an event time, the event time is determined from a timestamped communication and a logged operation of the quadcopter simulator having a timestamp corresponding to the event time is found. The quadcopter simulator is rewound to at least the logged operation and one or more operations of the quadcopter simulator and the AI piloting code are stepped through to identify AI piloting code errors relating to the AI piloting code event.

Abstract: A drone includes a frame and a plurality of motors attached to the frame. Each motor of the plurality of motors is connected to a respective propeller located below the frame. A tail motor is attached to the frame. The tail motor is connected to a tail propeller located above the frame. Cameras are attached to the frame and located above the frame. The cameras have fields of view extending over the plurality of propellers.

Abstract: A drone includes a drone chassis, a plurality of motors attached to the drone chassis, and a plurality of propellers coupled to the plurality of motors, the plurality of propellers extending above the drone chassis. A net assembly is mounted to the drone chassis. The net assembly extends above the plurality of propellers. The net assembly includes a frame and one or more portions of netting.

Abstract: An example of a drone includes a drone chassis, a plurality of motors attached to the drone chassis and a plurality of propellers coupled to the plurality of motors. The drone further includes a net assembly mounted to the drone chassis. The net assembly extends above the plurality of propellers. The net assembly including a bottom portion and a plurality of upright frame members that are mounted to the bottom portion by a plurality of articulating joints.

Abstract: An example of a drone includes a drone chassis extending along a plane, a plurality of motors attached to the drone chassis and a plurality of propellers coupled to the plurality of motors. The drone includes net assembly mounted to the drone chassis. The net assembly includes a net enclosure rotatably mounted such that an outward facing opening of the enclosure is rotatable about an axis of rotation that is parallel to the drone chassis.

Abstract: An example of a drone includes a drone chassis, a plurality of motors attached to the drone chassis and a plurality of propellers coupled to the plurality of motors. The drone also includes a net assembly mounted above the drone chassis. The net assembly includes an enclosure and a hinged portion that extends upwards from the enclosure in an open position and folds down in a closed position.