High-Altitude Drone Operation

UAV trajectory planning method and system that enables unmanned aerial vehicles (UAVs) to optimize their flight paths in complex wind environments, mimicking bird flight techniques. The method involves using wind field sensing to determine the best flight paths that maximize energy gain. It calculates optimal control instructions based on cost and return type functions. The system uses wind speed in the UAV dynamic model and sets weight coefficients to determine stages. The generated wind-aware flight paths are sent to the UAV controller.

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Energy-optimized UAV formation flying method that reduces energy consumption of multiple drones working together to complete a mission. The method involves coordinated control, communication, and energy sharing between the UAVs to minimize overall flight energy consumption. It includes steps like adjusting flight speed, height, and formation shape based on wind conditions, using updrafts to reduce energy, optimizing airflow around the UAVs, and sharing energy between drones with sufficient power to help those with insufficient power. The method also involves monitoring battery health and fuel consumption to detect problems. By cooperatively optimizing flight parameters and sharing energy, the UAVs can complete missions with lower total energy requirements compared to individual drones.

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Optimizing long-duration flight of UAV clusters working together to increase flight time and range of UAVs in complex terrain environments. The method involves using natural winds to enable unpowered flight or reduce power needs. UAVs cluster together, with a lead UAV planning flight paths. They build airflow models based on geographical indicators. The initial flight path airflow is expanded iteratively to create a full airspace model. Comparing with typical flight plans finds optimal paths for unpowered flight. This allows UAVs to glide efficiently with natural winds, maintain stability, and extend endurance.

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Solar-powered unmanned aerial vehicles (UAVs) can ascend to higher altitudes during the day when fully charged and then glide down to lower altitudes at night to conserve stored energy. This allows the UAVs to use excess solar power to climb to higher altitudes when the batteries are full rather than just wasting energy. The climb-up and glide-down process delays battery use until later in the night when there is less time to charge again.

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Controlling drone flight stability in thunderstorm weather using real-time attitude adjustment based on weather conditions. The drone obtains weather information like wind speed, rainfall, and magnetic field intensity on its flight route. It then inputs this data into a flight control function to calculate optimal pitch, roll, and heading angles for stable flight. The drone uses these angles to create a flight plan and adjust its attitude in real-time as it flies, ensuring stability even in severe weather.

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Automatically adjusting the sweep angle of a variable-sweep wing unmanned aerial vehicle (UAV) based on real-time flight conditions to improve mission execution efficiency and flight performance. The UAV has a sweep angle decision-making model that processes initial flight state parameters using a policy network and judgment network. This model can independently adjust the sweep angle corresponding to the wing based on flight conditions learned through training. It allows the UAV to adaptively select the optimal sweep angle for flight stages rather than fixed angles, enhancing performance in changing environments.

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A UAV control method and system to improve cruising capability by optimizing flight parameters based on weather forecasts along the route. The method involves obtaining weather information and positioning data, determining the weather trend along the route, and adjusting flight parameters like thrust, speed, and angle to compensate for weather conditions. This allows the UAV to better match power consumption to expected weather changes, improving efficiency and endurance.

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Calibrating the altitude readings of a small stereo vision device on a UAV to accurately measure height at any altitude above ground. The method involves recording stereo vision altitude against another sensor during ascent and then adjusting the altitude readings using the calibration data. This extends the reliable altitude range beyond the stereo vision device's normal capabilities.

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Energy efficiency design of unmanned aerial vehicle (UAV) communication systems accounting for wind interference. The design includes a propulsion energy consumption model considering wind effects in 3D space, and an online-offline optimization algorithm to dynamically adjust UAV flight speed based on real-time wind measurements. This improves energy efficiency by mitigating the impact of random winds. The model accurately describes wind influence on UAV flight state and energy consumption. The algorithm involves offline wind statistics for trajectory planning and user selection, then online wind measurement adjustments during flight.

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Method for unmanned aerial vehicles (UAVs) to safely navigate through wind shear zones in low altitude wind fields. The method involves assessing wind shear risks based on real-time UAV flight data and surrounding wind field data. If shear is detected with high vertical wind speeds, the UAV adjusts its attitude to stabilize flight and prevent damage from the shear. This is achieved by simultaneous rudder and rotor control to maintain fixed-wing flight. The UAV can also stop passing through shear zones altogether if risks are too high. This improves UAV flight safety in complex environments like forest fires by enabling stable operation in shear winds.

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Method for unmanned aerial vehicles (UAVs) to adaptively control their ground speed in response to wind conditions and target motion. The method involves calculating the true airspeed based on wind data, UAV airspeed, and ground speed. Then, it determines an optimal ground speed strategy within a range based on the relationship between UAV minimum/maximum airspeeds and target true airspeed at the current altitude. This allows the UAV to efficiently track targets and maintain formation while accounting for wind effects.

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An altitude control system for high-altitude unmanned aerial vehicles (UAVs) that compensates for thermal expansion mismatch. The system has a compressor assembly with a steel driveshaft inside an aluminum housing. A flexible plate applies preloading force to the bearings that change with temperature. This compensates for differential expansion rates between the steel shaft and aluminum housing to prevent bearing failure. The flexible plate moves closer to the housing as it expands, keeping the bearings loaded.

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A high-lift unmanned aerial vehicle (UAV) with adaptive flight control for operating in strong winds. The UAV has a tandem wing configuration, ducted fan, vector fan, and tether. It uses a self-adaptive flight control system to adjust fan speeds, fan deflection angles, and cable tension based on real-time wind data to maintain stability in windy conditions. The UAV can resist level 9 winds, expanding its usability compared to conventional UAVs.

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Long-stay flight planning for unmanned aerial vehicles (UAVs) that maximizes flight time by leveraging natural winds. The method involves building airflow models based on geographic indicators, comparing them to initial flight data, and expanding the models dynamically as the UAV flies. This allows the UAV to plan efficient flight paths using natural winds rather than relying solely on its own power.

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Optimizing the flight path of an aircraft like a drone in real-time as it flies based on current position and surroundings. The optimization process iteratively adjusts the flight path from the current location to the destination based on acquired position and environment information. This allows optimizing the route in response to dynamic changes mid-flight, rather than just pre-planning a fixed route.

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Drone with retractable wings that automatically deploy at altitude to improve efficiency and maneuverability. The drone has a rotary wing and retractable fixed wings. A control device deploys the fixed wings when the drone reaches a certain altitude. This allows efficient horizontal flight with the rotary wings at low altitude, then deploys the fixed wings for high altitude cruising. It avoids drag and wind interference during takeoff and landing with the rotary wings alone.

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Facilitating altitude-based device management in a wireless communications system, like 5G, allows for optimizing the performance of high-altitude devices like drones. The system involves having the devices report their altitude to the network so it can dynamically adjust their power, handover parameters, and other settings. This ensures proper network integration and prevents issues like interference, high PRB utilization, and handoff problems that can occur when high-altitude devices operate differently from ground-based ones.

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Dual redundant flight control system for unmanned aerial vehicles to improve safety, flight envelope, and control capability. The system uses onboard sensors to monitor the flight environment and determines optimal thrust and control settings for the vectorized thrust system and fixed thrust system based on the conditions. It also has closed-loop monitoring to detect failures and degradation in performance. This adaptive thrust and control optimization allows the UAV to optimize lift-drag ratio and control efficiency across a range of flight conditions.

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Unmanned aerial vehicle (UAV) flight control method and system that improves UAV efficiency by optimizing flight paths based on real-time weather and power data. The method involves calculating the remaining power needed to complete a flight given current power, payload, range, and wind conditions. If the remaining power is insufficient, the UAV is landed or re-routed to an alternate airport. This allows better decision making than just monitoring battery level alone. The method also calculates wind component in flight direction for more accurate power calculations.

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Hybrid flight method for tilt-rotor drones that combines vertical takeoff/landing of a multirotor with fixed-wing flight efficiency. The method involves calculating the tilt angle required to transition between vertical and horizontal flight modes at waypoints. This allows the drone to optimize its flight path by switching between multirotor and fixed-wing flight modes at waypoints to reduce distance, time, and energy consumption. The tilt angle is calculated based on factors like wind speed, target location, and drone capabilities. By intelligently switching between multirotor and fixed-wing flight modes, the drone can fly more efficiently and accurately.

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