2001 results about "Fixed wing" patented technology

An introduced autonomous aerial vehicle can include multiple cameras for capturing images of a surrounding physical environment that are utilized for motion planning by an autonomous navigation system. In some embodiments, the cameras can be integrated into one or more rotor assemblies that house powered rotors to free up space within the body of the aerial vehicle. In an example embodiment, an aerial vehicle includes multiple upward-facing cameras and multiple downward-facing cameras with overlapping fields of view to enable stereoscopic computer vision in a plurality of directions around the aerial vehicle. Similar camera arrangements can also be implemented in fixed-wing aerial vehicles.

The invention relates to the technical field of flight control, in particular to a fixed-wing unmanned aerial vehicle attitude correction and precise flight control method fused with visual navigation, which comprises the following steps: extracting ORB feature points and constructing a dynamic feature point cloud; simultaneously acquiring angular velocity and acceleration data of the inertial measurement unit; performing tight coupling fusion processing on the dynamic feature point cloud and the inertial measurement data to generate real-time pose data; inputting the real-time pose data into an attitude correction parameter calculation module, and generating an attitude correction parameter through a dynamic weight distribution algorithm in combination with a preset flight path planning model and GPS positioning data; and a control surface deflection instruction and an accelerator control instruction are generated through the multi-constraint optimization model, and unmanned aerial vehicle flight attitude closed-loop correction is completed. According to the method, aerodynamic parameters such as the air speed, the wind field lateral disturbance and the attack angle are introduced to serve as coupling input, the control surface deflection amount and limiting conditions are dynamically adjusted, and self-adaptive modeling and control over the nonlinear flight characteristics are achieved.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an intelligent flight path planning and energy management system and method for a long-endurance fixed-wing unmanned aerial vehicle. Comprising an environment sensing unit; the flight path planning unit is used for planning a flight path meeting task requirements, safety requirements and energy constraints based on the flight environment information of the unmanned aerial vehicle acquired by the environment sensing unit and pre-stored performance parameters of the unmanned aerial vehicle; and the energy management unit realizes energy dynamic management and optimization according to the real-time energy state of the unmanned aerial vehicle, the flight task and the planning result of the flight path planning unit. The flight path planning unit can call working condition energy consumption data such as navigational speed and height output by the energy management unit in real time, and dynamically adjust the weight of the path to avoid high-energy-consumption flight segments; the energy management unit synchronously and intelligently adjusts a main / standby battery charging and discharging strategy to optimize energy distribution according to a task time sequence (such as waypoint priority and track curvature) of a track.

An introduced autonomous aerial vehicle can include multiple cameras for capturing images of a surrounding physical environment that are utilized for motion planning by an autonomous navigation system. In some embodiments, the cameras can be integrated into one or more rotor assemblies that house powered rotors to free up space within the body of the aerial vehicle. In an example embodiment, an aerial vehicle includes multiple upward-facing cameras and multiple downward-facing cameras with overlapping fields of view to enable stereoscopic computer vision in a plurality of directions around the aerial vehicle. Similar camera arrangements can also be implemented in fixed-wing aerial vehicles.

An aircraft wing is disclosed having a fixed wing with a tip, and a wing tip device rotatably mounted on a hinge at the tip of the fixed wing, such that the wing tip device is rotatable about the hinge, and an actuation system for rotating the wing tip device about the hinge. The actuation system includes a motor, at least one geared rotary actuator, a reduction gearbox, a clutch for selectively decoupling rotation of the motor from rotation of the geared rotary actuator, the geared rotary actuator is driveable by the motor and arranged to convert rotary motion into a different rotary motion and is arranged to rotate the wing tip device relative to the tip of the fixed wing. The clutch is coupled to the geared rotary actuator by a shaft and the shaft is fixed in rotation to a mass disposed radially outwardly from the shaft.

The invention provides a three-dimensional modeling and mapping method, system and device based on a fixed-wing unmanned aerial vehicle, and relates to the technical field of geographic mapping. According to the method, through synchronous data acquisition of an inclined camera, a laser scanner and a position and attitude measurement system, and in combination with navigation trajectory calculation, point cloud coordinate transformation, image attitude calculation and multi-source data fusion processing, space collaboration of image data and point cloud data is realized under a unified coordinate system. And performing aerial triangulation based on the fused data, further carrying out spatial modeling and texture mapping, and effectively improving geometric consistency and modeling continuity among multi-source data. According to the method, ground control points do not need to be arranged, high-precision and high-consistency geographic space information expression can be achieved, and real scene modeling and multi-type surveying and mapping data result generation in a large-scale mapping scene are supported.

The invention discloses a fixed-wing unmanned aerial vehicle predetermined time cooperative path following formation control method, and relates to an unmanned aerial vehicle technology. A multi-unmanned aerial vehicle cooperative path following control strategy based on preset time stability, neural network adaptive control and preset performance control is provided; according to the method, the multiple fixed-wing unmanned aerial vehicles can realize preset time convergence of path following errors and preset time preset performance convergence of control signal tracking errors under the conditions of external disturbance and actuator faults, so that a high-precision and quick-response cooperative path following formation control task is completed; and meanwhile, the control precision and robustness are improved.

The invention discloses a fixed-wing unmanned aerial vehicle trajectory tracking control system and method based on a disturbance observer. The system acquires various state data of the unmanned aerial vehicle through the data acquisition module, the interference observer module estimates external interference in real time based on a dynamic model, the trajectory planning module generates an optimized trajectory according to tasks and environments, and the controller module realizes accurate control by adopting a model prediction control and sliding mode control composite strategy. And the execution mechanism driving module executes the control instruction. The method comprises the steps of data acquisition, interference estimation, trajectory planning, controller design and calculation, actuating mechanism driving and the like. The method can effectively improve the trajectory tracking accuracy and stability of the fixed-wing unmanned aerial vehicle in a complex environment, and has a wide application prospect.

A fixed-wing unmanned aerial vehicle large-attack-angle longitudinal aerodynamic characteristic test device and a test method relate to the technical field of aircraft aerodynamic characteristic test, and mainly comprise a wind tunnel simulation device, an unmanned aerial vehicle bearing and motion simulation device, a sensor arranged on an unmanned aerial vehicle or a model, a data acquisition system and the like. The simulation module is used for simulating longitudinal motion states and attitudes of the unmanned aerial vehicle in various pneumatic environments; the device is used for experiments, nonlinear longitudinal aerodynamic characteristics of the unmanned aerial vehicle under various attack angles are obtained, a phase diagram reflecting the attack angle-pitch angle speed change relation of the system state is obtained, a balance point under the normal working condition and the limit working condition is determined, and a basis is provided for flight control of the unmanned aerial vehicle under the large attack angle limit working condition.

The utility model relates to a variable-configuration tilting quad-rotor unmanned aerial vehicle which comprises rotors (1), motors (2), main wings (3), a fuselage (4), a vertical fin (7), a power supply unit (8), a control unit (9), tilting steering engines (10), driving rocker arms (11), tilting connecting rods (13), tilting rod supports (16), front tilting rods (17), rear tilting rods, front driven rocker arms (18) and rear driven rocker arms. The tilting mechanism is simple in configuration form, the appearance of the whole tilting mechanism is not greatly changed in the tilting process, and the pneumatic influence in the tilting process is relatively small. When the rotors tilt forwards, a conventional rotor fixed wing aircraft mode is adopted, when the rotors tilt upwards, a conventional four-rotor unmanned aerial vehicle mode is adopted, and various modes and modes such as vertical take-off and landing, hovering and forward flying can be achieved.

A glider system capable of sustained long-term flight includes a fixed-wing glider having a dual fuselage system. The top surface of the glider is covered with a plurality of photovoltaic cells capable of powering onboard sensors, propeller systems, and / or onboard processers. The glider includes wing spars with a composite material covering an inner foam core, with the type of foam core or use of reinforcement materials differs along the length or width of the wing spars. The glider is able to downward facing sacrificial winglets to provide a landing system without the need for bulkier landing gear.

The invention discloses an aviation magnetic survey compensation method and system for a fixed-wing aircraft, and the method comprises the steps: carrying out the calibration flight of the aircraft, and obtaining the related data of magnetic compensation in real time; secondly, based on magnetic compensation related data, an improved model based on a T-L model is established; and then magnetic compensation related data is applied to the improved model and then is processed, and a magnetic compensation coefficient is calculated by an improved truncated singular value method based on a crayfish optimization algorithm. And finally, separating the magnetic interference data by using the magnetic compensation coefficient to obtain normal magnetic induction data. According to the invention, the precision of the compensated magnetic field data is improved, and the environmental interference in the magnetic field data acquisition process is effectively removed.

The invention discloses a multi-vertical fixed-wing unmanned aerial vehicle flight path planning and intelligent obstacle avoidance method, and relates to the technical field of unmanned aerial vehicle flight path planning. Comprising the following steps: according to the dynamic characteristics of the multi-vertical fixed-wing unmanned aerial vehicle in a vertical take-off and landing mode and a horizontal flight mode, constructing a unified kinematics model and initializing unmanned aerial vehicle parameters and an environment model; carrying out global pre-flight path planning by adopting an improved particle swarm optimization algorithm, and generating a global flight path of the multi-vertical fixed-wing unmanned aerial vehicle according with flight characteristics; in the actual flight process, in combination with a deep reinforcement learning DDPG and an improved interference fluid power system IIFDS algorithm, flight modes of the unmanned aerial vehicle are intelligently switched, and multiple dynamic obstacles are efficiently and automatically avoided; and after obstacle avoidance is completed, the unmanned aerial vehicle rapidly restores the fixed-wing flight mode and flies along the preset route again. According to the method, the problem of multi-vertical fixed-wing unmanned aerial vehicle cooperative flight path planning in multiple complex scenes can be solved, and the purpose that the cost of task execution of multiple unmanned aerial vehicles is minimum is achieved.

The invention discloses an adversarial reinforcement learning training method for robust control of a fixed-wing aircraft, and the method comprises the steps: constructing a nonlinear simulation environment and a task set of the fixed-wing aircraft, and constructing a plurality of fixed-wing aircraft agents in parallel in the simulation environment; an adversarial agent module based on a neural network AdvNet is introduced to generate environmental disturbance. A near-end strategy optimized Actor-Critic structure is adopted, an intelligent agent and an adversarial agent module are subjected to joint training through a task set, and a robust control strategy is obtained step by step. In the training process, based on a course learning mechanism, disturbance constraint parameters of the confrontation agency are dynamically adjusted according to the completion condition of a flight task. After training convergence, obtained control strategy parameters are applied to the fixed-wing aircraft, and robust flight control is achieved. According to the method, the robustness and the control precision of the aircraft facing complex environment disturbance can be improved, and the method is suitable for various flight missions with uncertainty.

The invention discloses a foldable composite configuration vertical take-off and landing unmanned aerial vehicle which comprises a fuselage, a front wing, a rear wing, a control plane, an execution mechanism, a rotor wing motor and a propeller, the front wing and the rear wing are connected with the fuselage through a front folding mechanism and a rear folding mechanism respectively, and the front wing and the rear wing are in an X-shaped layout after being unfolded. Rotor motors and propellers are installed on the front wings, control surfaces and execution mechanisms are installed on the rear wings, and the front wings and the rear wings can be folded to be attached to the fuselage. According to the unmanned aerial vehicle, only one power system is used, the unmanned aerial vehicle has the vertical take-off and landing capacity and high flexibility of a multi-rotor unmanned aerial vehicle and the low-energy-consumption cruising and high-speed flying capacity of a fixed-wing aircraft at the same time, the wings can be folded to be attached to the fuselage, the outer contour is cylindrical after folding, and the unmanned aerial vehicle is compact in structure and more convenient to store, transport and carry; in addition, the device can support the modes of barrel type launching, ground takeoff, handheld takeoff, high-altitude spreading and the like for deployment.

The present application discloses an aircraft. The present application discloses a method of assembling or disassembling an aircraft. The assembly method includes mounting a first engine nacelle to a first wing, mounting a second engine nacelle to a second wing, causing the first wing to be extended relative to a fuselage mount, causing the second wing to be extended relative to the fuselage mount, and mounting the fuselage to the fuselage mount.

An introduced autonomous aerial vehicle can include multiple cameras for capturing images of a surrounding physical environment that are utilized for motion planning by an autonomous navigation system. In some embodiments, the cameras can be integrated into one or more rotor assemblies that house powered rotors to free up space within the body of the aerial vehicle. In an example embodiment, an aerial vehicle includes multiple upward-facing cameras and multiple downward-facing cameras with overlapping fields of view to enable stereoscopic computer vision in a plurality of directions around the aerial vehicle. Similar camera arrangements can also be implemented in fixed-wing aerial vehicles.

The invention discloses an unmanned aerial vehicle navigation obstacle avoidance method based on selective imitation enhanced deep reinforcement learning, imitation learning and deep reinforcement learning are combined to be used for fixed-wing unmanned aerial vehicle navigation and obstacle avoidance, and an intelligent agent directly maps non-ideal sensor data into a control instruction by learning an end-to-end strategy. For a sparse reward scene, an artificial potential field is constructed to generate a non-expert guidance action by accessing privilege state information which cannot be acquired by an intelligent agent, and a navigation strategy is continuously optimized according to an observation state and a sparse reward signal through real-time interaction with an environment and fusion of imitation learning and deep reinforcement learning. A Q-value-driven dynamic decision-making mechanism is adopted, and the motion of the fixed-wing unmanned aerial vehicle is determined by comparing the motion suggested by the instructor with the expected income of the motion generated by the learner, so that exploration-utilization balance is realized, and invalid exploration and local optimal decision are effectively avoided.

The utility model relates to a cross-medium aircraft convenient for adjusting flight attitude, which comprises a water-drop-shaped centrosymmetric aircraft body with an aircraft head and an aircraft body, and the aircraft head of the aircraft body is positioned on the front side of the aircraft body. The aircraft body is further provided with an underwater power mechanism used for providing underwater flight power and an air power mechanism used for providing air flight power, the side portion of the aircraft body is connected with four or six fixed wings, slip-flow rudders controlled to rotate are arranged on the rear edges of the fixed wings, and the rotating axes of the slip-flow rudders are parallel to the wing faces of the fixed wings and perpendicular to the long axis of the aircraft body. Each fixed wing is provided with a slipstream rudder, so that the cross-medium aircraft can be conveniently controlled to pitch, roll, yaw and other actions, and the cross-medium aircraft can be conveniently switched between a hovering flight attitude and a level flight attitude.

An aircraft wing has a leading edge, a fixed wing portion and a leading-edge spoiler device. The spoiler device is hingedly mounted relative to the fixed wing portion adjacent the leading edge, moveable between retracted and deployed positions. In the retracted position a spoiler surface forms a continuous surface with a fixed wing portion upper aerodynamic surface, and in the deployed position the spoiler surface is rotated relative to the upper aerodynamic surface. In the retracted position the spoiler surface has a first portion forward of the hinge and a second portion aft of the hinge. A center of pressure of the local wing section acts on the spoiler surface providing a moment about the hinge in a first direction to bias the spoiler device to the retracted position and providing a moment about the hinge in a second, opposite direction, rotating the spoiler device to the deployed position.

The invention discloses a multi-modal lightweight forest fire detection method suitable for a vertical take-off and landing fixed-wing unmanned aerial vehicle platform, and the method comprises the steps: carrying out the feature alignment and weight fusion of a visible light image and an infrared image, which are synchronously collected by an unmanned aerial vehicle, through a multi-modal early fusion method, and obtaining a fusion feature; carrying out lightweight down-sampling and multi-scale feature extraction on the fusion features to obtain a multi-scale feature set; performing cross-scale feature fusion on the multi-scale feature set by adopting a bidirectional feature pyramid network, and extracting dynamic change information to obtain time sequence features; performing multi-scale context enhancement on the time sequence features by using a spatial pyramid method based on cavity convolution, and performing global context and local texture modeling by using a lightweight Transform module to obtain high-level semantic features; and based on the high-level semantic features, a target detection frame, fire level classification, prediction uncertainty estimation and a pixel-level fire probability graph are generated in parallel through a multi-task output header.

An aircraft wing is provided having a fixed wing with a gulled wing tip rotatably mounted at the tip thereof, the gulled wing tip extending below a wing plane defined by the end of the fixed wing such that the centre of gravity of the gulled wing tip is located below the wing plane. Lowering the centre of gravity of the gulled wing tip has been found to reduce the onset of flutter. The gulled wing tip may be gulled about a hinge axis where it meets the fixed wing, or may be otherwise folded or curved to lower the centre of gravity of the gulled wing tip.

The embodiment of the invention discloses a formation control method, device and equipment for a distributed vertical fixed-wing unmanned aerial vehicle cluster and a storage medium, and relates to the technical field of unmanned aerial vehicle formation control. The method comprises the following steps: receiving topological position information of a formation, and determining a planned path; determining a first flight speed according to the current position information and the expected position information in the planned path; determining a second flight speed according to the current position information, the expected position information and topological position information in the formation; determining a third flight speed according to the current position information and the position relationship with other unmanned aerial vehicles in the formation; calculating a target flight speed based on the first flight speed, the second flight speed and the third flight speed; according to the target flight speed, the formation is controlled, and the stability and safety of the vertical fixed-wing unmanned aerial vehicle cluster formation are effectively guaranteed.

The disclosure relates to hybrid unmanned aerial vehicle (UAV) having vertical take-off and landing (VTOL) capabilities. Specifically, the disclosure relates to a stable hybrid fixed angle rotor arrays UAV having VTOL capabilities with hovering capabilities using rotors and cruising using fixed wing.

The invention discloses a variable-structure water-air amphibious robot and a motion control method. The robot comprises a water-air amphibious robot body, a variable-structure wing system and an electric control system. The robot body comprises a sealed cabin, a propeller fixing assembly, a fluid shell and a variable support tail cover. The variable-structure wing system comprises a driving gear transmission assembly, a two-section folding wing and a wing folding linkage assembly; the electric control system comprises a control core element, a visual module, a power supply module, a GPS module and an underwater depthometer module which are arranged in the cabin body; the motion control method is based on a deep reinforcement learning control method, control generalization ability is enhanced through teacher and student strategies and random domain, and the motion control method has more advantages in scenes such as inaccurate modeling and large external disturbance change. The structure of the variable-structure water-air amphibious robot integrates the structures of a rotorcraft, a fixed-wing aircraft, an underwater robot and the like, the modes of the wings can be switched, and efficient movement operation of the water-air amphibious robot is achieved.

The present application discloses an aircraft. The aircraft comprises a first wing and a second wing, a fuselage to which the first wing and the second wing are mounted, a first engine operatively mounted to the first wing, and a second engine operatively mounted to the second wing. The aircraft is configured to vertically take-off and land. The first engine and the second engine are used for both (i) vertical take-off and landing, and (ii) horizontal flight.

Vertical take-off and landing (VTOL) aircraft of the fixed-wing type, comprising a centre section defining a centreline of the aircraft, and a pair of wings, arranged on either side of the centre section, wherein the wings extend longitudinally from the centre section away from and mutually symmetrical with respect to a plane of symmetry extending through the centreline, wherein each wing comprises a main wing section extending longitudinally from the centre section, wherein the main wing section is configured for generating lift in an upward direction, a wingtip section extending longitudinally from the main wing section in a downwards sloping manner with respect to the main wing section, and a control surface provided in the wingtip section.

The invention relates to the technical field of fixed-wing aircraft fire extinguishing, in particular to a fixed-wing aircraft fire extinguishing task planning and efficiency evaluation system. Comprising a dynamic environment modeling module, an intelligent task planning module, a fire extinguishing agent distribution prediction module, a high-precision bomb dropping control module, an efficiency real-time evaluation module, a heterogeneous data collaboration module, a self-adaptive model iteration module and a man-machine collaborative decision-making module. The dynamic environment modeling module is used for real-time meteorological data fusion and three-dimensional terrain reconstruction. Based on a quantum annealing multi-objective optimization and multiphase flow coupling correction method, a flight path considering efficiency and precision is generated through environmental data fusion and path optimization, then fire extinguishing agent distribution is corrected and predicted based on physical simulation and data driving, and finally accurate execution of a bomb dropping trajectory is ensured through anti-interference guidance. A'planning-prediction-execution 'closed loop is formed, and the problems that a traditional scheme is low in efficiency and the fire extinguishing task of the fixed-wing aircraft cannot be planned and evaluated are solved.

The invention relates to an air route planning method based on an improved bidirectional fast random exploration tree algorithm, and is applied to the technical field of air route planning. The method comprises the following steps: acquiring a current node position, a target node position and terrain information of a target area of route planning; according to the terrain information, a search strategy combination of the target area is determined, the search strategy combination is used for constraining the extension direction of the air route nodes, and the air route nodes are determined based on an improved bidirectional fast random exploration tree algorithm. And determining a route node set according to the current node position, the target node position and the search strategy combination. The route nodes in the route node set are optimized, a target route is generated, and the target route is the route meeting the motion constraint of the fixed-wing aircraft. The expansion direction of the air route nodes is restrained through the search strategy combination, excessive redundant nodes caused during random sampling are avoided, and the convergence speed of air route planning can be increased. Therefore, the air route planning efficiency can be improved.

The invention relates to the technical field of aircraft trajectory planning, in particular to a dynamic gliding flight trajectory planning method for a fixed-wing aircraft, and the method comprises the steps: building an optimal control problem model with minimum system energy consumption as a target function; obtaining a nonlinear programming problem model; acquiring a corresponding single-time optimal trajectory and corresponding flight state data when the system energy consumption is minimum in the unpowered gliding flight stage and the powered recovery flight stage; and obtaining a multi-section type dynamic gliding flight path. According to the method, the iteration process of solving a nonlinear equation is avoided, the calculation burden of single iteration is remarkably reduced, the solving efficiency and robustness of the whole optimal control problem are greatly improved, and the optimal control effect is improved by designing the multi-section type dynamic gliding flight strategy of the unpowered gliding flight stage and the powered recovery flight stage. The stable periodic energy-obtaining gliding flight is realized by accurately compensating the flight energy deficit.