732 results about "Cruise" patented technology

A vertical take-off or landing (VTOL) aircraft is disclosed that includes a propulsion system comprising at least four tilting propulsion assemblies and two or more lifting propulsion assemblies. Actuation of the tilting mechanisms can convert the aircraft from a hover configuration, in which all propellers produce thrust generally upward to counteract the aircraft's weight, to a forward flight configuration, in which the four or more tilting propellers produce thrust generally in a forward direction parallel to the fuselage to overcome drag in cruise flight and the lifting propellers produce no thrust or a level of thrust generally less than that required in the hover configuration.

The invention relates to the field of unmanned ships, and discloses an intelligent cruise and collaborative operation method for a multifunctional unmanned ship, which comprises the following steps: debugging preparation: selecting a functional module according to an operation demand, installing the functional module on an unmanned ship modular platform through a standardized interface, completing initialization and establishing a data transmission link with a cloud; and cruise planning: acquiring environmental data in real time, planning an initial cruise path by using a self-adaptive algorithm in combination with position information acquired by Beidou or GPS navigation in real time, and monitoring environmental changes in real time, dynamically optimizing the path and adjusting a route and a speed to cover a task area during navigation. By collecting environmental data in real time and planning and optimizing a cruise path by using an adaptive algorithm, the unmanned ship can accurately cover a task area, does not depend on a fixed route any more, dynamically adjusts the route and speed according to the actual situation of a water area, quickly reaches a key monitoring point, and reduces unnecessary sailing time.

The invention is suitable for the technical field of unmanned aerial vehicles, and provides an unmanned aerial vehicle cruise detection method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the global path planning through employing an improved fast extension random tree algorithm; when a conflict risk is detected, a dynamic reward function is designed with returning to a global flight path after obstacle avoidance as a target, and a deep reinforcement learning model is adopted to realize control of actions of the unmanned aerial vehicle; and controlling the unmanned aerial vehicle to fly along the global aircraft path and the local obstacle avoidance path, and executing a target detection task based on the target detection model in the flight process until the task is completed and / or a target position is reached. According to the invention, global path planning is carried out by adopting the improved fast extended random tree algorithm, a local obstacle avoidance path is obtained in combination with the deep reinforcement learning model when facing an emergent obstacle, the autonomous cruising ability of the unmanned aerial vehicle is improved, real-time target detection is realized based on the target detection model in the flight process, and the task execution efficiency of the unmanned aerial vehicle is improved.

The invention relates to a multi-task-point cruise path planning method and device for an unmanned aerial vehicle. The method comprises the following steps: acquiring flight data of the unmanned aerial vehicle in multiple flight stages; the flight data comprises corner data when the flight stage is a corner stage; constructing a flight energy consumption model according to the undirected graph, the flight data and the rotation angle data; the energy consumption of each task point in the cruising process of the unmanned aerial vehicle is obtained; performing iterative optimization on the energy consumption of the plurality of task points based on a wild dog optimization algorithm to obtain a path planning result, and controlling the unmanned aerial vehicle to fly according to the path planning result; energy consumption of different flight stages is quantified by constructing a flight energy consumption model, including energy consumption of rotation angle data in a rotation angle stage, so that the complex environment adaptability is improved, iterative optimization is performed on a path in combination with a wild dog optimization algorithm, the problems of inaccurate energy consumption modeling and easy falling into local optimum are solved, and the energy consumption modeling efficiency is improved. The method has the advantages that the energy consumption optimization efficiency and accuracy of path planning are improved, and the local optimum problem is avoided.

The invention discloses an automatic control method of a four-power-source tiltable aircraft, relates to the technical field of flight control of tiltable aircrafts, is realized based on a PX4 flight control system, and is suitable for a tiltable aircraft provided with four independent tiltable power sources and corresponding tilting execution mechanisms. According to the method, through configuration of a tilting angle control module, a power distribution module and a full-stage flight logic scheduling module, full-stage automatic control of vertical take-off and landing, suspension, horizontal take-off, fixed-point horizontal flight, automatic cruise, one-key return flight, fixed-angle flight, power source fault handling and the like is achieved. Smooth transition of all flight modes is achieved, the stability of the attitude, the height and the position of the tiltable aircraft in different flight stages is maintained, meanwhile, the functions of automatic obstacle avoidance, fault emergency and the like are integrated, flight safety is guaranteed, flight stability and applicability are improved, and the method can be widely applied to various tiltable aircraft operation scenes.

The invention discloses an air-ground collaborative observation unmanned system key target intelligent search method, which comprises the following steps that: an unmanned aerial vehicle carries a positioning module to provide a positioning coordinate, and executes a preset fixed-point cruise task; the unmanned aerial vehicle performs data acquisition on the environment of the cruising area; a height self-adaptive target detection module is adopted to carry out target detection on image data collected by the unmanned aerial vehicle, a rescue target and temporary obstacles generated after a disaster are recognized, coordinate transformation is carried out on the obstacles and target points, and a detection result is mapped to a position under a global coordinate system; transmitting the recognized target point and obstacle coordinates to a ground mechanical dog in real time through a communication module; the ground mechanical dog updates a dynamic cost map according to the received environment information to realize real-time perception of the environment; and the ground mechanical dog performs path planning based on the environment map. According to the method, efficient perception and rapid rescue of the target point can be realized, and the task execution efficiency and the system robustness in the post-disaster complex environment are remarkably improved.

The invention discloses an intelligent driving control method and system for an unmanned ship, and belongs to the field of unmanned driving control. Firstly, the position and speed of the unmanned ship and the positions and speeds of surrounding obstacles are obtained through a sensor and a positioning device, then dynamic path tracking is carried out in combination with global path planning and local path planning, and finally the unmanned ship is driven to sail along an optimized path by controlling the course and an accelerator. Local path planning adopts an improved dynamic window method, and an unmanned ship trajectory prediction evaluation function is modified by introducing a dynamic risk evaluation layer and a rule compliance layer; the dynamic risk evaluation layer is used for designing a collision risk evaluation function to dynamically screen a speed sampling space and rejecting a speed vector conflicting with a predicted trajectory of a moving obstacle; and the rule compliance layer classifies the meeting situation, introduces a rule evaluation function to perform weight correction on the candidate velocity vector, and drives the unmanned ship to generate a course adjustment strategy conforming to the collision avoidance rule. The unmanned ship realizes full-autonomous cruise, high-precision obstacle avoidance and path tracking in a complex marine environment.

The invention belongs to the technical field of numerical simulation and analysis of unmanned aerial vehicles, and relates to a rigid-flexible coupled variable-camber-range deformable wing optimization design method, which comprises the following steps of: obtaining working conditions of an aircraft, determining wing types and basic parameters of wings of the aircraft, and establishing a three-dimensional aerodynamic model of the wings; variable-attack-angle pneumatic simulation is carried out on working conditions of the aircraft in take-off and cruise, optimal camber values and corresponding pneumatic loads of wings under multiple working conditions are determined, and the positions of rotating joints of the deformed wing ribs are adjusted to obtain the deformed wing ribs after primary optimization; dividing the optimization range of the deformed wing rib after primary optimization into a fixed area and an optimizable area, loading an aerodynamic load under the optimal camber value in the optimizable area to perform aerodynamic simulation to obtain a deformed wing rib after secondary optimization, and optimizing the structure; and a deformed wing rib sample is made, performance testing is conducted, and the optimizable area is adjusted till the wing performance meets the preset requirement. The aerodynamic efficiency of the full flight envelope can be improved.

The invention belongs to the field of track planning and intelligent control of a reusable vehicle, and relates to an intelligent track planning method for a cruise section of the reusable vehicle. The method comprises the following steps: constructing a three-degree-of-freedom centroid motion dynamics model of a cruise section vehicle, generating an offline optimal trajectory sample library covering wide working conditions based on a Gaussian pseudo-spectral method, designing a mapping relation between deep neural network learning task parameters and trajectory features, and outputting a high-quality trajectory planning initial value online. The distribution of collocation points is dynamically adjusted in combination with a self-adaptive collocation point method, a nonlinear programming problem is iteratively solved with a high-quality initial value as a starting point, and efficient and accurate optimization of the trajectory is achieved. Simulation results show that the method significantly reduces the sensitivity of online optimization to initial guess, still has fast response ability and high robustness under complex constraint and uncertainty working conditions, effectively improves the autonomous trajectory planning ability of the cruise section of the reusable vehicle, and ensures flight reliability and control precision.

The invention belongs to the technical field of coal mining, and discloses a coal mine collapse monitoring system and method, and the method comprises the steps: a deformation monitoring module carries out the deformation monitoring of a coal mine; the displacement stress monitoring module monitors rock mass displacement, stress state and strain change of a coal mine goaf or a potential collapse area; the underground water monitoring module measures the change of the underground water level in real time; the route planning module plans a cruise route of the unmanned aerial vehicle; the image acquisition module performs low-altitude flight shooting on a coal mine area; the image preprocessing module preprocesses the scanned image; the abnormity identification module performs feature extraction on the preprocessed image and identifies the abnormal condition of coal mine collapse; the comprehensive evaluation module performs multi-source data fusion and establishes a multi-parameter early warning model; when the monitoring data exceeds a preset threshold value, the alarm module triggers an early warning signal. Through multiple monitoring means, the functions of real-time continuous monitoring, intelligent analysis and evaluation and the like are achieved, and potential collapse risks can be found in time.

The invention belongs to the technical field of soil moisture monitoring, and discloses a soil moisture monitoring system and method, and the method comprises the steps that a radar monitoring unit obtains soil moisture distribution data; the meteorological data acquisition unit acquires meteorological data in real time; the route planning unit plans the optimal flight route of the unmanned aerial vehicle of the cruise monitoring unit; the cruise monitoring unit performs cruise monitoring according to the planned route; the radar data analysis unit identifies abnormal conditions of soil moisture; the image data analysis unit recognizes the abnormal condition of soil moisture; the infrared data analysis unit identifies the abnormal condition of soil moisture; and the comprehensive analysis unit comprehensively analyzes and predicts potential risk problems. By accurately setting the hovering detection position, it is ensured that the unmanned aerial vehicle efficiently covers the monitoring area, and on-site key detection is conducted on the key area; and the comprehensive analysis unit combines a multi-source monitoring result with meteorological and historical data, deeply mines association among the data, confirms abnormal conditions of soil moisture, and predicts potential risk problems.

The invention relates to an unmanned-driving-based air quality underway monitoring device which comprises an unmanned aerial vehicle main body, an air quality monitoring sensor module is arranged at the bottom of the unmanned aerial vehicle main body, and a data transmission module is arranged on the air quality monitoring sensor module. A positioning module, a control module and an energy supply module are arranged at the top of the unmanned aerial vehicle body, the control module controls the flight path, height, speed and take-off and landing points of the unmanned aerial vehicle body, a Gaussian diffusion model is constructed based on real-time monitoring data, the flight height and course are dynamically adjusted through deep reinforcement learning, and the flight speed is adjusted. An area with the maximum pollutant concentration gradient is preferentially explored. The air quality underway monitoring device is high in flexibility, high in real-time performance, low in cost, capable of monitoring multiple parameters, capable of monitoring multiple air quality monitoring parameters at the same time, capable of providing comprehensive air quality information and capable of providing a new generation of high-temporal-spatial-resolution monitoring solution for intelligent environmental protection.

The invention relates to the technical field of aircraft power systems, and discloses a hybrid power management system suitable for a vertical take-off and landing aircraft and a control method. A lithium battery pack; a super capacitor; the power distribution module is electrically connected with the main turboprop engine, the lithium battery pack and the super capacitor and used for controlling energy flow among the main turboprop engine, the lithium battery pack and the super capacitor according to instructions. The control method comprises the steps that a staged power distribution strategy is executed according to judged flight stages such as vertical take-off and landing, horizontal cruise or emergency, instantaneous power is compensated through a super capacitor during vertical take-off and landing, and combined propulsion or energy recovery is decided according to key parameters such as the lift-drag ratio during horizontal cruise. According to the scheme, the vertical take-off and landing response and flight stability are improved, the endurance mileage is increased, and the intelligence and safety of the system are improved through self-adaptive control and redundancy design based on the ground digital twin model.

The invention discloses an engine configuration using liquid hydrogen as a coolant and fuel and an overall design method, and relates to the field of aero-engines, and the engine configuration comprises an air inlet channel, a fan, a precooler, an air compressor, a main combustion chamber, a high-pressure turbine, a low-pressure turbine, a mixing chamber, an afterburner and an exhaust nozzle. Only the inner culvert airflow is cooled, on the basis of solving the difficulty of rotation limitation under the high Mach number working condition of the core engine, the problem of cooling capacity waste generated by precooling the outer culvert airflow is avoided, and the liquid hydrogen amount depends on the combustion amount needed by the main combustion chamber and the afterburner; therefore, the waste problem caused by the fact that the amount of liquid hydrogen needed by pre-cooling is larger than the amount of liquid hydrogen needed by combustion is avoided. According to the overall design of the engine, from the angle of flight / intake / launch integration, the size and performance parameters of an engine body are determined in a ground state based on the take-off task requirement of an aircraft, the size of an intake and exhaust system is determined in a cruise state based on the cruise task requirement of the aircraft, and a control rule is determined by the engine demand flow and the intake passage capture flow.

An air drop rack assembly is mounted within the cargo compartment of a cargo aircraft and has a forward part secured to the load deck and an aft part secured to the aircraft cargo ramp. The rack parts have rollers in conveyor assemblies mounted between C-channels which engage skidboards which support smaller aircraft such as gliders or cruise missiles. When the ramp is up two rack parts are tilted with respect to each other. At payload drop, ramp is deployed to bring the rack part conveyor assemblies into alignment. Although the aligned rack parts are spaced apart, when the cargo aircraft is tilted upwardly, the individual payloads on skidboards are discharged out the aircraft aft opening. Cruise missiles or bombs may be supported on a skidboard with a deformable surface, a forward ballast weight, and a spring, such that once launched the skidboard is pushed away from the payload.

The invention provides an aviation permanent magnet synchronous motor control architecture based on master-slave redundancy and model prediction, belongs to the field of aviation electric propulsion control systems, and aims to solve the problems of extreme environment parameter drift, single-fault shutdown, multi-target control conflict, fault diagnosis lag and the like of an existing system. The control architecture comprises a master-slave dual-redundancy control unit, a wide-temperature-range adaptive model prediction control unit, an electromagnetic interference adaptive suppression unit and a multi-dimensional fault tolerance unit. According to the invention, a DSP + FPGA heterogeneous redundant architecture is matched with two-out-of-three voting logic, so that fault non-perception switching is realized; an extended Kalman filter observer is embedded to update motor parameters on line, and take-off / cruise / landing three modes are preset; interference at the frequency band of 100kHz-10MHz is controlled and suppressed through adaptive notch filtering and a sliding mode variable structure; a long short-term memory network is fused to realize accurate diagnosis of early faults, and the system is adaptive to aviation scenes such as electric general aviation aircrafts and unmanned aerial vehicles.

The invention discloses a wing-flapping unmanned aerial vehicle bird repelling cruise route planning method based on a WSN idea, and belongs to the technical field of unmanned aerial vehicles. In order to solve the problems of low deterrence, short timeliness, small coverage range and the like of a traditional bird repelling means, sensor nodes are generated through an improved particle swarm algorithm, and efficient coverage of a target area is achieved; clustering and partitioning the sensor nodes by adopting an improved k-means algorithm, and dividing a detection area for each unmanned aerial vehicle; and a cruising path is optimized by applying a genetic algorithm, so that the unmanned aerial vehicle is ensured to ensure the biological deterrence effect, the labor cost is reduced, and the inspection efficiency and coverage are improved. The method is suitable for bird damage control in wide areas such as agriculture and forestry orchards, power transmission and distribution lines, high-voltage substations and airports, and has remarkable economic benefits and social benefits.

The invention discloses an intelligent decision-making method based on a maritime collision avoidance rule, and belongs to the technical field of intelligent ship collision avoidance decision-making, and the method comprises the following steps: S10, setting a global route of a ship autonomous cruise task; s20, obtaining ship positioning and environment perception prediction data; s30, acquiring a ship local reference trajectory through a local trajectory calculation module; s40, constructing a ship navigation encounter situation model; s50, constructing a multi-element composite collision avoidance risk assessment model; s60, constructing a behavior decision tree model based on a marine collision avoidance rule; s70, a trajectory planning module performs trajectory planning based on a behavior decision tree model result; s80, establishing a monitoring continuous decision operation mechanism; according to the invention, on the premise of guaranteeing the safety and efficiency of ship navigation, on the premise of complying with the International Marine Collision Regulation, the interactive collision avoidance behavior between the autonomous ship and the manned ship in a complex and changeable sea surface environment is explored, so that a rapid and reasonable collision avoidance decision is expected to be realized, and the navigation safety and efficiency are improved.

The invention discloses a large-scale cruise ship water chilling unit pipe network cold storage intelligent energy-saving control method based on double-layer deep reinforcement learning, which comprises the following steps: 1, carrying out inherent cold storage engineering modeling on a chilled water pipe network of a water chilling unit to obtain an energy balance relationship between equivalent cold storage capacity and cold release sustainable time of the pipe network and bearable cold capacity; the relationship is used as a physical prior to introduce strategy learning and a security boundary; 2, constructing a double-layer deep reinforcement learning architecture; 3, a safety layer is additionally arranged in the double-layer deep reinforcement learning architecture, the safety layer cuts and projects output feasible regions of a target layer and a sublayer through a hard constraint and barrier mechanism, the water supply temperature, the temperature difference, the start-stop interval, the condensation temperature and the power change rate are ensured, and the maritime affair safety requirement is met; and 4, on the basis of a pipe network inherent cold storage model, a double-layer deep reinforcement learning framework and a safety layer, peak load shifting control of low-load cold charging-high-load cold discharging is achieved, and unit cold energy consumption of the water chilling unit is reduced.

Principles described herein allow for wings to be optimized for aerodynamic and structural efficiency while reducing planform compromises required to address wing tip stall problems. All-moving outboard wings allow the outboard wing local angle of attack to be changed relative to the inner wing region to avoid tip stall at high aircraft angles of attack, such as that which is required for low-speed flight. During high-speed cruise flight, at low aircraft angle of attack, the outboard wing local angle of attack can be increased to achieve an ideal elliptical lift distribution.

The invention discloses a method for autonomous route planning and cruising of an unmanned aerial vehicle according to specific weather of a seawall, and aims to improve seawall inspection efficiency and safety. The method comprises the following steps: firstly, acquiring weather data of a seawall area in real time through a meteorological sensor, and dividing weather conditions into different grades after preprocessing; and then, according to the current weather level, dynamically adjusting the cruise route of the unmanned aerial vehicle, considering historical inspection data and seawall safety risk assessment in route planning, setting a key inspection area, and improving the inspection precision. In the cruising process of the unmanned aerial vehicle, inspection data such as images, videos, temperature and humidity of the seawall are collected through equipment such as a camera and a sensor. And finally, processing and analyzing the collected data, generating an inspection report, and timely discovering potential safety hazards of the seawall. The method can autonomously plan the route according to the specific weather condition of the seawall, improves the inspection efficiency, adapts to the complex weather environment, reduces the safety risk, and achieves the intelligentization and automation of seawall inspection.

The invention relates to the technical field of aircraft power control, and discloses a hybrid power coordination control method and system for a vertical fixed-wing aircraft, and the method comprises the steps: obtaining the health state data of a battery module, and evaluating the instantaneous maximum discharge power capability of each battery module according to the data, thereby achieving the hybrid power coordination control of the vertical fixed-wing aircraft. And the overall instantaneous maximum discharge power supply capability of the battery pack is obtained through aggregation. Meanwhile, in combination with flight state information and residual mission profile data of the aircraft, the demand of the future key flight stage for the instantaneous peak power is predicted. By comparing the supply capacity of the battery pack with the future demand, whether the risk of instantaneous power shortage exists can be judged prospectively. When a risk is identified, the method can actively adjust a power distribution strategy of the aircraft, including adjusting cruise parameters, optimizing a vertical landing strategy, and adjusting a battery charging strategy.

A VTOL aircraft includes a plurality of lift propellers configured to be rotated by lift motors to provide vertical thrust during takeoff, landing, and hover operations. The lift propeller is configured to generate a flow of cooling air to cool the lift motor during use. During cruise operation, the lift propellers may be stowed in a rest position when the VTOL aircraft is in forward motion. Thus, when the flow of cooling air is not needed, the flow of cooling air may be reduced or eliminated.

The embodiment of the invention discloses a region boundary early warning method and system based on unmanned aerial vehicle visual identification, and the method comprises the steps: obtaining a sample cruise video, obtaining a sample video frame based on the sample cruise video, inputting the sample video frame into a detection model for feature extraction, and obtaining a backbone output feature; carrying out multi-path convolution processing on the backbone output features to obtain enhanced features, carrying out cross attention based on the enhanced features to obtain attention fusion features, carrying out object prediction based on the attention fusion features to obtain prediction object parameters of sample objects, and training a detection model according to differences between label object parameters and the prediction object parameters to obtain a detection result; the to-be-detected cruise video and the region boundary parameters are obtained, the to-be-detected cruise video is input into the trained detection model for real-time object detection, the target object parameters of the target dynamic object are obtained, the early warning level is determined based on the target object parameters and the region boundary parameters, and the accuracy of region boundary early warning can be improved.

To provide cooling paths for motors, such as lift motors of powered aerial vehicles.SOLUTION: A VTOL aircraft includes a plurality of lift propellers configured to be rotated by lift motors to provide vertical thrust during takeoff, landing and hovering operations. The lift propellers are configured to generate a cooling airflow to cool the lift motors during use. During a cruise operation when the VTOL aircraft is in forward motion, the lift propellers may be stowed in a stationary position. Therefore, the cooling airflow may be reduced or eliminated when it is not needed.SELECTED DRAWING: Figure 4A

The invention relates to the technical field of aircrafts, and discloses an intelligent cruise method and device for a super-intelligent adaptive multi-sensor aircraft and a medium, and the method comprises the steps: carrying out the data timestamp marking and data reliability calculation of a position sensor, a speed sensor, an attitude sensor and an environment sensor in an aircraft cluster; obtaining a multi-source sensor data packet; performing time sequence alignment and feature extraction on the sensor data in each subgroup to obtain group state feature data; respectively calculating a stand-alone anomaly score, a local anomaly score and a global anomaly score to obtain a communication anomaly aircraft identification result; generating a segmented return path; performing clustering and cluster head election on normal aircrafts except the abnormal aircrafts, and constructing an optimized communication network topological structure; according to the method, the reliability of the intelligent cruise of the aircraft is improved, and the continuous and stable operation of the aircraft cluster is ensured.

The invention relates to the technical field of artificial intelligence, and discloses a big data processing-based ship arrival judgment and unmanned aerial vehicle scheduling method, which comprises the following steps of: firstly, acquiring real-time ship data, and constructing a multi-agent ship behavior simulation environment; analyzing ship group data by applying a group evolution learning algorithm, and extracting a ship group behavior mode; based on the extracted behavior mode, identifying main channels and gathering points of ship flowing, and predicting a future ship group distribution trend; constructing an unmanned aerial vehicle cluster collaborative model, designing a task allocation strategy based on regional division and conquering, allocating a proper number of unmanned aerial vehicles to each sub-region, and planning an optimal deployment position and a cruise path; and finally, dynamic adjustment of unmanned aerial vehicle resources is realized, and the unmanned aerial vehicle resources are redistributed in time according to real-time changes of ship group distribution. According to the invention, the ship group distribution trend can be accurately predicted, and efficient scheduling of unmanned aerial vehicle resources is realized.

The invention discloses an engine main bearing resonance parameter determination method and device, equipment and a medium, and relates to the technical field of mechanical state monitoring, and the method comprises the steps: obtaining a current working condition parameter of a target engine, and detecting whether the current working condition parameter meets a state threshold condition in a corresponding cruise state or not; if yes, acquiring corresponding equipment characteristic parameters, acquisition configuration parameters and original vibration data, determining fault characteristic frequency of each element of the main bearing of the target engine, acquiring harmonic amplitude of each order corresponding to the fault characteristic frequency, and constructing a target function; performing global optimization on the target function by using a preset swarm intelligence optimization algorithm according to the target constraint condition to obtain a first resonance parameter; when it is monitored that the impact signal performance index extracted based on the first resonance parameter is lower than a preset threshold value, the first resonance parameter serves as a search starting point, local optimization is conducted on the target function, and a second resonance parameter is output. And the most suitable resonance parameter is automatically selected in the actual operation process.

The invention discloses an unmanned aerial vehicle cruise path planning method for multi-priority dynamic coverage, and the method comprises the steps: carrying out the sorting of the detection priorities of different parts of a region according to the traversal period constraint, carrying out the high-frequency cruise detection of key parts, and carrying out the low-frequency cruise detection of general parts; secondly, according to the priority ranking, recursively constructing a series of cyclic cruise path planning schemes by adopting a stochastic optimization algorithm, so that the region is dynamically covered and meets corresponding traversal period constraints; and finally, analyzing and evaluating the cruise path planning scheme from two aspects of redundancy and priority, and outputting an optimal planning scheme. Compared with a traditional path planning method, cyclic cruise detection is carried out according to the priority, the whole area can be dynamically covered with emphasis, the cooperative cruise detection efficiency of the unmanned aerial vehicle is effectively improved, and the area change is accurately mastered; in addition, the cooperative cruise path can be adaptively adjusted according to the priority change, unmanned detection resources are efficiently utilized, and the method flexibly adapts to the dynamic coverage demand change.

An electric vertical take-off and landing aircraft comprises a fuselage and a tilt wing. The tilt wing is tiltable relative to the fuselage in a range of tilt wing angles. Control surfaces are arranged at the tilt wings. The aircraft comprises a horizontal stabilizer with an elevator, in particular a stabilator, a vertical stabilizer with a rudder, in particular a fully movable stabilizer, at least one electric engine for powering main propellers arranged at the tilt wing and at least one software control device. The control device is configured to control at least the control surfaces , the main propellers and the tilt wing angle during hover and transition between hover and cruise flight.