9871 results about "Aerospace engineering" patented technology

The invention relates to the technical field of unmanned aerial vehicle positioning, in particular to an unmanned aerial vehicle flight path positioning method and system based on multi-source information fusion. The method comprises the following steps: acquiring an original observation data stream of an unmanned aerial vehicle in real time through a sensor array, and preprocessing to output a multi-source data sample set; calculating relative motion increment between adjacent key frames through an IMU pre-integration model, and extracting local pose estimation through a visual geometric calculation method; evaluating the confidence of each sensor in real time to dynamically generate an adaptive weight coefficient; and constructing a tight coupling fusion filter taking position, speed and attitude errors as core state quantities, and outputting a global optimal trajectory of the unmanned aerial vehicle. According to the invention, the weight is dynamically distributed through the real-time confidence of the sensor, the multi-source data association is fully mined, and the flight path positioning precision and environmental adaptability of the unmanned aerial vehicle are improved.

The invention discloses a method for generating an autonomous inspection orthoimage of an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle surveying and mapping and autonomous navigation. Global optimization of an air route is realized through a path optimization strategy fused by a genetic algorithm in combination with grid characteristics of an inspection area and image parameter constraints, and candidate waypoints are used as nodes; redundant waypoints are screened through leg smoothness factors, route complexity is reduced, a genetic algorithm takes flight height and waypoint spacing as constraints, a fitness function containing flight distance, turning times and overlapping rate is constructed, a global optimal path is found through population iteration, multi-target requirements are optimized and balanced, and it is ensured that the route meets the image acquisition precision requirement and also meets the requirement of image acquisition. The flight distance can be shortened, the turning frequency is reduced, the cruising ability of the unmanned aerial vehicle is adapted, efficient propelling of the inspection task is guaranteed, meanwhile, waypoint coordinates output through simulation directly adapt to a flight control system, and it is guaranteed that actual flight parameters are consistent with planning parameters.

The invention relates to the field of navigation, and more particularly discloses a gradient optimization driven unmanned aerial vehicle real-time obstacle avoidance multi-stage trajectory planning method, which comprises the following steps of: in a trajectory initialization stage, firstly, searching a collision-free geometric path considering steering limitation of an unmanned aerial vehicle on an occupied grid map by utilizing an improved algorithm to generate an initial B-spline control point; then, in a trajectory optimization stage, constructing a multi-target trajectory optimization problem, introducing an obstacle avoidance constraint based on an Euclidean distance field map, and optimizing the initial control point set in combination with unmanned aerial vehicle parameters and optimization weights to obtain a trajectory meeting an obstacle avoidance requirement; and finally, for the optimized trajectory, performing dynamic feasibility evaluation based on unmanned aerial vehicle kinematics limitation in a trajectory correction stage, and if the trajectory does not meet the constraint, performing correction based on the minimum curvature constraint on the control point to ensure that the finally generated trajectory is not only obstacle-avoiding but also feasible in dynamics, and finally, determining that the trajectory does not meet the constraint. Therefore, the real-time obstacle avoidance capability of the unmanned aerial vehicle in a complex environment is effectively improved.

The invention discloses a path planning and hierarchical cooperative control method and system for an unmanned aerial vehicle cluster. The system comprises a path planning module and a formation motion control module. The method comprises the steps that firstly, an improved RRT * algorithm is adopted by a path planning module, through a multi-strategy heuristic node expansion mechanism fusing target bias and artificial potential field guidance and comprehensively considering path length, channel volume and Z-axis height change, a center path and a three-dimensional safe channel which take into account safety and smoothness are planned for an unmanned aerial vehicle cluster; and then, based on the central path, the formation motion control module adopts a distributed model prediction control framework, designs different optimization targets for a navigator and a follower, and solves an optimal control instruction on line, so that a cluster is guided to complete trajectory tracking, collision avoidance among individuals and self-adaptive formation reconstruction in a secure channel. According to the invention, the navigation problem of the unmanned aerial vehicle cluster in a complex obstacle environment is solved, and the path planning efficiency and the robustness of cooperative control are improved.

The invention discloses an unmanned aerial vehicle attitude feed-forward compensation control method for building wind field disturbance, and belongs to the technical field of unmanned aerial vehicle flight control, and the method comprises the steps: building a mapping relation between a building space position and a wind field disturbance characteristic; processing the real-time wind field data in combination with the mapping relation to generate a wind field prediction result; calculating a feed-forward compensation amount, and synchronously determining a dynamic weight factor reflecting the disturbance intensity of the wind field; obtaining an attitude error between a current attitude and an expected attitude of the unmanned aerial vehicle, and calculating a feedback control quantity; and performing weighted fusion on the feedforward compensation quantity and the feedback control quantity by using the dynamic weight factor, and generating a final control instruction to control the attitude of the unmanned aerial vehicle. According to the method, the wind field mapping relation is established and the wind field is predicted to calculate the feed-forward compensation quantity, and then the dynamic weight factor is used to carry out weighted fusion on the feed-forward compensation quantity and the feedback control quantity, so that the disturbance of the wind field can be actively inhibited, and the attitude control stability and precision of the unmanned aerial vehicle in a complex environment are improved.

The invention discloses an unmanned aerial vehicle optimal path self-adaptive planning method adopting particle swarm optimization, and relates to the field of unmanned aerial vehicle path planning, and the method comprises the steps: constructing a space constraint model of an unmanned aerial vehicle flight task; initializing a particle swarm based on the spatial constraint model; combining the path smoothness, the path threat probability and the voyage efficiency to establish a multi-target fitness function, and calculating the fitness value of each particle based on a particle swarm; hierarchical particle swarm optimization iteration is executed, in each iteration, control parameters are adaptively adjusted based on the current particle swarm distribution characteristics, and the path node positions of particles are updated; and when a convergence condition is satisfied, outputting a global optimal path as a final flight path of the unmanned aerial vehicle, and controlling the unmanned aerial vehicle to execute. According to the unmanned aerial vehicle optimal path self-adaptive planning method based on particle swarm optimization, the problems that the unmanned aerial vehicle route path optimization target is single and difficult to cooperate, and the route planning effect is poor are solved.

The invention belongs to the technical field of unmanned aerial vehicle flight control, and particularly relates to an unmanned aerial vehicle intelligent dynamic obstacle avoidance method and system based on ultrasonic frequency self-adaption. The method comprises the following steps: 1, monitoring the position and distance of a static obstacle in real time, and adjusting the ultrasonic emission frequency; the neighborhood environment of the unmanned aerial vehicle is detected in real time through barometer equipment, the attitude, acceleration and angular velocity of the unmanned aerial vehicle are provided through an inertial sensor, and data are preprocessed after the surrounding environment of the unmanned aerial vehicle is comprehensively sensed; 2, performing a dual-stage mode of offline training and online updating through CNN-AE and LSTM decision engines, generating an obstacle avoidance path, and dynamically adjusting a flight strategy according to a real-time environment; 3, adaptively adjusting the reward weight according to the obstacle distance through a dynamic priority reward function, and guiding the unmanned aerial vehicle to make an optimal decision and path optimization in the flight process; and 4, through an emergency control module, triggering a local decision based on a Q value table when communication is interrupted, and ensuring that the unmanned aerial vehicle can still fly safely under an abnormal condition.

The invention relates to the technical field of unmanned aerial vehicle application and urban airspace management, in particular to an intelligent site selection method and system for unmanned aerial vehicle take-off and landing points in an urban building group, and the intelligent site selection system for the unmanned aerial vehicle take-off and landing points in the urban building group specifically comprises the following steps: S1, carrying out the multi-source heterogeneous data fusion and high-precision three-dimensional environment modeling; s2, fluid dynamics simulation and airflow field pre-calculation are calculated; s3, real-time meteorological monitoring and dynamic risk correction; s4, establishing a quantitative safety evaluation model and multi-objective optimization site selection; and S5, visual decision support and feedback learning. According to the scheme, by deeply fusing multi-source heterogeneous geographic information data and constructing a high-precision three-dimensional digital twinborn city environment, accurate simulation and risk assessment of an airflow field around a building group are realized, geometric, material and semantic information is automatically extracted by using oblique photography, laser point cloud and a building information model, and the construction efficiency is improved. A unified three-dimensional grid with physical attributes is formed, and a reliable basis is provided for subsequent fluid calculation.

The invention provides an ultra-low-altitude-domain three-dimensional radio map generation system, and the system comprises a three-dimensional grid division and data preprocessing module which is used for dividing a target region into voxel grids containing latitude and longitude and height coordinates; the satellite remote sensing image feature extraction module is used for generating environment high-dimensional image features of the target area; the communication base station parameter encoder is used for generating base station space propagation characteristics of the target area; the two-dimensional feature migration and three-dimensional feature generation module is used for generating initial three-dimensional feature representation; the three-dimensional interpolation and height correction module is used for outputting corrected three-dimensional RSRP features; and the multi-modal fusion and decoding module is used for fusing the corrected three-dimensional RSRP features, the environment high-dimensional image features and the base station space propagation features, and inputting a fusion result into a three-dimensional decoding network to generate a final three-dimensional radio signal power distribution diagram. The three-dimensional radio map is generated for the urban low-altitude scene.

The invention relates to the technical field of data processing, and discloses a VICTS antenna attitude estimation and correction method and system based on satellite pointing feedback, and the method comprises the steps: constructing a tight coupling depth fusion system with extended Kalman filtering as a frame, introducing satellite communication antenna pointing information as a new observation source on the basis of traditional IMU / GNSS fusion, and carrying out the satellite communication antenna attitude estimation and correction. By deducing the Jacobian matrix of the carrier attitude, effective fusion of the observed quantity is realized, so that the attitude estimation precision and robustness of the carrier are reversely corrected and remarkably improved, the three-axis attitude error is estimated and corrected more comprehensively and steadily, and the problem of lack of roll angle observation is fundamentally solved. Observation information of different dimensions is unified into the same state estimation framework through accurate mathematical modeling, and the precision, autonomy and robustness in a complex environment of the system are greatly improved.

The invention relates to a distributed trajectory planning method and system for an unmanned aerial vehicle cluster in an obstacle environment. The method comprises the steps of initializing a system, constructing a local Euclidean symbol distance site map, and realizing real-time interaction of state information of the unmanned aerial vehicle. An initial collision-free path is generated using jump point search. And solving an optimal control point through an L-BFGS algorithm through multi-constraint trajectory optimization in combination with a load swing dynamics model, four-rotor dynamics limitation, cluster collision avoidance and environment obstacle avoidance requirements. And a dynamic time redistribution strategy is adopted, and the track time interval is adjusted according to speed and acceleration overrun conditions. The method further comprises an adaptive re-planning mechanism, and local target points are updated in real time and adjacent aircraft collaborative optimization is triggered based on local map boundary detection and quadrotor track safety detection. According to the method, efficient, safe and stable trajectory planning of the hanging load quad-rotor unmanned aerial vehicle cluster in a complex environment is realized, the requirement of autonomously and efficiently completing tasks is met, and the task execution efficiency and safety are improved.

A system and method for dynamic two-way ranging using unmanned aerial vehicles may use ultrawideband transceivers for dynamic two-way ranging between unmanned aerial vehicles among a first set of unmanned aerial vehicles. Embodiments of the system and method may allow for dynamic two-way ranging where GPS information may be limited or not be available at all.

The invention relates to the technical field of flight path planning, in particular to an autonomous flight path planning method and system for a road slope inspection unmanned aerial vehicle, and the method comprises the following steps: controlling the unmanned aerial vehicle to fly in a road slope region according to a preset flight path, collecting the aerial image data of the unmanned aerial vehicle, analyzing the aerial inspection adaptive feature value of the unmanned aerial vehicle, and determining the flight path of the unmanned aerial vehicle. Judging whether the feature value is lower than a preset inspection adaptation feature threshold value or not; analyzing a field-of-view missing feature set of the unmanned aerial vehicle based on the aerial image data of the unmanned aerial vehicle if the field-of-view missing feature set is lower than the preset routing inspection adaptive feature value threshold; performing flight path planning processing on the unmanned aerial vehicle based on the field-of-view missing feature set; according to the method, the unmanned aerial vehicle is subjected to flight path planning processing on the basis of the field-of-view missing feature set, so that when an aerial picture is deviated, fuzzy or blind areas, judgment and automatic adjustment are performed in real time, self-adaptive optimization of the flight path is realized, and the road slope inspection efficiency is remarkably improved.

The invention discloses an unmanned aerial vehicle and robot dog cooperative inspection system, and relates to the technical field of unmanned aerial vehicles, the unmanned aerial vehicle and robot dog cooperative inspection system comprises an unmanned aerial vehicle inspection module, a robot dog inspection module and a cooperative control module, the unmanned aerial vehicle inspection module is used for aerial aerial view of large-scale crowds, and real-time calculation of crowd density, velocity field and congestion hotspots; the robot dog inspection module is used for carrying out close inspection in a ground crack corridor, detecting gait stability and falling individuals in real time, forming a soft boundary to carry out differential diversion guidance and carrying out physical intervention on dangerous situations, and carrying out real-time inspection on the ground crack corridor. The cooperative control module is used for integrating the aerial view angle of the unmanned aerial vehicle and the ground detection information of the robot dog, dynamically updating a routing inspection path and triggering sound-light alarm and linkage guidance when a risk is identified, so that air-ground integrated risk prevention and control are realized, the unmanned aerial vehicle routing inspection module comprises a visual perception unit, and the unmanned aerial vehicle routing inspection system has the characteristic of near execution.

The invention discloses an unmanned aerial vehicle soft landing control method based on track prediction and multi-source cooperative decoy, and the method comprises the steps: introducing a communication protocol recognition mechanism in a blocking process of an instruction link of an unmanned aerial vehicle, and achieving the conversion from extensive broadband suppression to protocol precise interference; the problems that in the prior art, power consumption is high, interference on legal communication is large, and the frequency hopping unmanned aerial vehicle resisting effect is insufficient can be effectively solved. In the scheme, signal integrity is guaranteed through monitoring and preprocessing, an unmanned aerial vehicle link protocol is identified through feature extraction and protocol library matching, and then a targeted interference template is generated, so that the interference effect can accurately fall on key positions such as a leader sequence, a CRC field, a subcarrier or a control frame and the like; therefore, synchronization, verification or data transmission can be destroyed under the condition of low power, and accidental damage of broadband noise to services such as co-frequency Wi-Fi and Bluetooth is avoided.

The application discloses a thunderstorm monitoring device and path planning method of unmanned aerial vehicle based on electric field and magnetic field detection. The device comprises a quadrature magnetic antenna array, a vertical differential electric field sensor, a signal processing module, a positioning algorithm module, a distance estimation module, an autonomous decision module, a GNSS module and an inertial measurement module. The quadrature magnetic antenna array is composed of two orthogonally arranged magnetic antennas, which are at a 45° angle with the flight direction of the unmanned aerial vehicle, and is used for receiving the horizontal magnetic field signal of lightning radiation. The vertical differential electric field sensor comprises two groups of upper and lower electrode plates and measures the differential value of the vertical electric field intensity. Through the cooperative measurement of the magnetic antenna array and the electric field sensor, the lightning azimuth (θ) is calculated by combining the magnetic field intensity ratio, and the quadrant is corrected by using the electric field polarity. Based on the magnetic field amplitude attenuation model and the waveform rise time correction factor, a distance estimation model is constructed. The autonomous decision module generates an approach path or an obstacle avoidance path according to the lightning azimuth and distance, and drives the flight control system to adjust the heading.

The invention discloses an electronic cabin assembly quality detection method based on three-dimensional vision. The method comprises the following steps: firstly, generating data for comparison during detection for a standard electronic cabin; shooting all to-be-detected objects in the to-be-detected electronic cabin to obtain a depth image and a color image of each to-be-detected object; according to the depth image and the color image of the to-be-detected object, combining with the data of the standard electronic cabin for comparison during detection; and whether screws of the electronic cabin to be detected are neglected and not installed in place, whether cable plugs are neglected and not installed in place, whether connectors and cable plugs in the wiring unit are wrongly matched, and whether the bending radius of cables is too small are detected in sequence. Through fusion of depth information, three-dimensional quantitative detection of the assembly quality is realized, and the detection precision, reliability and automation level are significantly improved.

The invention discloses a dynamic hydrodynamic modeling and parameter intelligent identification method for sailing of a trailing suction dredger, and relates to the technical field of sailing of trailing suction dredgers. According to the hydrodynamic modeling and parameter intelligent identification method for the sailing dynamic state of the trailing suction hopper dredger, core data covering an operation manual, historical cases, ship design data and all-working-condition sailing data are systematically obtained, so that a comprehensive basis is provided for modeling; an MMG reference model parameter set is constructed in combination with a hydrostatic calculation book, all working condition data are fused to obtain an environment adaptive fusion model, model deviation is corrected through parameter compensation, real-time data are processed at high frequency and the model is dynamically optimized by means of an edge calculation unit, and a sliding window can be adjusted according to error feedback to accelerate convergence. It is ensured that the final model prediction error is smaller than a threshold value, reliable kinematics support is provided for intelligent operation such as ship autonomous collision avoidance and trajectory tracking, and dredging operation safety risks and energy losses are effectively reduced.

The invention provides a low-altitude space path planning method and system, and relates to the technical field of low-altitude space management and path planning, and the method comprises the steps: S1, dividing a target airspace into a plurality of levels of three-dimensional voxels, and generating a unified-level three-dimensional code for each voxel; s2, voxelizing a task starting point, a task ending point and constraint elements based on unified hierarchical three-dimensional coding to generate a confinement three-dimensional corridor so as to limit a subsequent search space; s3, in the confinement three-dimensional corridor, hierarchical path search from the coarse hierarchy to the target hierarchy is executed, and a discrete path is output; s4, when the dynamic change of the environment is detected, performing increment re-planning on the basis of the discrete path, and updating the affected local path; and S5, smooth processing and safety verification are carried out on the discrete path or the updated path, and a final continuous flight path is generated. According to the invention, the real-time performance, the safety and the verifiability of the low-altitude flight task path can be realized.

The invention relates to the technical field of topographic change analysis, in particular to an unmanned aerial vehicle-based topographic change detection system, which comprises a slope direction sensing track control module, a texture structure extraction module, a crack evolution track construction module, a direction trend comparison module and a patrol recheck positioning module. According to the method, a continuous elevation point column of an unmanned aerial vehicle scanning area is extracted, laser reflection point coordinates are fused, a space relation of transition point distribution is constructed, dynamic adjustment of a ground-imitated flight path is achieved, and a texture structure area with continuous directivity is recognized in combination with a high-angle image boundary communication relation; texture boundary evolution is compared at different time nodes to form a crack path, the stability of the path and the slope direction is judged through an included angle sequence, recognition and sorting of areas with the consistent direction are completed, a space comparison result is registered in a three-dimensional coordinate system, terrain change areas are accurately marked, and rapid positioning and continuous tracking of high-risk areas are achieved.

The invention provides a multi-unmanned aerial vehicle adaptive migration method for a sudden no-fly zone, and relates to the technical field of unmanned aerial vehicles. And acquiring fusion environment data through cooperative sensing of multiple unmanned aerial vehicles, processing the data by adopting a semantic boundary extraction algorithm based on deep learning, and outputting a sudden no-fly zone map and unmanned aerial vehicle safety state codes. On the basis, the unmanned aerial vehicles are shunted according to the safety state codes and the sudden no-fly zone map, real-time obstacle avoidance tracks are generated for the non-intruding unmanned aerial vehicles, and cluster collaborative separation is executed for the intruding unmanned aerial vehicles. For unmanned aerial vehicles whose tasks are interrupted due to obstacle avoidance or separation, task decomposition is realized based on the sudden no-fly zone map and space-time isolation, and continuous execution of cluster tasks is realized through an energy consumption constraint auction mechanism, so that a plurality of unmanned aerial vehicles can better cope with a complex and changeable sudden no-fly zone environment.

The invention provides a power supply control method for a prefabricated cabin type energy storage system, and the method comprises the steps: obtaining a turn-off signal trigger of a secondary output channel, and forming an initial voltage fluctuation data set; according to the initial voltage fluctuation data set, the influence degree of turn-off energy dissipation on a main output channel is analyzed, and specific parameters of a fluctuation interference source are determined; obtaining a turn-off frequency range of a secondary output channel and real-time data of response delay after turn-off, and judging an adaptive frequency adjustment interval; dynamically calibrating the voltage according to the judged frequency regulation interval to obtain a preliminarily stable voltage output curve; and through the final voltage stability regulation scheme, obtaining system response data after the secondary output channel is turned off, and determining voltage stability guarantee parameters under long-term operation.

The invention discloses an unmanned aerial vehicle cluster collaborative operation path planning method based on distributed computing power. The method comprises the following steps: constructing a space-time safety corridor composed of convex polyhedrons for each unmanned aerial vehicle; an initial connected track is generated in the corridor, invariant re-parameterization based on curvature and torsion is carried out, and optimization solution is carried out in an invariant space; the result is expressed as a curvature continuous spline curve, a target function containing bending energy and path cost is constructed with control points and node time as variables, multiple constraints are applied, and complementary curvature constraints are established; minimizing the target function under constraint to obtain a smooth track; when an obstacle or a near conflict is detected, local re-optimization is carried out; and the edge nodes are responsible for constraint synchronization, independent optimization of each unmanned aerial vehicle and rolling updating of the flight path. According to the method, the stability of path planning and the energy utilization efficiency are improved by combining distributed computing power collaboration, geometric invariant re-parameterization and complementary curvature constraint.

The invention relates to the technical field of unmanned aerial vehicle path planning, in particular to an unmanned aerial vehicle automatic navigation method and system for power transmission line inspection. Comprising the steps of collecting terrain elevation data and a wind speed fluctuation signal, generating a line corridor boundary elevation distribution diagram, analyzing the influence of a terrain gradient on a conductor sag, and determining a curvature limitation adjustment demand; re-planning the flight path in combination with the obstacle position information, and generating a detection path sequence; calculating a height abrupt change value and an attitude angle deviation value, judging whether an acceleration impact suppression requirement exists or not, and generating an inspection risk score of the vegetation invasion area; determining a cross span distance risk quantitative index, and generating a flight control instruction sequence; and verifying whether the path meets a boundary integrity standard, and generating an automatic navigation path sequence. According to the method, the problems of instability, insufficient coverage and poor safety of an unmanned aerial vehicle routing inspection path under a complex terrain condition are solved, and stable, continuous and efficient automatic generation of the power transmission line routing inspection path is realized.

The invention provides an unmanned aerial vehicle flight path dynamic planning method and system, and relates to the technical field of flight path planning, and the method comprises the steps: obtaining the starting and ending points of the flight of an unmanned aerial vehicle, and planning an initial unmanned aerial vehicle flight path based on the starting and ending points of the flight of the unmanned aerial vehicle and a preset constraint; constructing an unmanned aerial vehicle flight environment model based on a preset flight area map, the elevation information and the obstacle information; route optimization is carried out based on the initial unmanned aerial vehicle flight route and a flight environment model, and an unmanned aerial vehicle initial obstacle avoidance route is generated; the unmanned aerial vehicle initial obstacle avoidance route is optimized based on a preset iterative optimization model, and an optimized unmanned aerial vehicle obstacle avoidance route is obtained; and updating the optimized unmanned aerial vehicle obstacle avoidance route to the initial unmanned aerial vehicle flight route to generate a final unmanned aerial vehicle flight route. According to the invention, the flight time and cost are saved, the adaptability to the environment, especially the urban complex environment, is enhanced, and the safety is guaranteed.

The present disclosure discloses a method for attitude control of a quadrotor UAV, comprising establishing an attitude dynamics model of the quadrotor UAV, establishing a motion equation and a state-space equation of a UAV control system, determining an LADRC-CFO, and establishing a differential tracker for reducing a system overshoot.

The invention provides a low-altitude logistics distribution method and system based on an electromagnetic launching unmanned aerial vehicle technology, and the method comprises the steps: installing a modular electromagnetic launching system in a designated region of a first logistics park; the unmanned aerial vehicle is connected with the modular electromagnetic emission system, and cargo loading and parameter calibration are carried out; dynamically planning a flight route of the unmanned aerial vehicle from the first logistics park to the second logistics park; the electromagnetic emission system is started to accelerate the unmanned aerial vehicle, and the pulse power modulation technology is utilized to control the output of specific pulse power in different stages, so that the unmanned aerial vehicle reaches a specified take-off speed within a preset distance range; the unmanned aerial vehicle autonomously flies along the flight route and autonomously performs obstacle avoidance and path correction, and the flight route or task sequence of the unmanned aerial vehicle is dynamically adjusted; and deploying a modular catapult stopping system in the second logistics park to complete stopping of the unmanned aerial vehicle. According to the invention, the acceleration efficiency can be improved to ensure that the unmanned aerial vehicle keeps a safe distance from the obstacle while keeping the distribution efficiency.

The invention discloses a vertical take-off and landing airport air traffic collaborative management method and system. The method comprises the following steps: constructing an airport air model integrating a physical environment, an airspace structure, a natural environment, an aircraft state and observation information; receiving observation information in real time to drive model synchronization; performing prospective multi-dimensional conflict prediction based on the synchronous model and eVTOL dynamics; on the basis of the prediction result, generating a cooperative regulation strategy when multiple constraint conditions are met; converting the strategy into an instruction, issuing the instruction through a security data link, and verifying an execution effect based on observation information to realize closed-loop control; according to the method, the air traffic environment of the vertical take-off and landing airport is systematically and digitally reconstructed through the quintuple model, unified representation of the operating environment and the traffic subject is achieved, the problem of heterogeneous information fusion is solved, the airspace utilization efficiency and safety under high-density operation can be remarkably improved, and the method is suitable for large-scale popularization and application. And the method has strong adaptive capacity to dynamic changes such as wind power disturbance and emergency conditions.

The invention discloses an urban low-altitude-oriented grid dynamic evaluation and intelligent route planning system, and belongs to the field of urban low-altitude airspace and routes. And the data processing module is used for inputting static data including the task number, the task time, the unmanned aerial vehicle number, the take-off and landing field number and the total airspace, the continuous airspace is divided into grid units by a project, and a quantitative evaluation model with seven factors including the underlying surface, the communication quality, the navigation quality, the meteorological environment, the electromagnetic environment, the noise and the countering as the core is constructed. The airworthiness score of each grid is calculated through normalization processing and weighted summation, a real-time and scientific decision basis is provided for path planning of the unmanned aerial vehicle, crossing from static planning to dynamic evaluation is achieved, and a set of airspace gridding dynamic evaluation and task planning system is provided and implemented. The system aims to cope with flight risks caused by multiple factors such as complex underlying surfaces, dynamic weather and communication navigation interference in urban low-altitude flight, and the safety and reliability of unmanned aerial vehicle logistics are improved.

The invention provides an unmanned aerial vehicle formation conflict avoidance control method and system and a medium, and the method comprises the steps: introducing a virtual leader-follower-based Stackelberg game architecture, enabling a virtual leader unmanned aerial vehicle to adaptively adjust the trajectory according to the formation state, and enabling the follower unmanned aerial vehicle to maintain the stability of the formation while completing a set tracking task; constructing an obstacle avoidance penalty term based on a speed obstacle method, and embedding the obstacle avoidance penalty term into an optimization objective function of the follower unmanned aerial vehicle to ensure that the follower unmanned aerial vehicle realizes collision avoidance in an obstacle environment; and respectively solving Hamiltonian-Jacobian-Bellman equations corresponding to the leader unmanned aerial vehicle and the follower unmanned aerial vehicle by adopting a single-network ADP algorithm, and generating a controller in real time. According to the invention, the problems of safe obstacle avoidance and tracking control of a multi-unmanned aerial vehicle system with formation stability requirements are effectively solved.