Low-altitude unmanned aerial vehicle route protection zone automatic generation and three-dimensional visualization method and system

Abstract

The present application belongs to the technical field of low-altitude unmanned aerial vehicle route design, protected area generation and three-dimensional geographic information visualization, and particularly relates to a low-altitude unmanned aerial vehicle route protected area automatic generation and three-dimensional visualization method and system. The method comprises: Step 1, multi-source data input; Step 2, route data preprocessing; Step 3, flight log analysis and parameter estimation; Step 4, route segmentation identification; Step 5, protected area geometric generation; Step 6, CZML and metadata encapsulation; and Step 7, Cesium three-dimensional visualization display. The low-altitude unmanned aerial vehicle route protected area automatic generation and three-dimensional visualization method can realize a closed-loop process from multi-source operation data input, automatic calculation of protected area parameters to three-dimensional visualization display, and improve the automation, interpretability and reproducibility of low-altitude unmanned aerial vehicle route design, simulation verification and engineering review.

Description

Technical Field

[0001] This invention belongs to the field of low-altitude unmanned aerial vehicle (UAV) route planning technology, specifically relating to a method and system for automatically generating and three-dimensionally visualizing low-altitude UAV route protection zones. Background Technology

[0002] The operation of logistics drones in urban low-altitude airspace is characterized by dense route networks, limited flight altitude, complex obstacle environment, frequent turning sections, and the coexistence of wind field disturbances and flight control errors. Traditional methods that rely solely on manually drawing route centerlines, fixed half-width expansion, or two-dimensional map display are insufficient to simultaneously meet the needs of automatic generation of low-altitude route protection zones, three-dimensional spatial representation, and engineering review visualization.

[0003] Existing low-altitude UAV route design and display systems mostly focus on the static display of waypoints or flight paths, and do not make sufficient use of multi-source data such as waypoint CSV, wind field data, and PX4 ULog flight logs. This makes it difficult to automatically extract control following error, response time, average speed, and wind disturbance parameters based on the actual flight conditions. At the same time, a uniform outward expansion method is usually used for straight and turning segments, and there is a lack of geometric expression for deterministic outward drift and asymmetric protection zones on the outside of turns. As a result, the generated results cannot accurately reflect the actual operational risks of UAVs during turns.

[0004] Furthermore, in existing technologies, the calculation results of protected areas and their 3D visualization are often disconnected. The calculated half-width, turning parameters, and protected area geometry need to be manually converted before they can be displayed on the 3D platform. There is a lack of a method that can encapsulate the flight path centerline, straight-line protected area, turning protected area, half-width parameters, turning parameters, and statistical parameters into Cesium-loadable data for interactive display, making it difficult to directly support low-altitude flight path scheme comparison, simulation verification, engineering reporting, and review. Summary of the Invention

[0005] This invention aims to propose a method and system that integrates multi-source data access, automatic calculation of route protection zones, CZML data encapsulation, and Cesium 3D visualization. By fusing waypoint CSV, ERA5 wind field data, and PX4 ULog flight logs, it automatically generates 3D tubular protection zones for straight flight segments and asymmetric 3D protection zones for turning segments based on the acquisition of real flight status and environmental disturbance parameters. These are then visualized in a Cesium 3D scene, thereby improving the automation and interpretability of low-altitude UAV route design, simulation verification, engineering reporting, and review.

[0006] To address the aforementioned technical problems, the first aspect of this invention provides a method for automatically generating and 3D visualizing low-altitude unmanned aerial vehicle (UAV) flight path protection zones, comprising: Step 1, Multi-source data input: Input waypoint CSV file, ERA5 wind field CSV file and PX4 ULog flight log file; Step 2, route data preprocessing: perform field recognition on the waypoint CSV file and preprocess the waypoints to obtain one or more route centerlines; Step 3, Flight Log Analysis and Parameter Estimation: The PX4 ULog flight log file is analyzed to extract the UAV's position, speed, navigation status, unlock status and setpoint data. Valid closed-loop flight segments are automatically identified, and control following error, response time, average speed, wind disturbance error and map error parameters are estimated by combining ERA5 wind field data. Step 4, Route segment identification: Calculate the turning angle based on the direction vectors of adjacent route segments, and divide the route into straight segments and turning segments; Step 5, Geometric generation of protected area: For straight flight segments, a three-dimensional tubular protected area is generated based on the probability and statistical tolerance terms and the institutional / data uncertainty terms; for turning flight segments, an asymmetric three-dimensional protected area with outward extension is generated based on the turning direction, equivalent turning radius, flight speed, control response time, and deterministic outward drift on the outside of the turn. Step 6, CZML and metadata encapsulation: Encapsulate the route centerline, straight protection zone, turning protection zone, straight section half-width, turning section inner half-width, turning section outer half-width, turning angle, equivalent turning radius, control error, wind disturbance error, average speed and response time into CZML data and metadata; Step 7, Cesium 3D Visualization: The front end loads the CZML data and metadata, and displays the route centerline, upper and lower boundary lines, waypoints, straight protection zones, turning protection zones, results panel and legend in the Cesium 3D scene, outputting the 3D visualization results of the route protection zones.

[0007] A second aspect of the present invention provides an automatic generation and 3D visualization system for low-altitude unmanned aerial vehicle (UAV) flight path protection zones, comprising: The data input module is used to receive waypoint CSV files, ERA5 wind field CSV files, and PX4 ULog flight log files; The route data preprocessing module is used to identify fields and preprocess the waypoints in the waypoint CSV file to obtain one or more route centerlines. The flight log parsing module is used to extract information such as the drone's position, speed, navigation status, unlock status, and setpoint from the PX4 ULog flight log. The parameter estimation module is used to estimate the control follow-up error, response time, average velocity, wind disturbance error, map error, and maximum lateral gust acceleration. The route segmentation module is used to identify straight segments and turning segments, and to calculate the turning direction, entry point, exit point, tangent length, and equivalent turning radius. The Straight Line Protection Zone Generation Module is used to generate three-dimensional tubular protection zones for straight line routes. The Turning Protection Zone Generation Module is used to generate asymmetric three-dimensional protection zones for turning sections. The CZML encapsulation module is used to encapsulate the flight path centerline, straight protection zone, turning protection zone, and calculation parameters into CZML data and metadata. The Cesium 3D rendering module is used to load and display the centerline, upper and lower boundary lines, waypoints, straight protection zones, and turning protection zones in a Cesium 3D scene. The results display module shows the number of routes, the half-width of straight sections, the half-width of turning sections, and legend information. The beneficial effects of this invention are: First, it can automatically estimate control follow-up error and response time using PX4 ULog flight logs, making the source of route protection zone parameters closer to the actual flight state; Second, it can use ERA5 wind field data and OU stochastic process to estimate wind disturbance error and maximum lateral gust acceleration, so that the process of generating protected areas can reflect the impact of environmental disturbances. Third, it can automatically identify straight sections and turning sections, and generate three-dimensional tubular protection zones for straight sections and asymmetrical three-dimensional protection zones for turning sections respectively; Fourth, it can incorporate the deterministic drift caused by control lag, gust shift and geometric drift on the outer side of the turn into the protection zone generation, making the expression of the protection zone on the outer side of the turn segment more consistent with the actual operational risks of UAVs; Fifth, it can encapsulate the flight path centerline, straight-line protection zone, turning protection zone, and key calculation parameters into CZML and metadata, and load, overlay, and display them in the Cesium 3D scene, improving the automation, interpretability, and visualization of low-altitude UAV flight path design, simulation verification, engineering reporting, and review. Attached Figure Description

[0008] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0009] Figure 1 This is a flowchart of the method for automatically generating and 3D visualizing low-altitude UAV flight path protection zones according to the present invention; Figure 2 This provides an overall framework diagram for the multi-source data input, error modeling, and route protection zone generation of the present invention. Figure 3 This is a schematic diagram illustrating the variation of the half-width of the outer protection zone of the turning section as a function of control response time according to the present invention. Figure 4 This is a statistical result of the lateral tracking error of the control closed loop based on PX4 ULog in this invention; Figure 5 Initial interface diagram of the low-altitude UAV flight path protection zone visualization platform; Figure 6 3D preview of the flight path centerline and waypoints; Figure 7 This is a diagram illustrating the three-dimensional tubular protection zone for straight sections and the asymmetrical three-dimensional protection zone for turning sections of the present invention. Figure 8 A diagram showing the upper and lower boundaries of the three-dimensional tubular protection zone for straight sections and air routes. Detailed Implementation

[0010] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the specific implementation methods of the present invention will be described below in conjunction with the technical flow of the present invention. It should be understood that the following embodiments are only for explaining the present invention and are not intended to limit the scope of protection of the present invention. All equivalent substitutions, modifications, or combinations made based on the technical concept of the present invention should fall within the scope of protection of the present invention.

[0011] See Figure 1 and Figure 2 This embodiment provides a method for automatically generating and 3D visualizing low-altitude UAV flight path protection zones, including: Step 1, Multi-source data input: Input waypoint CSV file, ERA5 wind field CSV file and PX4 ULog flight log file; Step 2, route data preprocessing: perform field recognition on the waypoint CSV file and preprocess the waypoints to obtain one or more route centerlines; Step 3, Flight Log Analysis and Parameter Estimation: The PX4 ULog flight log file is analyzed to extract the UAV's position, speed, navigation status, unlock status and setpoint data. Valid closed-loop flight segments are automatically identified, and control following error, response time, average speed, wind disturbance error and map error parameters are estimated by combining ERA5 wind field data. Step 4, Route segment identification: Calculate the turning angle based on the direction vectors of adjacent route segments, and divide the route into straight segments and turning segments; Step 5, Geometric generation of protected area: For straight flight segments, a three-dimensional tubular protected area is generated based on the probability and statistical tolerance terms and the institutional / data uncertainty terms; for turning flight segments, an asymmetric three-dimensional protected area with outward extension is generated based on the turning direction, equivalent turning radius, flight speed, control response time, and deterministic outward drift on the outside of the turn. Step 6, CZML and metadata encapsulation: Encapsulate the route centerline, straight protection zone, turning protection zone, straight section half-width, turning section inner half-width, turning section outer half-width, turning angle, equivalent turning radius, control error, wind disturbance error, average speed and response time into CZML data and metadata; Step 7, Cesium 3D Visualization: The front end loads the CZML data and metadata, and displays the route centerline, upper and lower boundary lines, waypoints, straight protection zones, turning protection zones, results panel and legend in the Cesium 3D scene, outputting the 3D visualization results of the route protection zones.

[0012] In one embodiment, the input can be a waypoint CSV file, an ERA5 wind field CSV file, and a PX4 ULog flight log file. The backend performs route preprocessing, flight log parsing, wind disturbance parameter estimation, straight-segment protection zone calculation, turning-segment asymmetric protection zone calculation, and CZML data encapsulation. The frontend uses Cesium to provide a three-dimensional display of the route centerline, upper and lower boundary lines, straight-segment protection zone, turning-segment protection zone, waypoints, results panel, and legend.

[0013] Specifically, in Step 1 of this embodiment, the system front-end constructs a 3D geographic scene based on Cesium and provides upload portals for waypoint CSV files, ERA5 wind field CSV files, and PX4 ULog flight log files. The functions of these three types of input data are as follows: (1) A waypoint CSV file, used to provide the longitude, latitude, altitude, point sequence, waypoint number, and point name; (2) ERA5 wind field CSV file, used to provide wind field time series, including at least time field, east-west wind speed component and north-south wind speed component; (3) PX4 ULog flight log file, used to provide the actual flight status of the UAV, including position, speed, navigation status, unlock status and setpoint information.

[0014] In this embodiment, the front end can also provide functions such as base map mode selection, closure mode selection, route preview, calculated map generation, back-end connection check, result overview, and legend display. The base map modes include Cesium online image base map and no base map mode; the closure modes include automatic loop closure recognition, forced non-loop closure, and forced loop closure, see [link to relevant documentation]. Figure 5 As shown.

[0015] Furthermore, in Step 2, after the backend reads the route CSV file, it adaptively identifies the field names. The longitude field can be identified as lon, lng, longitude, or x; the latitude field can be identified as lat, latitude, or y; the altitude field can be identified as agl_m, alt, height, or z; the point sequence field can be identified as seq, order, or idx; the route number field can be identified as route_id, route, line_id, or inferred from the waypoint name prefix; and the waypoints are grouped and sorted according to the route number field or the waypoint name prefix.

[0016] Specifically, for each valid waypoint, its longitude, latitude, and relative altitude are recorded as follows: in, Let i be the longitude of the i-th waypoint. Let i be the latitude of the i-th waypoint. Let be the altitude of the i-th waypoint. The system groups waypoints according to their waypoint numbers and sorts them in order within each group, resulting in one or more waypoint centerlines: in, Let r represent the centerline of the r-th route, and n be the number of waypoints included in the route.

[0017] The waypoint preprocessing includes: using the route start point as a local coordinate reference point, converting the latitude and longitude coordinates of the waypoints into local planar coordinates; Calculate the distance between adjacent waypoints in the local plane coordinate system. If the distance between the current waypoint and the previous retained waypoint is less than a preset threshold, delete the current waypoint. When the distance is greater than or equal to the preset threshold, the current waypoint is retained; After completing the cleanup of near-duplication points, the centerline of the route to be calculated is generated according to the route number and point sequence.

[0018] Specifically, in order to perform distance, turning angle, and protected area geometry calculations, this embodiment uses the starting point of each route as a local coordinate reference point, converting latitude and longitude coordinates into local planar coordinates. Let the reference point be: Then the local eastward coordinate x of the i-th waypoint i and north coordinates y i It can be represented as: Among them, R e The average radius of the Earth , , , All coordinates are expressed in radians. After coordinate transformation, the system calculates the planar distance between the current waypoint and the previous retained waypoint: Among them, P j This is the previous reserved waypoint. When When the current waypoint is considered to be a near duplicate of the previous saved waypoint, the current waypoint is deleted; when When this happens, the current waypoint is retained. In this embodiment, d min The distance can be 1 meter, or adjusted according to the accuracy of waypoint acquisition. After this step, the cleaned waypoint centerline is obtained.

[0019] Furthermore, in Step 3 of this embodiment, the backend parses the PX4 ULog flight log, first reading the timestamp, location, and speed information from the local location dataset, denoted as: in, , This represents the actual position of the UAV in the local coordinate system. , The horizontal velocity component of the drone; Further read the navigation status and unlock status from the flight status dataset, denoted as: in, Indicates navigation status. This indicates that the device is unlocked.

[0020] Simultaneously read the trajectory setpoint or position setpoint data to obtain the setpoint time series: When there is no direct direct match in the setpoint dataset , When using the field, you can read position[0], position[1], or current.x, current.y fields as the setpoint coordinates. Then, interpolate the setpoint sequence onto the local location time series to obtain: To eliminate the translational offset between the actual coordinate system and the setpoint coordinate system, this embodiment uses the median deviation within the effective flight segment for correction: The corrected coordinates of the setpoint are thus obtained: ; The automatic identification of valid closed-loop flight segments includes: dividing the flight log into several candidate segments according to the navigation status; filtering candidate segments based on unlock status, number of samples, flight duration, average speed, and lateral error quantile; constructing a scoring function for the candidate segments and selecting the candidate segment with the highest score as the valid closed-loop flight segment; wherein the scoring function is positively correlated with the duration of the candidate segment and negatively correlated with the lateral error quantile.

[0021] In one embodiment, specifically, to avoid estimating control errors during takeoff, landing, hovering, or abnormal states, this embodiment automatically identifies valid closed-loop flight segments based on navigation status, unlock status, flight duration, average speed, and lateral error quantiles. First, based on the navigation status... The flight log is divided into several candidate segments. For each candidate segment, it must satisfy the following condition: in, The number of candidate fragment samples. For the duration of the candidate segment, The average speed of the candidate segments, , , These are preset thresholds.

[0022] The average speed of the candidate segments is: Then calculate the lateral tracking error quantile within the candidate segment. And require: in, This represents the upper limit of the permissible lateral error.

[0023] For candidate segments that meet the above conditions, construct a scoring function: in, Score the candidate segments. This represents the error penalty coefficient. The scoring function is positively correlated with the candidate segment duration and negatively correlated with the lateral error quantile. The system selects the candidate segment with the highest score as the effective closed-loop flight segment. This flight segment is used for subsequent control tracking error, response time, and average flight speed estimation.

[0024] The estimation of the control tracking error includes: determining the trajectory normal vector based on the horizontal velocity component of the UAV; determining the position error vector based on the difference between the actual position of the UAV and the position of the set point; projecting the position error vector onto the trajectory normal vector to obtain the lateral tracking error; performing detrending processing on the lateral tracking error and determining the control tracking error based on its quantile; determining the correlation time based on the autocorrelation function of the lateral tracking error, and determining the control response time based on the correlation time.

[0025] Specifically, within the effective closed-loop flight segment, the trajectory normal vector is constructed based on the UAV's horizontal velocity direction. The horizontal velocity magnitude is: in, To prevent small values ​​from being divided by zero, the track normal vector is: Let the error vector between the actual position and the setpoint position be: The lateral tracking error is: Right now: To remove the influence of slow drift on control error estimation, this embodiment uses a moving average to detrend the lateral tracking error: in, Represents the moving average operator. For detrending time windows, This represents the lateral tracking error after detrending.

[0026] The control of the following error can be determined by the quantiles of the detrended lateral error: in, To control the following error, This is the quantile operator. In this embodiment, a quantile operator can be selected. , or These correspond to different levels of conservatism; The control response time is determined by the autocorrelation characteristics of the lateral tracking error, see [link to relevant documentation]. Figure 4 As shown. Let the lateral tracking error after detrending be... Its discrete sequence is Then there is a lag. The autocorrelation coefficient of the step can be expressed as: in, For the first The autocorrelation coefficient at each lag step size The mean of the error. This represents the number of samples.

[0027] set up The sampling time interval is taken from the effective lag range before the correlation function first becomes less than or equal to zero. Therefore, the correlation time is: in, This is the maximum lag step before the autocorrelation function first becomes less than or equal to zero. The control response time can be expressed as: In engineering implementation, to avoid instability in subsequent calculations due to abnormally small or missing values, an effective correlation time can be further set: in, This is the minimum response time threshold.

[0028] The estimation of wind disturbance error includes: reading the time field, east-west wind speed component, and north-south wind speed component from the ERA5 wind field CSV file; interpolating the wind speed components into the flight log time series; decomposing the wind speed into a lateral wind speed component based on the UAV track normal vector; and performing mean removal and random process fitting on the lateral wind speed component to obtain the wind speed standard deviation, wind field related parameters, wind disturbance displacement error, and maximum lateral gust acceleration.

[0029] Specifically, in this embodiment, the ERA5 wind farm CSV file includes at least a time field. East-west wind speed component and north-south wind speed components The system first converts the ERA5 time series into relative time: Then the wind speed component is interpolated into the flight log time series: in, This represents the time interpolation operator.

[0030] Based on the track normal vector By decomposing the wind speed into the lateral direction of the flight path, we obtain the lateral wind speed component: in, , For the normal vector components of the trajectory, This represents the lateral wind speed component.

[0031] To remove background wind or diurnal variation trends, this embodiment performs a moving average processing on the lateral wind speed component: in, For the background trend time window of the wind field The lateral wind speed residual after detrending.

[0032] In this embodiment, the detrended lateral wind speed residual is... It approximates an Ornstein-Uhlenbeck stochastic process. Its continuous form can be expressed as: in, For the response rate parameter, For the diffusion intensity of the OU process, It is Brownian motion.

[0033] In discrete time, a first-order autoregressive form can be used for approximation: in, These are the autoregressive coefficients. The residuals are the autoregressive coefficients, which can be estimated using the least squares method. The response rate of the OU process is then obtained: Let the residual variance be: The diffusion intensity of the OU process can then be expressed as: The standard deviation of lateral wind speed can be expressed as: Based on the simplified aerodynamic model of the UAV, the conversion factor from wind speed to lateral acceleration is: in, air density, The drag coefficient, The equivalent windward area of ​​the drone. The average wind speed, For the quality of drones.

[0034] Wind disturbance displacement error can be expressed as: in, This is due to wind-induced displacement error. To control response time, This is the wind disturbance amplification factor.

[0035] The maximum lateral gust acceleration can be estimated from the lateral wind speed component: in, For maximum lateral gust acceleration, The 95th percentile operator is used. Higher quantiles can also be selected based on operational safety requirements.

[0036] In Step 4, the turning angle is calculated based on the direction vectors of adjacent route segments, dividing the route into straight segments and turning segments, including: Construct the entry segment direction vector and the exit segment direction vector based on three consecutive waypoints; The signed turning angle is calculated based on the cross product and dot product of the two direction vectors; When the absolute value of the signed turning angle is greater than a preset turning angle threshold, the corresponding waypoint is identified as a turning point; Centered on the turning point, the tangent length is calculated based on the lengths of the adjacent segments before and after it. The entry point and exit point are respectively intercepted on the entry segment and the exit segment. The turning segment is formed by "entry point - turning point - exit point" and a straight segment that connects with the turning segment without overlapping is formed.

[0037] In one embodiment, specifically, for three consecutive waypoints , , Construct the direction vectors for entering and leaving the flight segment: The turning angle is determined by both the cross product and the dot product: in, For signed turning angles. When When, it can be determined as a left turn; when At that time, it can be determined as a right turn. If: Then Identified as a turning point, where This is the preset turning angle threshold.

[0038] The calculation of the entry point, exit point, and equivalent turning radius specifically includes: Let the length of the entry segment be... The departure segment length is Then the tangent length can be taken as: in, This is the proportionality coefficient. and These are the lower and upper limits of the tangent length, respectively. This is the amplitude limiting function.

[0039] Entry point lie in to On that segment of the flight, the distance from the turning point The distance is Cutting point lie in to On that segment of the flight, the distance from the turning point The distance is .

[0040] The equivalent turning radius can be determined by the tangent length and the turning angle: To avoid the impact of extremely small turning radii or abnormally large radii on the formation of the protected area, the following can be done: Limiting the amplitude: in, and These are the lower and upper limits of the equivalent turning radius, respectively.

[0041] In Step 5, for straight segments, the half-width of the protection zone consists of a probability and statistical tolerance term and a regulatory / data uncertainty term. The half-width of the protection zone for straight segments is: In the formula: H req The width of the straight section of the route is half; L tol The probability statistical tolerance for straight-line segments is determined based on positioning error, control following error, wind disturbance error, turning tracking amplification factor, and wind-control coupling term; D obs This indicates the institutional baseline and data uncertainty. The probability and statistical tolerance term can be determined by the root sum of the positioning error, control tracking error, and wind disturbance displacement error: Where k is the statistical coverage coefficient. For positioning error, To control the following error, This represents the wind-induced displacement error.

[0042] D obs Indicating institutional baselines and data uncertainties: Low-altitude airway protection zones are affected not only by flight control and wind disturbances, but also by errors in map and obstacle data and coordinate systems. Let the error in map or orthophoto stitching and geometric orientation be... The geometric error of the obstacle database is The coordinate datum and projection transformation error is The overall geographic data error can then be expressed as: Institutional baselines and data uncertainties can be expressed as: in, The minimum lateral distance system baseline required by regulations, operating procedures, or safety reviews. The coverage coefficient represents the data uncertainty. This is for redundant items in operation management.

[0043] In one engineering implementation method, it is also possible to... The map generalization error is incorporated into the statistical error of the straight line segment for unified calculation, thereby obtaining the equivalent half-width calculation result of the protected area.

[0044] Considering the uncertainties in the system / data, the required half-width for a straight flight segment can be: In another implementation, geographical data errors are included as a comprehensive error term in the unified statistical combination, resulting in: Both of the above methods are equivalent implementations of the present invention, and their core is to incorporate flight status error, wind disturbance error, geographical data error, and institutional lateral distance into the half-width calculation of the protection zone for straight flight segments.

[0045] In this embodiment, the half-width of the straight flight segment is obtained. Subsequently, the system generates a three-dimensional tubular protected area along the centerline of the straight flight segment. Optionally, the straight protected area is represented by a rectangular cross-section. Let the half-height of the protected area be... Then the cross-sectional shape of the straight line segment can be expressed as: By sweeping the rectangular cross-section along the centerline of the flight segment, a three-dimensional tubular protected area for the straight flight segment is obtained. This protected area can be represented by a polylineVolume object in CZML, and its spatial location is determined by the latitude, longitude, and altitude sequence of one or more points at the two ends of the flight segment, while the cross-section is determined by the aforementioned rectangular point set.

[0046] In one embodiment, the turning segment differs from the straight segment. During the turn, the UAV needs to continuously generate lateral acceleration and is affected by control bandwidth, trajectory curvature, and wind-control coupling. See [link to relevant documentation]. Figure 3 As shown. Therefore, this embodiment introduces a turning tracking amplification factor. It is used to amplify the following error in the turning segment control.

[0047] The lateral closed-loop bandwidth can be determined by the effective correlation time: in, This refers to the horizontal closed-loop bandwidth. For effective relevant time, This is the minimum time threshold.

[0048] The turning tracking magnification factor is: in, For flight speed, For the equivalent turning radius, This represents the lateral closed-loop bandwidth. This formula shows that the higher the speed, the smaller the turning radius, or the lower the closed-loop bandwidth, the more significant the amplification of the tracking error during the turning segment.

[0049] Calculation of statistical tolerance for turning sections: The statistical tolerance term for the turning section includes at least the positioning error, map error, control following error magnified by the turning angle, turning wind disturbance amplification term, and control-wind disturbance coupling term. Its statistical error can be expressed as: in, For statistical errors in the turning section, This is the amplification factor for wind disturbance during turns. To control the correlation coefficient between error and wind disturbance error.

[0050] The inner half-width of the turning section can be expressed as: in, It is half the width of the inner side of the turning section.

[0051] Calculation of deterministic outward drift on the outer side of a turn: In addition to statistical tolerance, the outer protection zone of a turn should also consider the deterministic drift caused by control response lag, short-term lateral gust shift, and geometric drift. In this embodiment, the deterministic drift on the outer side of the turn is: in, For the deterministic outward drift on the outside of the turn, For flight speed, To control response time or effective correlation time, For maximum lateral gust acceleration, The geometric outward drift coefficient, This is the equivalent turning radius.

[0052] The geometric drift coefficient increases with the increase of the turning angle: in, and These are the lower and upper limits of the geometric outward drift coefficient, respectively. For reference turning angle.

[0053] To prevent extreme parameters from causing excessive expansion of the protected area, the outward drift can be limited: in, and These are the lower and upper limits of the outward drift, respectively.

[0054] The required half-width of the route on the outside of the turning segment is: in, The required half-width of the route on the outer side of the bend. This is the probability statistical tolerance term for the outer side of the turning segment. For institutional baselines and data uncertainties, This refers to the deterministic outward drift on the outside of the turn.

[0055] In a practical implementation, the inner half-width of the turning segment can be: The outer half-width of the turning section can be: .

[0056] The outer edge of the protected area is determined by the direction of the turn. If it's a left turn, the outer edge is on the right; if it's a right turn, the outer edge is on the left. Let the width of the left side be... The width on the right is ,but: When the outer side is on the left: When the outer side is on the right side: .

[0057] The construction of the asymmetric turning protection zone planar polygon includes: For the entry point of the turning section Turning point Cutting point Construct the unit vectors for the entering and leaving directions respectively: The corresponding left normal vector is: The left offset line can be represented as: The right offset line can be represented as: Calculate the intersection of the offset lines on the same side to obtain the left vertex. and the right vertex The following six points form the planar polygon of the asymmetric turning protection zone: in, , , , These are the left and right offset points at the entry and exit points, respectively.

[0058] Furthermore, the generation of 3D protected area height includes: For both straight sections and turning sections, a half-height protection zone is set in this embodiment. If the centerline altitude of the flight path is Then the base height and top height of the protected area are respectively: For straight sections, the system generates a three-dimensional tubular protective structure with a rectangular cross-section along the centerline of the flight segment; for turning sections, the system generates an asymmetric planar polygon. According to the bottom height and top height Stretching is performed to obtain an asymmetric three-dimensional protection zone for the turning segment.

[0059] In one implementation, The height can be 30 m, but can be adjusted according to the flight path height, drone performance, operating procedures, or review requirements.

[0060] In Step 6 of one embodiment, after completing the geometric calculation of the protected area, the route centerline, straight-line protected area, and turning protected area are encapsulated as CZML data.

[0061] The route centerline entity includes entity number, name, available time interval, point style, path style, and position sequence. The position sequence uses: The format is used to represent the spatial location of waypoints as they change with sequence number or time.

[0062] The straight-line protection zone entity is represented by polylineVolume, which includes: positions, the latitude, longitude and altitude coordinate sequence of the flight segment centerline; shape, the set of rectangular cross-section points; material, transparent color material; and outline, the outline display attribute.

[0063] The cross section of the straight protection zone can be written as: The turning protection zone entity is represented by a polygon, which includes: positions, the latitude and longitude coordinate sequence of the asymmetric turning protection zone polygon; height, the base height; extrudedHeight, the top height; material, the transparent color material; and outline, the outline display attribute.

[0064] The system also outputs metadata, including but not limited to: effective closed-loop flight segment time range, flight duration, navigation status, average speed, control follow error, response time, wind disturbance error, map error, maximum lateral gust acceleration, number of routes, number of waypoints, number of straight segments, number of turning segments, half-width of straight segments, inner half-width of turning segments, outer half-width of turning segments, turning direction, turning angle, tangent length, equivalent turning radius, and polygon coordinates of the turning protection zone.

[0065] In Step 7 of one embodiment, after the front end receives the CZML data and metadata returned by the back end, it performs classification rendering in the Cesium 3D scene.

[0066] For the preview of the route CSV, the front end directly draws the route centerline, upper boundary line, lower boundary line, waypoints, and waypoint labels based on the waypoints. The upper and lower boundary lines can be calculated by adding or subtracting half the height from the centerline height, respectively. get: For CZML data returned by the backend, if the object contains a polylineVolume field, the frontend extracts the half-width of the protected area from its shape field and converts the object into a corridor entity with width, height, and stretched height in Cesium for display; if the object contains a polygon field, the frontend converts it into a Cesium stretched polygon entity based on its positions, height, and stretchedHeight fields for display.

[0067] Straight-line protected areas can be displayed using the first transparent color, while turning protected areas can be displayed using the second transparent color, so as to intuitively distinguish different types of protected areas in a three-dimensional scene.

[0068] Results panel and legend display: The front-end extracts key metrics from the metadata and displays them in the results panel, including the number of routes, the half-width of straight segments, and the half-width of turning segments. The half-width of straight segments can be the maximum value of the half-width of the straight segments for each route, and the half-width of turning segments can be the maximum value of the outer half-width of each turning segment. See [link to relevant documentation]. Figure 6 As shown.

[0069] The front-end also provides legends to illustrate the meaning of different visual objects, including the route centerline, upper boundary line, lower boundary line, straight-line protection zone, turning protection zone, and waypoint or node markers. See [link / reference]. Figure 6 As shown.

[0070] In this way, users can simultaneously view the route centerline, upper and lower boundary lines, route nodes, three-dimensional tubular protection zones for straight sections and asymmetric three-dimensional protection zones for turning sections in the Cesium 3D scene, and complete the inspection and review of the route protection zone design results in conjunction with the results panel.

[0071] Accordingly, based on the above embodiments, one embodiment of this application also provides an automatic generation and 3D visualization system for low-altitude unmanned aerial vehicle (UAV) flight path protection zones, including: The data input module is used to receive waypoint CSV files, ERA5 wind field CSV files, and PX4 ULog flight log files; The route data preprocessing module is used to identify fields and preprocess the waypoints in the waypoint CSV file to obtain one or more route centerlines. The flight log parsing module is used to extract information such as the drone's position, speed, navigation status, unlock status, and setpoint from the PX4 ULog flight log. The parameter estimation module is used to estimate the control follow-up error, response time, average velocity, wind disturbance error, map error, and maximum lateral gust acceleration. The route segmentation module is used to identify straight segments and turning segments, and to calculate the turning direction, entry point, exit point, tangent length, and equivalent turning radius. The Straight Line Protection Zone Generation Module is used to generate three-dimensional tubular protection zones for straight line routes. The Turning Protection Zone Generation Module is used to generate asymmetric three-dimensional protection zones for turning sections. The CZML encapsulation module is used to encapsulate the flight path centerline, straight protection zone, turning protection zone, and calculation parameters into CZML data and metadata. The Cesium 3D rendering module is used to load and display the centerline, upper and lower boundary lines, waypoints, straight protection zones, and turning protection zones in a Cesium 3D scene. The results display module is used to show the number of routes, the half-width of straight sections, the half-width of turning sections, and legend information.

[0072] In this embodiment, those skilled in the art will clearly understand that, for convenience and brevity, the specific working process of the system described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0073] In summary, this invention automates the process from waypoint CSV files, ERA5 wind field CSV files, and PX4 ULog flight log files to 3D visualization results of the route protection zone. Compared to methods relying solely on manual half-width settings or 2D route displays, this invention offers the following advantages: First, it can automatically estimate control follow-up error and response time using PX4 ULog flight logs, making the source of route protection zone parameters closer to the actual flight state; Second, it can use ERA5 wind field data and OU stochastic process to estimate wind disturbance error and maximum lateral gust acceleration, so that the process of generating protected areas can reflect the impact of environmental disturbances. Third, it can automatically identify straight sections and turning sections, and generate three-dimensional tubular protection zones for straight sections and asymmetrical three-dimensional protection zones for turning sections respectively; Fourth, it can incorporate the deterministic drift caused by control lag, gust shift and geometric drift on the outer side of the turn into the protection zone generation, making the expression of the protection zone on the outer side of the turn segment more consistent with the actual operational risks of UAVs; Fifth, it can encapsulate the flight path centerline, straight-line protection zone, turning protection zone, and key calculation parameters into CZML and metadata, and load, overlay, and display them in the Cesium 3D scene, improving the automation, interpretability, and visualization of low-altitude UAV flight path design, simulation verification, engineering reporting, and review.

[0074] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for automatically generating and 3D visualizing low-altitude unmanned aerial vehicle (UAV) flight path protection zones, characterized in that, include: Step 1, Multi-source data input: Input waypoint CSV file, ERA5 wind field CSV file and PX4 ULog flight log file; Step 2, route data preprocessing: perform field recognition on the waypoint CSV file and preprocess the waypoints to obtain one or more route centerlines; Step 3, Flight Log Analysis and Parameter Estimation: The PX4 ULog flight log file is analyzed to extract the UAV's position, speed, navigation status, unlock status and setpoint data. Valid closed-loop flight segments are automatically identified, and control following error, response time, average speed, wind disturbance error and map error parameters are estimated by combining ERA5 wind field data. Step 4, Route segment identification: Calculate the turning angle based on the direction vectors of adjacent route segments, and divide the route into straight segments and turning segments; Step 5, Geometric generation of protected area: For straight flight segments, a three-dimensional tubular protected area is generated based on the probability and statistical tolerance terms and the institutional / data uncertainty terms; for turning flight segments, an asymmetric three-dimensional protected area with outward extension is generated based on the turning direction, equivalent turning radius, flight speed, control response time, and deterministic outward drift on the outside of the turn. Step 6, CZML and metadata encapsulation: Encapsulate the route centerline, straight protection zone, turning protection zone, straight section half-width, turning section inner half-width, turning section outer half-width, turning angle, equivalent turning radius, control error, wind disturbance error, average speed and response time into CZML data and metadata; Step 7, Cesium 3D visualization: The front end loads the CZML data and metadata, and displays the route centerline, upper and lower boundary lines, waypoints, straight protection zones, turning protection zones, results panel and legend in the Cesium 3D scene, outputting the 3D visualization results of the route protection zones.

2. The method for automatic generation and three-dimensional visualization of low-altitude UAV flight path protection zones according to claim 1, characterized in that, In Step 1, the waypoint CSV file is used to provide waypoint longitude, latitude, altitude, point sequence, and waypoint number information; the ERA5 wind field CSV file is used to provide wind field time series information; and the PX4 ULog flight log file is used to provide the UAV's actual flight position, speed, navigation status, unlock status, and setpoint information.

3. The method for automatic generation and three-dimensional visualization of low-altitude UAV flight path protection zones according to claim 2, characterized in that, Step 2 involves field identification of the waypoint CSV file, including: The longitude field is identified as any one of lon, lng, longitude, or x; The latitude field is identified as any one of lat, latitude, or y; The height field is identified as any one of agl_m, alt, height, or z; The dotted sequence field is identified as any one of seq, order, or idx; The route number field is identified as any one of route_id, route, line_id, or a waypoint name prefix; and Waypoints are grouped and sorted according to the waypoint number field or waypoint name prefix.

4. The method for automatic generation and three-dimensional visualization of low-altitude UAV flight path protection zones according to claim 3, characterized in that, In Step 2, the waypoint preprocessing includes: Using the starting point of the route as a local coordinate reference point, the latitude and longitude coordinates of the route point are converted into local planar coordinates; Calculate the distance between adjacent waypoints in the local plane coordinate system. If the distance between the current waypoint and the previous retained waypoint is less than a preset threshold, delete the current waypoint. When the distance is greater than or equal to the preset threshold, the current waypoint is retained; After completing the cleanup of near-duplication points, the centerline of the route to be calculated is generated according to the route number and point sequence.

5. The method for automatic generation and three-dimensional visualization of low-altitude UAV flight path protection zones according to claim 1, characterized in that, In Step 3, the automatic identification of valid closed-loop flight segments includes: The flight log is divided into several candidate segments according to the navigation status; Candidate segments were selected based on unlock status, number of samples, flight duration, average speed, and lateral error quantiles. A scoring function is constructed for the candidate segments, and the candidate segment with the highest score is selected as the effective closed-loop flight segment; where The scoring function is positively correlated with the duration of candidate segments and negatively correlated with the lateral error quantile.

6. The method for automatic generation and three-dimensional visualization of low-altitude UAV flight path protection zones according to claim 1, characterized in that, In Step 3, the estimation of the control following error includes: Determine the trajectory normal vector based on the horizontal velocity component of the UAV; The position error vector is determined based on the difference between the actual position of the UAV and the position of the set point; The position error vector is projected onto the track normal vector to obtain the lateral tracking error; The lateral tracking error is detrended, and the control tracking error is determined based on its quantile. The correlation time is determined based on the autocorrelation function of the lateral tracking error, and the control response time is determined based on the correlation time; and The estimation of the wind disturbance error includes: Read the time field, east-west wind speed component, and north-south wind speed component from the ERA5 wind field CSV file; Interpolate the wind speed components to the flight log time series; The wind speed is decomposed into lateral wind speed components based on the drone's trajectory normal vector. By removing the mean and fitting a random process to the transverse wind speed component, the standard deviation of wind speed, wind field related parameters, wind disturbance displacement error, and maximum transverse gust acceleration are obtained.

7. The method for automatic generation and three-dimensional visualization of low-altitude UAV flight path protection zones according to claim 1, characterized in that, In Step 4, the turning angle is calculated based on the direction vectors of adjacent route segments, dividing the route into straight segments and turning segments, including: Construct the entry segment direction vector and the exit segment direction vector based on three consecutive waypoints; The signed turning angle is calculated based on the cross product and dot product of the two direction vectors; When the absolute value of the signed turning angle is greater than a preset turning angle threshold, the corresponding waypoint is identified as a turning point; Taking the turning point as the center, calculate the tangent length based on the length of the adjacent segments before and after it, and cut the entry point and exit point on the entry segment and exit segment respectively. The turning segment is formed by "entry point-turning point-exit point", and a straight segment that connects with the turning segment and does not overlap is formed.

8. The method for automatic generation and three-dimensional visualization of low-altitude UAV flight path protection zones according to claim 1, characterized in that, In Step 5, the half-width of the route within the protection zone for straight sections is: ； Where: H req The width of the straight section of the route is half; L tol The straight-line segment probability statistical tolerance is determined based on positioning error, control following error, wind disturbance error, turning tracking amplification factor, and wind-control coupling term; D obs This indicates the institutional baseline and data uncertainty. The half-width of the outer route of the protection zone for the turning section is: ； In the formula H req，turn The outer half-width of the channel in the turning section; This is the probability statistical tolerance term for the outer side of the turning segment; This refers to the deterministic outward drift on the outside of the turn.

9. The method for automatic generation and three-dimensional visualization of low-altitude UAV flight path protection zones according to claim 8, characterized in that, The turning tracking amplification factor is determined based on the flight speed, equivalent turning radius, and closed-loop bandwidth, and satisfies the following: ； In the formula k track ω is the amplification factor for the dynamic response error, determined by the curvature command frequency and the closed-loop bandwidth; c This represents the horizontal closed-loop bandwidth. v is the drone's flight speed; R is the drone's turning radius; The equivalent turning radius is determined by the geometric relationship between the entry point, the turning apex, and the exit point of the flight path, or is checked by constraints of flight speed, gravitational acceleration, and roll angle. The deterministic outward drift on the outer side of the turn is: In the formula Δ det,outer This represents the deterministic outward drift on the outer side of the turn; V is the flight speed; τ is the control response time; a wind,max This is the upper bound of the maximum lateral gust acceleration within the short window. If a gust acceleration a is encountered within the control response time τ... wind,max This will produce an approximately deterministic outward shift. ; χR is the geometric overhang, and the geometric overhang coefficient χ increases with the increase of the turning angle, and takes a value between the preset lower limit and the preset upper limit.

10. A system for automatically generating and 3D visualizing low-altitude unmanned aerial vehicle (UAV) flight path protection zones, characterized in that, include: The data input module is used to receive waypoint CSV files, ERA5 wind field CSV files, and PX4 ULog flight log files; The route data preprocessing module is used to identify fields and preprocess the waypoints in the waypoint CSV file to obtain one or more route centerlines. The flight log parsing module is used to extract information such as the drone's position, speed, navigation status, unlock status, and setpoint from the PX4 ULog flight log. The parameter estimation module is used to estimate the control follow-up error, response time, average velocity, wind disturbance error, map error, and maximum lateral gust acceleration. The route segmentation module is used to identify straight segments and turning segments, and to calculate the turning direction, entry point, exit point, tangent length, and equivalent turning radius. The Straight Line Protection Zone Generation Module is used to generate three-dimensional tubular protection zones for straight line routes. The Turning Protection Zone Generation Module is used to generate asymmetric three-dimensional protection zones for turning sections. The CZML encapsulation module is used to encapsulate the flight path centerline, straight protection zone, turning protection zone, and calculation parameters into CZML data and metadata; The Cesium 3D rendering module is used to load and display the centerline, upper and lower boundary lines, waypoints, straight protection zones, and turning protection zones in a Cesium 3D scene. The results display module is used to show the number of routes, the half-width of straight sections, the half-width of turning sections, and legend information.

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