A method and system for controlling a UAV to turn, a terminal and a storage medium

Abstract

The application relates to a UAV turning control method and system, a terminal and a storage medium, and relates to the technical field of UAV control. The method comprises the following steps: acquiring sliding waypoint data and UAV operation data; determining a real-time turning waypoint according to the sliding waypoint data; acquiring a bending operation boundary according to the real-time turning waypoint; analyzing the sliding waypoint data and the bending operation boundary to determine a dynamic bending difference value; analyzing the sliding waypoint data, the UAV operation data and the dynamic bending difference value to determine turning control data; controlling the preset UAV turning according to the turning control data; and training a preset learning model according to the sliding waypoint data, the UAV operation data, the dynamic bending difference value and the turning control data to assist in UAV turning control. The application has the effect of improving the operation stability and operation accuracy of the UAV.

Description

Technical Field

[0001] This application relates to the technical field of unmanned aerial vehicle (UAV) control, and in particular to a UAV turning control method, system, terminal, and storage medium. Background Technology

[0002] Drone turning control refers to the process of controlling a drone to turn between waypoints on adjacent routes while it is performing autonomous operations according to a predetermined route, and controlling the drone to complete continuous operations according to the route.

[0003] In related technologies, when controlling a drone to turn, a direct angle turn is usually adopted. The drone is controlled to run according to the autonomous route. When the drone reaches the target waypoint along the autonomous route, the drone is not subjected to trajectory smoothing control or speed gradual transition. Instead, the drone is directly controlled to turn according to the heading angle of the next route segment and enter the next straight route segment to continue running in a straight line.

[0004] Regarding the aforementioned technologies, when controlling a drone to turn using the direct angle turning method, the lack of smooth trajectory control and gradual speed transition during the turn can lead to sudden changes in the drone's speed and attitude, causing the drone's fuselage to shake and its flight trajectory to deviate. This results in low operational stability and poor operational accuracy, indicating room for improvement. Summary of the Invention

[0005] To improve the operational stability and accuracy of unmanned aerial vehicles (UAVs), this application provides a UAV turning control method, system, terminal, and storage medium.

[0006] Firstly, this application provides a method for controlling the turning of an unmanned aerial vehicle (UAV), employing the following technical solution: A method for controlling the turning of an unmanned aerial vehicle (UAV), comprising: Acquire slip waypoint data and UAV operational data; Determine real-time turning waypoints based on slip waypoint data; Obtain the bending operation boundary based on real-time turning waypoints; Analyze the slip waypoint data and bending operation boundaries to determine the dynamic bending difference; Analyze the slip waypoint data, UAV operation data, and dynamic bending difference to determine the turning control data; The system controls the drone to turn based on the turn control data, and trains the preset learning model based on the slip waypoint data, drone operation data, dynamic bending difference, and turn control data to assist in the drone's turn control.

[0007] Optionally, the steps of analyzing the slip waypoint data and bending operation boundaries to determine the dynamic bending difference include: Data analysis is performed on the slip waypoint data to determine the turning angle of the route and the current entry route into the curve; The bending operation boundary is discretized to determine the discrete boundary points; Calculate the vertical distance between the discrete boundary points and the current curve entry route to determine the boundary vertical distance; Data analysis of the vertical distance to the boundary is used to determine the maximum boundary distance; The maximum boundary distance and the turning angle of the flight path are analyzed to determine the dynamic bending difference.

[0008] Optionally, the steps of analyzing the maximum boundary distance and the flight path turning angle to determine the dynamic bending difference include: Obtain the drone's coverage width and maximum turning radius; Input the drone's coverage width, maximum boundary distance, and flight path turning angle into a preset full coverage model to determine the theoretical coverage deviation; Input the maximum turning radius and the turning angle of the route into the preset constraint model to determine the constraint coverage deviation; The minimum value among the constraint coverage deviation, theoretical coverage deviation, and preset safety deviation threshold is determined as the final bending deviation; The maximum value between the final bending deviation and the preset lower bending threshold is determined as the dynamic bending difference.

[0009] Optionally, the steps of analyzing slip waypoint data, UAV operational data, and dynamic bend difference to determine turn control data include: Perform data analysis on the slip waypoint data to determine the current turning angle, the entry line vector, the exit line vector, and the turning waypoint coordinates; Input the current turning angle and dynamic bending difference into the preset turning radius model to determine the turning control radius; The current turning angle, turning control radius, dynamic bending difference, entry line vector, exit line vector, and turning waypoint coordinates are analyzed to determine the entry point coordinates, exit point coordinates, and turning center coordinates. The dynamic bending difference, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates are analyzed to determine the turning control data.

[0010] Optionally, the steps to analyze the current turning angle, turning control radius, dynamic bending difference, entry line vector, exit line vector, and turning waypoint coordinates to determine the entry point coordinates, exit point coordinates, and turning center coordinates include: Input the entry and exit line vectors into the preset vector calculation model to determine the turning unit vector; Input the turning waypoint coordinates, turning control radius, dynamic bending difference, and turning unit vector into the preset center coordinate model to determine the turning center coordinates; Input the current turning angle, exit line vector, entry line vector, turning center coordinates, and turning control radius into the preset circular arc tangent point model to determine the entry point coordinates and exit point coordinates.

[0011] Optionally, the steps to analyze the dynamic bending difference, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates to determine the turning control data include: The distance is estimated by determining the arc length based on the turning control radius and the current turning angle. Determine whether the estimated arc length distance is greater than the preset operation and maintenance threshold; If it is not greater than, then the turning control radius is determined as the reference control radius; If it is greater than the threshold, the baseline control radius is determined based on the operation and maintenance threshold and the current turning angle. The operation and maintenance threshold is set as the arc length estimation distance, and the coordinates of the entry point, exit point, and turning center are updated synchronously. Calculate the product of the reference control radius and the preset maximum angular velocity to determine the initial turning linear velocity; The minimum value between the initial turning linear velocity and the preset drone cruise speed is determined as the baseline control linear velocity; Extract data from the drone's operational data to determine the drone's current speed; Input the drone's current speed and the preset drone stability acceleration into the preset braking distance model to determine the redundant braking distance; The sum of redundant braking distance, arc length estimation distance, and preset exit curve extension length is calculated to determine the total length of smooth turning; The analysis of arc length estimation distance, dynamic bending difference, baseline control linear velocity, smooth turning total length, current turning angle, UAV operation data, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates is used to determine the turning control data.

[0012] Optionally, the steps to determine the turning control data include analyzing the arc length estimation distance, dynamic bending difference, baseline control linear velocity, smooth turning total length, current turning angle, UAV operation data, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates: Obtain the total length of the inflection point route; Determine whether the total length of a smooth turn is greater than the total length of the inflection point route; If it is not greater than, then the preset maximum acceleration of the drone, the preset acceleration step size of the drone, the reference control linear velocity, the drone operation data and the coordinates of the entry point are input into the preset seven-segment S-curve planning model to determine the braking control data. The baseline control linear velocity, braking control data, current turning angle, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates are integrated to determine the turning control data. If it is greater than, the dynamic bending difference, the baseline control line speed, the baseline control radius and the arc length estimated distance are iteratively reduced according to the preset control scaling factor to determine the downward turning data, and the total smooth turning length is iteratively determined according to the downward turning data until the total smooth turning length is not greater than the total length of the inflection point route. Obtain the iterative control linear velocity, iterative control radius, coordinates of the iterative entry point, coordinates of the iterative exit point, and coordinates of the iterative circle center; Input the drone's maximum acceleration, drone acceleration step size, iterative control linear velocity, drone operation data, and iterative curve entry point coordinates into the seven-segment S-curve programming model to determine the braking control data. The iterative control linear velocity, braking control data, current turning angle, iterative control radius, coordinates of the iterative entry point, coordinates of the iterative exit point, and coordinates of the iterative center are integrated to determine the turning control data.

[0013] Secondly, this application provides a UAV turning control system, which adopts the following technical solution: A drone turning control system includes: The acquisition module is used to acquire sliding waypoint data, UAV operation data, and bending operation boundaries; A memory for storing a program for a UAV turning control method as described in any of the preceding claims; The processor and the program in the memory can be loaded and executed by the processor to implement a UAV turning control method as described in any of the above.

[0014] Thirdly, this application provides a smart terminal, which adopts the following technical solution: A smart terminal includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any of the preceding claims for a drone turning control method.

[0015] Fourthly, this application provides a computer storage medium capable of storing corresponding programs, which facilitates improving the operational stability and accuracy of UAVs, and adopts the following technical solution: A computer-readable storage medium storing a computer program that can be loaded by a processor and executed by any of the above-described unmanned aerial vehicle (UAV) turning control methods.

[0016] In summary, this application includes at least one of the following beneficial technical effects: 1. By acquiring slip waypoint data and UAV operation data, real-time turning waypoints are determined based on the slip waypoint data, and the bending operation boundary is obtained based on the real-time turning waypoints. The slip waypoint data and bending operation boundary are analyzed to determine the dynamic bending difference. The slip waypoint data, UAV operation data, and dynamic bending difference are analyzed to determine the turning control data. The UAV is controlled to turn based on the turning control data. The learning model is trained based on the slip waypoint data, UAV operation data, dynamic bending difference, and turning control data to assist in UAV turning control, thereby improving the decision-making efficiency of UAV turning control. 2. Estimate the arc length distance by determining the arc length based on the turning control radius and the current turning angle; determine if the estimated arc length distance is greater than the preset operation and maintenance threshold. If it is not greater, the turning control radius is determined as the baseline control radius; if it is greater, the baseline control radius is determined based on the operation and maintenance threshold and the current turning angle, and the operation and maintenance threshold is determined as the estimated arc length distance. Simultaneously update the coordinates of the entry point, exit point, and turning center. Calculate the product of the baseline control radius and the preset maximum angular velocity to determine the initial turning linear velocity. The minimum value between the initial turning linear velocity and the preset UAV cruise speed is determined as the baseline control linear velocity. The system extracts data from the drone's operation to determine its current speed. The current speed and a preset stable acceleration are then input into a preset braking distance model to determine the redundant braking distance. The system calculates the sum of the redundant braking distance, the estimated arc length, and the preset exit curve extension length to determine the total smooth turning length. Furthermore, it analyzes the estimated arc length, dynamic bending difference, baseline control linear velocity, total smooth turning length, current turning angle, drone operation data, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates to determine turning control data, thereby improving the stability of the drone's operation. 3. By analyzing the sliding waypoint data, the turning angle of the flight path and the current approach path are determined. The boundary of the turning operation is discretized to determine the discrete boundary points. The vertical distance between the discrete boundary points and the current approach path is calculated to determine the boundary vertical distance. Data analysis of the boundary vertical distance is performed to determine the maximum boundary distance. The maximum boundary distance and the turning angle of the flight path are analyzed to determine the dynamic turning difference. This is used to minimize the coverage of non-operational areas and optimize the control accuracy of UAV cruise operations. Attached Figure Description

[0017] Figure 1 This is a flowchart of a drone turning control method according to an embodiment of this application.

[0018] Figure 2 This is a flowchart in this application embodiment of analyzing sliding waypoint data and bending operation boundaries to determine the dynamic bending difference.

[0019] Figure 3 This is a flowchart illustrating the analysis of the maximum boundary distance and the turning angle of the flight path in this embodiment of the application to determine the dynamic bending difference.

[0020] Figure 4 This is a flowchart in this application embodiment that analyzes slip waypoint data, UAV operation data, and dynamic bending difference to determine turning control data.

[0021] Figure 5 This is a flowchart in this application embodiment that analyzes the current turning angle, turning control radius, dynamic bending difference, entry curve vector, exit curve vector, and turning waypoint coordinates to determine the entry curve coordinates, exit curve coordinates, and turning center coordinates.

[0022] Figure 6 This application embodiment is a flowchart that analyzes dynamic bending difference, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates to determine the turning control data.

[0023] Figure 7 This application embodiment is a flowchart that analyzes the arc length estimation distance, dynamic bending difference, reference control linear velocity, smooth turning total length, current turning angle, UAV operation data, reference control radius, entry point coordinates, exit point coordinates and turning center coordinates to determine the turning control data. Detailed Implementation

[0024] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figures 1 to 7 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0025] This application discloses a method, system, terminal, and storage medium for UAV turning control. Specifically, it discloses a processing terminal that acquires slip waypoint data and UAV operation data, determines real-time turning waypoints based on the slip waypoint data, obtains the bending operation boundary based on the real-time turning waypoints, analyzes the slip waypoint data and bending operation boundary to determine the dynamic bending difference, analyzes the slip waypoint data, UAV operation data, and dynamic bending difference to determine turning control data, controls the UAV to turn based on the turning control data, and trains a learning model based on the slip waypoint data, UAV operation data, dynamic bending difference, and turning control data to assist in UAV turning control and improve the decision-making efficiency of UAV turning control.

[0026] Reference Figure 1 This application discloses a method for controlling the turning of an unmanned aerial vehicle (UAV), comprising the following steps: Step S100: Acquire slip waypoint data and UAV operation data.

[0027] Among them, sliding waypoint data refers to three-point route data extracted by sliding. Sliding waypoint data includes the starting waypoint of the current flight segment of the UAV, the inflection point between the current flight segment and the next flight segment, the ending waypoint of the next flight segment, and the complete flight data between the three points, including waypoint coordinates, flight length, and flight direction vector. The processing terminal determines the three-segment flight data by sliding the data collected in real time based on the flight segment of the UAV, thereby realizing real-time smooth turning control of the UAV's autonomous cruise operation and improving the stability of UAV operation.

[0028] Drone operation data refers to the operation and control data of a drone, including the drone's real-time speed, real-time position, and real-time acceleration data, which are determined by the processing terminal by retrieving the drone's real-time operation data.

[0029] Step S101: Determine the real-time turning waypoint based on the slip waypoint data.

[0030] Among them, the real-time turning waypoint refers to the coordinates of the inflection point between the current flight segment and the next flight segment of the UAV, that is, the real-time turning point of the UAV. The processing terminal analyzes the sliding waypoint data, determines the three specific waypoints in the sliding waypoint data, and then updates the second waypoint as the real-time turning waypoint according to the UAV's cruise direction.

[0031] Step S102: Obtain the bending operation boundary based on the real-time turning waypoints.

[0032] Among them, the turning operation boundary refers to the outer boundary of the area to be covered by the cruise operation corresponding to the real-time turning waypoint. It is determined by the processing terminal by extending the operation boundary to the left and right sides of the real-time turning waypoint after determining the real-time turning waypoint, and extracting the outer operation boundary of the route on the left and right sides of the real-time turning waypoint.

[0033] Step S103: Analyze the sliding waypoint data and bending operation boundary to determine the dynamic bending difference.

[0034] The dynamic bending difference refers to the difference between the distance between the center of the turning arc and the real-time turning waypoint and the radius of the turning arc when the UAV smoothly turns to the target waypoint along an arc trajectory. This difference is determined with the constraint of covering the bending operation boundary and the objective of minimizing the coverage of non-operational areas, thereby optimizing the control accuracy of the UAV's cruise operation. It is determined by the processing terminal through analysis of the sliding waypoint data and the bending operation boundary. Specific analysis steps are detailed below. Figure 2 The steps in the process.

[0035] Step S104: Analyze the slip waypoint data, UAV operation data, and dynamic bending difference to determine the turning control data.

[0036] Among them, turning control data refers to the control data for controlling the UAV to make smooth turns. This includes the turning angle, center and radius of the turning arc, coordinates of the UAV's entry point, coordinates of the UAV's exit point, turning linear velocity, and braking control data during the pre-turn phase. This data is determined by the processing terminal through analysis of slip waypoint data, UAV operational data, and dynamic turning differences. Specific analysis steps are detailed in [reference needed]. Figure 4 The steps in the process.

[0037] Step S105: Control the preset UAV to turn based on the turn control data, and train the preset learning model based on the slip waypoint data, UAV operation data, dynamic bending difference and turn control data to assist UAV turn control.

[0038] Among them, drones refer to drones that patrol and operate on predetermined routes to perform tasks such as aerial photography, patrol, and plant protection.

[0039] The learning model refers to a parameter self-adaptive learning model. This model takes slip waypoint data, real-time UAV operation data, dynamic bend difference, and turn control data as input. By learning the constraints, operational parameter limitations, and inherent relationships between the UAV's turn control parameters during turn operations, it outputs optimal dynamic bend difference and turn control data. This enables smooth UAV turns and the autonomous generation of turn operation parameters, improving the decision-making efficiency for smooth turns. The learning model, trained in real-time using turn data generated during multiple UAV operations, is then further trained in real-time by the processing terminal using turn control data generated during UAV turns. Simultaneously, the model is back-trained based on the deviation between its output and real-time decision results, iteratively optimizing model weights and parameters. The calculation logic continues until the output of the learning model stabilizes and the deviation between it and the real-time decision data reaches the calibrated deviation threshold. Then, the output of the learning model is used to assist the UAV's turning control process. During this assistance process, the learning model outputs optimized trajectory parameters, including turning linear velocity data and turning trajectory data, based on the current real-time flight conditions and flight path data of the UAV. The system compares the difference between the learning model's output data and the actual calculated data. Once the difference is within the calibrated fine-tuning range and the model's output meets the operating parameter limits, the output parameters of the learning model are used as the final turning control parameters. Simultaneously, the learning model is continuously iteratively trained based on the turning data and the actual operation of the UAV after control based on the model's output parameters, thereby improving the stability of the UAV's operation.

[0040] Reference Figure 2 The steps for analyzing slip waypoint data and bending operation boundaries to determine the dynamic bending difference include: Step S200: Perform data analysis on the slip waypoint data to determine the turning angle of the route and the current approach route.

[0041] The turning angle refers to the angle between the current flight path segment and the next flight path segment of the UAV. The processing terminal first extracts the direction vectors of the first and second flight path segments from the sliding waypoint data, then calculates the cosine value of the angle between the first and second flight path segments using the vector cosine formula, and finally determines the angle between the first and second flight path segments using the inverse cosine function, which is the turning angle.

[0042] The current forward curve route refers to the geometric data of the route segment where the UAV is currently located in real time. It is determined by the processing terminal by extracting the geometric data of the UAV's route from the sliding waypoint data.

[0043] Step S201: Discretize the bending operation boundary to determine the discrete boundary points.

[0044] Discrete boundary points refer to the coordinate points of the bending operation boundary after discretization. The processing terminal extracts discretized data of the bending operation boundary according to the sampling interval stored in the system to determine the discretized coordinate points of the bending operation boundary, which are the discrete boundary points.

[0045] Step S202: Calculate the vertical distance between the discrete boundary point and the current curve entry route to determine the boundary vertical distance.

[0046] Among them, the boundary vertical distance refers to the vertical distance from each discrete boundary point to the current curve entry route, which is determined by the processing terminal by calculating the vertical distance from each discrete boundary point to the current curve entry route.

[0047] Step S203: Perform data analysis on the vertical distance of the boundary to determine the maximum boundary distance.

[0048] The maximum boundary distance refers to the maximum value among the vertical distances of the boundary. The processing terminal determines the maximum value among the vertical distances of the boundary by traversing the vertical distances of the boundary, which is the maximum boundary distance.

[0049] Step S204: Analyze the maximum boundary distance and the turning angle of the flight path to determine the dynamic bending difference.

[0050] The dynamic bending difference value is consistent with the dynamic bending difference value in step S103, and is determined by the processing terminal through analysis of the maximum boundary distance and the flight path turning angle. Specific analysis steps are detailed below. Figure 3 The steps in the process.

[0051] Reference Figure 3 The steps for analyzing the maximum boundary distance and the turning angle of the flight path to determine the dynamic bending difference include: Step S300: Obtain the drone's coverage width and maximum turning radius.

[0052] Among them, the drone coverage width refers to the effective coverage area of ​​the work area when the drone is running stably, which is determined by the processing terminal by retrieving the drone operation data stored in the system.

[0053] The maximum turning radius refers to the maximum permissible turning radius of a drone, which is determined by the processing terminal by retrieving the drone performance data stored in the system.

[0054] Step S301: Input the UAV coverage width, maximum boundary distance and flight path turning angle into the preset full coverage model to determine the theoretical coverage deviation.

[0055] The full coverage model refers to a model that determines the maximum theoretical bending deviation by using the completion of the coverage boundary as a constraint. Since the theoretical broken line route is set with the premise of complete coverage of the area to be detected during the process of determining waypoints and planning routes, this model determines the coverage margin of the UAV for the bending boundary by the difference between half of the UAV's coverage width and the maximum boundary distance. The quotient of the coverage margin and the sine of the turning half angle is uniquely determined. The specific model formula is as follows: .

[0056] In the formula, Due to theoretical coverage bias, For human-machine coverage width, The maximum boundary distance, This refers to the turning angle of the flight path.

[0057] Theoretical coverage deviation refers to the theoretical bending difference value determined based on the maximum boundary distance. It is the theoretical bending difference value that ensures the UAV covers the maximum boundary distance during the turning process, minimizing the coverage of non-operational areas during the turning process, thereby improving the material utilization rate of the UAV. It is calculated and determined by the processing terminal by inputting the UAV coverage width, maximum boundary distance and flight path turning angle into the full coverage model.

[0058] Step S302: Input the maximum turning radius and the turning angle of the route into the preset constraint model to determine the constraint coverage deviation.

[0059] The constraint model refers to a formulaic model that determines the maximum feasible deviation value of a UAV based on its radius constraint. The model is based on the geometric relationship between the turning center and the waypoint. The distance from the center to the waypoint is the difference between the maximum radius and the sine of the turning angle, while the deviation distance is the difference between the distance from the waypoint to the cloud center and the radius. This determines the constraint coverage deviation. The specific model formula is as follows: .

[0060] In the formula, To constrain coverage deviation, The maximum turning radius, This refers to the turning angle of the flight path.

[0061] Constraint coverage deviation refers to the maximum bending difference that a UAV can tolerate during operation at the current flight path turning angle, determined by the dynamic constraints of the UAV. It is calculated by the processing terminal by inputting the maximum turning radius and flight path turning angle into the constraint model, thereby improving the stability of UAV operation.

[0062] Step S303: Determine the minimum value among constraint coverage deviation, theoretical coverage deviation, and preset safety deviation threshold as the final bending deviation.

[0063] Among them, the safety deviation threshold refers to the upper limit of the safety of dynamic bending deviation, which is set at 3m. It is used to limit the trajectory deviation of the drone during the turning process and prevent the drone from deviating too much from the trajectory. It is determined by the operator based on the accuracy requirements of the drone's cruise operation mission, the width of the drone's coverage area, and the drone's trajectory tracking limitations.

[0064] The final bending deviation refers to the final selectable bending difference value obtained after limiting the constraint coverage deviation and the safety deviation threshold. The processing terminal determines the minimum value among the constraint coverage deviation, theoretical coverage deviation and safety deviation threshold by performing numerical analysis on the constraint coverage deviation, theoretical coverage deviation and safety deviation threshold, which is the final bending deviation.

[0065] Step S304: The maximum value between the final bending deviation and the preset lower bending threshold is determined as the dynamic bending difference.

[0066] Among them, the lower limit threshold for bending refers to the lower limit threshold for dynamic bending deviation. It is used to limit the bending trajectory of the UAV during the turning process, so as to avoid the UAV's unstable operation and sudden changes in flight status due to the excessively small turning radius. It is determined by the operator through pre-experimentation based on the accuracy requirements of the UAV's cruise operation mission and the dynamic limitations of the UAV, to determine the minimum bending difference that can be allowed for stable operation of the UAV during the turning process.

[0067] The dynamic bending difference is consistent with the dynamic bending difference in step S204. The processing terminal determines the maximum value between the final bending deviation and the lower bending limit threshold by performing numerical analysis on the final bending deviation and the lower bending limit threshold. This maximum value is the dynamic bending difference.

[0068] Reference Figure 4 The steps for analyzing slip waypoint data, UAV operational data, and dynamic bend difference to determine turn control data include: Step S400: Perform data analysis on the slip waypoint data to determine the current turning angle, the entry line vector, the exit line vector, and the coordinates of the turning waypoint.

[0069] The current turning angle is consistent with the route turning angle in step S200, and is determined by the processing terminal based on the direction vectors of the first and second route segments in the sliding waypoint data.

[0070] The curve entry vector refers to the direction vector of the current flight path of the UAV, which is determined by the processing terminal by extracting the direction vector of the current flight path of the UAV from the sliding waypoint data.

[0071] The exit curve vector refers to the direction vector of the next segment of the current flight path of the UAV. It is determined by the processing terminal by extracting the direction vector of the next segment of the current flight path of the UAV from the sliding waypoint data.

[0072] The turning waypoint coordinates are consistent with the real-time turning waypoint in step S101, and are determined by the processing terminal through data extraction of the sliding waypoint data.

[0073] Step S401: Input the current turning angle and dynamic bending difference into the preset turning radius model to determine the turning control radius.

[0074] The turning radius model refers to a formula for determining the turning radius using inverse cosine geometry. This model involves drawing a perpendicular line from the center of the turning arc to the direction of the entry curve, and then constructing a right triangle using the center, the foot of the perpendicular, and the real-time turning waypoint. The angle containing the real-time turning waypoint in this triangle is half the current turning angle. Since the foot of the perpendicular is the tangent point between the arc and the entry curve (i.e., the starting point of the turning arc), the line connecting the center and the foot of the perpendicular represents the radius of the turning arc. Simultaneously, the line connecting the center and the real-time turning waypoint represents the sum of the turning radius and the dynamic bending deviation. The turning radius can then be calculated using the cosine relationship. The specific formula is as follows: .

[0075] In the formula, For turning control radius, This is the dynamic bending difference. This represents the current turning angle.

[0076] The turning control radius refers to the theoretical radius of the turning arc when the UAV makes a smooth turn, determined based on the dynamic bending difference. It is calculated and determined by the processing terminal by inputting the current turning angle and the dynamic bending difference into the turning radius model.

[0077] Step S402: Analyze the current turning angle, turning control radius, dynamic bending difference, entry line vector, exit line vector, and turning waypoint coordinates to determine the entry point coordinates, exit point coordinates, and turning center coordinates.

[0078] The entry point coordinates refer to the coordinates of the starting point of the turning trajectory when the UAV makes a smooth turn on its current flight path. The exit point coordinates refer to the coordinates of the ending point of the turning trajectory when the UAV enters the next flight path after a smooth turn. The turning center coordinates refer to the coordinates of the center of the smooth turning arc trajectory when the UAV makes a smooth turn. All of the above data are determined by the processing terminal through analysis of the current turning angle, turning control radius, dynamic bending difference, entry line vector, exit line vector, and turning waypoint coordinates. Specific analysis steps are detailed in [reference needed]. Figure 5 The steps in the process.

[0079] Step S403: Analyze the dynamic bending difference, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates to determine the turning control data.

[0080] The turning control data is consistent with the turning control data in step S104. It is determined by the processing terminal through analysis of dynamic bending difference, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates. Specific analysis steps are detailed below. Figure 6 The steps in the process.

[0081] Reference Figure 5 The steps to determine the coordinates of the entry point, exit point, and center of the turn, by analyzing the current turning angle, turning control radius, dynamic bending difference, entry line vector, exit line vector, and turning waypoint coordinates, include: Step S500: Input the entry curve vector and exit curve vector into the preset vector calculation model to determine the turning unit vector.

[0082] The vector calculation model refers to a formulaic model that determines the direction vector of the angle bisector by calculating the vector sum of the entry and exit route vectors, and then normalizing the vector sum. The specific model formula is as follows: .

[0083] In the formula, For turning unit vectors, The entry vector of the curve. This is the exit vector for the curve.

[0084] The turning unit vector refers to the bisector of the angle between the drone's entry and exit curve paths. The turning direction vector points inwards towards the inside of the turning arc segment and is used to locate the center of the turning arc. The processing terminal determines this vector by inputting the entry and exit curve vectors into the vector calculation model when the drone is operating normally and the turning angle is less than the reverse turning angle threshold (below 180°). When the drone performs a reverse turn and the turning angle reaches 180°, the processing terminal first calculates the cross product between the entry and exit curve direction vectors. Based on the sign of the cross product, it determines the corresponding left or right turning control direction for the drone. Then, the unit vector perpendicular to the entry curve path and pointing inwards towards the turning direction is determined as the turning unit vector. When the drone performs a reverse turn and enters U-turn mode, the turning speed is set to the minimum of the drone's real-time speed and cruise speed, and the turning distance is set to the operation maintenance threshold. The drone is directly controlled to perform the reverse turn based on the assigned data, without entering the subsequent judgment and calculation process.

[0085] Step S501: Input the turning waypoint coordinates, turning control radius, dynamic bending difference, and turning unit vector into the preset center coordinate model to determine the turning center coordinates.

[0086] The circle center coordinate model refers to a formulaic model that determines the direction of the circle center by pointing the angle bisector vector of the turning angle, and then determines the circle center coordinates based on the geometric relationship that the sum of the radius and the dynamic bending difference is the distance between the circle center and the turning waypoint coordinates. The specific model formula is as follows: .

[0087] In the formula, Let these be the coordinates of the center of the turning circle. For the waypoint coordinates of the turn, For turning control radius, This is the dynamic bending difference. This is the unit vector for turning.

[0088] The turning center coordinates are consistent with the turning center coordinates in step S402, and are calculated and determined by the processing terminal by inputting the turning waypoint coordinates, turning control radius, dynamic bending difference, and turning unit vector into the center coordinate model.

[0089] Step S502: Input the current turning angle, exit line vector, entry line vector, turning center coordinates, and turning control radius into the preset arc tangent point model to determine the entry point coordinates and exit point coordinates.

[0090] The circular arc tangent point model refers to a formulaic model based on the parametric equations of a circle. It determines the coordinates of the tangent points between the turning arc and the entry and exit curves by shifting the center coordinates by the radius along the normal vectors pointing from the center to the curve's entry and exit points, respectively. The specific model formula is as follows: ; .

[0091] In the formula, for, for, The unit normal vector pointing from the center of the circle towards the direction of entry into the curve is determined by the processing terminal through the cross product of the entry-curve vector and the turning unit vector, followed by normalization. The unit normal vector pointing from the center of the circle outwards is determined by the processing terminal by rotating the unit normal vector of the inwards direction by the current turning angle based on the turning direction.

[0092] The coordinates of the entry point are consistent with those in step S402. They are determined by the processing terminal by inputting the current turning angle, exit line vector, entry line vector, turning center coordinates, and turning control radius into the arc tangent point model.

[0093] The coordinates of the exit point are consistent with those in step S402. They are determined by the processing terminal by inputting the current turning angle, exit line vector, entry line vector, turning center coordinates, and turning control radius into the arc tangent point model.

[0094] Reference Figure 6 The steps to determine the turning control data include analyzing the dynamic bending difference, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates. Step S600: Determine the arc length and estimate the distance based on the turning control radius and the current turning angle.

[0095] Among them, the arc length estimation distance refers to the length of the turning arc from the entry point to the exit point during the smooth turning process of the UAV, which is determined by the arc length estimation of the turning arc. It is used to estimate and determine the length of the flight path occupied by the UAV when turning, so as to avoid the UAV overshooting and deviating from the cruise flight path. The processing terminal first calculates the product of the turning control radius and the current turning angle, and then converts the product into arc length.

[0096] Step S601: Determine whether the estimated arc length distance is greater than the preset operation and maintenance threshold.

[0097] Among them, the operation maintenance threshold refers to the lower limit threshold of the arc length estimation distance, which is set to 4m. It is used to maintain the operation process of the UAV and avoid the situation that the UAV has insufficient turning preparation distance or insufficient operation distance on the next flight path after completing the turn. The operator sets up a smooth turn pre-experiment according to the common working conditions in the UAV cruise operation, performs different turning angles to evaluate and determine that the UAV can operate stably without affecting the determination of the upper limit of the arc length corresponding to the subsequent turn and cruise process.

[0098] By processing the terminal to determine whether the arc length estimation distance is greater than the operation and maintenance threshold, it can be determined whether the turning route corresponding to the current turning radius excessively occupies the airway, thereby improving the stability of UAV patrol operations.

[0099] Step S6011: If it is not greater than, then the turning control radius is determined as the reference control radius.

[0100] If the processing terminal determines that the estimated arc length distance is not greater than the operation and maintenance threshold, it indicates that the turning route corresponding to the current turning control radius has not excessively occupied the waterway, and the turning operation can be performed normally according to the current turning radius. Therefore, the turning control radius is determined as the benchmark control radius at this time.

[0101] The baseline control radius refers to the smooth turning radius of a UAV that meets the operation and maintenance threshold requirements. The processing terminal directly determines the turning control radius as the baseline control radius when the distance estimated by the arc length is not greater than the operation and maintenance threshold.

[0102] Step S6012: If it is greater than the threshold, determine the reference control radius based on the operation maintenance threshold and the current turning angle, set the operation maintenance threshold as the arc length estimation distance, and update the coordinates of the entry point, exit point, and turning center simultaneously.

[0103] If the processing terminal determines that the estimated arc length distance is greater than the operation and maintenance threshold, it indicates that the turning route corresponding to the current turning control radius is excessively occupying the airway and needs to be further restricted. Therefore, at this time, the reference control radius is determined based on the operation and maintenance threshold and the current turning angle. Based on the new reference control radius and the operation and maintenance threshold, the coordinates of the entry point, exit point, and turning center are calculated backward according to the calculation formulas for the coordinates of the entry point, exit point, and turning center to determine the updated coordinates of the entry point, exit point, and turning center, thereby improving the stability of the UAV operation.

[0104] The baseline control radius is consistent with the baseline control radius in step S6011. It is determined by the processing terminal based on the operation and maintenance threshold and the current turning angle when the estimated arc length distance exceeds the operation and maintenance threshold. The specific calculation formula is as follows: .

[0105] In the formula, As the reference control radius, For operation maintenance threshold, Given the current turning angle, the operation and maintenance threshold is updated to the arc length estimation distance, and the baseline control radius is determined by working backward from the operation and maintenance threshold.

[0106] The arc length estimation distance is consistent with the arc length estimation distance in step S600. After the processing terminal determines that the turning route corresponding to the current turning control radius is excessively occupying the waterway, it updates the operation maintenance threshold to the arc length estimation distance, thereby avoiding the occurrence of excessive waterway occupation.

[0107] Step S602: Calculate the product of the reference control radius and the preset maximum angular velocity to determine the initial turning linear velocity.

[0108] The maximum angular velocity refers to the maximum angular velocity that the drone can operate stably, which is calibrated by the operator in the system based on the drone's performance parameter data.

[0109] The initial turning linear velocity refers to the initial maximum value of the smooth turning linear velocity of the UAV, determined based on the reference control radius and the maximum angular velocity. It is determined by the processing terminal by calculating the product of the reference control radius and the maximum angular velocity.

[0110] Step S603: Determine the minimum value between the initial turning linear velocity and the preset drone cruise speed as the reference control linear velocity.

[0111] Among them, the drone's cruise speed refers to the constant speed at which the drone cruises along the flight path and has not entered the turning control phase. It is calibrated by the operator in the system based on the drone's operating parameters.

[0112] The baseline control linear speed refers to the upper limit of the smooth turning linear speed of the drone after the drone's cruise speed limit. The processing terminal determines the minimum value between the initial turning linear speed and the drone's cruise speed by analyzing the data. This value is the baseline control linear speed, which avoids the drone turning too fast, causing sudden speed changes and instability after exiting the turn, thereby improving the stability of the drone's operation.

[0113] Step S604: Extract the drone's operational data to determine the drone's current speed.

[0114] The current speed of the drone refers to the real-time linear velocity of the drone at that moment, which is determined by the processing terminal by extracting the drone speed data from the drone's operational data.

[0115] Step S605: Input the current speed of the UAV and the preset stable acceleration of the UAV into the preset braking distance model to determine the redundant braking distance.

[0116] Among them, the stable acceleration of the drone refers to the maximum acceleration that the drone can achieve during stable operation, which is calibrated by the operator in the system based on the drone's operating performance.

[0117] The braking distance model is a formulaic model that calculates the flight path length of a UAV from its current speed to 0 based on the acceleration braking formula. The specific model formula is as follows: .

[0118] In the formula, For redundant braking distance, The current speed of the drone. To stabilize the acceleration of the drone.

[0119] Redundant braking distance refers to the flight path length required for a drone to decelerate from its current speed to 0. Since the drone braking segment adopts a seven-segment S-curve control to decelerate the drone's speed from its current speed to its turning linear speed, and the S-curve control gradually increases the magnitude of acceleration to avoid sudden acceleration changes, the braking distance would be greater than the distance the drone would need to travel to adjust its speed to the target linear speed directly based on a fixed maximum acceleration. Therefore, setting the distance required to decelerate to 0 is equivalent to selecting the maximum redundant distance required for braking, thereby improving the drone's turning stability. This distance is calculated and determined by the processing terminal by inputting the drone's current speed into the braking distance model.

[0120] Step S606: Calculate the sum of redundant braking distance, arc length estimation distance, and preset exit curve extension length to determine the total length of smooth turn.

[0121] The extended length after exiting the curve refers to the extended length by which the UAV maintains its linear velocity and continues to travel at a constant speed when smoothly turning into the next segment of the flight path. This is used to restore the UAV's flight attitude and confirm its flight direction, thereby improving the stability of the UAV's operation. Because the operator conducts pre-turning experiments on the UAV in common cruise scenarios to determine the initial stable distance required for the UAV to operate stably after completing a smooth turn and continue to perform subsequent channel cruise operations, the operator then sets a certain safety redundancy on the initial stable distance based on the channel planning of the current cruise mission.

[0122] The total smooth turning length refers to the total flight path length required for the UAV to turn. This includes the braking length required to smoothly adjust the speed to the turning linear speed during the pre-turn phase, the turning flight path length required during the UAV turn, and the length of the extended section after the UAV exits the turn. It is determined by the processing terminal by calculating the redundant braking distance, the arc length estimation distance, and the extended length after exiting the turn.

[0123] Step S607: Analyze the arc length estimation distance, dynamic bending difference, baseline control linear velocity, smooth turning total length, current turning angle, UAV operation data, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates to determine the turning control data.

[0124] The turning control data is consistent with the turning control data in step S403. It is determined by the processing terminal through analysis of the arc length estimation distance, dynamic bending difference, baseline control linear velocity, UAV operation data, smooth turning total length, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates. The specific analysis steps are as follows: Figure 7 The steps in the process.

[0125] Reference Figure 7 The steps to determine the turning control data include analyzing the arc length estimation distance, dynamic bending difference, baseline control linear velocity, smooth turning total length, current turning angle, UAV operation data, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates. Step S700: Obtain the total length of the inflection point route.

[0126] The total length of the inflection point route refers to the length of the next route after the current route of the UAV. It is determined by the processing terminal by first retrieving the sliding waypoint data and then extracting the length of the next route segment from the current route segment in the sliding waypoint data.

[0127] Step S701: Determine whether the total length of the smooth turn is greater than the total length of the inflection point route.

[0128] Specifically, the terminal determines whether the total length of the smooth turn is greater than the total length of the inflection point route. Based on the principle of conservative estimation, the feasibility of the current turning parameters is determined by comparing the total length of the smooth turn with the length of the next route segment. Since the route consumed by the braking segment of the UAV's turn is the terminal channel of the UAV's current route, the main channel consumption length is the UAV's smooth turn length and the UAV's exit extension segment. Therefore, the remaining available space length of the channel should be the sum of the turn and the exit extension segment. Therefore, in order to simplify the UAV's decision-making process and improve the UAV's turning control efficiency, the turn segment and the exit extension segment are all incorporated into the next channel for estimation and comparison to optimize the UAV's operating effect.

[0129] Step S7011: If not greater than, input the preset maximum acceleration of the UAV, the preset acceleration step size of the UAV, the reference control linear velocity, the UAV operation data and the coordinates of the entry point into the preset seven-segment S-curve planning model to determine the braking control data.

[0130] If the processing terminal determines that the total length of the smooth turn is not greater than the total length of the inflection point route, it indicates that the turning control parameters of the UAV are matched with the route and turning control can be performed. Therefore, the maximum acceleration of the UAV, the acceleration step size of the UAV, the reference control linear velocity, the UAV operation data and the coordinates of the entry point are input into the preset seven-segment S-curve planning model to determine the braking control data.

[0131] The maximum acceleration of a drone refers to the maximum acceleration that a drone can achieve during stable operation, which is determined by the operator based on the drone's performance parameters.

[0132] The drone acceleration step size refers to the maximum allowable acceleration adjustment step size of the drone. It is determined by the operator based on the drone's operating performance, and then calibrated in the system.

[0133] The seven-segment S-curve planning model is a trajectory planning algorithm based on acceleration step size to determine the braking trajectory. This algorithm divides the velocity change process into seven control segments, using the UAV's real-time position, real-time velocity, maximum acceleration, acceleration adjustment step size, and the target velocity, target acceleration, and target jerk of the UAV at the braking target position. In this step, the UAV's target velocity is the baseline control linear velocity, the target acceleration is 0, the target jerk is 0, and the target position is the coordinates of the curve entry point. After inputting the above data into the model, in the first stage of acceleration adjustment, the model determines the UAV's position sequence, velocity sequence, and acceleration sequence based on the time series through dynamic integration. Within this stage... The drone is controlled to adjust its acceleration in increments until the target acceleration is reached. In the second stage, the drone maintains the target acceleration and accelerates uniformly. In the third stage, the acceleration is smoothly reduced to 0 in increments. When the acceleration drops to 0 but the speed has not yet reached the target speed, the drone enters the fourth stage of uniform speed. After entering the fourth stage, the acceleration increment adjustment stage is symmetrically performed with the first, second, and third stages. This ensures that the drone reaches the target speed, acceleration, and jerk at the target position. The entire speed planning stage of the model is a continuous trapezoid, and the speed curve is a smooth S-shaped curve, which avoids sudden acceleration changes in the drone and improves the stability of the drone during operation.

[0134] Braking control data refers to the braking control data of the UAV in the pre-turn segment, which smoothly adjusts the speed of the UAV at the entry point of the curve to the reference control linear velocity. It includes the speed sequence, position sequence and acceleration control sequence of the UAV. It is calculated and determined by the processing terminal by inputting the maximum acceleration of the UAV, the acceleration step size of the UAV, the reference control linear velocity, the UAV operation data and the coordinates of the entry point of the curve into the seven-segment S-curve planning model.

[0135] Step S7012: Integrate the baseline control linear velocity, braking control data, current turning angle, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates to determine the turning control data.

[0136] The turning control data is consistent with the turning control data in step S607. The processing terminal determines the turning control data by integrating the reference control linear velocity, braking control data, current turning angle, reference control radius, entry point coordinates, exit point coordinates, and turning center coordinates when the total length of the smooth turn is not greater than the total length of the turning point route, i.e., the turning control parameters of the UAV match the airway and the turning control can be directly performed. This improves the control accuracy of the UAV turning and enhances the operational stability of the UAV. When the turning angle of the UAV is 180°, the UAV enters the U-turn mode. At this time, the UAV's U-turn linear velocity is the minimum value between the UAV's current speed and the UAV's cruise speed, and the UAV's entry distance into the turn is the operation and maintenance threshold. The UAV turns directly based on the above data.

[0137] Step S7013: If it is greater than, then according to the preset control scaling factor, the dynamic bending difference, the reference control linear velocity, the reference control radius and the arc length estimated distance are iteratively reduced proportionally to determine the downward turning data, and the total smooth turning length is iteratively determined according to the downward turning data until the total smooth turning length is not greater than the total length of the inflection point route.

[0138] Among them, the control scaling factor refers to the spatial compression parameter when the turning parameters do not match the channel. This parameter compresses the entire turning trajectory proportionally and iteratively without changing the geometric similarity of the smooth turning trajectory and the physical relationship between each turning control parameter. The operator sets the scaling factor in the system to be the quotient of the inflection point route length and the total smooth turning length. Before each iteration, the processing terminal first calculates the quotient of the inflection point route length and the total smooth turning length according to the calibration formula.

[0139] Downgraded turning data refers to the integrated data of dynamic bending difference, baseline control linear velocity, turning control radius, and arc length estimation distance after the control scaling factor has been downgraded. This data is iterative data. The processing terminal calculates the product of the control scaling factor and the dynamic bending difference, baseline control linear velocity, baseline control radius, and arc length estimation distance in successive iterations to obtain the downgraded data. Based on the iterative downgraded data, the smooth total turning length corresponding to the downgraded data is calculated and determined according to the same steps until the smooth total turning length is not greater than the total length of the inflection point route. The iteration process stops then. When the number of iterations exceeds the iteration threshold calibrated in the system, if the smooth total turning length is still greater than the total length of the inflection point route, the iteration process is terminated. According to the turning planning steps, the large turning angle is divided into two small turning processes to generate turning control parameters, and an alarm prompt is given to the operator. If the split turning parameters still do not match the lane, the UAV is controlled to hover in place and perform an in-place turning operation to achieve the turning process.

[0140] If the processing terminal determines that the total length of the smooth turn is greater than the total length of the inflection point route, it indicates that the UAV's turning control parameters do not match the route and cannot be directly turned. Therefore, the dynamic bending difference, reference control linear velocity, reference control radius, and arc length estimated distance are iteratively reduced according to the control scaling factor to determine the downward turning data. The total length of the smooth turn is then iteratively determined based on the downward turning data until the total length of the smooth turn is no greater than the total length of the inflection point route.

[0141] Step S7014: Obtain the iterative control linear velocity, iterative control radius, coordinates of the inflection point, coordinates of the outflection point, and coordinates of the center of the iterative circle.

[0142] The iterative control linear velocity refers to the UAV turning control linear velocity that, after repeated iterations, ensures the total smooth turning length is no greater than the total length of the inflection point flight path. The processing terminal iteratively calculates the product of the baseline control linear velocity and the control scaling factor, and synchronously calculates and determines the total smooth turning length based on the reduced turning data after each iteration. This process continues until the total smooth turning length is no greater than the total length of the inflection point flight path. At this point, the corresponding reduced baseline control linear velocity is extracted, which is the iterative control linear velocity.

[0143] The iterative control radius refers to the UAV's baseline control radius that, after iterative iteration, ensures the total smooth turning length is no greater than the total length of the inflection point route. The processing terminal iteratively calculates the product of the turning control radius and the control scaling factor, and synchronously calculates and determines the total smooth turning length based on the reduced turning data after each iteration. This process continues until the total smooth turning length is no greater than the total length of the inflection point route. At this point, the corresponding reduced turning control radius is extracted, which is the iterative control radius.

[0144] The iterative entry point coordinates refer to the UAV entry point coordinates that, after iterative iteration, result in a smooth turn with a total length not exceeding the total length of the inflection point flight path. The processing terminal determines these coordinates by extracting the entry point coordinates based on the final iteration results after the iteration ends. The calculation process for the iterative entry point coordinates is consistent with the calculation process for the entry point coordinates, and the input variables are updated from the original data to the iterative data each time.

[0145] The iterative exit point coordinates refer to the coordinates of the UAV exit point after repeated iterations, which ensure that the total length of the smooth turn is no greater than the total length of the inflection point flight path. The processing terminal determines the exit point coordinates by extracting the exit point coordinates based on the final iteration results after the iteration ends. The calculation process of the iterative exit point is the same as the calculation process of the exit point coordinates, and the input variables are updated from the original data to the iterative data one by one.

[0146] The iterative center coordinates refer to the center coordinates of the UAV's smooth turning arc after repeated iterations, ensuring that the total smooth turning length is no greater than the total length of the inflection point flight path. The center coordinates are determined by the processing terminal by extracting the turning center coordinates based on the final iteration results after the iteration ends. The calculation process of the iterative center coordinates is the same as that of the turning center coordinates, and the input variables are updated from the original data to the iterative data one by one.

[0147] Step S7015: Input the UAV's maximum acceleration, UAV acceleration step size, iterative control linear velocity, UAV operation data, and iterative curve entry point coordinates into the seven-segment S-curve programming model to determine the braking control data.

[0148] Among them, the braking control data is consistent with the braking control data in step S7011. It is determined by the processing terminal by inputting the UAV's maximum acceleration, UAV acceleration step size, iterative control linear velocity, UAV operation data and iterative entry point coordinates into the seven-segment S-curve planning model when the total length of the smooth turn is greater than the total length of the inflection point route.

[0149] Step S7016: Integrate the iterative control linear velocity, braking control data, current turning angle, iterative control radius, iterative entry point coordinates, iterative exit point coordinates, and iterative center coordinates to determine the turning control data.

[0150] The turning control data is consistent with the turning control data in step S607. It is determined by the processing terminal by integrating the iterative control linear velocity, braking control data, current turning angle, iterative control radius, iterative entry point coordinates, iterative exit point coordinates, and iterative center coordinates when the total length of the smooth turn is greater than the total length of the inflection point route.

[0151] Based on the same inventive concept, embodiments of this application provide a drone turning control system, including: The acquisition module is used to acquire sliding waypoint data, UAV operation data, bending operation boundary, UAV coverage width, maximum turning radius, total length of inflection point route, iterative control linear velocity, iterative control radius, iterative entry point coordinates, iterative exit point coordinates, and iterative circle center coordinates. A memory used to store a program for a drone turning control method; The processor can load and execute programs in memory to implement a method for controlling the turning of a drone.

[0152] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0153] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a method for controlling the turning of an unmanned aerial vehicle (UAV).

[0154] Computer storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0155] Based on the same inventive concept, this application provides a smart terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded and executed by the processor to perform a drone turning control method.

[0156] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0157] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A method for controlling the turning of an unmanned aerial vehicle (UAV), characterized in that, include: Acquire slip waypoint data and UAV operational data; Sliding waypoint data refers to three-point route data extracted by sliding, which includes the starting waypoint of the route segment where the UAV is currently located, the inflection waypoint between the route where the UAV is currently located and the next route, the ending waypoint of the next route where the UAV is currently located, and the complete route data between the three points. It is determined by the three-segment route data collected in real time by sliding the UAV on the route. Determine real-time turning waypoints based on slip waypoint data; Obtain the bending operation boundary based on real-time turning waypoints; Analyze the slip waypoint data and bending operation boundaries to determine the dynamic bending difference; The steps for analyzing slip waypoint data and bending operation boundaries to determine dynamic bending differences include: Data analysis is performed on the slip waypoint data to determine the turning angle of the route and the current entry route into the curve; The bending operation boundary is discretized to determine the discrete boundary points; Calculate the vertical distance between the discrete boundary points and the current curve entry route to determine the boundary vertical distance; Data analysis of the vertical distance to the boundary is performed to determine the maximum boundary distance; The maximum boundary distance and the turning angle of the flight path are analyzed to determine the dynamic bending difference. The steps for analyzing the maximum boundary distance and the turning angle of the flight path to determine the dynamic bending difference include: Obtain the drone's coverage width and maximum turning radius; Input the drone's coverage width, maximum boundary distance, and flight path turning angle into a preset full coverage model to determine the theoretical coverage deviation; Input the maximum turning radius and the turning angle of the route into the preset constraint model to determine the constraint coverage deviation; The minimum value among the constraint coverage deviation, theoretical coverage deviation, and preset safety deviation threshold is determined as the final bending deviation; The maximum value between the final bending deviation and the preset lower bending threshold is determined as the dynamic bending difference. Analyze the slip waypoint data, UAV operation data, and dynamic bending difference to determine the turning control data; The system controls the drone to turn based on the turn control data, and trains the preset learning model based on the slip waypoint data, drone operation data, dynamic bending difference and turn control data to assist the drone's turn control. The learning model refers to a parameter self-adaptive learning model. The output results of the learning model are used to assist the turning control process of the UAV. By comparing the difference between the output data of the learning model and the actual calculated data, it is determined that the difference is within the calibrated fine-tuning range and the model output meets the operating parameter limits. Then, the output parameters of the learning model are used as the final turning control parameters. At the same time, the learning model is continuously iteratively trained based on the turning data and the actual operation of the UAV after controlling the UAV according to the model output parameters.

2. The UAV turning control method according to claim 1, characterized in that, The steps for analyzing slip waypoint data, UAV operational data, and dynamic bend difference to determine turn control data include: Perform data analysis on the slip waypoint data to determine the current turning angle, the entry line vector, the exit line vector, and the coordinates of the turning waypoint; Input the current turning angle and dynamic bending difference into the preset turning radius model to determine the turning control radius; The current turning angle, turning control radius, dynamic bending difference, entry line vector, exit line vector, and turning waypoint coordinates are analyzed to determine the entry point coordinates, exit point coordinates, and turning center coordinates. The dynamic bending difference, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates are analyzed to determine the turning control data.

3. The UAV turning control method according to claim 2, characterized in that, The steps to determine the coordinates of the entry point, exit point, and center of the turn by analyzing the current turning angle, turning control radius, dynamic bending difference, entry line vector, exit line vector, and turning waypoint coordinates include: Input the entry and exit line vectors into the preset vector calculation model to determine the turning unit vector; Input the turning waypoint coordinates, turning control radius, dynamic bending difference, and turning unit vector into the preset center coordinate model to determine the turning center coordinates; Input the current turning angle, exit line vector, entry line vector, turning center coordinates, and turning control radius into the preset circular arc tangent point model to determine the entry point coordinates and exit point coordinates.

4. The UAV turning control method according to claim 2, characterized in that, The steps to determine the turning control data by analyzing the dynamic bending difference, current turning angle, UAV operation data, turning control radius, entry point coordinates, exit point coordinates, and turning center coordinates include: The distance is estimated by determining the arc length based on the turning control radius and the current turning angle. Determine whether the estimated arc length distance is greater than the preset operation and maintenance threshold; If it is not greater than, then the turning control radius is determined as the reference control radius; If it is greater than the threshold, the baseline control radius is determined based on the operation and maintenance threshold and the current turning angle. The operation and maintenance threshold is set as the arc length estimation distance, and the coordinates of the entry point, exit point, and turning center are updated synchronously. Calculate the product of the reference control radius and the preset maximum angular velocity to determine the initial turning linear velocity; The minimum value between the initial turning linear velocity and the preset drone cruise speed is determined as the baseline control linear velocity; Extract data from the drone's operational data to determine the drone's current speed; Input the drone's current speed and the preset drone stability acceleration into the preset braking distance model to determine the redundant braking distance; The sum of redundant braking distance, arc length estimation distance, and preset exit curve extension length is calculated to determine the total length of smooth turning; The analysis of arc length estimation distance, dynamic bending difference, baseline control linear velocity, smooth turning total length, current turning angle, UAV operation data, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates is used to determine the turning control data.

5. The UAV turning control method according to claim 4, characterized in that, The steps to determine the turning control data include analyzing the arc length estimation distance, dynamic bending difference, baseline control linear velocity, smooth turning total length, current turning angle, UAV operation data, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates. Obtain the total length of the inflection point route; Determine whether the total length of a smooth turn is greater than the total length of the inflection point route; If it is not greater than, then the preset maximum acceleration of the drone, the preset acceleration step size of the drone, the reference control linear velocity, the drone operation data and the coordinates of the entry point are input into the preset seven-segment S-curve planning model to determine the braking control data. The baseline control linear velocity, braking control data, current turning angle, baseline control radius, entry point coordinates, exit point coordinates, and turning center coordinates are integrated to determine the turning control data. If it is greater than, the dynamic bending difference, the baseline control line speed, the baseline control radius and the arc length estimated distance are iteratively reduced according to the preset control scaling factor to determine the downward turning data, and the total smooth turning length is iteratively determined according to the downward turning data until the total smooth turning length is not greater than the total length of the inflection point route. Obtain the iterative control linear velocity, iterative control radius, coordinates of the iterative entry point, coordinates of the iterative exit point, and coordinates of the iterative circle center; Input the drone's maximum acceleration, drone acceleration step size, iterative control linear velocity, drone operation data, and iterative curve entry point coordinates into the seven-segment S-curve programming model to determine the braking control data. The iterative control linear velocity, braking control data, current turning angle, iterative control radius, coordinates of the iterative entry point, coordinates of the iterative exit point, and coordinates of the iterative center are integrated to determine the turning control data.

6. A turning control system for unmanned aerial vehicles (UAVs), characterized in that, include: The acquisition module is used to acquire sliding waypoint data, UAV operation data, and bending operation boundaries; A memory for storing a program of a UAV turning control method as described in any one of claims 1 to 5; The processor and the program in the memory can be loaded and executed by the processor to implement the UAV turning control method as described in any one of claims 1 to 5.

7. A smart terminal, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any one of claims 1 to 5 for a UAV turning control method.

8. A computer-readable storage medium, characterized in that, The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1 to 5.

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