Multi-screen display picture control method and system for unmanned aerial vehicle

Abstract

The invention relates to the technical field of multi-screen display, in particular to a multi-screen display picture control method and system for an unmanned aerial vehicle, and the method comprises the following steps: comparing the flight height with an obstacle position parameter according to the flight path planning data of the unmanned aerial vehicle and real-time obstacle information; and performing path segmentation calculation of adjacent areas by combining the speed and the flight direction of the unmanned aerial vehicle, evaluating the minimum safety distance of the obstacle, and outputting a path planning safety coefficient. According to the invention, through multi-parameter dynamic comparison of the flight height, the obstacle position, the speed and the direction, the flexibility of path adjustment and the obstacle avoidance precision are improved, and the dynamic distribution of the flight picture and state information is combined with the view angle switching position parameters, so that efficient distribution of multiple devices is realized; real-time environment data processing is combined with image frame feature extraction and region division scheduling, navigation data priority distribution is optimized, information synchronization is optimized through path overlapping parameters and communication delay, and multi-machine cooperation efficiency and task execution reliability are improved.

Description

Technical Field

[0001] The present invention relates to the field of multi-screen display technology, and in particular to a multi-screen display image control method and system for realizing unmanned aerial vehicle (UAV) display. Background Art

[0002] The field of multi-screen display technology involves methods and systems for providing visual output using multiple display units, and is widely used in various devices and scenarios, including computer workstations, advertising screens, aviation control centers, and drone control systems. Multi-screen display can improve information processing capabilities and the interactivity of the user interface, and effectively enhance the user's operating experience and decision-making efficiency by displaying data or images from multiple perspectives. In drone applications, multi-screen display enables operators to simultaneously monitor the drone's flight status, environmental information, and other key mission indicators, supporting the execution of complex tasks such as search and rescue, geographic mapping, and environmental monitoring.

[0003] Among them, the multi-screen display image control method for realizing UAV is a solution for managing and controlling the image output of UAV on multiple display interfaces, involving hardware design such as the layout and interface of the display screen, and software aspects such as the development of image processing algorithms and user interaction interfaces. Its main purpose is to improve the visibility and flexibility of UAV operations, so that operators can more effectively monitor and control multiple tasks of UAVs, especially when precise operations are required or tasks are performed in visually complex environments, thereby increasing the safety and efficiency of UAV missions, which is very valuable in emergency response and precision operation scenarios.

[0004] The existing technology has a weak ability to comprehensively compare multiple parameters in path planning, making it difficult to quickly complete path adjustments in dynamic and complex environments, resulting in reduced reliability in obstacle avoidance. The multi-screen information display lacks a dynamic distribution mechanism, resulting in insufficient content coordination between display screens. The problem of incoherent information display significantly increases the complexity of task operations. Insufficient power consumption management of display devices limits battery life. The single strategy of refresh rate and brightness adjustment cannot adapt to changes in task scenarios, and energy utilization efficiency is low. The limitation of environmental data processing capabilities makes the display of real-time navigation data in complex scenarios poor, and the priority scheduling lacks refinement, making it difficult to meet the rapid response requirements of multiple tasks. The multi-machine collaborative monitoring mechanism lags in the optimization of path overlapping parameters and information synchronization, and the efficiency of collaborative task execution is low, resulting in frequent problems such as extended task completion time and unstable execution results. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a multi-screen display control method and system for realizing a drone.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for realizing multi-screen display image control of a drone, comprising the following steps: S1: Based on the UAV flight path planning data and real-time obstacle information, the flight altitude is compared with the obstacle position parameters, and the path segmentation calculation of the adjacent areas is performed in combination with the UAV speed and flight direction, the minimum safe distance of the obstacle is evaluated, and the path planning safety factor is output; S2: Based on the path planning safety factor, the flight picture data displayed by the VR head display and the flight status information of the remote controller with screen are allocated, the flight direction, speed and perspective switching position parameters are dynamically distributed and matched, the flight picture is synchronously mapped to the difference display device, and a multi-screen display mapping matrix is ​​generated; S3: Based on the multi-screen display mapping matrix, the remaining battery power of the VR head display and the remote controller with screen is obtained, the refresh rate adjustment range of each display screen is calculated, the screen brightness and image resolution are graded, the display frequency and power output are associated and controlled, and the display dynamic frequency division adjustment parameters are generated; S4: Based on the display dynamic frequency division adjustment parameters, the environmental data collected during the flight of the UAV is processed in real time, the key feature values ​​of the image frame sequence are extracted, and the environmental navigation data display and scheduling are performed in combination with the flight area division to generate the task information priority distribution parameters; S5: Based on the mission information priority distribution parameters, the monitoring parameters of the overlapping intervals of the flight paths are compared with the mission distribution parameters, and the monitoring screen allocation of the multi-machine collaborative mission is performed in combination with the UAV communication delay and data synchronization rate to generate a multi-machine collaborative monitoring allocation plan.

[0007] As a further solution of the present invention, the path planning safety factor includes an obstacle safety distance threshold, a flight path segmentation coefficient and an adjacent area path connection coefficient; the multi-screen display mapping matrix includes a flight picture allocation parameter, a perspective switching matching parameter and a device display synchronization parameter; the display dynamic frequency division adjustment parameter includes a screen refresh rate adjustment amplitude, a screen brightness grading parameter and an image resolution grading parameter; the task information priority distribution parameter includes an image frame sequence eigenvalue distribution parameter, a flight area division priority parameter and an environmental navigation scheduling parameter; the multi-machine collaborative monitoring allocation scheme includes a path overlap interval monitoring parameter, a communication delay allocation parameter and a data synchronization rate distribution parameter.

[0008] As a further solution of the present invention, based on the UAV flight path planning data and real-time obstacle information, the flight altitude is compared with the obstacle position parameters, the path segmentation calculation of the adjacent area is performed in combination with the UAV speed and flight direction, the minimum safe distance of the obstacle is evaluated, and the specific steps of outputting the path planning safety factor are as follows: S111: Based on the UAV flight path planning data, extract the flight path height parameter, analyze the real-time obstacle information and identify the position parameter, compare the spatial range relationship between the flight height parameter and the obstacle position parameter, judge the obstacle interference area, and generate the flight height and obstacle position comparison result; S112: Based on the comparison result of the flight altitude and the obstacle position, the speed parameter of the UAV is called to calculate the displacement range per unit time, and the path change trend of the adjacent area is determined in combination with the flight direction parameter, and the adjustment range of each area of ​​the flight path is calculated in segments, and the path segmentation and dynamic parameter matching result are generated; S113: Based on the path segmentation and dynamic parameter matching results, combined with the segmented path information of the adjacent area, the minimum safe distance of obstacles is evaluated, the altitude parameters of the flight path are matched with the obstacle safety range, the comprehensive safety factor of each path segment is calculated, and the path planning safety factor is output.

[0009] As a further solution of the present invention, based on the path planning safety factor, the flight picture data displayed by the VR head display and the flight status information of the remote controller with screen are allocated, the flight direction, speed and perspective switching position parameters are dynamically distributed and matched, and the flight picture is synchronously mapped to the difference display device. The specific steps of generating a multi-screen display mapping matrix are as follows: S211: based on the path planning safety factor, obtaining flight picture data corresponding to the path, calling speed change and direction change parameters in the flight path in sections, matching distribution parameters of the VR head display range, distributing picture data to the display device in different regions, and generating VR head display picture distribution results; S212: based on the VR head display screen allocation result, extract the display parameters of the remote controller with screen, call the real-time flight direction and speed parameters in the flight status information, compare the parameter distribution of the display status by region, map the flight status information to the remote controller display screen, and generate the flight status mapping result of the remote controller with screen; S213: Based on the flight status mapping result of the remote control with screen, the synchronization parameters of the VR head display screen and the remote control display information are extracted, the perspective switching position parameters and the real-time path display area are matched, the flight path image data and the display device distribution parameters are integrated, and the multi-screen display mapping matrix is ​​output.

[0010] As a further solution of the present invention, based on the multi-screen display mapping matrix, the remaining battery power of the VR head display and the remote controller with screen is obtained, the refresh rate adjustment range of each display screen is calculated, the screen brightness and image resolution are graded, and the display frequency and power output are associated and controlled. The specific steps of generating the display dynamic frequency division adjustment parameters are as follows: S311: Based on the multi-screen display mapping matrix, collect the real-time battery power remaining value parameters of the VR head display and the remote control with screen, synchronously extract the current refresh rate, analyze the correlation between the power status and the refresh rate of each device, calculate the display refresh rate adjustment value, and generate the display refresh rate adjustment result; S312: Based on the display refresh rate adjustment result, extract device screen brightness and image resolution parameters, calculate the power consumption corresponding to the brightness level and resolution in a graded manner, match the remaining power value with the graded brightness and resolution relationship, and generate a display brightness and resolution graded result; S313: Based on the display brightness and resolution grading results, extract the dynamic adjustment range of the display frequency parameter and the power output parameter, calculate the power output requirement according to the refresh rate distribution, associate the matching rules of frequency change and power output, and generate the display dynamic frequency division adjustment parameter.

[0011] As a further solution of the present invention, the display refresh rate adjustment value is according to the formula: ; Calculate, where Indicates the real-time remaining power of the VR headset in percentage, reflecting the current available power of the device. Indicates the real-time remaining power value of the remote control with screen, in percentage, reflecting the current available power of the device. Indicates the current refresh rate of the VR headset, in Hz, reflecting the operating refresh rate status of the device. Indicates the current refresh rate of the remote control with screen, in Hz, reflecting the running refresh rate status of the device. Indicates the final display refresh rate adjustment value in Hz, which is used to optimize the unified refresh rate of the display.

[0012] As a further solution of the present invention, based on the display dynamic frequency division adjustment parameters, the environmental data collected during the flight of the UAV is processed in real time, the key feature values ​​of the image frame sequence are extracted, and the environmental navigation data display scheduling is performed in combination with the flight area division. The specific steps of generating the task information priority distribution parameters are as follows: S411: Based on the display dynamic frequency division adjustment parameter, the environmental data collected during the flight of the UAV is analyzed, the color distribution, edge intensity and motion trajectory information in the image sequence are extracted frame by frame, and the key feature values ​​are screened by matching the dynamic change characteristics of each frame data to generate an image frame feature extraction result; S412: Based on the image frame feature extraction result, the flight area division information is matched, the spatial distribution parameters associated with the area coordinates and dynamic features in the environmental data are called, the environmental feature data is integrated according to the flight area segments, the feature differences and dynamic relationships between the regions are analyzed, and the environmental navigation data distribution results are generated; S413: Based on the environmental navigation data distribution result, extract the environmental change parameters and image feature dynamic values ​​in the flight path, prioritize the task data according to feature importance, map the task priority to the scheduling range of the display device, and generate the task information priority distribution parameters.

[0013] As a further solution of the present invention, based on the task information priority distribution parameters, the monitoring parameters of the overlapping intervals of the flight paths are compared with the task distribution parameters, and the monitoring screen allocation of the multi-machine collaborative tasks is performed in combination with the UAV communication delay and data synchronization rate. The specific steps of generating the multi-machine collaborative monitoring allocation scheme are as follows: S511: Based on the task information priority distribution parameters, extract the monitoring parameters of the overlapping intervals in the flight path, call the regional priority data in the task distribution parameters in sections, analyze the regional matching degree between the monitoring parameters and the task distribution, obtain the corresponding relationship between the overlapping intervals and tasks, and generate the monitoring comparison result of the overlapping intervals of the path; S512: Based on the monitoring and comparison results of the path overlap interval, the communication delay parameters and data synchronization rate parameters between the acquisition machine and the UAV are collected, the impact of the delay on the task handover is calculated, the distribution priority of the communication task is dynamically adjusted, and the multi-machine communication and synchronization matching results are generated; S513: Based on the multi-machine communication and synchronization matching results, extract the screen distribution parameters of the multi-machine collaborative monitoring, match the monitoring screen task priority with the overlapping tasks in the flight path area, allocate the monitoring tasks to the display area of ​​each device, adjust the display screen distribution order, and generate a multi-machine collaborative monitoring allocation plan.

[0014] As a further solution of the present invention, the influence of the delay on task handover is calculated according to the formula ; Calculate, where Indicates the impact magnitude value, Indicates the communication delay between drones in milliseconds, which is collected in real time through the communication protocol delay monitoring module. Indicates the time required for data synchronization between drones, in milliseconds, calculated by the transmission time of the synchronization data packet. Indicates the data synchronization rate in percentage, which is calculated by monitoring the ratio of successfully synchronized data packets to the total transmitted data packets. Indicates the transmission rate of the communication link, in Mbps, obtained through the rate detection of the real-time communication module. Indicates the length of the path overlap interval in meters, which is obtained through geometric calculation of the route planning data.

[0015] A multi-screen display control system for realizing an unmanned aerial vehicle, comprising: The path planning analysis module analyzes real-time obstacle information and identifies location parameters based on the UAV flight path planning data, determines the obstacle interference area, determines the path change trend of the adjacent area based on the flight direction parameters, matches the height parameters of the flight path with the obstacle safety range, and outputs the path planning safety factor; The multi-screen mapping module, based on the path planning safety factor, calls the speed change and direction change parameters in the flight path in sections, compares the parameter distribution of the display state by region, matches the view switching position parameters and the real-time path display area, integrates the flight path image data and the display device distribution parameters, and outputs a multi-screen display mapping matrix; The refresh rate adjustment module analyzes the correlation between the power status and the refresh rate of each device based on the multi-screen display mapping matrix, calculates the display refresh rate adjustment value, matches the power remaining value with the graded brightness and resolution, calculates the power output requirement according to the refresh rate distribution, associates the matching rules of frequency change and power output, and generates the display dynamic frequency division adjustment parameters; The task priority sorting module analyzes the environmental data collected during the flight of the UAV based on the display dynamic frequency division adjustment parameters, matches the dynamic change characteristics of each frame data, screens key feature values, analyzes the feature differences and dynamic relationships between regions, prioritizes the task data according to the feature importance, maps the task priority to the scheduling range of the display device, and generates the task information priority distribution parameters; The task distribution optimization module analyzes the regional matching degree between monitoring parameters and task distribution based on the task information priority distribution parameters, obtains the corresponding relationship between overlapping interval tasks, calculates the impact of delay on task handover, dynamically adjusts the distribution priority of communication tasks, allocates monitoring tasks to the display area of ​​each device, adjusts the distribution order of display screens, and generates a multi-machine collaborative monitoring allocation plan.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, the flexibility of path adjustment and the accuracy of obstacle avoidance are improved through dynamic comparison of multiple parameters such as flight altitude, obstacle position, speed and direction. The dynamic distribution of flight pictures and status information is combined with the perspective switching position parameters to achieve efficient allocation of multiple devices. Real-time environmental data processing is combined with image frame feature extraction and area division scheduling to optimize the priority distribution of navigation data. Information synchronization is optimized through path overlap parameters and communication delays to improve multi-machine collaboration efficiency and task execution reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the steps of the present invention; Figure 2 is a flow chart of the steps of S1 of the present invention; Figure 3is a flow chart of the steps of S2 of the present invention; Figure 4 is a flow chart of the steps of S3 of the present invention; Figure 5 is a flow chart of the steps of S4 of the present invention; Figure 6 is a flow chart of the steps of S5 of the present invention; Figure 7 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0020] See also Figure 1 , a method for realizing a multi-screen display image control method of a drone, comprising the following steps: S1: Based on the UAV flight path planning data and real-time obstacle information, the flight altitude is compared with the obstacle position parameters, and the path segmentation calculation of the adjacent areas is performed in combination with the UAV speed and flight direction, the minimum safe distance of the obstacle is evaluated, and the path planning safety factor is output; S2: Based on the path planning safety factor, the flight picture data displayed by the VR headset and the flight status information of the remote controller with screen are allocated, the flight direction, speed and perspective switching position parameters are dynamically distributed and matched, the flight picture is synchronously mapped to the difference display device, and a multi-screen display mapping matrix is ​​generated; S3: Based on the multi-screen display mapping matrix, obtain the remaining battery power of the VR headset and the remote controller with screen, calculate the refresh rate adjustment range of each display screen, perform graded processing on the screen brightness and image resolution, perform correlation control on the display frequency and power output, and generate display dynamic frequency division adjustment parameters; S4: Based on the display dynamic frequency division adjustment parameters, the environmental data collected during the flight of the UAV is processed in real time, the key feature values ​​of the image frame sequence are extracted, the display scheduling of the environmental navigation data is performed in combination with the flight area division, and the task information priority distribution parameters are generated; S5: Based on the priority distribution parameters of the mission information, the monitoring parameters of the overlapping intervals of the flight paths are compared with the mission distribution parameters. Combined with the communication delay and data synchronization rate between UAVs, the monitoring screen allocation of the multi-machine collaborative mission is performed to generate a multi-machine collaborative monitoring allocation plan.

[0021] The path planning safety factor includes the obstacle safety distance threshold, the flight path segmentation coefficient and the adjacent area path connection coefficient. The multi-screen display mapping matrix includes the flight screen allocation parameters, the perspective switching matching parameters and the device display synchronization parameters. The display dynamic frequency division adjustment parameters include the screen refresh rate adjustment range, the screen brightness grading parameters and the image resolution grading parameters. The task information priority distribution parameters include the image frame sequence eigenvalue distribution parameters, the flight area division priority parameters and the environmental navigation scheduling parameters. The multi-machine collaborative monitoring allocation scheme includes the path overlapping interval monitoring parameters, the communication delay allocation parameters and the data synchronization rate distribution parameters.

[0022] See also Figure 2 , the specific steps of S1 are: S111: Based on the UAV flight path planning data, extract the flight path height parameter, analyze the real-time obstacle information and identify the position parameter, compare the spatial range relationship between the flight height parameter and the obstacle position parameter, judge the obstacle interference area, and generate the flight height and obstacle position comparison result; Based on the UAV flight path planning data, the altitude information of the flight path is first recorded in real time through the altitude sensor installed on the UAV, and these data are segmented according to the time axis. The altitude parameter at each time point will be compared with the standard flight altitude in the path planning, and the flight altitude range on the path will be obtained through the segmented statistical method. Then, environmental detection equipment, such as laser rangefinders and cameras, are used to scan the surrounding obstacles in real time. The location information of the obstacles will be recorded in the form of three-dimensional coordinates, including the distance, angle and height of the obstacles. The recorded three-dimensional location information is compared with the flight altitude data of the UAV to calculate the interference area range in the flight path. The interference area is determined by judging whether the area where the UAV's flight altitude is located is covered by the height, width and depth range of the obstacle. Finally, the comparison results are recorded, including the coordinate range of all affected areas in the flight path, the degree of interference and other information, as the basic data for flight path adjustment.

[0023] S112: Based on the comparison results of the flight altitude and the obstacle position, the speed parameter of the drone is called to calculate the displacement range per unit time, and the path change trend of the adjacent area is determined in combination with the flight direction parameter, and the adjustment range of each area of ​​the flight path is calculated in segments to generate the path segmentation and dynamic parameter matching results; Based on the comparison results of flight altitude and obstacle position, the possibility of dynamic adjustment of the path is further analyzed. First, the obstacle area in the comparison result is segmented and sorted, and the obstacle position information is combined with the current speed and flight direction of the UAV. The speed sensor of the UAV is used to record the speed data second by second, and the displacement range per unit time is calculated through the time interval. Then, based on the flight direction, the change trend of the path is analyzed. Each path segment will determine its adjustable spatial range according to the flight altitude and displacement range. Specifically, through the detection of real-time displacement range, the possible offset angle and height change value of the path segment are calculated. At the same time, the overlap between the area after path adjustment and the obstacle is recorded, and the feasibility of each segmented path adjustment is determined in turn. The direction, amplitude and spatial position of the path adjustment are recorded, and all adjusted area data are saved one by one. A detailed record of the matching of each segmented path with the dynamic adjustment parameters is generated to facilitate subsequent comprehensive analysis and path optimization.

[0024] S113: Based on the path segmentation and dynamic parameter matching results, combined with the segmented path information of the adjacent area, the minimum safe distance of obstacles is evaluated, the altitude parameters of the flight path are matched with the obstacle safety range, the comprehensive safety factor of each path segment is calculated, and the path planning safety factor is output; Based on the results of path segmentation and dynamic parameter matching, a detailed assessment of the minimum safe distance of obstacles is started. During the assessment process, real-time measured data is needed to calculate the shortest distance from each obstacle to the UAV path. The calculation method uses spatial geometry formulas to analyze the spatial distance between the three-dimensional position coordinates of the obstacle and the current position of the UAV in the path, and compares the distance value with the safety threshold. At the same time, the size of the obstacle is measured, and the width, height and depth data of the obstacle are combined with the flight path of the UAV to calculate the maximum range that the UAV may touch the obstacle. For each segmented path, the shortest distance to the obstacle is recorded, and it is checked whether the safety range is met. Finally, the segmented path is combined with the safety factor for analysis. By comprehensively evaluating the overall safety of the path, the safety assessment value of the path is output, the global safety assessment of the path planning is completed, and the risk level of each path is recorded to guide subsequent flight path planning adjustments and optimizations.

[0025] See also Figure 3 , the specific steps of S2 are: S211: based on the path planning safety factor, obtaining the flight picture data corresponding to the path, calling the speed change and direction change parameters in the flight path in sections, matching the distribution parameters of the VR head display range, distributing the picture data to the display device in different regions, and generating the VR head display picture distribution result; Based on the path planning safety factor, the image data corresponding to the flight path is obtained. First, the path planning safety factor is matched with the flight path segment. The safety factor value of each segment is extracted from the path planning data and marked on the corresponding flight path. At the same time, the real-time camera equipment of the drone collects the image data during flight, and the image is cut and sorted according to the path segment. Each segment of the image data will be stored in association with the path height and safety factor information. Then, the flight image data is displayed and adapted, and the image resolution and the display range of the VR headset are measured to determine the specific proportion of the image data that can be correctly distributed in the display device. Each segment of the image data is cropped or expanded to the resolution and range that meets the display area in turn, and the display priority and distribution area of ​​the image are adjusted according to the real-time parameters of the flight speed change and direction change to ensure the dynamic and accuracy of the display, and finally generate the distribution result of the flight path image in the VR headset.

[0026] S212: Based on the VR head display screen allocation result, extract the display parameters of the remote controller with screen, call the real-time flight direction and speed parameters in the flight status information, compare the parameter distribution of the display status by region, map the flight status information to the remote controller display screen, and generate the flight status mapping result of the remote controller with screen; Based on the VR head display screen allocation results, the display parameters of the remote control with screen are extracted, including the size, resolution, refresh rate and other physical characteristics of the remote control screen. At the same time, real-time flight speed and direction information are obtained from the flight status data. The data of each path segment are sorted in turn, and the display parameters of the remote control are associated with the flight status data. By measuring the range of flight status information (such as speed change range, direction angle change range, etc.), the display content distribution in each area is calculated, and the flight speed and direction data are proportionally mapped to different positions in the display area of ​​the screen. The mapping ratio is adjusted so that the information can completely cover the screen display range, and the text and graphic ratios of the display content are fine-tuned to ensure its clear presentation on the remote control display screen. Finally, the flight status mapping result of the remote control with screen is generated, and the flight status display content corresponding to each segmented path is recorded.

[0027] S213: Based on the flight status mapping result of the remote controller with screen, the synchronization parameters of the VR head display screen and the remote controller display information are extracted, the view switching position parameters and the real-time path display area are matched, the flight path screen data and the display device distribution parameters are integrated, and the multi-screen display mapping matrix is ​​output; Based on the flight status mapping results of the remote control with screen, the synchronization data of the VR headset screen and the remote control display information are further extracted, the time synchronization relationship of the display content between the two devices is analyzed, the flight path screen data and the regional parameters involved in the display information are compared and sorted respectively, and the adjustment range of each path screen during the perspective change process is determined by reading the perspective switching parameters, and different screen content distribution areas are divided according to the real-time flight path display area when the perspective is switched. The display area of ​​the VR headset and the size and resolution of the remote control display are compared, and the display coverage of different display devices is calculated. The flight path screen data is integrated according to the device distribution parameters in turn to generate a screen distribution matrix that can be displayed on multiple display devices simultaneously, ensuring that the two display devices can maintain consistency in display content, and finally output a multi-screen display mapping matrix to meet the needs of synchronous display.

[0028] See also Figure 4 , the specific steps of S3 are: S311: Based on the multi-screen display mapping matrix, collect the real-time battery power remaining value parameters of the VR head display and the remote control with screen, synchronously extract the current refresh rate, analyze the correlation between the power status and the refresh rate of each device, calculate the display refresh rate adjustment value, and generate the display refresh rate adjustment result; Display refresh rate adjustment value, according to the formula: ; Calculate, where Indicates the real-time remaining power of the VR headset in percentage, reflecting the current available power of the device. Indicates the real-time remaining power value of the remote control with screen, in percentage, reflecting the current available power of the device. Indicates the current refresh rate of the VR headset, in Hz, reflecting the operating refresh rate status of the device. Indicates the current refresh rate of the remote control with screen, in Hz, reflecting the running refresh rate status of the device. Indicates the final display refresh rate adjustment value in Hz, which is used to optimize the unified refresh rate of the display.

[0029] Indicates the real-time remaining power value of the VR headset in percentage. The remaining power value is obtained by monitoring the real-time battery parameters of the VR headset. The current power value is 76% as detected by the device power management module.

[0030] Indicates the real-time remaining power of the remote controller with screen in percentage. By monitoring the remote controller battery management system, the current power is 54%.

[0031] Indicates the current refresh rate of the VR headset in Hz. Get real-time refresh rate data through the display refresh rate detection system of the VR device, and the current refresh rate is 90Hz.

[0032] Indicates the current refresh rate of the remote controller with screen, in Hz. Obtain the refresh rate data through the display refresh rate monitoring module of the remote controller, and obtain the current refresh rate as 60Hz.

[0033] Substitute the known parameters into the formula: ; Calculate the square of the difference between power and refresh rate: ; ; Substituting the square of the difference into the formula: ; Compute the sum and mean of squared differences: ; ; Calculate the square root: ; The results show that the adjusted display refresh rate should be 10.77Hz. Since this value represents the balanced adjustment between device power and refresh rate, it is necessary to use this value as a reference to coordinate the display refresh rate adjustment of VR headsets and remote controllers with screens. The calculation results show that by synchronizing the differences in device power and refresh rate, the refresh rate matching status of multiple devices can be effectively optimized, thereby achieving a smoother multi-screen display experience.

[0034] S312: Based on the display refresh rate adjustment result, extract the device screen brightness and image resolution parameters, calculate the power consumption corresponding to the brightness level and resolution in a graded manner, match the remaining power value with the graded brightness and resolution relationship, and generate a display brightness and resolution graded result; Based on the display refresh rate adjustment result, the screen brightness and image resolution parameters of the device are further extracted, and the brightness data of the device is divided into several levels according to the actual measured value, such as minimum brightness, medium brightness and maximum brightness, and the image resolution of the device is graded according to different display modes, such as low resolution, medium resolution and high-definition resolution. Then, the combination of brightness and resolution is adjusted one by one, and the power consumption of the device under each combination is measured. The specific steps include fixing the screen brightness at a certain level, measuring the power drop rate of low, medium and high resolution in turn, and recording the power consumption value corresponding to the brightness and resolution combination. Thereafter, each power state in the refresh rate adjustment result is associated with the combination of brightness and resolution, and by generating a table of the relationship between the remaining power value and brightness and resolution, the recommended brightness and resolution combination under different power states is analyzed, and finally the display brightness and resolution grading results are generated and organized into a clear matching relationship.

[0035] S313: extracting the dynamic adjustment range of the display frequency parameter and the power output parameter based on the display brightness and resolution classification results, calculating the power output requirement according to the refresh rate distribution, associating the matching rules of the frequency change and the power output, and generating the display dynamic frequency division adjustment parameter; Based on the display brightness and resolution grading results, the dynamic adjustment frequency range of the device display is extracted and divided into low-frequency intervals, medium-frequency intervals and high-frequency intervals, and the time intervals and display conditions corresponding to the frequency changes are recorded. At the same time, the actual measured values ​​of the power output parameters are extracted, and the dynamic association between power output and frequency range is divided into multiple intervals, such as low-frequency intervals corresponding to lower power output, medium-frequency intervals corresponding to medium power output, etc. The specific operations include: measuring the instantaneous value of the device power output for different frequency intervals, calculating the matching rules between the power change range and the frequency change range, and organizing these rules into dynamic adjustment suggestions corresponding to power and frequency. Combined with the current display conditions of the device, the power output required for the current display is calculated according to the distribution of the refresh rate, and the display dynamic frequency division adjustment suggestions of the device are recorded as a parameter table, clarifying the power output requirements and adjustment range of each frequency interval, completing the generation of the display dynamic frequency division adjustment parameters and synchronizing them to the relevant records.

[0036] See also Figure 5 , the specific steps of S4 are: S411: Based on the display dynamic frequency division adjustment parameters, the environmental data collected during the flight of the UAV is analyzed, and the color distribution, edge intensity and motion trajectory information in the image sequence are extracted frame by frame. By matching the dynamic change characteristics of each frame data, the key feature values ​​are screened to generate the image frame feature extraction results; Based on the display dynamic frequency division adjustment parameters, the environmental data collected in real time during the flight of the drone is first analyzed, and the image sequence in the flight video is extracted frame by frame as an image file. Each frame of the image is analyzed and gradually decomposed into pixel units. By analyzing the pixel color values, the distribution ratio of different colors in the image is statistically analyzed, and the coverage range of the main colors is marked. Next, the edge intensity information in the frame is detected using an image processing device. By calculating the change in the pixel brightness gradient point by point, the areas with obvious edges in the image are identified, and the intensity values ​​and position coordinates of these areas are recorded. At the same time, the motion trajectory of the object in the picture is analyzed according to the continuous changes between frames, and the starting point, direction and displacement of the motion trajectory are extracted. The information of color distribution, edge intensity and motion trajectory is saved and compared respectively, and frames with obvious changes or characteristic significance are selected and marked as key frames. The characteristic values ​​of each frame are recorded in detail, and finally the image frame feature extraction results are generated.

[0037] S412: Based on the image frame feature extraction result, the flight area division information is matched, the spatial distribution parameters associated with the area coordinates and dynamic features in the environmental data are called, the environmental feature data is integrated according to the flight area segments, the feature differences and dynamic relationships between the regions are analyzed, and the distribution results of the environmental navigation data are generated; Based on the feature extraction results of the image frame, the extracted color distribution, edge intensity and motion trajectory data are associated with the division information of the flight area. First, the spatial coordinate range of the flight area is analyzed, the flight path of the drone is divided into regions, and each region is marked in three-dimensional space. Then, the feature data of each frame is regionally classified, and the feature values ​​corresponding to the image frame are matched with the regional coordinates according to the spatial position of the object in the image. By comparing the distribution of feature values ​​in different regions, the differences in color, edge and motion trajectory of each region are gradually analyzed, and the feature change amplitude and direction between regions are recorded. At the same time, the degree of association between regions is calculated according to the dynamic change characteristics of the feature values, and the dynamic relationship between regions is summarized. Finally, the environmental feature data of all flight areas are integrated to generate the distribution results of environmental navigation data including dynamic feature association and regional feature differences, and a detailed description of the features of each region is recorded.

[0038] S413: based on the distribution result of the environmental navigation data, extract the environmental change parameters and image feature dynamic values ​​in the flight path, prioritize the task data according to the feature importance, map the task priority to the scheduling range of the display device, and generate the task information priority distribution parameter; Based on the distribution results of environmental navigation data, the environmental change parameters and dynamic values ​​of image features recorded in the flight path are extracted, and the environmental parameters and image feature values ​​are sorted into a list and sorted according to their change amplitude and frequency of occurrence. First, the dynamic change data of each area in the flight path is extracted, and the color distribution, edge intensity and motion trajectory parameters of each area are analyzed item by item, the change amount and fluctuation amplitude of the parameters at different times are calculated, and the parameters with larger changes are marked as high priority. Then, according to the priority sorting results and the real-time needs of the UAV flight mission, the task priority is mapped to the scheduling range of the display device, and the high-priority task data is mapped to the main display device or the main display range. The tasks with medium and low priorities are assigned to the secondary display area. At the same time, the priority level of each task data and the display device allocation results are recorded, and finally the task information priority distribution parameters are generated, and detailed task scheduling range records are sorted out.

[0039] See also Figure 6 , the specific steps of S5 are: S511: Based on the task information priority distribution parameters, the monitoring parameters of the overlapping intervals in the flight path are extracted, the regional priority data in the task distribution parameters are called in sections, the regional matching degree between the monitoring parameters and the task distribution is analyzed, the corresponding relationship between the overlapping interval tasks is obtained, and the monitoring comparison result of the path overlapping interval is generated; Based on the task information priority distribution parameters, the specific data of the overlapping intervals in the UAV flight path are first analyzed, and the path is marked section by section according to the time period and spatial position. The start time, end time and corresponding spatial range of each overlapping interval are marked in detail. At the same time, the monitoring parameters in the overlapping area are extracted. These parameters include flight altitude, speed, direction change and real-time environmental characteristics in the task area, such as temperature, humidity and light intensity. Then, the regional priority of each task is read from the task information priority distribution parameters, and the monitoring parameters in the overlapping interval are compared with the task priority data one by one. Each task is scored according to the matching degree. The specific process is to record the degree of fit between the variation range of the monitoring parameters in the overlapping area and the task requirements, calculate the matching level of each task in different areas, and generate a priority ranking table of the task area based on these matching levels. Finally, the corresponding relationship of the tasks in the overlapping interval is summarized to form the monitoring comparison result of the path overlapping interval.

[0040] S512: Based on the monitoring and comparison results of the path overlap interval, the communication delay parameters and data synchronization rate parameters between the acquisition machine and the UAV are collected, the impact of the delay on the task handover is calculated, the distribution priority of the communication task is dynamically adjusted, and the multi-machine communication and synchronization matching results are generated; The impact of delay on task handover is calculated according to the formula ; Calculate, where Indicates the impact magnitude value, Indicates the communication delay between drones in milliseconds, which is collected in real time through the communication protocol delay monitoring module. Indicates the time required for data synchronization between drones, in milliseconds, calculated by the transmission time of the synchronization data packet. Indicates the data synchronization rate in percentage, which is calculated by monitoring the ratio of successfully synchronized data packets to the total transmitted data packets. Indicates the transmission rate of the communication link, in Mbps, obtained through the rate detection of the real-time communication module. Indicates the length of the path overlap interval in meters, which is obtained through geometric calculation of the route planning data.

[0041] The value is obtained by monitoring the communication protocol delay between drones. For example, the communication delay measured in the test environment is 40 milliseconds.

[0042] The value is calculated by calculating the time required for the drone to complete data synchronization. For example, the monitoring synchronization data packet takes 25 milliseconds.

[0043] The value is calculated by counting the number of packets that are successfully synchronized out of the total number of packets transmitted. For example, if 450 of the 500 packets transmitted are successfully synchronized, the synchronization rate is calculated as .

[0044] The value is obtained by detecting the transmission rate of the communication link in real time, for example, the current rate is 10 Mbps.

[0045] The value is the length of the path overlap interval calculated by geometry. For example, the path overlap length calculated by route data is 500 meters.

[0046] Enter specific parameters: ; Calculate the absolute value of the communication delay and synchronization time difference: ; Calculate the square root of the product of the data synchronization rate and the communication rate: ; Compute the sum of the numerators: ; Calculate the final result: ; The calculation result of the task handover impact amplitude is 0.09, which indicates the actual impact of communication delay on task handover. The lower impact amplitude value indicates that the current communication and data synchronization efficiency is high, and the dynamic communication synchronization optimization algorithm can further adjust the task priority and improve the overall task coordination efficiency.

[0047] S513: Based on the multi-machine communication and synchronization matching results, extract the screen distribution parameters of the multi-machine collaborative monitoring, match the monitoring screen task priority with the overlapping tasks in the flight path area, allocate the monitoring tasks to the display area of ​​each device, adjust the display screen distribution order, and generate a multi-machine collaborative monitoring allocation plan; Based on the results of multi-machine communication and synchronization matching, the distribution parameters of the multi-machine collaborative monitoring screen are further extracted, and each part of the monitoring screen is marked as an area with high, medium, and low task priority, and the display content of each area is classified in detail. First, the overlapping tasks in the flight path are extracted, and the display area of ​​the screen is matched according to the priority, and the display proportion of each monitoring screen on the screen is measured. According to the task priority, the monitoring screen of the high-priority task is arranged in the main display area to ensure that the drone operator can observe the real-time information of important tasks first. At the same time, the distribution order of each monitoring screen in different display screens is measured, and the display order of the medium and low priority task screens is adjusted so that they are arranged in sequence without affecting the high-priority monitoring screen. The corresponding relationship between the distribution order of all monitoring screens and the task display area is recorded, and finally a multi-machine collaborative monitoring allocation plan is generated to clarify the display area of ​​each device and the allocation content of the task screen.

[0048] See also Figure 7 , a multi-screen display control system for realizing an unmanned aerial vehicle, comprising: The path planning analysis module analyzes real-time obstacle information and identifies location parameters based on the UAV flight path planning data, determines the obstacle interference area, determines the path change trend of the adjacent area based on the flight direction parameters, matches the height parameters of the flight path with the obstacle safety range, and outputs the path planning safety factor; The multi-screen mapping module uses the speed change and direction change parameters in the flight path in sections based on the path planning safety factor, compares the parameter distribution of the display status by region, matches the view switching position parameters and the real-time path display area, integrates the flight path image data and the display device distribution parameters, and outputs the multi-screen display mapping matrix; The refresh rate adjustment module analyzes the relationship between the power status and refresh rate of each device based on the multi-screen display mapping matrix, calculates the display refresh rate adjustment value, matches the remaining power value with the graded brightness and resolution, calculates the power output demand according to the refresh rate distribution, associates the matching rules of frequency change and power output, and generates the display dynamic frequency division adjustment parameters; The task priority sorting module is based on the display dynamic frequency division adjustment parameters, analyzes the environmental data collected during the flight of the drone, matches the dynamic change characteristics of each frame data, screens key feature values, analyzes the feature differences and dynamic relationships between regions, prioritizes the task data according to the feature importance, maps the task priority to the scheduling range of the display device, and generates the task information priority distribution parameters; The task distribution optimization module analyzes the regional matching degree between monitoring parameters and task distribution based on the task information priority distribution parameters, obtains the corresponding relationship between overlapping interval tasks, calculates the impact of delay on task handover, dynamically adjusts the distribution priority of communication tasks, allocates monitoring tasks to the display area of ​​each device, adjusts the distribution order of display screens, and generates a multi-machine collaborative monitoring distribution plan.

[0049] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for realizing multi-screen display control of an unmanned aerial vehicle, characterized in that: The following steps are involved: S1: Based on the UAV flight path planning data and real-time obstacle information, the flight altitude is compared with the obstacle position parameters, and the path segmentation calculation of the adjacent areas is performed in combination with the UAV speed and flight direction, the minimum safe distance of the obstacle is evaluated, and the path planning safety factor is output; S2: Based on the path planning safety factor, the flight picture data displayed by the VR head display and the flight status information of the remote controller with screen are allocated, the flight direction, speed and perspective switching position parameters are dynamically distributed and matched, the flight picture is synchronously mapped to the difference display device, and a multi-screen display mapping matrix is ​​generated; S3: Based on the multi-screen display mapping matrix, the remaining battery power of the VR head display and the remote controller with screen is obtained, the refresh rate adjustment range of each display screen is calculated, the screen brightness and image resolution are graded, the display frequency and power output are associated and controlled, and the display dynamic frequency division adjustment parameters are generated; S4: Based on the display dynamic frequency division adjustment parameters, the environmental data collected during the flight of the UAV is processed in real time, the key feature values ​​of the image frame sequence are extracted, and the environmental navigation data display and scheduling are performed in combination with the flight area division to generate the task information priority distribution parameters; S5: Based on the mission information priority distribution parameters, the monitoring parameters of the overlapping intervals of the flight paths are compared with the mission distribution parameters, and the monitoring screen allocation of the multi-machine collaborative mission is performed in combination with the UAV communication delay and data synchronization rate to generate a multi-machine collaborative monitoring allocation plan.

2. The method for realizing multi-screen display image control of a drone according to claim 1, characterized in that: The path planning safety factor includes an obstacle safety distance threshold, a flight path segmentation coefficient and an adjacent area path connection coefficient; the multi-screen display mapping matrix includes a flight picture allocation parameter, a perspective switching matching parameter and a device display synchronization parameter; the display dynamic frequency division adjustment parameter includes a screen refresh rate adjustment amplitude, a screen brightness grading parameter and an image resolution grading parameter; the task information priority distribution parameter includes an image frame sequence eigenvalue distribution parameter, a flight area division priority parameter and an environmental navigation scheduling parameter; the multi-machine collaborative monitoring allocation scheme includes a path overlap interval monitoring parameter, a communication delay allocation parameter and a data synchronization rate distribution parameter.

3. The method for realizing multi-screen display image control of a drone according to claim 1, characterized in that: According to the UAV flight path planning data and real-time obstacle information, the flight altitude is compared with the obstacle position parameters, and the path segmentation calculation of the adjacent area is performed in combination with the UAV speed and flight direction to evaluate the minimum safe distance of the obstacle. The specific steps for outputting the path planning safety factor are as follows: S111: Based on the UAV flight path planning data, extract the flight path height parameter, analyze the real-time obstacle information and identify the position parameter, compare the spatial range relationship between the flight height parameter and the obstacle position parameter, judge the obstacle interference area, and generate the flight height and obstacle position comparison result; S112: Based on the comparison result of the flight altitude and the obstacle position, the speed parameter of the UAV is called to calculate the displacement range per unit time, and the path change trend of the adjacent area is determined in combination with the flight direction parameter, and the adjustment range of each area of ​​the flight path is calculated in segments, and the path segmentation and dynamic parameter matching result are generated; S113: Based on the path segmentation and dynamic parameter matching results, combined with the segmented path information of the adjacent area, the minimum safe distance of obstacles is evaluated, the altitude parameters of the flight path are matched with the obstacle safety range, the comprehensive safety factor of each path segment is calculated, and the path planning safety factor is output.

4. The method for realizing multi-screen display image control of a drone according to claim 1, characterized in that: Based on the path planning safety factor, the flight picture data displayed by the VR head display and the flight status information of the remote controller with screen are allocated, the flight direction, speed and perspective switching position parameters are dynamically distributed and matched, and the flight picture is synchronously mapped to the difference display device. The specific steps of generating a multi-screen display mapping matrix are as follows: S211: based on the path planning safety factor, obtaining flight picture data corresponding to the path, calling speed change and direction change parameters in the flight path in sections, matching distribution parameters of the VR head display range, distributing picture data to the display device in different regions, and generating VR head display picture distribution results; S212: based on the VR head display screen allocation result, extract the display parameters of the remote controller with screen, call the real-time flight direction and speed parameters in the flight status information, compare the parameter distribution of the display status by region, map the flight status information to the remote controller display screen, and generate the flight status mapping result of the remote controller with screen; S213: Based on the flight status mapping result of the remote control with screen, the synchronization parameters of the VR head display screen and the remote control display information are extracted, the perspective switching position parameters and the real-time path display area are matched, the flight path image data and the display device distribution parameters are integrated, and the multi-screen display mapping matrix is ​​output.

5. The method for realizing multi-screen display image control of a drone according to claim 1, characterized in that: Based on the multi-screen display mapping matrix, the remaining battery power of the VR head display and the remote controller with screen is obtained, the refresh rate adjustment range of each display screen is calculated, the screen brightness and image resolution are graded, and the display frequency and power output are associated and controlled to generate the display dynamic frequency division adjustment parameters. The specific steps are: S311: Based on the multi-screen display mapping matrix, collect the real-time battery power remaining value parameters of the VR head display and the remote control with screen, synchronously extract the current refresh rate, analyze the correlation between the power status and the refresh rate of each device, calculate the display refresh rate adjustment value, and generate the display refresh rate adjustment result; S312: Based on the display refresh rate adjustment result, extract device screen brightness and image resolution parameters, calculate the power consumption corresponding to the brightness level and resolution in a graded manner, match the remaining power value with the graded brightness and resolution relationship, and generate a display brightness and resolution graded result; S313: Based on the display brightness and resolution grading results, extract the dynamic adjustment range of the display frequency parameter and the power output parameter, calculate the power output requirement according to the refresh rate distribution, associate the matching rules of frequency change and power output, and generate the display dynamic frequency division adjustment parameter.

6. The method for realizing multi-screen display control of a drone according to claim 5, characterized in that: The display refresh rate adjustment value is based on the formula: ； Calculate, where Indicates the real-time remaining power value of the VR headset. Indicates the real-time remaining power value of the remote controller with screen. Indicates the current refresh rate of the VR headset. Indicates the current refresh rate of the remote controller with screen. Indicates the final display refresh rate adjustment value.

7. The method for controlling a multi-screen display of an unmanned aerial vehicle according to claim 1, characterized in that: Based on the display dynamic frequency division adjustment parameters, the environmental data collected during the flight of the UAV is processed in real time, the key feature values ​​of the image frame sequence are extracted, and the environmental navigation data display and scheduling are performed in combination with the flight area division. The specific steps of generating the priority distribution parameters of the task information are as follows: S411: Based on the display dynamic frequency division adjustment parameter, the environmental data collected during the flight of the UAV is analyzed, the color distribution, edge intensity and motion trajectory information in the image sequence are extracted frame by frame, and the key feature values ​​are screened by matching the dynamic change characteristics of each frame data to generate an image frame feature extraction result; S412: Based on the image frame feature extraction result, the flight area division information is matched, the spatial distribution parameters associated with the area coordinates and dynamic features in the environmental data are called, the environmental feature data is integrated according to the flight area segments, the feature differences and dynamic relationships between the regions are analyzed, and the environmental navigation data distribution results are generated; S413: Based on the environmental navigation data distribution result, extract the environmental change parameters and image feature dynamic values ​​in the flight path, prioritize the task data according to feature importance, map the task priority to the scheduling range of the display device, and generate the task information priority distribution parameters.

8. The method for controlling a multi-screen display of an unmanned aerial vehicle according to claim 1, characterized in that: Based on the mission information priority distribution parameters, the monitoring parameters of the overlapping intervals of the flight paths are compared with the mission distribution parameters. Combined with the UAV communication delay and data synchronization rate, the monitoring screen allocation of the multi-machine collaborative mission is performed. The specific steps for generating the multi-machine collaborative monitoring allocation scheme are as follows: S511: Based on the task information priority distribution parameters, extract the monitoring parameters of the overlapping intervals in the flight path, call the regional priority data in the task distribution parameters in sections, analyze the regional matching degree between the monitoring parameters and the task distribution, obtain the corresponding relationship between the overlapping intervals and tasks, and generate the monitoring comparison result of the overlapping intervals of the path; S512: Based on the monitoring and comparison results of the path overlap interval, the communication delay parameters and data synchronization rate parameters between the acquisition machine and the UAV are collected, the impact of the delay on the task handover is calculated, the distribution priority of the communication task is dynamically adjusted, and the multi-machine communication and synchronization matching results are generated; S513: Based on the multi-machine communication and synchronization matching results, extract the screen distribution parameters of the multi-machine collaborative monitoring, match the monitoring screen task priority with the overlapping tasks in the flight path area, allocate the monitoring tasks to the display area of ​​each device, adjust the display screen distribution order, and generate a multi-machine collaborative monitoring allocation plan.

9. The method for realizing multi-screen display image control of a drone according to claim 8, characterized in that: The impact of the delay on task handover is calculated according to the formula ； Calculate, where Indicates the impact magnitude value, represents the communication delay between drones, Indicates the time required for data synchronization between drones. Indicates the data synchronization rate, Indicates the transmission rate of the communication link, Indicates the length of the path overlap interval.

10. A multi-screen display control system for realizing an unmanned aerial vehicle, characterized in that: According to any one of claims 1 to 9, the method for realizing multi-screen display image control of a drone comprises: The path planning analysis module analyzes real-time obstacle information and identifies location parameters based on the UAV flight path planning data, determines the obstacle interference area, determines the path change trend of the adjacent area based on the flight direction parameters, matches the height parameters of the flight path with the obstacle safety range, and outputs the path planning safety factor; The multi-screen mapping module, based on the path planning safety factor, calls the speed change and direction change parameters in the flight path in sections, compares the parameter distribution of the display state by region, matches the view switching position parameters and the real-time path display area, integrates the flight path image data and the display device distribution parameters, and outputs a multi-screen display mapping matrix; The refresh rate adjustment module analyzes the correlation between the power status and the refresh rate of each device based on the multi-screen display mapping matrix, calculates the display refresh rate adjustment value, matches the power remaining value with the graded brightness and resolution, calculates the power output requirement according to the refresh rate distribution, associates the matching rules of frequency change and power output, and generates the display dynamic frequency division adjustment parameters; The task priority sorting module analyzes the environmental data collected during the flight of the UAV based on the display dynamic frequency division adjustment parameters, matches the dynamic change characteristics of each frame data, screens key feature values, analyzes the feature differences and dynamic relationships between regions, prioritizes the task data according to the feature importance, maps the task priority to the scheduling range of the display device, and generates the task information priority distribution parameters; The task distribution optimization module analyzes the regional matching degree between monitoring parameters and task distribution based on the task information priority distribution parameters, obtains the corresponding relationship between overlapping interval tasks, calculates the impact of delay on task handover, dynamically adjusts the distribution priority of communication tasks, allocates monitoring tasks to the display area of ​​each device, adjusts the distribution order of display screens, and generates a multi-machine collaborative monitoring allocation plan.

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