Low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning

Abstract

The invention relates to the technical field of unmanned aerial vehicle interaction, in particular to a low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning. The full-fusion low-altitude unmanned aerial vehicle management and control system comprises a model building module, an acquisition module, a data transmission module, a calculation module, an analysis module and an instruction control module, the model building module accurately builds a digital twin virtual model according to entity unmanned aerial vehicle parameters and a force action principle, and the acquisition module periodically acquires unmanned aerial vehicle information and transmits the unmanned aerial vehicle information to the instruction control module. The data transmission module transmits the data to the calculation module for processing, the analysis module evaluates the simulation degree according to a result and sends an adjustment instruction, and the instruction control module optimizes a positioning difference value and a data compression ratio or sends a notification accordingly. According to the method, the real-time simulation precision of the system is remarkably improved, and the high consistency of the three-dimensional model and the actual scene is ensured, so that a more scientific and accurate basis is provided for the low-altitude unmanned aerial vehicle management and control decision, and the reliability and effectiveness of the decision are effectively enhanced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle interaction, and particularly relates to a low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning. BACKGROUND

[0002] In the current era, the use of unmanned aerial vehicles is becoming increasingly diverse, and their presence has been widely seen in military reconnaissance, logistics transportation, environmental monitoring, emergency rescue and many other fields. With their outstanding flexibility, efficiency and significant cost-effectiveness, unmanned aerial vehicles are gradually becoming key tools relied on by many industries. However, with the rapid development of unmanned aerial vehicle technology and the continuous expansion of application scenarios, unmanned aerial vehicles inevitably encounter many risks and challenges when performing tasks, especially when facing dangerous environments or complex tasks. In this context, unmanned aerial vehicle virtualization technology has emerged, which opens up a new solution path for the research and development, testing and operation training of unmanned aerial vehicles by building virtual flight environments and device models.

[0003] Chinese patent CN119918172A discloses a fixed-wing unmanned aerial vehicle digital twinning modeling simulation method, which includes: establishing a fixed-wing unmanned aerial vehicle three-dimensional model; establishing fixed-wing unmanned aerial vehicle dynamics and kinematics equations; deriving a fixed-wing unmanned aerial vehicle linear model and an actuator fault model; establishing a fixed-wing unmanned aerial vehicle digital twinning model; establishing real-time communication between the fixed-wing unmanned aerial vehicle digital twinning model and the physical fixed-wing unmanned aerial vehicle model; running the fixed-wing unmanned aerial vehicle digital twinning model for simulation and outputting flight state data in a visual interface. As can be seen, the above-mentioned scheme proposes a method of using digital twinning technology to build a simulation model and realizing communication between the digital twinning model and the physical unmanned aerial vehicle, but does not explicitly require simulation degree. For the unmanned aerial vehicle model established based on digital twinning technology, high simulation degree, especially high simulation degree in real-time environment, is a key factor to realize accurate model establishment and effective control. However, if there is no effective control of simulation degree, the established model will be difficult to achieve ideal control effect and meet current actual needs. SUMMARY

[0004] Therefore, the present application provides a low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning to solve the problem of low synchronization rate and insufficient simulation degree of the system established based on digital twinning technology in the prior art.

[0005] The present application provides a low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning, which comprises:

[0006] The model construction module is configured to construct an initial virtual UAV unit based on the entity UAV parameter information, and to establish a digital twin low-altitude UAV virtual model based on a force action principle to guide the flight state of the virtual UAV unit.

[0007] The acquisition module includes a plurality of sensors arranged on the entity UAV to periodically acquire low-altitude UAV information.

[0008] The data transmission module is connected with the acquisition module to realize communication between the entity UAV and the twin virtual UAV.

[0009] The calculation module is connected with the data transmission module and the model construction module to calculate the obtained data.

[0010] The analysis module is connected with the calculation module to determine whether the current system simulation degree meets the standard based on the deviation proportion, to determine the reason why the current system simulation degree does not meet the standard based on the average positioning difference value in a case where it is determined that the current system simulation degree does not meet the standard, and to generate a corresponding correction instruction or issue a corresponding notification instruction based on the corresponding reason to re-determine the preset deviation proportion, the preset average positioning difference value, or the data compression ratio.

[0011] The instruction control module is connected with the analysis module, the model construction module, and the calculation module to adjust corresponding parameters to corresponding values based on the received instructions and to issue a corresponding notification.

[0012] The deviation proportion is a ratio between the number of entity UAVs with positioning deviation and the total number of entity UAVs in the low-altitude UAV virtual reality fusion management and control system.

[0013] The average positioning difference value is an average value of the positioning difference values between each entity UAV and the twin virtual UAV.

[0014] Further, the analysis module is configured to determine whether the current simulation degree meets the standard based on the deviation proportion obtained by the calculation module, to determine whether the current simulation degree meets the standard based on the average value of the speed difference values between each entity UAV and the twin virtual UAV in a case where it is determined that the current simulation degree cannot meet the standard, or to determine the reason why the simulation degree does not meet the standard based on the average positioning difference value.

[0015] Further, the analysis module is configured to determine whether the current simulation degree meets the standard based on the average value of the absolute difference in moving speed obtained by the calculation module, and determine whether the current simulation degree meets the standard based on the average value of the included angle between each entity unmanned aerial vehicle and the corresponding twin virtual unmanned aerial vehicle, or determine the reason why the current simulation degree does not meet the standard based on the average positioning difference value, wherein the average value of the absolute difference in moving speed is the average value of the sum of the absolute values of the speed difference between each entity unmanned aerial vehicle and the corresponding twin virtual unmanned aerial vehicle.

[0016] Further, the analysis module is configured to determine whether the current simulation degree meets the standard based on the average value of the included angle difference, and correct the deviation proportion based on the ratio between the average value of the speed difference between each entity unmanned aerial vehicle and the corresponding twin virtual unmanned aerial vehicle and the preset average value of the absolute difference in moving speed, or determine the reason why the current simulation degree does not meet the standard based on the average positioning difference value, wherein the average value of the included angle is the average value of the difference between the included angle between each entity unmanned aerial vehicle and the horizontal ground and the included angle between the corresponding twin virtual unmanned aerial vehicle and the horizontal ground.

[0017] Further, the analysis module is configured to increase the preset deviation proportion based on the average value of the absolute difference in moving speed, and the increase range of the preset deviation proportion is proportional to the ratio between the current average value of the absolute difference in moving speed and the preset average value of the absolute difference in moving speed.

[0018] Further, the analysis module is also configured to determine the reason why the simulation degree does not meet the standard based on the deviation proportion, and generate corresponding processing instructions based on the determined reason, including:

[0019] The analysis module determines the reason why the current simulation degree does not meet the standard based on the deviation proportion, the analysis module determines the reason why the current simulation degree does not meet the standard based on the average positioning difference value, or the analysis module sends a positioning exception notification instruction, or the analysis module corrects the current transmission data compression ratio based on the ratio between the average positioning difference value and the set second positioning difference value, or determines the reason why the current average positioning difference value does not meet the standard based on the variance of the positioning difference value between each entity unmanned aerial vehicle and the corresponding twin virtual unmanned aerial vehicle, wherein the average positioning difference value is the average value of the positioning difference value between each entity unmanned aerial vehicle and the corresponding twin virtual unmanned aerial vehicle.

[0020] Further, the analysis module is further used to determine the reason why the current simulation degree does not meet the standard based on the positioning variance, or the analysis module issues a positioning exception notification instruction, or the analysis module determines to correct the preset average positioning difference value based on the wind speed value, wherein the positioning variance refers to the variance of the positioning difference value between each entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle.

[0021] Further, the analysis module is used to increase the preset average positioning difference value based on the real-time wind speed value collected by the collection module, and the increase amplitude of the preset average positioning difference value is proportional to the wind speed value.

[0022] Further, the analysis module is further used to determine whether the current simulation degree meets the standard by the deviation proportion based on the corrected result, and in the case that the current simulation degree cannot meet the standard, the analysis module corrects the current transmission data compression ratio based on the positioning difference value ratio.

[0023] Further, the analysis module is further used to increase the compression ratio of the transmission data based on the positioning difference value ratio, and the amplitude of the compression ratio of the transmission data is proportional to the positioning difference value ratio, wherein the positioning difference value ratio is the ratio between the average positioning difference value and the set second positioning difference value.

[0024] Compared with the prior art, the beneficial effects of the present application are that the present application sets a model construction module, a collection module, a data transmission module, a calculation module, an analysis module and an instruction control module, the model construction module constructs an initial virtual unmanned aerial vehicle unit based on the entity unmanned aerial vehicle parameter information, and guides the flight state of the virtual unmanned aerial vehicle unit through the force action principle, establishes a digital twin low-altitude unmanned aerial vehicle virtual model, which can accurately simulate the flight characteristics of the entity unmanned aerial vehicle, and provides a basic framework for the full fusion of the system; the collection module periodically collects low-altitude unmanned aerial vehicle information, the data transmission module realizes the communication contact between the entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle, the calculation module compares and calculates the obtained data, the analysis module analyzes the model simulation degree based on the calculation result and issues corresponding adjustment instructions, and the instruction control module regulates the cooperative work of each module according to the received instructions, the present system not only constructs a full-fusion low-altitude unmanned aerial vehicle management and control system, but also effectively improves the real-time simulation degree of the system, and the full-fusion system architecture ensures that the model is highly consistent with the actual situation, improves the real-time simulation degree of the system, and thus provides a scientific basis for management and control decisions.

[0025] Further, in the present application, the analysis module determines whether the simulation degree meets the standard based on the deviation proportion obtained by the calculation module, and further analyzes the reasons based on the average speed difference value or the deviation proportion when the simulation degree does not meet the standard. This multi-dimensional judgment method can more accurately evaluate the simulation degree and timely find the key factors affecting the simulation degree, so as to take corresponding adjustment measures and improve the real-time simulation degree of the system to the flight state of the low-altitude unmanned aerial vehicle. The real-time simulation degree of the system is improved, and a reliable scientific basis is provided for control decision.

[0026] Further, the analysis module provided in the present application further combines the average direction angle for one step of judgment when judging whether the simulation degree meets the standard through the average absolute difference of moving speed. This analysis method considering speed and direction factors comprehensively enables the system to more comprehensively evaluate the difference between the flight state of the low-altitude unmanned aerial vehicle and the virtual model, so as to more accurately adjust and optimize the virtual model and improve the real-time simulation degree.

[0027] Further, the analysis module provided in the present application corrects the deviation proportion based on the average absolute difference of moving speed ratio when the simulation degree does not meet the standard, or analyzes the reasons for not meeting the standard. This enables the system to make detailed analysis and adjustment for different deviation factors, and further improves the ability to improve the real-time simulation degree of the flight state of the low-altitude unmanned aerial vehicle.

[0028] Further, the analysis module provided in the present application increases the preset deviation proportion based on the average absolute difference of moving speed ratio. This dynamic adjustment of the preset deviation proportion can timely and accurately correct the simulation degree of the system according to the speed difference in actual flight, so as to better maintain and improve the performance of the low-altitude unmanned aerial vehicle virtual reality fusion control system in real-time simulation degree.

[0029] Further, the analysis module provided in the present application can judge the reasons for not meeting the standard based on the deviation proportion, average positioning difference value and other factors, and generate corresponding processing instructions, such as issuing a notification or correcting the data compression ratio. This enables the system to take effective measures to solve different problems, timely adjust the difference between the virtual model and the entity unmanned aerial vehicle, and ensure that the flight state of the low-altitude unmanned aerial vehicle is simulated in virtual reality with high precision in real time.

[0030] Further, the analysis module provided in the present application judges the reasons for not meeting the standard based on the positioning variance, and the analysis module issues a notification or corrects the average positioning difference value based on the wind speed value. By introducing the analysis and processing of positioning variance and wind speed, the system can more comprehensively consider various factors affecting the positioning accuracy of the low-altitude unmanned aerial vehicle, so as to more accurately adjust the virtual model and improve the real-time simulation degree of the positioning state of the entity unmanned aerial vehicle.

[0031] Further, the analysis module provided by the application increases the preset average positioning difference value according to the real-time wind speed value, and the two are proportional. This way of dynamically adjusting the average positioning difference value according to the actual environmental factors (wind speed) can make the system better adapt to the complex and changeable low-altitude flight environment, ensure the positioning accuracy of the virtual model under different wind speed conditions, and thus improve the real-time simulation degree of the entire management and control system to the positioning state of the low-altitude unmanned aerial vehicle.

[0032] Further, when the analysis module judges that the simulation degree does not meet the standard, the analysis module corrects the current transmission data compression ratio based on the positioning difference value ratio. This mechanism of dynamically adjusting the data compression ratio based on the positioning difference value can accurately restore the positioning information of the entity unmanned aerial vehicle while ensuring the efficiency of data transmission, thereby improving the real-time simulation degree of the virtual model to the positioning state of the entity unmanned aerial vehicle.

[0033] Further, the analysis module provided by the application increases the preset average positioning difference value according to the real-time wind speed value, and the two are proportional. This way of dynamically adjusting the average positioning difference value according to the actual environmental factors (wind speed) can make the system better adapt to the complex and changeable low-altitude flight environment, ensure the positioning accuracy of the virtual model under different wind speed conditions, and thus improve the real-time simulation degree of the entire management and control system to the positioning state of the low-altitude unmanned aerial vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1 A low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning in the application;

[0035] Figure 2 A workflow diagram of the low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning in the embodiment of the application;

[0036] Figure 3 A flowchart for judging whether the current simulation degree meets the standard based on the deviation proportion in the embodiment of the application;

[0037] Figure 4 A flowchart for judging the reason why the current simulation degree does not meet the standard based on the average positioning difference value in the embodiment of the application. DETAILED DESCRIPTION

[0038] In order to make the purpose and advantages of the application clearer and more apparent, the application will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the application and do not limit the application.

[0039] The preferred embodiments of the application will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the application and do not limit the protection scope of the application.

[0040] Please refer toFigure 1 As shown, it is the structural block diagram of the low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning of the embodiment of the application. The system described in the embodiment of the application comprises a model construction module, an acquisition module, a data transmission module, a calculation module, an analysis module and an instruction control module;

[0041] The model construction module is used to construct an initial virtual unmanned aerial vehicle unit based on entity unmanned aerial vehicle parameter information, guide the flight state of the virtual unmanned aerial vehicle unit based on the principle of force action, and establish a digital twinning low-altitude unmanned aerial vehicle virtual model;

[0042] The acquisition module comprises a plurality of sensors arranged on the entity unmanned aerial vehicle to periodically acquire low-altitude unmanned aerial vehicle information;

[0043] The data transmission module is connected with the acquisition module to realize communication between the entity unmanned aerial vehicle and the twinned virtual unmanned aerial vehicle;

[0044] The calculation module is connected with the data transmission module and the model construction module to calculate the obtained data;

[0045] The analysis module is connected with the calculation module to judge whether the current system simulation degree meets the standard based on the deviation proportion, and to judge the reason why the current system simulation degree does not meet the standard based on the average positioning difference value in the case that the current system simulation degree does not meet the standard, and to determine the preset deviation proportion, the preset average positioning difference value or the data compression ratio based on the corresponding reason, and to generate the corresponding correction instruction or to issue the corresponding notification instruction;

[0046] The instruction control module is connected with the analysis module, the model construction module and the calculation module to adjust the corresponding parameters to the corresponding values based on the received instructions, and to issue the corresponding notifications;

[0047] The deviation proportion is the ratio between the number of entity unmanned aerial vehicles with positioning deviation and the total number of entity unmanned aerial vehicles in the low-altitude unmanned aerial vehicle virtual reality fusion management and control system. The deviation proportion directly reflects the universality of the positioning deviation between the entity unmanned aerial vehicles and the twinned virtual unmanned aerial vehicles in the system. By calculating the deviation proportion, the positioning deviation in the system can be quantified, providing an intuitive, real-time and easy-to-operate index for the evaluation of the simulation degree. At the same time, the deviation proportion can not only directly reflect the overall simulation effect of the system, but also can be combined with other indexes for multi-dimensional analysis, thereby providing strong support for the optimization and decision-making of the system;

[0048] The average positioning difference value is an average value of the positioning difference values between each entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle, and the average positioning difference value reflects the overall deviation degree of the entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle in positioning in the system. A smaller average positioning difference value means that the positioning state of the virtual model has a higher simulation degree on the entity unmanned aerial vehicle. A larger average positioning difference value means that there is a larger difference between the positioning state of the virtual model and the entity unmanned aerial vehicle, and the simulation degree is lower. Through the judgment of the average positioning difference value, on the one hand, it is helpful to quickly classify the simulation degree that does not meet the standard, so as to improve the control efficiency. On the other hand, it is also helpful to grasp the simulation of the whole system, so as to provide a reliable basis for further judgment.

[0049] Referring to Figure 2 Fig. 1 is a workflow diagram of a low-altitude unmanned aerial vehicle virtual reality fusion management and control system based on digital twinning according to an embodiment of the present application.

[0050] Specifically, in the embodiment of the present application, the 3DMAX initial virtual unmanned aerial vehicle unit is utilized according to the entity unmanned aerial vehicle parameter information, and the entity unmanned aerial vehicle parameter information includes: body length, body width, body height, unmanned aerial vehicle shape, unmanned aerial vehicle thickness, unmanned aerial vehicle landing gear length, unmanned aerial vehicle landing gear width, unmanned aerial vehicle landing gear height, unmanned aerial vehicle landing gear track, unmanned aerial vehicle landing gear diameter, wing span length, wing chord distance, wing area, wing thickness, wing airfoil, horizontal tail area, vertical tail area, motor power, propeller diameter, and pitch.

[0051] Subsequently, based on the principle of force action, a virtual unmanned aerial vehicle unit flight state formula is established:

[0052] The unmanned aerial vehicle is mainly affected by lift, gravity, thrust, drag, and side force during flight. Therefore, the translational motion equation of the entity unmanned aerial vehicle is as follows:

[0053]

[0054] wherein a x is the acceleration of the unmanned aerial vehicle in the x-axis direction, θ is the pitch angle, φ is the roll angle, D x is the air resistance in the x-axis direction, a y is the acceleration of the unmanned aerial vehicle in the y-axis direction, D y is the air resistance in the y-axis direction, a z is the acceleration of the unmanned aerial vehicle in the z-axis direction, D z is the air resistance in the z-axis direction.

[0055] The rotational motion equation of the entity unmanned aerial vehicle is as follows:

[0056]

[0057] wherein Ix is the moment of inertia of the UAV about the x-axis, P is the roll angular acceleration, q is the pitch angular velocity, r is the yaw angular velocity, I y is the moment of inertia of the UAV about the y-axis, Q is the pitch angular acceleration, p is the roll angular velocity, I z is the moment of inertia of the UAV about the z-axis, R is the yaw angular acceleration.

[0058] The communication link between the entity UAV and the twin virtual UAV is established through the TSN protocol, and then the flight state data is output by the low-altitude UAV virtual reality fusion management and control system.

[0059] During operation, the clocks of the entity UAV and the twin virtual UAV are synchronized, and the periodical collection module collects real-time wind speed, online number of entity UAVs, real-time positioning data of entity UAVs, real-time speed of entity UAVs, and the angle between each entity UAV and the horizontal ground in one fifteenth of the minimum time constant of the system as the collection period, and transmits the data to the calculation module through the data transmission module, the analysis module determines whether the current simulation degree meets the requirements according to the deviation proportion of the entity UAV obtained by the calculation module, and determines the reason when it is determined that it does not meet the requirements, and determines the processing parameters again based on the reason determined when it does not meet the requirements.

[0060] Further, the analysis module is used to determine whether the current simulation degree meets the standard based on the deviation proportion obtained by the calculation module, and in the case that the current simulation degree cannot meet the standard, it is determined whether the current simulation degree meets the standard based on the average value of the speed difference between each entity UAV and the twin virtual UAV, or the reason why the simulation degree does not meet the standard is determined based on the deviation proportion.

[0061] Please refer to Figure 3 , which is a flowchart for determining whether the current simulation degree meets the standard based on the deviation proportion P in the embodiment of the application.

[0062] The analysis module obtains the deviation proportion P and compares the deviation proportion P with the set first deviation proportion P1 and the second deviation proportion P2, wherein the first deviation proportion P1 is set to one tenth of the total number of entity UAVs, and the second deviation proportion P2 is set to three tenths of the total number of entity UAVs.

[0063] If the deviation proportion P is less than or equal to the P1, the analysis module determines that the current simulation degree meets the standard;

[0064] If the deviation proportion P is greater than the P1 and less than or equal to the P2, the analysis module needs to further determine whether the current simulation degree meets the standard in combination with the average value of the absolute difference in speed between each entity UAV and the twin virtual UAV;

[0065] If the deviation ratio P is greater than P2, the analysis module determines that the current simulation degree cannot meet the requirement, and determines the reason why the current simulation degree does not meet the standard based on the average positioning difference value.

[0066] Further, the analysis module is used to determine whether the current simulation degree meets the standard based on the average absolute speed difference value obtained by the calculation module, and determine whether the current simulation degree meets the standard based on the average value of the direction included angle between each entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle, or determine the reason why the current simulation degree does not meet the standard based on the average value of the positioning difference value between each entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle, in the case that it is determined that the current simulation degree does not meet the standard.

[0067] The average absolute speed difference value is the average value of the sum of the absolute value of the speed difference value between each entity unmanned aerial vehicle and the corresponding twin virtual unmanned aerial vehicle, and the average absolute speed difference value reflects the overall deviation degree of the entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle in the system in terms of speed. By calculating the average absolute speed difference value, the overall degree of speed deviation in the system can be quantified. When the deviation ratio cannot directly determine whether the simulation degree meets the requirement, the average absolute speed difference value can provide additional information, so as to more accurately determine whether the current simulation degree meets the requirement.

[0068] Specifically, in the embodiment of the application, the analysis module obtains the average absolute speed difference value M, and compares the average absolute speed difference value M with the preset average absolute speed difference value M1, wherein M1∈[0.15, 0.5m / s] is set.

[0069] If the average absolute speed difference value M is greater than M1, the analysis module determines that the current simulation degree does not meet the standard.

[0070] If the average absolute speed difference value M is less than or equal to M1, the analysis module further determines whether the current simulation degree meets the standard in combination with the average value of the direction included angle between each entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle.

[0071] Further, the analysis module is configured to determine whether the current simulation degree meets the standard based on the average value of the direction angle difference value obtained by the calculation module, and correct the deviation proportion based on the ratio between the average value of the speed difference between each entity drone and the corresponding virtual drone and the average value of the preset absolute speed difference, or determine the reason why the current simulation degree does not meet the standard based on the average value of the positioning difference between each entity drone and the corresponding virtual drone, when it is determined that the current simulation degree does not meet the standard. The average value of the direction angle difference value is the average value of the difference between the angle between each entity drone and the horizontal ground and the angle between the corresponding virtual drone and the horizontal ground. By calculating the average value of the direction angle difference value based on the deviation proportion and the average value of the absolute speed difference, the overall degree of direction deviation in the system can be quantified, thereby providing a basis for determining the current simulation degree.

[0072] The analysis module determines whether the current simulation degree meets the standard based on the average value of the direction angle difference value obtained by the calculation module.

[0073] The analysis module obtains the average value of the direction angle difference value K and compares it with the preset average value of the direction angle K1, wherein the preset average value of the direction angle K1 is in the range of [3°, 10°].

[0074] If the average value of the direction angle difference value K is less than or equal to the preset average value of the direction angle K1, the analysis module optimizes the deviation proportion based on the ratio between the average value of the speed difference between each entity drone and the corresponding virtual drone and the average value of the preset absolute speed difference.

[0075] If the average value of the direction angle difference value K is greater than the preset average value of the direction angle K1, the analysis module determines that the current flight simulation degree does not meet the standard, and determines the reason why the current flight simulation degree does not meet the standard based on the average value of the positioning difference between each entity drone and the corresponding virtual drone.

[0076] Further, the analysis module is configured to increase the preset deviation proportion based on a ratio of the average absolute speed difference, and the increase range of the preset deviation proportion is proportional to the ratio of the average absolute speed difference; wherein the ratio of the average absolute speed difference is a ratio between the current average absolute speed difference and a preset average absolute speed difference; and the preset deviation proportion is an important threshold for the system to determine whether the simulation degree meets the requirements. In actual operation, the running environment and task requirements of the system may change, resulting in that the preset deviation proportion is no longer applicable. By dynamically adjusting the preset deviation proportion, the system can better adapt to these changes and ensure more accurate simulation degree evaluation; and by setting the increase range of the preset deviation proportion to be in a positive proportional relationship with the ratio of the average absolute speed difference, the adjustment range can be better matched with the speed deviation degree when the average difference value K of the direction angle is less than or equal to the preset average direction angle K1, so as to ensure the system simulation degree while improving the adaptability and flexibility of the system.

[0077] Specifically, the process of increasing the preset deviation proportion based on the ratio of the average absolute speed difference includes:

[0078] comparing the ratio J of the average absolute speed difference with a preset first preset ratio J1 of the average absolute speed difference and a preset second preset ratio J2 of the average absolute speed difference, wherein the first preset ratio J1 of the average absolute speed difference is set to be in a range of [0.3, 0.6], and the second preset ratio J2 of the average absolute speed difference is set to be in a range of (0.6, 0.9];

[0079] if the ratio J of the average absolute speed difference is less than or equal to the first preset ratio J1 of the average absolute speed difference, the first deviation proportion P1 and the second deviation proportion P2 are corrected to corresponding values by using a first proportion correction coefficient a1, wherein the first proportion correction coefficient a1 is set to be 1.05, the corrected first deviation proportion P1' is P1 x a1, and the corrected second deviation proportion P2' is P2 x a1;

[0080] if the ratio J of the average absolute speed difference is greater than the first preset ratio J1 of the average absolute speed difference and less than or equal to the second preset ratio J2 of the average absolute speed difference, the first deviation proportion P1 and the second deviation proportion P2 are corrected to corresponding values by using a second proportion correction coefficient a2, wherein the second proportion correction coefficient a2 is set to be 1.13, the corrected first deviation proportion P1' is P1 x a2, and the corrected second deviation proportion P2' is P2 x a2;

[0081] If the absolute difference average ratio of the moving speed J is greater than the second preset absolute difference average ratio of the moving speed J2, the first deviation proportion P1 and the second deviation proportion P2 are corrected to corresponding values using a third proportion correction coefficient α3, the third proportion correction coefficient α3 is set to 1.2, the corrected first deviation proportion P1' is P1*α3, and the corrected second deviation proportion P2' is P2*α3.

[0082] Further, the analysis module is further used to determine the reason why the simulation degree does not meet the standard based on the deviation proportion, and generate corresponding processing instructions based on the determined reason, including:

[0083] The analysis module determines the reason why the current simulation degree does not meet the standard based on the deviation proportion, the analysis module determines the reason why the current simulation degree does not meet the standard based on the average positioning difference value, or the analysis module issues a positioning exception notification instruction, or the analysis module corrects the current transmission data compression ratio based on the ratio between the average positioning difference value and the set second positioning difference value, or determines the reason why the standard is not met based on the variance of the positioning difference value between each entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle when it is determined that the current average positioning difference value does not meet the standard. Since the average positioning difference value reflects the overall deviation degree of the entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle in positioning in the system, by comparing the average positioning difference value with the set first preset average positioning difference value and the second preset average positioning difference value, the reason why the current simulation degree does not meet the standard can be effectively determined. When the average positioning difference value is less than the first preset average positioning difference value, it indicates that the overall positioning of the entity unmanned aerial vehicle and the overall positioning of the virtual unmanned aerial vehicle do not have a large gap at this time, but it still does not meet the simulation degree standard at this time, which indicates that there may be an abnormal positioning. Therefore, a positioning exception notification is issued. When the average positioning difference value is greater than the second preset average positioning difference value, it indicates that there may be a serious data packet loss at this time. Therefore, the transmission data compression ratio can be increased to reduce the data transmission pressure. When the average positioning difference value is greater than the first preset average positioning difference value and less than or equal to the second preset average positioning difference value, there may be a current wind speed that is too large or an abnormal positioning at this time. Therefore, the reason needs to be determined in combination with the variance of the positioning difference value between the entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle.

[0084] Please refer to Figure 4 Fig. 4 is a flowchart of the process of determining the reason why the current simulation degree does not meet the standard based on the average positioning difference value in the embodiment of the present application, as shown in the figure. The process of determining the reason why the current simulation degree does not meet the standard based on the average positioning difference value by the analysis module includes:

[0085] The analysis module obtains the average positioning difference value U and compares the average positioning difference value U with the set first preset average positioning difference value U1 and the second preset average positioning difference value U2, wherein the first preset average positioning difference value U1 is set to be in [2, 6 cm], and the second preset average positioning difference value U2 is set to be in (6, 10 cm].

[0086] The average positioning difference value U is compared with the first preset average positioning difference value U1 and the second preset average positioning difference value U2;

[0087] If the U is less than or equal to the U1, the analysis module judges that the current positioning is abnormal, and the analysis module sends a positioning abnormality notification.

[0088] If the U is greater than the U1 and less than or equal to the U2, the analysis module judges that the current simulation degree does not meet the standard based on the variance of the positioning difference value between each entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle.

[0089] If the U is greater than the U2, the analysis module corrects the current transmission data compression ratio based on the positioning difference value ratio.

[0090] Further, the analysis module is also used to increase the compression ratio of the transmission data based on the positioning difference value ratio, and the compression ratio of the transmission data is proportional to the positioning difference value ratio, wherein the positioning difference value ratio is the ratio between the average positioning difference value and the second preset average positioning difference value. Since the positioning difference value ratio represents the average position deviation between the entity unmanned aerial vehicle and the twin virtual model, when the average positioning difference value is greater than the second preset average positioning difference value, it indicates that there is a significant lag or distortion in the data synchronization between the entity unmanned aerial vehicle and the twin virtual model. Therefore, the embodiment of the present application increases the compression ratio of the transmission data based on the positioning difference value ratio, and the compression ratio of the transmission data is proportional to the positioning difference value ratio, which improves the flexibility of the system and optimizes the real-time simulation degree.

[0091] Specifically, the process of increasing the compression ratio of the transmission data based on the positioning difference value ratio includes:

[0092] The calculation module calculates the current positioning difference value ratio G, and compares the current positioning difference value ratio G with the first preset positioning difference value ratio G1 and the second preset positioning difference value ratio G2, wherein the first preset positioning difference value ratio G1 is set to be in the range of [0.25, 0.6], and the second preset positioning difference value ratio G2 is set to be in the range of (0.6, 0.8].

[0093] The positioning difference value ratio G is compared with the first preset positioning difference value ratio G1 and the second preset positioning difference value ratio G2.

[0094] If the positioning difference value ratio G is less than or equal to the first preset positioning difference value ratio G1, the analysis module corrects the compression ratio Z to a corresponding value using a first compression ratio correction coefficient r1, and the first compression ratio correction coefficient r1 is set to be 1.1, and the compression ratio Z' is Zxr1.

[0095] If the positioning difference ratio G is greater than the first preset positioning difference ratio G1 and less than or equal to the second preset positioning difference ratio G2, the analysis module uses a second compression ratio correction coefficient r2 to correct the compression ratio Z to a corresponding value, and the second compression ratio correction coefficient r2 is set to 1.25, and the compression ratio Z' is Zxr2;

[0096] If the positioning difference ratio G is greater than the second preset positioning difference ratio G2, the analysis module uses a third compression ratio correction coefficient r3 to correct the compression ratio Z to a corresponding value, and the third compression ratio correction coefficient r3 is set to 1.43, and the compression ratio Z' is Zxr3.

[0097] Further, the analysis module is also used to determine the reason why the current simulation degree does not meet the standard based on the positioning variance, or the analysis module issues a positioning abnormality notification instruction, or the analysis module determines to correct the preset average positioning difference value based on the wind speed value, wherein the positioning variance refers to the variance of the positioning difference value between each entity unmanned aerial vehicle and the twin virtual unmanned aerial vehicle, and the positioning variance reflects the dispersion degree of the positioning difference value, thereby providing a reliable basis for determining the reason why the current simulation degree does not meet the standard;

[0098] The process of determining the reason why the current simulation degree does not meet the standard based on the positioning variance includes:

[0099] The analysis module acquires the positioning variance H and compares the positioning variance H with a set positioning variance H1, wherein the specific value of the positioning variance H1 can be summarized according to actual conditions and the law of each historical data;

[0100] If the positioning variance H is less than or equal to the preset positioning variance H1, the analysis module issues a positioning abnormality notification instruction;

[0101] If the positioning variance H is greater than the preset positioning variance H1, the analysis module corrects the preset average positioning difference value based on the wind speed value.

[0102] Further, the analysis module is used to increase the preset average positioning difference value based on the real-time wind speed value collected by the collection module, and the increase amplitude of the preset average positioning difference value is proportional to the wind speed value. In a low-altitude flight environment, wind speed is one of the important factors affecting the flight state and positioning accuracy of an unmanned aerial vehicle. Changes in wind speed will cause changes in the flight trajectory and speed of the unmanned aerial vehicle, thereby affecting its positioning accuracy. By increasing the preset average positioning difference value according to the wind speed value, the system can more accurately simulate the flight state of the entity unmanned aerial vehicle under actual wind speed conditions, thereby improving the simulation degree of the virtual model. Setting the increase amplitude of the average positioning difference value to be proportional to the wind speed value can ensure that the adjustment amplitude matches the influence of the wind speed, thereby improving the real-time simulation performance of the system.

[0103] The process of increasing the preset average positioning difference value based on the real-time wind speed value collected by the collection module includes:

[0104] The collection module collects the current wind speed F, and the analysis module compares the current wind speed F with the set first preset wind speed F1 and the second preset wind speed F2, wherein the first preset wind speed F1 ∈ [7, 10 m / s] and the second preset wind speed F2 ∈ (0, 12 m / s].

[0105] If the current wind speed F is less than or equal to the first preset wind speed F1, the analysis module uses the first positioning difference correction coefficient β1 to correct the first preset average positioning difference value U1 and the second preset average positioning difference value U2 to corresponding values, wherein the first positioning difference correction coefficient β1 is set to 1.06, the corrected first preset average positioning difference value U1' = U1 × β1, and the corrected second preset average positioning difference value U2' = U2 × β1.

[0106] If the current wind speed F is greater than the first preset wind speed F1 and less than or equal to the second preset wind speed F2, the analysis module uses the second positioning difference correction coefficient β2 to correct the first preset average positioning difference value U1 and the second preset average positioning difference value U2 to corresponding values, wherein the second positioning difference correction coefficient β2 is set to 1.12, the corrected first preset average positioning difference value U1' = U1 × β2, and the corrected second preset average positioning difference value U2' = U2 × β2.

[0107] If the current wind speed F is greater than the second preset wind speed F2, the analysis module uses the third positioning difference correction coefficient β3 to correct the first preset average positioning difference value U1 and the second preset average positioning difference value U2 to corresponding values, wherein the third positioning difference correction coefficient β3 is set to 1.18, the corrected first preset average positioning difference value U1' = U1 × β3, and the corrected second preset average positioning difference value U2' = U2 × β3.

[0108] Further, the analysis module is also used to determine whether the current simulation degree meets the standard through the deviation proportion based on the corrected result, and in the case that the current simulation degree cannot meet the standard, the analysis module corrects the current transmission data compression ratio based on the positioning difference ratio.

[0109] The process of the analysis module determining whether the current simulation degree meets the standard through the deviation proportion based on the corrected result includes:

[0110] The analysis module obtains the corrected second deviation proportion P2' and compares the current deviation proportion P with the corrected second deviation proportion P2'.

[0111] If the deviation proportion P is greater than the second corrected deviation proportion P2', the analysis module increases the compression ratio of the transmission data based on the positioning deviation ratio;

[0112] If the deviation proportion P is less than or equal to the second corrected deviation proportion P2', it is determined that the current simulation degree meets the standard.

[0113] Thus far, the technical solutions of the present application have been described in connection with the preferred embodiments shown in the drawings, but those skilled in the art will readily understand that the scope of protection of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the relevant technical features without departing from the principles of the present application, and the technical solutions after such changes or replacements will all fall within the scope of protection of the present application.

[0114] The above description is merely preferred embodiments of the present application and is not intended to limit the present application; for those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A low-altitude UAV virtual reality fusion control system based on digital twins, characterized by: include: The model building module is used to build an initial virtual drone unit based on the physical drone parameter information, and to guide the flight state of the virtual drone unit based on the force action principle to establish a digital twin low-altitude drone virtual model; The acquisition module includes a plurality of sensors provided on the physical drone, and is used to periodically collect information of the physical drone; A data transmission module, which is connected to the acquisition module to realize communication between the physical drone and the twin virtual drone; a calculation module, connected to the data transmission module and the model building module, for calculating the acquired data; an analysis module connected to the calculation module, configured to determine whether the current system simulation degree meets the standard based on the deviation ratio, and, if it is determined that the current system simulation degree does not meet the standard, determine the reason why the current system simulation degree does not meet the standard based on the average positioning difference, and, based on the corresponding reason, re-determine a preset deviation ratio, a preset average positioning difference, or a data compression ratio, and generate a corresponding correction instruction, or issue a corresponding notification instruction; an instruction control module connected to the analysis module, the model building module, and the calculation module, and configured to control corresponding modules to adjust corresponding parameters to corresponding values ​​based on received instructions, and to issue corresponding notifications; Among them, the deviation ratio is the ratio between the number of physical drones with positioning deviations and the total number of physical drones in the low-altitude UAV virtual reality fusion control system, and the average positioning difference is the average value of the positioning differences between each physical UAV and the twin virtual UAV.

2. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 1 is characterized in that: The analysis module is used to determine whether the current simulation degree meets the standard based on the deviation ratio obtained by the calculation module, and, when it is determined that the current simulation degree cannot meet the standard, determine whether the current simulation degree meets the standard based on the average value of the absolute speed difference between each physical drone and the twin virtual drone, or, determine the reason why the simulation degree does not meet the standard based on the average positioning difference.

3. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 2 is characterized in that: The analysis module is used to determine whether the current simulation degree meets the standard based on the average value of the absolute difference in movement speed obtained by the calculation module, and if it is determined that the current simulation degree does not meet the standard, determine whether the current simulation degree meets the standard based on the average value of the direction angle between each physical drone and the twin virtual drone, or determine the reason why the current simulation degree does not meet the standard based on the average positioning difference; The average absolute speed difference is the average of the sum of the absolute speed differences between each physical drone and its corresponding twin virtual drone.

4. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 3 is characterized in that: The analysis module is used to determine whether the current simulation degree meets the standard based on the average value of the direction angle difference obtained by the calculation module, and when it is determined that the current simulation degree meets the standard, optimize the simulation degree based on the ratio between the average value of the speed difference between each physical drone and the twin virtual drone and the set average value of the absolute difference of the preset movement speed, and correct the deviation ratio, or the analysis module determines the reason why the current simulation degree does not meet the standard based on the average positioning difference; The average value of the direction angle difference is the average value of the difference between the angle between each physical drone and the horizontal ground and the angle between the corresponding twin virtual drone and the horizontal ground.

5. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 4 is characterized in that: The analysis module is configured to increase the preset deviation ratio based on the ratio of the average absolute difference of the moving speeds, and the increase in the preset deviation ratio is proportional to the ratio of the average absolute difference of the moving speeds; The moving speed absolute difference average value ratio is a ratio between the current moving speed absolute difference average value and a preset moving speed absolute difference average value.

6. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 2 is characterized in that: The analysis module is further configured to determine the reason why the simulation degree does not meet the standard based on the deviation ratio, and generate a corresponding processing instruction based on the determined reason, including: The analysis module determines the reason why the current simulation degree does not meet the standard based on the deviation ratio, the analysis module determines the reason why the current simulation degree does not meet the standard based on the average positioning difference, or the analysis module issues a positioning abnormality notification instruction, or the analysis module corrects the current transmission data compression ratio based on the ratio between the average positioning difference and the set second positioning difference, or, when it is determined that the current average positioning difference does not meet the standard, the reason for not meeting the standard is determined based on the variance of the positioning difference between each physical drone and the twin virtual drone.

7. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 6 is characterized in that: The analysis module is also used to determine the reason why the current simulation degree does not meet the standard based on the positioning variance, or to issue a positioning abnormality notification instruction, or to determine whether to correct the preset average positioning difference based on the wind speed value, wherein the positioning variance refers to the variance of the positioning difference between each physical drone and the twin virtual drone.

8. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 7 is characterized in that: The analysis module is used to increase the preset average positioning difference based on the real-time wind speed value collected by the collection module, and the increase range of the preset average positioning difference is proportional to the wind speed value.

9. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 8 is characterized in that: The analysis module is also used to determine whether the current simulation degree meets the standard based on the corrected result through the deviation ratio, and, when it is determined that the current simulation degree cannot meet the standard, the analysis module corrects the current transmission data compression ratio based on the positioning difference ratio.

10. The low-altitude UAV virtual reality fusion management and control system based on digital twin according to claim 6 is characterized in that: The analysis module is also used to increase the compression ratio of the transmitted data based on the positioning difference ratio, and the compression ratio of the transmitted data is proportional to the positioning difference ratio, wherein the positioning difference ratio is the ratio between the average positioning difference and the set second positioning difference.

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