Unmanned aerial vehicle parameter debugging method and device, equipment and storage medium

Abstract

The application discloses a kind of unmanned vehicle parameter debugging method, device, equipment and storage medium, the method is controlled unmanned vehicle take-off based on test parameter value, obtains the flight state value of unmanned vehicle in this flight test;Flight state value and expected state value are detected whether matching;If it is detected that flight state value and expected state value do not match, then determine the adjustment direction of test parameter value based on flight state value and pre-stored best state value, and determine the adjustment range of test parameter value based on the state problem point of flight state value;Based on adjustment direction and adjustment range, generate the estimated parameter value of unmanned vehicle in next flight test, use estimated parameter value as test parameter value, and return to execute the step of controlling unmanned vehicle take-off based on test parameter value, until it is detected that flight state value and expected state value match, then determine test parameter value as target parameter value.The application improves the parameter debugging efficiency of unmanned vehicle.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) technology, and particularly relates to a method, apparatus, device, and storage medium for UAV parameter debugging. Background Technology

[0002] With the rapid development of technology, drones are being used more and more widely in both military and civilian fields, and drone research and development has become one of the focal points of emerging technology industries.

[0003] Currently, in order to apply drones to various military and civilian applications, it is usually necessary to first test their functions. Only after the test results confirm that the drone's functions meet the standards can it be put into use. Specifically, the ultimate goal of functional testing is to adjust the drone's various flight control parameters to a certain range so that the drone can perform its various functions. However, the existing methods for parameter tuning of drones typically involve manually inputting parameter values, recording flight data, and then manually adjusting the parameter values. When problems occur during drone test flights, flight test personnel need to rely on experience and manually exported flight logs to carefully analyze the flight situation and then find solutions. When there are many drones that need to be tuned, the same tuning process needs to be performed on each drone, and the analysis of the same flight problems often relies on experience, resulting in low efficiency in parameter tuning. Summary of the Invention

[0004] The main objective of this invention is to provide a method, apparatus, device, and storage medium for debugging drone parameters, aiming to improve the efficiency of drone parameter debugging.

[0005] To achieve the above objectives, the present invention provides a method for debugging UAV parameters, the method comprising the following steps:

[0006] The drone is controlled to take off based on the test parameter values, and the flight status values ​​of the drone in this flight test are obtained;

[0007] Detect whether the flight status value matches the expected status value;

[0008] If the flight status value is detected to be mismatched with the expected status value, the adjustment direction of the test parameter value is determined based on the flight status value and the pre-stored optimal status value, and the adjustment range of the test parameter value is determined based on the status problem points of the flight status value.

[0009] Based on the adjustment direction and the adjustment range, the estimated parameter values ​​of the UAV in the next flight test are generated. The estimated parameter values ​​are used as the test parameter values, and the step of controlling the UAV to take off based on the test parameter values ​​is returned to be executed until the flight state value is detected to match the expected state value. Then the test parameter value is determined to be the target parameter value.

[0010] Optionally, the step of obtaining the flight status values ​​of the UAV during this flight test includes:

[0011] Acquire flight video data, wherein the flight video data is obtained by recording and monitoring the flight test process of the UAV;

[0012] Multiple image data are extracted from the flight video data, and the flight status value of the UAV in this flight test is calculated based on each image data.

[0013] Optionally, the step of determining the adjustment direction of the test parameter value based on the flight state value and the pre-stored optimal state value includes:

[0014] Obtain the pre-stored optimal state value and the optimal parameter value corresponding to the pre-stored optimal state value;

[0015] Calculate the first difference between the flight state value and the expected state value, and calculate the second difference between the pre-stored optimal state value and the expected state value;

[0016] Detect whether the first difference is less than the second difference;

[0017] If the first difference is detected to be less than the second difference, then the adjustment direction of the test parameter value is determined to be from the optimal parameter value to the test parameter value;

[0018] If the first difference is detected to be greater than or equal to the second difference, then the adjustment direction of the test parameter value is determined to be from the test parameter value to the optimal parameter value.

[0019] Optionally, after the step of determining that the adjustment direction of the test parameter value is from the optimal parameter value to the test parameter value, the method further includes:

[0020] Update the pre-stored optimal state value to the flight state value;

[0021] Update the optimal parameter value to the test parameter value.

[0022] Optionally, after the step of detecting that the first difference is less than the second difference, the method further includes:

[0023] Obtain the flight log of the UAV during this flight test, and check whether the flight attribute data in the flight log is within the preset standard range;

[0024] If the flight attribute data is detected to be within the preset standard range, then the flight log is saved;

[0025] If the flight attribute data is detected to be outside the preset standard range, an error message will be output to remind the tester to troubleshoot the drone.

[0026] Optionally, the step of determining the adjustment range of the test parameter value based on the state problem point of the flight state value includes:

[0027] The state problem points of the flight state value are determined based on the relationship between the flight state value and the expected state value;

[0028] Based on the status problem point, the parameter setting range corresponding to the status problem point is obtained from the preset problem solution library, and the parameter setting range is used as the adjustment range of the test parameter value.

[0029] Optionally, the step of determining the state problem point of the flight state value based on the relationship between the flight state value and the expected state value includes:

[0030] Detect whether the flight status value is less than the expected status value;

[0031] If the detected flight status value is less than the expected status value, then the problem with the flight status value is determined to be that the flight status value is too small;

[0032] If the detected flight status value is greater than the expected status value, then the problem with the flight status value is determined to be that the flight status value is too large.

[0033] Furthermore, to achieve the above objectives, the present invention also provides a UAV parameter debugging device, which includes the following steps:

[0034] The flight status value module is used to control the UAV to take off based on test parameter values ​​and to obtain the flight status value of the UAV in this flight test.

[0035] The judgment module is used to detect whether the flight status value matches the expected status value;

[0036] The adjustment basis module is used to determine the adjustment direction of the test parameter value based on the flight status value and the pre-stored optimal status value if the flight status value is detected to be mismatched with the expected status value, and to determine the adjustment range of the test parameter value based on the status problem points of the flight status value.

[0037] The parameter adjustment module is used to generate the estimated parameter values ​​of the UAV in the next flight test based on the adjustment direction and the adjustment range, use the estimated parameter values ​​as the test parameter values, and return to execute the step of controlling the UAV to take off based on the test parameter values ​​until the flight state value is detected to match the expected state value, then the test parameter value is determined to be the target parameter value.

[0038] In addition, to achieve the above objectives, the present invention also provides a drone parameter debugging device, which includes: a memory, a processor, and a drone parameter debugging program stored in the memory and executable on the processor. When the drone parameter debugging program of the drone parameter debugging device is executed by the processor, it implements the steps of the drone parameter debugging method as described above.

[0039] In addition, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a UAV parameter debugging program, which, when executed by a processor, implements the steps of the UAV parameter debugging method described above.

[0040] This invention controls the takeoff of a drone based on pre-set test parameter values ​​and acquires the drone's flight status values ​​during the current flight test. It then checks whether these flight status values ​​match the expected status values. If a mismatch is detected, the adjustment direction of the test parameter values ​​is determined based on the flight status values ​​and pre-stored optimal status values. The adjustment range of the test parameter values ​​is determined based on the problematic points in the flight status values. The test parameter values ​​are then adjusted according to the adjustment direction and range to generate estimated parameter values ​​for the drone in the next flight test. These estimated parameter values ​​are used as the test parameter values ​​to control the drone to take off again in the next flight test. If a match is detected between the flight status values ​​and the expected status values, the drone's flight parameter tuning result (i.e., the target parameter values) is determined to be the aforementioned test parameter values. Thus, compared to the traditional method that requires testers to manually analyze test problems and manually input test parameter values, this embodiment of the invention determines the adjustment direction of test parameter values ​​based on the flight state values ​​in the current test and the pre-stored optimal state values, determines the adjustment range of test parameter values ​​based on the state problem points of the flight state values, and then automatically adjusts the test parameter values ​​according to the adjustment direction and adjustment range to obtain the test parameter values ​​for the next flight test, until the flight state of the UAV meets the expected effect and the test parameter values ​​corresponding to the expected effect are obtained, thereby improving the parameter debugging efficiency of the UAV. Attached Figure Description

[0041] Figure 1This is a schematic diagram of the hardware operating environment of the UAV parameter debugging equipment involved in the embodiments of the present invention;

[0042] Figure 2 This is a flowchart illustrating the steps of the first embodiment of the UAV parameter debugging method of the present invention;

[0043] Figure 3 This is a schematic diagram of the drone parameter debugging process according to an embodiment of the drone parameter debugging method of the present invention;

[0044] Figure 4 This is a functional module diagram of an embodiment of the UAV parameter debugging device of the present invention.

[0045] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0046] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0047] Reference Figure 1 , Figure 1 This is a schematic diagram of the hardware operating environment of the drone parameter debugging device involved in the embodiment of the present invention.

[0048] It should be noted that the embodiments of the present invention relate to drone parameter debugging equipment in the field of drone technology. Specifically, the drone parameter debugging equipment can be a drone, an aircraft, a smartphone, a PC (Personal Computer), a tablet computer, a portable computer, etc.

[0049] like Figure 1 As shown, the UAV parameter debugging device may include: a processor 1001, such as a CPU; a communication bus 1002; a user interface 1003; a network interface 1004; and a memory 1005. The communication bus 1002 is used to establish communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0050] Those skilled in the art will understand that Figure 1The structure of the UAV parameter debugging equipment shown does not constitute a limitation on the UAV parameter debugging equipment. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0051] like Figure 1 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a UAV parameter debugging program.

[0052] exist Figure 1 In the terminal shown, network interface 1004 is mainly used to connect to the backend server and communicate with it; user interface 1003 is mainly used to connect to the client and communicate with it; and processor 1001 can be used to call the UAV parameter debugging program stored in memory 1005 and perform the following operations:

[0053] The drone is controlled to take off based on the test parameter values, and the flight status values ​​of the drone in this flight test are obtained;

[0054] Detect whether the flight status value matches the expected status value;

[0055] If the flight status value is detected to be mismatched with the expected status value, the adjustment direction of the test parameter value is determined based on the flight status value and the pre-stored optimal status value, and the adjustment range of the test parameter value is determined based on the status problem points of the flight status value.

[0056] Based on the adjustment direction and the adjustment range, the estimated parameter values ​​of the UAV in the next flight test are generated. The estimated parameter values ​​are used as the test parameter values, and the step of controlling the UAV to take off based on the test parameter values ​​is returned to be executed until the flight state value is detected to match the expected state value. Then the test parameter value is determined to be the target parameter value.

[0057] Furthermore, the operation of obtaining the flight status values ​​of the UAV during this flight test includes:

[0058] Acquire flight video data, wherein the flight video data is obtained by recording and monitoring the flight test process of the UAV;

[0059] Multiple image data are extracted from the flight video data, and the flight status value of the UAV in this flight test is calculated based on each image data.

[0060] Furthermore, the operation of determining the adjustment direction of the test parameter value based on the flight state value and the pre-stored optimal state value includes:

[0061] Obtain the pre-stored optimal state value and the optimal parameter value corresponding to the pre-stored optimal state value;

[0062] Calculate the first difference between the flight state value and the expected state value, and calculate the second difference between the pre-stored optimal state value and the expected state value;

[0063] Detect whether the first difference is less than the second difference;

[0064] If the first difference is detected to be less than the second difference, then the adjustment direction of the test parameter value is determined to be from the optimal parameter value to the test parameter value;

[0065] If the first difference is detected to be greater than or equal to the second difference, then the adjustment direction of the test parameter value is determined to be from the test parameter value to the optimal parameter value.

[0066] Furthermore, after determining that the adjustment direction of the test parameter value is from the optimal parameter value to the test parameter value, the processor 1001 can also be used to call the UAV parameter debugging program stored in the memory 1005 to perform the following operations:

[0067] Update the pre-stored optimal state value to the flight state value;

[0068] Update the optimal parameter value to the test parameter value.

[0069] Furthermore, after the step of detecting that the first difference is less than the second difference, the processor 1001 can also be used to call the UAV parameter debugging program stored in the memory 1005 and perform the following operations:

[0070] Obtain the flight log of the UAV during this flight test, and check whether the flight attribute data in the flight log is within the preset standard range;

[0071] If the flight attribute data is detected to be within the preset standard range, then the flight log is saved;

[0072] If the flight attribute data is detected to be outside the preset standard range, an error message will be output to remind the tester to troubleshoot the drone.

[0073] Furthermore, the operation of determining the adjustment range of the test parameter value based on the state problem point of the flight state value includes:

[0074] The state problem points of the flight state value are determined based on the relationship between the flight state value and the expected state value;

[0075] Based on the status problem point, the parameter setting range corresponding to the status problem point is obtained from the preset problem solution library, and the parameter setting range is used as the adjustment range of the test parameter value.

[0076] Furthermore, the operation of determining the state problem point of the flight state value based on the magnitude relationship between the flight state value and the expected state value includes:

[0077] Detect whether the flight status value is less than the expected status value;

[0078] If the detected flight status value is less than the expected status value, then the problem with the flight status value is determined to be that the flight status value is too small;

[0079] If the detected flight status value is greater than the expected status value, then the problem with the flight status value is determined to be that the flight status value is too large.

[0080] Based on the above structure, various embodiments of the UAV parameter debugging method are proposed.

[0081] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the UAV parameter debugging method of the present invention. It should be noted that although the logical order is shown in the flowchart, in some cases, the UAV parameter debugging method of the present invention may execute the steps shown or described in a different order. In this embodiment, the executing entity of the UAV parameter debugging method can be a vehicle, personal computer, smartphone, or other device; there is no limitation in this embodiment. For ease of description, the executing entity is omitted from the following description of each embodiment. The UAV parameter debugging method includes:

[0082] Step S10: Control the drone to take off based on the test parameter values, and obtain the flight status values ​​of the drone in this flight test;

[0083] The drone is controlled to take off based on pre-set test parameter values, and the flight status values ​​of the drone during this flight test are obtained.

[0084] It should be noted that the purpose of drone flight testing is to adjust the drone's various parameters to achieve the functions corresponding to each parameter. Therefore, to facilitate quickly finding suitable flight control parameters, a simple page can be created on the testing equipment (including but not limited to the user's mobile terminal) during parameter tuning. This page can have many input boxes, each corresponding to a different flight control attribute. Before adjusting parameters, each parameter can be read and its current value checked. Then, a specific parameter can be fine-tuned, and the aircraft can be taken off based on the adjusted parameters. The test parameter values ​​mentioned above refer to the flight control parameter values ​​during the testing process. The aforementioned testing equipment includes, but is not limited to, the user's mobile terminal, and this testing equipment must have an application installed to control the drone's flight test.

[0085] In one feasible implementation, when optimizing a certain flight control parameter of a UAV, a random value can be automatically generated by testing equipment, or the parameter value can be entered by the tester in an input box. Then, based on this test parameter value, the UAV is controlled to take off, and the flight status value of the UAV during this flight test is obtained. This flight status value includes, but is not limited to, the UAV's displacement, flight acceleration, and offset angle within a preset time period. It should be understood that the aforementioned flight status value represents the final flight performance of the UAV.

[0086] Furthermore, in a feasible embodiment, step S10, the step of "obtaining the flight status value of the UAV in this flight test" includes:

[0087] Step S101: Obtain flight video data, wherein the flight video data is obtained by recording and monitoring the flight test process of the UAV;

[0088] The flight test process of the drone was monitored by recording video to obtain flight video data.

[0089] In one feasible implementation, a camera is installed on the drone's fuselage to continuously record video from the time the drone starts up until it stops, thus obtaining a flight video data.

[0090] Step S102: Extract multiple image data from the flight video data, and calculate the flight status value of the UAV in this flight test based on each image data.

[0091] Multiple image data are extracted from the flight video data, and the flight status value of the UAV in this flight test is calculated based on each image data.

[0092] In one feasible implementation, the flight video data is decomposed into multiple frames of image data. Then, by combining the time and the positional changes of fixed reference objects in the background in the video within the image data, the displacement, velocity, acceleration, and offset angle of the UAV within a preset time period are calculated. The offset angle of the UAV during the flight test can also be obtained from the azimuth changes acquired by various sensors and gyroscopes on the aircraft.

[0093] Thus, this invention records the flight process of the drone using a camera installed on the drone body, and extracts the drone's flight status values ​​from the recorded video data, thereby converting the drone's flight performance into numerical form and more intuitively reflecting the drone's parameter debugging progress.

[0094] Step S20: Detect whether the flight status value matches the expected status value;

[0095] The test checks whether the drone's flight status values ​​match the expected status values.

[0096] It should be noted that the aforementioned expected state values ​​represent the anticipated effects of the drone's flight state. Flight state includes the drone's flight mode and flight adjustments. Flight modes include, but are not limited to, hovering, escaping, return-to-home, recording, and following a person. Flight conditions include, but are not limited to, flight speed adjustment and flight state switching. In essence, each flight state corresponds to a function of the drone, and the expected state value is the drone's state value when that function is achieved. It should be understood that the aforementioned expected state value can be a single value or multiple values; that is, it can be a fixed value or a threshold range.

[0097] In one feasible implementation, since the flight status values ​​include the displacement, angular velocity, and offset angle of the UAV within a preset time period, the corresponding expected status values ​​also include, but are not limited to, the displacement, angular velocity, and offset angle within the preset time period. After obtaining the flight status values ​​for this test, it is checked whether the current flight status values ​​match the expected status values.

[0098] Step S30: If the flight status value is detected to be mismatched with the expected status value, then the adjustment direction of the test parameter value is determined based on the flight status value and the pre-stored optimal status value, and the adjustment range of the test parameter value is determined based on the status problem points of the flight status value.

[0099] If a mismatch is detected between the flight status value and the expected status value, the adjustment direction of the test parameter value is determined based on the flight status value and the pre-stored optimal status value, and the adjustment range of the test parameter value is determined based on the status problem points of the flight status value.

[0100] It's important to note that optimizing drone flight control parameters is a continuous process. It involves identifying the specific parameters that need optimization for the current test, given that other flight control parameters are already fixed. This optimized parameter is then established and refined before moving on to the next parameter. During the optimization of a particular flight control parameter, the flight state value corresponding to the best-performing flight test from the completed flight tests is saved—this is the aforementioned optimal state value. Furthermore, this optimal state value includes, but is not limited to, displacement, acceleration, and offset angle within a preset time period.

[0101] In one feasible implementation, for the case where the flight status value in this flight test is the displacement within a preset time period, that is, the displacement of the UAV within 1 minute, assuming the flight status value is 4 meters, the pre-stored optimal status value is 5 meters, and the expected status value is 6 meters, then it can be determined that the flight status value in this flight test is not equal to the expected status value. Therefore, the adjustment direction of the test parameter value is determined based on the flight status value and the optimal status value, and the adjustment range of the test parameter value is determined based on the status problem points of the flight status value.

[0102] Step S40: Based on the adjustment direction and the adjustment range, generate the estimated parameter value of the UAV in the next flight test, use the estimated parameter value as the test parameter value, and return to execute the step of controlling the UAV to take off based on the test parameter value until the flight state value is detected to match the expected state value, then determine the test parameter value as the target parameter value.

[0103] Based on the adjustment direction and adjustment range, the estimated parameter values ​​of the UAV are generated for the next flight test. The estimated parameter values ​​are used as test parameter values. The UAV is controlled to take off again based on the test parameter values ​​until the flight status value is detected to match the expected status value. Then the test parameter value is determined to be the target parameter value.

[0104] In one feasible implementation, the adjustment direction and range of flight control parameters are obtained through an automatic analysis algorithm in the testing equipment, and the estimated parameter values ​​of the UAV in the next flight test are automatically generated. Then, control commands are generated based on the estimated parameter values ​​to control the UAV to take off again. The process continues until the flight status value is detected to match the expected status value. At this point, the test parameter value is determined to be the target parameter value, and the parameter debugging ends.

[0105] It should be noted that the above target parameter values ​​are the final parameter tuning results, representing the flight control parameter values ​​corresponding to the expected effect.

[0106] In one feasible implementation, such as Figure 3As shown, after a drone flight test, the system automatically extracts the best results from pre-stored historical flight tests, reads the current flight results and flight log bin, compares the historical best results with the current flight results, determines the direction of flight control parameter adjustments based on the comparison results, and then judges whether the current flight results meet expectations. If the current flight results do not meet expectations, the automatic analysis algorithm automatically adjusts the flight control parameters, outputs recommended flight control parameters, inputs them into the parameter input box of the application, and the testing equipment transmits the parameters in the input box to the drone's flight controller to control the drone to take off again and obtain the flight data at the time of takeoff. If the current flight results meet expectations, the drone parameter debugging ends.

[0107] In this embodiment, the UAV parameter debugging method of the present invention controls the UAV to take off based on pre-set test parameter values; the flight test process of the UAV is recorded and monitored to obtain flight video data, multiple image data are extracted from the flight video data, and the flight status value of the UAV in this flight test is calculated based on each image data; it is detected whether the flight status value of the UAV in this test matches the expected status value; if the flight status value does not match the expected status value, the adjustment direction of the test parameter value is determined based on the flight status value and the pre-stored optimal status value, and the adjustment range of the test parameter value is determined based on the status problem points of this flight test; based on the adjustment direction and adjustment range, the estimated parameter value of the UAV in the next flight test is generated, and the estimated parameter value is used as the test parameter value, and the UAV is controlled to take off again based on the test parameter value; if the flight status value matches the expected status value, that is, the current flight effect achieves the expected effect, the test parameter value is determined to be the target parameter value, and the parameter debugging ends.

[0108] Thus, this invention controls the drone to take off based on pre-set test parameter values ​​and acquires the drone's flight status values ​​during the current flight test, detecting whether these flight status values ​​match the expected status values. If a mismatch is detected, the adjustment direction of the test parameter values ​​is determined based on the flight status values ​​and pre-stored optimal status values, and the adjustment range of the test parameter values ​​is determined based on the problematic points of the flight status values. Then, the test parameter values ​​are adjusted based on the adjustment direction and adjustment range to generate estimated parameter values ​​for the drone in the next flight test. These estimated parameter values ​​are used as test parameter values ​​to control the drone to take off again in the next flight test. If a match is detected between the flight status values ​​and the expected status values, then the test parameter values ​​are determined to be the target parameter values, and parameter debugging ends. Thus, compared to the traditional method that requires testers to manually analyze test problems and manually input test parameter values, this embodiment of the invention determines the adjustment direction of test parameter values ​​based on the flight state values ​​in the current test and the pre-stored optimal state values, determines the adjustment range of test parameter values ​​based on the state problem points of the flight state values, and then automatically adjusts the test parameter values ​​according to the adjustment direction and adjustment range to obtain the test parameter values ​​for the next flight test, until the flight state of the UAV meets the expected effect and the test parameter values ​​corresponding to the expected effect are obtained, thereby improving the parameter debugging efficiency of the UAV.

[0109] Furthermore, based on the first embodiment of the UAV parameter debugging method of the present invention described above, a second embodiment of the UAV parameter debugging method of the present invention is proposed.

[0110] In this embodiment, step S30, "determining the adjustment direction of the test parameter value based on the flight state value and the pre-stored optimal state value," may include:

[0111] Step A10: Obtain the pre-stored optimal state value and the optimal parameter value corresponding to the pre-stored optimal state value;

[0112] Obtain the pre-stored optimal state value and the optimal parameter value corresponding to that optimal state value.

[0113] In one feasible implementation, it is assumed that the flight control parameter for this flight test is 22, which is the test parameter value mentioned above, and the flight control parameter corresponding to the pre-stored optimal state value is 25, which is the optimal parameter value mentioned above.

[0114] Step A20: Calculate the first difference between the flight state value and the expected state value, and calculate the second difference between the pre-stored optimal state value and the expected state value;

[0115] Calculate the difference between the flight state value and the expected state value (hereinafter referred to as the first difference for distinction), and calculate the difference between the optimal state value and the expected state value (hereinafter referred to as the second difference for distinction).

[0116] In one feasible implementation, given a flight state value of 4 meters, a pre-stored optimal state value of 5 meters, and an expected state value of 6 meters, a first difference of 2 and a second difference of 1 can be obtained.

[0117] Step A30: Detect whether the first difference is less than the second difference;

[0118] Check if the first difference is less than the second difference.

[0119] Step A40: If the first difference is detected to be less than the second difference, then the adjustment direction of the test parameter value is determined to be from the optimal parameter value to the test parameter value.

[0120] If the first difference is detected to be less than the second difference, then the direction of adjustment of the test parameter value is determined to be from the optimal parameter value to the test parameter value.

[0121] In one feasible implementation, assuming the flight state value is 10 meters, the expected state value is 12 meters, and the pre-stored optimal state value is 8 meters, then the first difference is less than the second difference, meaning that the flight effect of this test is closer to the expected flight effect than the pre-stored flight effect. Therefore, with the optimal parameter value being 25 and the test parameter value being 22, the adjustment direction of the test parameter value is determined to be from 25 to 22, that is, the test parameter value is adjusted to be less than 22.

[0122] Step A50: If the first difference is detected to be greater than or equal to the second difference, then the adjustment direction of the test parameter value is determined to be from the test parameter value to the optimal parameter value.

[0123] If the first difference is detected to be greater than or equal to the second difference, then the direction of adjustment of the test parameter value is determined to be from the test parameter value to the optimal parameter value.

[0124] In one feasible implementation, assuming the flight state value is 4 meters, the expected state value is 6 meters, and the pre-stored optimal state value is 5 meters, then the first difference is greater than the second difference, that is, the pre-stored flight effect is closer to the expected flight effect than the flight effect of this test. So, with the optimal parameter value being 25 and the test parameter value being 22, the adjustment direction of the test parameter value is determined to be from 22 to 25, that is, the test parameter value is adjusted in a direction greater than 22.

[0125] Thus, this invention obtains the optimal parameter value corresponding to the pre-stored optimal state value, calculates the first difference between the current flight state value and the expected state value, and calculates the second difference between the optimal state value and the expected state value. When the first difference is greater than the second difference, it indicates that the current flight performance is worse than the flight performance corresponding to the optimal state value. Therefore, the current test parameter value needs to be adjusted towards the direction of the optimal parameter value. When the first difference is less than the second difference, it indicates that the current flight performance is better than the flight performance corresponding to the optimal state value. Therefore, the current test parameter value needs to be adjusted towards the direction of the optimal parameter value, thereby determining the direction of parameter adjustment.

[0126] Furthermore, in a feasible embodiment, after the step of "detecting that the first difference is less than the second difference" in step A40, the method may further include:

[0127] Step B10: Update the pre-stored optimal state value to the flight state value;

[0128] Step B20: Update the optimal parameter value to the test parameter value.

[0129] When the first difference is less than the second difference, the pre-stored optimal state value is updated to the flight state value in this test, and the optimal parameter value is updated to the test parameter value in this flight test.

[0130] In this way, the state and parameter values ​​corresponding to the best effect are automatically and dynamically updated, which makes it easier to readjust the drone's parameters later.

[0131] Furthermore, in a feasible embodiment, after the step of "detecting that the first difference is less than the second difference" in step A40, the method may further include:

[0132] Step C10: Obtain the flight log of the UAV during this flight test, and check whether the flight attribute data in the flight log is within the preset standard range;

[0133] When the first difference is less than the second difference, the flight log recorded by the UAV in this flight test is obtained, and the flight attribute data in the flight log is checked to see if it is within the preset standard range.

[0134] It should be noted that in drone flight testing, the flight attribute data to be checked varies depending on the flight control parameters. For example, in PID (Proportional, Integral, Differential) tuning tests, the flight attribute data to be checked includes, but is not limited to, gyroscope curves and motor outputs, with the corresponding preset standard range being gyroscope curve smoothing and motor output smoothing.

[0135] In one feasible implementation, after the flight test is completed, the flight log recorded by the UAV during the flight test is obtained. The flight log records some attribute data corresponding to the functions of the UAV in this test. Each of these attribute data has a corresponding normal variation range, namely the aforementioned preset standard range. The flight attribute data is then checked to see if it is within the preset standard range.

[0136] Step C20: If the flight attribute data is detected to be within the preset standard range, then the flight log is saved;

[0137] If the flight attribute data is detected to be within the preset standard range, the flight log is saved.

[0138] In one feasible implementation, if the flight attribute data of this flight test are detected to be within the preset standard range, that is, the various components of the UAV are operating normally, then the current flight log is stored.

[0139] Step C30: If the flight attribute data is detected to be outside the preset standard range, an error message is output to remind the tester to troubleshoot the UAV.

[0140] If the flight attribute data is detected to be outside the preset standard range, an error message will be output to remind the tester to troubleshoot the drone.

[0141] In one feasible implementation, if the flight attribute data of this flight test is detected to be outside the preset standard range, that is, the flight effect achieved by the UAV in this flight test is not real, then an abnormal prompt needs to be output to remind the test personnel to troubleshoot the UAV.

[0142] In another feasible implementation, during the PID test of the UAV, an automatic analysis algorithm in the testing equipment provides a flight control parameter p. The testing equipment simulates a flight tester inputting p into the input box of the application, and then transmits this flight control parameter to the flight control program to control the UAV to take off. At the same time as takeoff, the automatic analysis module starts recording, recording the entire takeoff effect and writing it to the current flight log bin file. The recording stops and the log writing ends when the aircraft lands. Then, the automatic analysis algorithm is started, and the algorithm extracts the previously stored best effect (i.e., the optimal state value), obtains the corresponding video recording and log bin file, and then compares it with the current video recording and bin file. If the current video effect shows obvious slight fluctuations, then confirm whether the corresponding attributes in the bin file have also changed accordingly and within a safe range. After confirming that there are no errors, discard the previous best effect recording and bin file, save the current recording and bin file as the best effect, and then continue to reduce the p value for the next takeoff, recording, and comparison. If the video effect stabilizes too slowly or cannot return to the initial stable state, it means that the p value is too small. Discard the current recording and bin file, increase the p value, and then perform the next takeoff, recording, and comparison.

[0143] Thus, this invention avoids situations where the flight performance of a drone improves due to abnormalities in the drone itself by checking log data when the current test flight performance is better than the historical best performance, thereby avoiding randomness.

[0144] In this embodiment, the UAV parameter debugging method of the present invention obtains a pre-stored optimal state value and the optimal parameter value corresponding to the optimal state value; calculates a first difference between the flight state value and the expected state value, and calculates a second difference between the optimal state value and the expected state value; detects whether the first difference is less than the second difference; if the first difference is detected to be less than the second difference, it determines that the adjustment direction of the test parameter value is from the optimal parameter value to the test parameter value, and then updates the pre-stored optimal state value to the flight state value in this test, and updates the optimal parameter value to the test parameter value in this flight test; when the first difference is less than the second difference, it obtains the flight log recorded by the UAV in this flight test, and detects whether the flight attribute data in the flight log is within the preset standard range; if the flight attribute data is detected to be within the preset standard range, it saves the flight log; if the flight attribute data is detected to be outside the preset standard range, it outputs an abnormal prompt to remind the test personnel to troubleshoot the UAV; if the first difference is detected to be greater than or equal to the second difference, it determines that the adjustment direction of the test parameter value is from the test parameter value to the optimal parameter value.

[0145] Thus, by comparing the flight performance achieved by the UAV in this flight test with the pre-stored historical best performance, the present invention determines the direction for adjusting the test parameter values ​​in the next flight test, providing a reliable basis for automatically generating test parameter values.

[0146] Furthermore, based on the first and / or second embodiments of the UAV parameter debugging method of the present invention described above, a third embodiment of the UAV parameter debugging method of the present invention is proposed.

[0147] In this embodiment, step S30, "determining the adjustment range of the test parameter value based on the state problem point of the flight state value," may include:

[0148] Step D10: Determine the state problem point of the flight state value based on the relationship between the flight state value and the expected state value;

[0149] The problem points in this flight test are determined based on the relationship between the flight status value and the expected status value.

[0150] Furthermore, in one feasible implementation, step D10 above may include:

[0151] Step D101: Detect whether the flight status value is less than the expected status value;

[0152] Step D102: If the flight status value is detected to be less than the expected status value, then the problem with the flight status value is determined to be that the flight status value is too small.

[0153] Step D103: If the detected flight status value is greater than the expected status value, then the status problem of the flight status value is determined to be that the flight status value is too large.

[0154] The system checks whether the flight status value in this flight test is lower than the expected status value. If the flight status value is lower than the expected status value, the problem is determined to be that the flight status value is too small. If the flight status value is higher than the expected status value, the problem is determined to be that the flight status value is too large.

[0155] In one feasible implementation, assuming the flight state value is the displacement of the UAV within a preset time period, the flight state value is 4 meters, and the expected state value is 6 meters, then the state problem point in this flight test is determined to be that the UAV displacement is too small.

[0156] Step D20: Obtain the parameter setting range corresponding to the status problem point from the preset problem solution library, and use the parameter setting range as the adjustment range of the test parameter value.

[0157] Based on the status problem point, the parameter setting range corresponding to the status problem point is obtained from the preset problem solution library, and the parameter setting range is used as the adjustment range of the test parameter value.

[0158] In one feasible implementation, the aforementioned preset problem-solving library stores various problems that may occur during the testing of the UAV, and each problem corresponds to an adjustment range of flight control parameters. Assuming the current problem is that the UAV's displacement is too small, the preset problem-solving library finds that the corresponding parameter range for this problem is 20 to 24. The current flight state value is 4 meters, the optimal state value is 5 meters, the expected state value is 6 meters, the test parameter value is 22, and the optimal parameter value is 25. It can be determined that the adjustment direction for the test parameter value is towards a value greater than 22. Therefore, the test parameter value can be adjusted within the aforementioned parameter range towards a value greater than 22, generating flight control parameter 23.

[0159] It should be noted that flight status values ​​include, but are not limited to, displacement, acceleration, and offset angle within a preset time period. In other words, if multiple status issues arise during a single flight test, the highest priority status issue will be addressed first, according to a pre-set priority.

[0160] In this embodiment, the UAV parameter debugging method of the present invention detects whether the flight status value in this flight test is less than the expected status value. If the flight status value is detected to be less than the expected status value, the status problem point of the flight status value is determined to be that the flight status value is too small. If the flight status value is detected to be greater than the expected status value, the status problem point of the flight status value is determined to be that the flight status value is too large. Based on the status problem point, the parameter setting range corresponding to the status problem point is obtained from the preset problem solution library, and the parameter setting range is used as the adjustment range of the test parameter value.

[0161] Thus, by comparing the differences between the flight performance achieved by the UAV in this flight test and the expected performance, the present invention identifies the status problem points in this flight test, and finds the corresponding parameter adjustment range based on the status problem points, providing another reliable basis for automatically generating test parameter values.

[0162] In addition, this invention also provides a device for adjusting the parameters of a drone.

[0163] Please refer to Figure 4 , Figure 4 This is a functional module diagram of an embodiment of the UAV parameter debugging device of the present invention, as shown below. Figure 4 As shown, the UAV parameter debugging device of the present invention includes:

[0164] The acquisition module 10 is used to control the drone to take off based on the test parameter values ​​and acquire the flight status values ​​of the drone in this flight test;

[0165] The judgment module 20 is used to detect whether the flight status value matches the expected status value;

[0166] The determination module 30 is used to determine the adjustment direction of the test parameter value based on the flight state value and the pre-stored optimal state value if the flight state value is detected to be mismatched with the expected state value, and to determine the adjustment range of the test parameter value based on the state problem points of the flight state value.

[0167] The adjustment module 40 is used to generate an estimated parameter value for the UAV in the next flight test based on the adjustment direction and the adjustment range, use the estimated parameter value as the test parameter value, and return to execute the step of controlling the UAV to take off based on the test parameter value until the flight state value is detected to match the expected state value, then the test parameter value is determined to be the target parameter value.

[0168] Furthermore, module 10 includes:

[0169] A monitoring unit is used to acquire flight video data, wherein the flight video data is obtained by recording and monitoring the flight test process of the UAV;

[0170] The image processing unit is used to extract multiple image data from the flight video data and calculate the flight status value of the UAV in this flight test based on each image data.

[0171] Further, module 30 is defined as including:

[0172] The historical data acquisition unit is used to acquire the pre-stored optimal state value and the optimal parameter value corresponding to the pre-stored optimal state value;

[0173] The difference calculation unit is used to calculate a first difference between the flight state value and the expected state value, and to calculate a second difference between the pre-stored optimal state value and the expected state value;

[0174] A difference detection unit is used to detect whether the first difference is less than the second difference;

[0175] The first direction determining unit is configured to determine, if the first difference is detected to be less than the second difference, the adjustment direction of the test parameter value is from the optimal parameter value to the test parameter value.

[0176] The second direction determining unit is configured to determine, if the first difference is detected to be greater than or equal to the second difference, that the adjustment direction of the test parameter value is from the test parameter value to the optimal parameter value.

[0177] Furthermore, the UAV parameter debugging device of the present invention also includes:

[0178] The first update module is used to update the pre-stored optimal state value to the flight state value;

[0179] The second update module is used to update the optimal parameter value to the test parameter value.

[0180] Furthermore, the UAV parameter debugging device of the present invention also includes:

[0181] The attribute data detection module is used to obtain the flight log of the UAV in this flight test and detect whether the flight attribute data in the flight log is within the preset standard range.

[0182] The log saving module is used to save the flight log if the flight attribute data is detected to be within the preset standard range;

[0183] The prompting module is used to output an abnormal prompt if the flight attribute data is detected to be outside the preset standard range, so as to remind the tester to troubleshoot the UAV.

[0184] Further, module 30 is defined as including:

[0185] The problem point determination unit is used to determine the state problem points of the flight state value based on the magnitude relationship between the flight state value and the expected state value.

[0186] The lookup unit is used to retrieve the parameter setting range corresponding to the status problem point from a preset problem-solving library based on the status problem point, and use the parameter setting range as the adjustment range of the test parameter value.

[0187] Furthermore, the problem point determination unit is also used to detect whether the flight status value is less than the expected status value; if the flight status value is detected to be less than the expected status value, then the problem point of the flight status value is determined to be that the flight status value is too small; if the flight status value is detected to be greater than the expected status value, then the problem point of the flight status value is determined to be that the flight status value is too large.

[0188] The present invention also provides a computer storage medium storing a drone parameter debugging program, wherein when the drone parameter debugging program is executed by a processor, the drone parameter debugging program method as described in any of the above embodiments is implemented.

[0189] The specific embodiments of the computer storage medium of the present invention are basically the same as the embodiments of the UAV parameter debugging program method of the present invention described above, and will not be repeated here.

[0190] The present invention also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the UAV parameter debugging method of the present invention as described in any of the above embodiments, which will not be repeated here.

[0191] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0192] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0193] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a drone parameter debugging device (which may be a TWS earphone, etc.) to execute the methods described in the various embodiments of the present invention.

[0194] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for adjusting parameters of a UAV, characterized in that, Includes the following steps: The drone is controlled to take off based on the test parameter values, and the flight status values ​​of the drone in this flight test are obtained. The flight status values ​​include the displacement, flight acceleration and offset angle of the drone within a preset time period. Detect whether the flight status value matches the expected status value, wherein the expected status value is the status value of the drone when it is able to perform drone functions; If the flight status value is detected to be mismatched with the expected status value, the adjustment direction of the test parameter value is determined based on the flight status value and the pre-stored optimal status value, and the adjustment range of the test parameter value is determined based on the status problem points of the flight status value. Based on the adjustment direction and the adjustment range, the estimated parameter value of the UAV in the next flight test is generated. The estimated parameter value is used as the test parameter value, and the step of controlling the UAV to take off based on the test parameter value is returned to be executed until the flight state value is detected to match the expected state value. Then the test parameter value is determined to be the target parameter value. The step of determining the adjustment direction of the test parameter value based on the flight state value and the pre-stored optimal state value includes: Obtain the pre-stored optimal state value and the optimal parameter value corresponding to the pre-stored optimal state value; Calculate the first difference between the flight state value and the expected state value, and calculate the second difference between the pre-stored optimal state value and the expected state value; Detect whether the first difference is less than the second difference; If the first difference is detected to be less than the second difference, then the adjustment direction of the test parameter value is determined to be from the optimal parameter value to the test parameter value; If the first difference is detected to be greater than or equal to the second difference, then the adjustment direction of the test parameter value is determined to be from the test parameter value to the optimal parameter value.

2. The UAV parameter debugging method as described in claim 1, characterized in that, The steps for obtaining the flight status values ​​of the UAV in this flight test include: Acquire flight video data, wherein the flight video data is obtained by recording and monitoring the flight test process of the UAV; Multiple image data are extracted from the flight video data, and the flight status value of the UAV in this flight test is calculated based on each image data.

3. The UAV parameter debugging method as described in claim 1, characterized in that, After the step of determining that the adjustment direction of the test parameter value is from the optimal parameter value to the test parameter value, the method further includes: Update the pre-stored optimal state value to the flight state value; Update the optimal parameter value to the test parameter value.

4. The UAV parameter debugging method as described in claim 1, characterized in that, After the step of detecting that the first difference is less than the second difference, the method further includes: Obtain the flight log of the UAV during this flight test, and check whether the flight attribute data in the flight log is within the preset standard range; If the flight attribute data is detected to be within the preset standard range, then the flight log is saved; If the flight attribute data is detected to be outside the preset standard range, an error message will be output to remind the tester to troubleshoot the drone.

5. The UAV parameter debugging method according to any one of claims 1 to 4, characterized in that, The step of determining the adjustment range of the test parameter value based on the state problem point of the flight state value includes: The state problem points of the flight state value are determined based on the relationship between the flight state value and the expected state value; Based on the status problem point, the parameter setting range corresponding to the status problem point is obtained from the preset problem solution library, and the parameter setting range is used as the adjustment range of the test parameter value.

6. The UAV parameter debugging method as described in claim 5, characterized in that, The step of determining the state problem point of the flight state value based on the relationship between the flight state value and the expected state value includes: Detect whether the flight status value is less than the expected status value; If the detected flight status value is less than the expected status value, then the problem with the flight status value is determined to be that the flight status value is too small; If the detected flight status value is greater than the expected status value, then the problem with the flight status value is determined to be that the flight status value is too large.

7. A device for adjusting parameters of an unmanned aerial vehicle (UAV), characterized in that, Includes the following steps: The acquisition module is used to control the drone to take off based on test parameter values ​​and acquire the flight status values ​​of the drone in this flight test, wherein the flight status values ​​include the displacement, flight acceleration and offset angle of the drone within a preset time period; The judgment module is used to detect whether the flight status value matches the expected status value, wherein the expected status value is the status value of the drone when it is able to perform drone functions; The determination module is configured to, if a mismatch is detected between the flight status value and the expected status value, determine the adjustment direction of the test parameter value based on the flight status value and a pre-stored optimal status value, and determine the adjustment range of the test parameter value based on the status problem points of the flight status value; acquire the pre-stored optimal status value and the optimal parameter value corresponding to the pre-stored optimal status value; calculate a first difference between the flight status value and the expected status value, and calculate a second difference between the pre-stored optimal status value and the expected status value; detect whether the first difference is less than the second difference; if the first difference is less than the second difference, determine that the adjustment direction of the test parameter value is from the optimal parameter value to the test parameter value; if the first difference is greater than or equal to the second difference, determine that the adjustment direction of the test parameter value is from the test parameter value to the optimal parameter value. The adjustment module is used to generate estimated parameter values ​​for the UAV in the next flight test based on the adjustment direction and the adjustment range, use the estimated parameter values ​​as the test parameter values, and return to execute the step of controlling the UAV to take off based on the test parameter values ​​until the flight state value is detected to match the expected state value, then the test parameter value is determined to be the target parameter value.

8. A device for adjusting parameters of an unmanned aerial vehicle (UAV), characterized in that, The UAV parameter debugging device includes: a memory and a processor. The memory stores a UAV parameter debugging program that can run on the processor. When the UAV parameter debugging program is executed by the processor, it implements the steps of the UAV parameter debugging method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a UAV parameter debugging program, which, when executed by a processor, implements the steps of the UAV parameter debugging method as described in any one of claims 1 to 6.

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