Unmanned aerial vehicle performance evaluation method, device, equipment and storage medium

Abstract

The invention discloses an unmanned aerial vehicle performance evaluation method, apparatus and device, and a storage medium. The method comprises the steps of calculating a subjective weight coefficient and an objective weight coefficient corresponding to each performance index of an unmanned aerial vehicle; determining the score of each performance index of the unmanned aerial vehicle according to the subjective weight coefficient, the objective weight coefficient and subjective and objective evaluation results of each performance index of the unmanned aerial vehicle; and based on the score of each performance index of the unmanned aerial vehicle and the weight coefficient allocated to each performance index, determining the comprehensive performance score of the unmanned aerial vehicle so as to evaluate the performance of the unmanned aerial vehicle. The comprehensive performance of the unmanned aerial vehicle can be accurately evaluated, and the safety and reliability of the unmanned aerial vehicle are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle performance evaluation, and in particular to a method, device, equipment and storage medium for unmanned aerial vehicle performance evaluation. Background Art

[0002] With the rapid development of drone technology, drones are increasingly being used in agriculture, logistics, surveying and mapping, emergency rescue, and other fields. However, existing drone performance evaluation methods typically use fixed weighting coefficients, making them difficult to adapt to the diverse needs of different user groups and application scenarios. Furthermore, traditional evaluation methods lack a comprehensive integration of subjective experience and objective data, resulting in deviations between evaluation results and actual application requirements.

[0003] Therefore, how to accurately evaluate the flight performance of UAVs is a technical problem that needs to be solved urgently. Summary of the Invention

[0004] The main purpose of the present invention is to provide a drone performance evaluation method, device, equipment and storage medium, which can accurately evaluate the comprehensive performance of drones and improve the safety and reliability of drones.

[0005] In a first aspect, the present application provides a method for evaluating the performance of a drone, wherein the method comprises the steps of:

[0006] Calculate the subjective weight coefficient and objective weight coefficient corresponding to each performance indicator of the UAV;

[0007] Determine the score of each performance indicator of the drone based on the subjective weight coefficient and the objective weight coefficient and the subjective and objective evaluation results of each performance indicator of the drone;

[0008] Based on the scores of each performance indicator of the drone and the weight coefficient assigned to each performance indicator, the comprehensive performance score of the drone is determined to evaluate the performance of the drone.

[0009] In combination with the first aspect above, as an optional implementation method, based on the statistical results of user importance, the subjective experience of each performance item and the importance of the objective performance indicator are scored;

[0010] Normalize the subjective experience of each performance item and the importance score of the objective performance indicator;

[0011] Based on the proportion of the total normalized scores of users on subjective experience and objective performance, the subjective weight and objective weight corresponding to each performance indicator of the drone are calculated.

[0012] In combination with the first aspect above, as an optional implementation method, based on historical user rating data, user group characteristics, usage scenario labels, and corresponding subjective weight and objective weight distribution results are extracted as a training set;

[0013] The training set is used to train a weight prediction model, and the current user group characteristics and scene labels are input into the trained weight prediction model to output updated subjective and objective weight coefficients to dynamically adjust the subjective weights and objective weights corresponding to various performance indicators of the drone.

[0014] In combination with the first aspect above, as an optional implementation method, user feedback on the evaluation results is collected, and the training set is updated regularly to iteratively update the weight prediction model.

[0015] In combination with the first aspect above, as an optional implementation method, according to formula s i =S 客观 *W1+S 主观 *W2, calculate the scores of various performance indicators, where W1 is the objective weight coefficient and W2 is the subjective weight coefficient. The various performance indicators include: flight speed, flight altitude, endurance, load capacity, stability, controllability and wind resistance.

[0016] In combination with the first aspect above, as an optional implementation method, according to the formula: 客观 =i 实际 / i 设计最大 ×100, calculate the objective scores of flight speed, flight altitude, endurance time, and payload capacity, where i is the performance index of the UAV;

[0017] According to the formula: St客观 =100-(k x |ΔθX|+k y |ΔθY|+k z |ΔθZ|), calculate the objective stability score, where |ΔθX|, |ΔθY|, and |ΔθZ| are the absolute values ​​of the angular changes around the X-axis, Y-axis, and Z-axis, respectively, and k x 、k y and k z are the weight coefficients corresponding to the X-axis, Y-axis, and Z-axis;

[0018] According to the formula: Op客观 =wr·(1-T r / T r，max )+wa·(1-d error / d max ), calculate the objective score of controllability, where T r is the actual response time, T r，maxis the maximum allowed response time, d error is the error distance between the actual response flight trajectory or position and the expected response flight trajectory or position, d max is the maximum allowed error distance;

[0019] According to the formula: W客观 =(1-(D 实际 / D 设计最大 )-(A 实际 / A 设计最大 ))×100, calculate the objective score of wind resistance, where D 设计最大 The maximum permissible value of position deviation set by drone design and safety standards, A 设计最大 The maximum permissible values ​​of attitude changes set for drone design and safety standards;

[0020] Evaluate the subjective scores of each performance indicator based on experts or actual usage scenarios 主观 .

[0021] In combination with the first aspect above, as an optional implementation method, a weight coefficient assigned to each performance indicator is obtained using a hierarchical analysis method;

[0022] According to the formula: Calculate the comprehensive performance score of the drone, where n represents the total number of evaluation indicators, s i is the score of the i-th performance indicator, x i is the weight coefficient corresponding to the i-th performance indicator.

[0023] In a second aspect, the present application provides a drone performance evaluation device, which includes:

[0024] A calculation module is used to calculate the subjective weight coefficient and objective weight coefficient corresponding to each performance indicator of the UAV;

[0025] a processing module, configured to determine a score for each performance indicator of the drone based on the subjective weight coefficient and the objective weight coefficient and subjective and objective evaluation results of each performance indicator of the drone;

[0026] The evaluation module is used to determine the comprehensive performance score of the drone based on the scores of each performance indicator of the drone and the weight coefficient assigned to each performance indicator, so as to evaluate the performance of the drone.

[0027] In a third aspect, the present application further provides an electronic device comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method described in any one of the first aspects is implemented.

[0028] In a fourth aspect, the present application further provides a computer-readable storage medium storing computer program instructions, which, when executed by a computer, enables the computer to execute any one of the methods described in the first aspect.

[0029] This application provides a drone performance evaluation method, apparatus, device, and storage medium. The method includes the following steps: calculating subjective and objective weight coefficients corresponding to each drone performance indicator; determining scores for each drone performance indicator based on the subjective and objective weight coefficients and the subjective and objective evaluation results of each drone performance indicator; and determining a comprehensive performance score for the drone based on the scores for each drone performance indicator and the weight coefficients assigned to each performance indicator to evaluate the drone's performance. This application enables accurate evaluation of drone comprehensive performance, improving drone safety and reliability.

[0030] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0032] Figure 1 This is a flow chart of a method for evaluating drone performance provided in an embodiment of the present application;

[0033] Figure 2 This is a schematic diagram of a UAV performance evaluation device provided in an embodiment of the present application;

[0034] Figure 3 A schematic diagram of an electronic device provided in an embodiment of the present application;

[0035] Figure 4 A schematic diagram of a computer-readable program medium provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0037] Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the blocks shown in the drawings are functional entities that do not necessarily correspond to physically or logically separate entities.

[0038] The embodiments of the present application are further described in detail below with reference to the accompanying drawings.

[0039] Reference Figure 1 , Figure 1 The figure shows a flow chart of a UAV performance evaluation method provided by the present invention, as shown in FIG. Figure 1 As shown, the method includes the steps of:

[0040] Step S101: Calculate the subjective weight coefficient and objective weight coefficient corresponding to each performance indicator of the drone.

[0041] Specifically, based on the statistical results of user importance, the subjective experience of each performance item and the importance of the objective performance indicators are scored;

[0042] Normalize the subjective experience of each performance item and the importance score of the objective performance indicator;

[0043] Based on the proportion of the total normalized scores of users on subjective experience and objective performance, the subjective weight and objective weight corresponding to each performance indicator of the drone are calculated.

[0044] In one embodiment, based on historical user rating data, user group characteristics, usage scenario labels, and corresponding subjective weight and objective weight distribution results are extracted as a training set;

[0045] The training set is used to train a weight prediction model, and the current user group characteristics and scene labels are input into the trained weight prediction model to output updated subjective and objective weight coefficients to dynamically adjust the subjective weights and objective weights corresponding to various performance indicators of the drone.

[0046] In one embodiment, user feedback on the evaluation results is collected, and the training set is updated regularly to iteratively update the weight prediction model.

[0047] For easier understanding, let’s take an example: 1) User rating collection:

[0048] Subjective Importance Rating: Users rate the importance of their subjective experience of each feature (1-10 points).

[0049] Objective importance rating: Users rate the importance of each specific objective performance indicator of performance (1-10 points).

[0050] 2) Normalization

[0051] Method: Normalize all scores to the interval [0,1] to eliminate dimension differences

[0052] 3) Weight coefficient calculation

[0053] Subjective weight coefficient: the proportion of users' normalized ratings of their subjective experience to the total value.

[0054] Objective weight coefficient: the proportion of users' normalized scores on objective performance to the total value.

[0055] Machine learning driven weight prediction:

[0056] Training data set construction: Based on historical user rating data, user group characteristics, usage scenario labels and corresponding weight distribution (subjective weight, objective weight) are extracted as training samples.

[0057] Model training: Train the weight prediction model, with the input being user group characteristics and usage scenario labels, and the output being dynamic weight coefficients (W1, W2).

[0058] Online prediction: In real-time evaluation, the model predicts dynamic weight coefficients based on the current user group characteristics and scenario labels.

[0059] Dynamic adjustment mechanism:

[0060] Feedback loop: Collect user feedback on evaluation results (such as "satisfied" and "unsatisfied") as input for model optimization.

[0061] Model iteration: Regularly update the training dataset, retrain the model, and improve the accuracy of weight prediction.

[0062] This dynamic adjustment mechanism makes the evaluation results more targeted and practical, and can better meet the needs of different user groups or usage scenarios.

[0063] Step S102: Determine the scores of each performance indicator of the drone based on the subjective weight coefficient and the objective weight coefficient and the subjective and objective evaluation results of each performance indicator of the drone.

[0064] Specifically, according to formula s i =S 客观 *W1+S 主观 *W2, calculate the scores of various performance indicators, where W1 is the objective weight coefficient and W2 is the subjective weight coefficient. The various performance indicators include: flight speed, flight altitude, endurance, load capacity, stability, controllability and wind resistance.

[0065] In one embodiment, according to the formula: 客观 =i 实际 / i 设计最大×100, calculate the objective scores of flight speed, flight altitude, endurance time, and payload capacity, where i is the performance index of the UAV;

[0066] According to the formula: St客观 =100-(k x |ΔθX|+k y |ΔθY|+k z |ΔθZ|), calculate the objective stability score, where |ΔθX|, |ΔθY|, and |ΔθZ| are the absolute values ​​of the angular changes around the X-axis, Y-axis, and Z-axis, respectively, and k x 、k y and k z are the weight coefficients corresponding to the X-axis, Y-axis, and Z-axis;

[0067] According to the formula: Op客观 =wr·(1-T r / T r，max )+wa·(1-d error / d max ), calculate the objective score of controllability, where T r is the actual response time, T r，max is the maximum allowed response time, d error is the error distance between the actual response flight trajectory or position and the expected response flight trajectory or position, d max is the maximum allowed error distance;

[0068] According to the formula: W客观 =(1-(D 实际 / D 设计最大 )-(A 实际 / A 设计最大 ))×100, calculate the objective score of wind resistance, where D 设计最大 The maximum permissible value of position deviation set by drone design and safety standards, A 设计最大 The maximum permissible values ​​of attitude changes set for drone design and safety standards;

[0069] Evaluate the subjective scores of each performance indicator based on experts or actual usage scenarios 主观 . For easy understanding, examples are given to illustrate performance indicators and calculation formulas:

[0070] 1) Flight speed (V): Evaluated by the flight speed of the drone under specific conditions. The calculation formula is:

[0071] Flight speed score S v客观 =V 实际 / V 设计最大 ×100, V 设计最大It refers to the theoretical maximum value of the performance indicators determined during the design phase of the UAV.

[0072] Flight speed score S v主观 Experts or users rate their satisfaction with flight speed based on actual usage scenarios, such as whether the aircraft can stably and continuously maintain the expected speed during actual flight, with a score range of 0 to 100.

[0073] s v =s v客观 *W 1飞行速度 +S v主观 *W 2飞行速度 , s v : Comprehensive score of flight speed performance.

[0074] 2) Flight altitude (H): Evaluated by the maximum flight altitude that the drone can reach. The calculation formula is: Flight altitude score S H客观 =H 实际 / H 设计最大 ×100

[0075] H 设计最大 It refers to the theoretical maximum value of the performance indicators determined during the design phase of the UAV.

[0076] Flight altitude score S H主观 Experts or users rate the satisfaction with the flight altitude based on actual usage scenarios, such as obstacle avoidance during actual flight and adaptability to different weather conditions, with a score ranging from 0 to 100.

[0077] s H =s H客观 *W 1飞行高度 +S H主观 *W 2飞行高度 , s H : Comprehensive score of individual performance of flight altitude

[0078] 3) Endurance (T): This is evaluated by the continuous flight time of the drone when fully charged. The calculation formula is: Endurance S T客观 =T 实际 / T 设计最大 ×100,

[0079] T 设计最大 It refers to the theoretical maximum value of the performance indicators determined during the design phase of the UAV.

[0080] Battery life score S T主观 Experts or users rate satisfaction with battery life based on actual usage scenarios, such as fluctuations in battery life, energy efficiency, and whether it meets expectations, with a score ranging from 0 to 100.

[0081] sT =s T客观 *W 1续航时间 +S T主观 *W 2续航时间 , s T : The comprehensive score of the battery life performance.

[0082] 4) Load capacity (L): Evaluated by the maximum payload that the drone can carry. The calculation formula is: Load capacity score S L客观 =L 实际 / L 设计最大 ×100

[0083] , L 设计最大 It refers to the theoretical maximum value of the performance indicators determined during the design phase of the UAV.

[0084] Load capacity score S L主观 Experts or users rate satisfaction with payload capacity based on actual usage scenarios, such as how close the actual payload capacity is to user expectations and task adaptability (how it affects operational efficiency and whether frequent payload changes are required), with a score ranging from 0 to 100.

[0085] s L =s L客观 *W 1载荷能力 +S L主观 *W 2载荷能力 , s L : Comprehensive score of load capacity individual performance.

[0086] 5) Stability (St): This is evaluated by the stability of the drone's attitude during flight over a period of time. The calculation formula is: Stability score s St客观 =100-(k x |ΔθX|+k y |ΔθY|+k z |ΔθZ|), where |ΔθX|, |ΔθY|, and |ΔθZ| are the absolute values ​​of the angle changes around the X-axis, Y-axis, and Z-axis, respectively, and k x 、k y and k z are the weight coefficients corresponding to the X-axis, Y-axis, and Z-axis.

[0087] Stability Score St主观 Experts or users rate their satisfaction with stability based on actual usage scenarios. For example, the degree to which the aircraft's ability to maintain a stable flight attitude, remain unaffected by external interference, and accurately execute commands matches the user or expert's expectations, with a score ranging from 0 to 100.

[0088] s St =s St客观 *W1稳定性 +s St主观 *W 2稳定性 , s St : Comprehensive score of stability individual performance.

[0089] 6) Controllability (Op): This is evaluated by the drone's response speed and accuracy to control commands. It is calculated using indicators such as error rate and response time in the control test. The calculation formula is: Controllability score s Op客观 =wr·(1-T r / T r，max )+wa·(1-d error / d max ), calculate the objective score of controllability, where T r is the actual response time, T r，max is the maximum allowed response time, d error is the error distance between the actual response flight trajectory or position and the expected response flight trajectory or position, d max is the maximum allowed error distance.

[0090] Handling Score Op主观 Experts or users rate their satisfaction with controllability based on actual usage scenarios. For example, the degree to which response speed, control accuracy, flight mode switching, and ease of use match the user or expert's expectations is rated on a scale of 0 to 100.

[0091] s op =s op客观 *W 1操控性 +s Op主观 *W 2操控性 , s Op : Comprehensive score of stability individual performance.

[0092] Not only the response time is taken into consideration, but also the concept of error distance is introduced, making the evaluation of controllability more comprehensive.

[0093] 7) Wind resistance (W): The wind resistance score is calculated by quantifying the hovering stability of the drone under the corresponding maximum wind speed through simulation or actual testing. The calculation formula is: W客观 =(1-(D 实际 / D 设计最大 )-(A 实际 / A 设计最大 ))×100, where D 设计最大 The maximum permissible value of position deviation set by drone design and safety standards, A 设计最大 The maximum permissible value of attitude changes set by UAV design and safety standards.

[0094] Wind resistance score W主观Experts or users rate their satisfaction with wind resistance based on actual usage scenarios. For example, the degree to which the aircraft's ability to maintain stable flight and control under different wind speeds and directions matches the user or expert's expectations, with a score ranging from 0 to 100.

[0095] s W =s W客观 *W 1抗风能力 +s W主观 *W 2抗风能力 , s W The comprehensive score of individual wind resistance performance.

[0096] Not only the influence of position offset but also the influence of posture change is taken into account. By designing a calculation formula for wind resistance score, the evaluation of wind resistance is made more scientific and accurate.

[0097] Step S103: Based on the scores of each performance indicator of the drone and the weight coefficients assigned to each performance indicator, determine the comprehensive performance score of the drone to evaluate the performance of the drone.

[0098] Specifically, the analytic hierarchy process is used to obtain the weight coefficients assigned to each performance indicator;

[0099] According to the formula: Calculate the comprehensive performance score of the drone, where n represents the total number of evaluation indicators, s i is the score of the i-th performance indicator, x i is the weight coefficient corresponding to the i-th performance indicator.

[0100] In one embodiment, various performance indicators of the drone are monitored in real time, and an early warning is issued when an abnormality occurs or the indicator approaches a limit value.

[0101] In summary, a comprehensive and scientific drone performance evaluation system is constructed to conduct a comprehensive evaluation of various drone performance indicators from multiple performance dimensions; at the same time, a machine learning algorithm is introduced to collect and deeply analyze user rating data, so that the system can automatically learn and grasp the preferences of different user groups and the unique characteristics of usage scenarios, and then dynamically adjust the weight coefficients of various performance indicators, so that the evaluation results can accurately adapt to the needs of different users and scenarios; in addition, an innovative model that combines objective and subjective scores is used to calculate the comprehensive performance score, which effectively avoids the limitations of a single evaluation method and greatly improves the accuracy and reliability of the evaluation results.

[0102] The beneficial effects of this application include:

[0103] Dynamic weight adjustment: Dynamically adjust weight coefficients through machine learning algorithms and user preferences to make evaluation results more targeted and practical.

[0104] Combination of subjective and objective factors: Organically combine objective data with subjective scores to fully reflect the actual performance of the drone.

[0105] Multi-dimensional evaluation: covering multiple dimensions such as flight speed, flight altitude, endurance, payload capacity, stability, controllability and wind resistance, providing more comprehensive evaluation results.

[0106] Real-time monitoring and early warning: The integrated real-time performance monitoring function can detect anomalies and issue early warnings in a timely manner, improving the safety and reliability of drones.

[0107] Reference Figure 2 , Figure 2 FIG. 1 is a schematic diagram of a UAV performance evaluation device provided by the present invention, as shown in FIG. Figure 2 As shown, the device includes:

[0108] Calculation module 201: It is used to calculate the subjective weight coefficient and objective weight coefficient corresponding to each performance indicator of the drone.

[0109] Processing module 202 is used to determine the scores of various performance indicators of the drone based on the subjective weight coefficient and the objective weight coefficient and the subjective and objective evaluation results of various performance indicators of the drone.

[0110] Evaluation module 203: It is used to determine the comprehensive performance score of the drone based on the scores of each performance indicator of the drone and the weight coefficients assigned to each performance indicator, so as to evaluate the performance of the drone.

[0111] Furthermore, in a possible implementation, the calculation module is further configured to score the subjective experience of each performance item and the importance of the objective performance indicator based on the statistical results of user importance;

[0112] Normalize the subjective experience of each performance item and the importance score of the objective performance indicator;

[0113] Based on the proportion of the total normalized scores of users on subjective experience and objective performance, the subjective weight and objective weight corresponding to each performance indicator of the drone are calculated.

[0114] Furthermore, in a possible implementation, the processing module is further configured to extract user group characteristics, usage scenario labels, and corresponding subjective weights and objective weight distribution results as a training set based on historical user rating data;

[0115] The training set is used to train a weight prediction model, and the current user group characteristics and scene labels are input into the trained weight prediction model to output updated subjective and objective weight coefficients to dynamically adjust the subjective weights and objective weights corresponding to various performance indicators of the drone.

[0116] Furthermore, in a possible implementation, the processing module is further configured to collect user feedback on the evaluation results and regularly update the training set to iteratively update the weight prediction model.

[0117] Furthermore, in a possible implementation manner, the processing module is further configured to calculate the value of the formula s according to the formula i =S 客观 *W1+S 主观 *W2, calculate the scores of various performance indicators, where W1 is the objective weight coefficient and W2 is the subjective weight coefficient. The various performance indicators include: flight speed, flight altitude, endurance, load capacity, stability, controllability and wind resistance.

[0118] Furthermore, in a possible implementation manner, the calculation module is further configured to calculate the value of the formula: 客观 =i 实际 / i 设计最大 ×100, calculate the objective scores of flight speed, flight altitude, endurance time, and payload capacity, where i is the performance index of the UAV;

[0119] According to the formula: St客观 =100-(k x |ΔθX|+k y |ΔθY|+k z |ΔθZ|), calculate the objective stability score, where |ΔθX|, |ΔθY|, and |ΔθZ| are the absolute values ​​of the angular changes around the X-axis, Y-axis, and Z-axis, respectively, and k x 、k y and k z are the weight coefficients corresponding to the X-axis, Y-axis, and Z-axis;

[0120] According to the formula: Op客观 =wr·(1-T r / T r，max )+wa·(1-d error / d max ), calculate the objective score of controllability, where T r is the actual response time, T r，max is the maximum allowed response time, d error is the error distance between the actual response flight trajectory or position and the expected response flight trajectory or position, d max is the maximum allowed error distance;

[0121] According to the formula: W客观 =(1-(D 实际 / D 设计最大 )-(A 实际 / A 设计最大))×100, calculate the objective score of wind resistance, where D 设计最大 The maximum permissible value of position deviation set by drone design and safety standards, A 设计最大 The maximum permissible values ​​of attitude changes set for drone design and safety standards;

[0122] Evaluate the subjective scores of each performance indicator based on experts or actual usage scenarios 主观 .

[0123] Furthermore, in a possible implementation, the evaluation module is further configured to obtain a weight coefficient assigned to each performance indicator using an analytic hierarchy process;

[0124] According to the formula: Calculate the comprehensive performance score of the drone, where n represents the total number of evaluation indicators, s i is the score of the i-th performance indicator, x i is the weight coefficient corresponding to the i-th performance indicator.

[0125] Refer to the following Figure 3 The electronic device 300 according to this embodiment of the present invention will be described. Figure 3 The electronic device 300 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0126] like Figure 3 As shown, electronic device 300 is implemented as a general-purpose computing device. Components of electronic device 300 may include, but are not limited to, the aforementioned at least one processing unit 310, the aforementioned at least one storage unit 320, and a bus 330 connecting various system components (including storage unit 320 and processing unit 310).

[0127] The storage unit stores program codes, which can be executed by the processing unit 310, so that the processing unit 310 performs the steps according to various exemplary embodiments of the present invention described in the above “Example Method” section of this specification.

[0128] The storage unit 320 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 321 and / or a cache memory unit 322 , and may further include a read-only memory unit (ROM) 323 .

[0129] The storage unit 320 may also include a program / utility 324 having a set (at least one) of program modules 325, such program modules 325 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0130] Bus 330 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0131] The electronic device 300 can also communicate with one or more external devices (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 300, and / or any device that enables the electronic device 300 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication can occur via an input / output (I / O) interface 350. Furthermore, the electronic device 300 can also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 360. As shown, the network adapter 360 communicates with other modules of the electronic device 300 via a bus 330. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 300, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0132] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0133] According to the solution of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above-mentioned method of this specification is stored. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product, which includes program code. When the program product is executed on a terminal device, the program code is used to cause the terminal device to perform the steps according to various exemplary embodiments of the present invention described in the "Exemplary Methods" section of this specification.

[0134] refer to Figure 4As shown, a program product 400 for implementing the above method according to an embodiment of the present invention is described. The program product 400 may be a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0135] The program product may be implemented in any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0136] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0137] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0138] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0139] Furthermore, the above-described figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes illustrated in the above-described figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0140] The foregoing is merely a list of specific embodiments of the present application, intended to enable those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the broadest scope consistent with the principles and novel features of the present application.

[0141] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

Claims

1. A method for evaluating the performance of an unmanned aerial vehicle, characterized in that: include: Calculate the subjective weight coefficient and objective weight coefficient corresponding to each performance indicator of the UAV; Determine the score of each performance indicator of the drone based on the subjective weight coefficient and the objective weight coefficient and the subjective and objective evaluation results of each performance indicator of the drone; Based on the scores of each performance indicator of the drone and the weight coefficient assigned to each performance indicator, the comprehensive performance score of the drone is determined to evaluate the performance of the drone.

2. The method according to claim 1, characterized in that The calculation of the subjective weight coefficient and the objective weight coefficient corresponding to each performance indicator of the drone includes: Based on the statistical results of user importance, score the subjective experience of each performance and the importance of objective performance indicators; Normalize the subjective experience of each performance item and the importance score of the objective performance indicator; Based on the proportion of the total normalized scores of users on subjective experience and objective performance, the subjective weight and objective weight corresponding to each performance indicator of the drone are calculated.

3. The method according to claim 2, characterized in that Also includes: Based on historical user rating data, user group characteristics, usage scenario labels, and corresponding subjective and objective weight distribution results are extracted as training sets; The training set is used to train a weight prediction model, and the current user group characteristics and scene labels are input into the trained weight prediction model to output updated subjective and objective weight coefficients to dynamically adjust the subjective weights and objective weights corresponding to various performance indicators of the drone.

4. The method according to claim 3, characterized in that Also includes: Collect user feedback on the evaluation results and regularly update the training set to iteratively update the weight prediction model.

5. The method according to claim 1, wherein Determining the scores of the various performance indicators of the drone based on the subjective weight coefficient and the objective weight coefficient and the subjective and objective evaluation results of the various performance indicators of the drone includes: According to the formula i =S 客观 *W1+S 主观 *W2, calculate the scores of various performance indicators, where W1 is the objective weight coefficient and W2 is the subjective weight coefficient. The various performance indicators include: flight speed, flight altitude, endurance, load capacity, stability, controllability and wind resistance.

6. The method according to claim 5, characterized in that Also includes: According to the formula: 客观 =i 实际 / i 设计最大 ×100, calculate the objective scores of flight speed, flight altitude, endurance time, and payload capacity, where i is the performance index of the UAV; According to the formula: St客观 =100-(k x |ΔθX|+k y |ΔθY|+k z |ΔθZ|), calculate the objective stability score, where |ΔθX|, |ΔθY|, and |ΔθZ| are the absolute values ​​of the angular changes around the X-axis, Y-axis, and Z-axis, respectively, and k x 、k y and k z are the weight coefficients corresponding to the X-axis, Y-axis, and Z-axis; According to the formula: Op客观 =wr·(1-T r / T r，max )+wa·(1-d error / d max ), calculate the objective score of controllability, where T r is the actual response time, T r，max is the maximum allowed response time, d error is the error distance between the actual response flight trajectory or position and the expected response flight trajectory or position, d max is the maximum allowed error distance; According to the formula: W客观 =(1-(D 实际 / D 设计最大 )-(A 实际 / A 设计最大 ))×100, calculate the objective score of wind resistance, where D 设计最大 The maximum permissible value of position deviation set by drone design and safety standards, A 设计最大 The maximum permissible values ​​of attitude changes set for drone design and safety standards; Evaluate the subjective scores of each performance indicator based on experts or actual usage scenarios 主观 .

7. The method according to claim 1, characterized in that The comprehensive performance score of the drone is determined based on the scores of each performance indicator of the drone and the weight coefficients assigned to each performance indicator to evaluate the performance of the drone, including: The weight coefficients assigned to each performance indicator are obtained using the analytic hierarchy process; According to the formula: Calculate the comprehensive performance score of the drone, where n represents the total number of evaluation indicators, s i is the score of the i-th performance indicator, x i is the weight coefficient corresponding to the i-th performance indicator.

8. A drone performance evaluation device, characterized in that: include: A calculation module is used to calculate the subjective weight coefficient and objective weight coefficient corresponding to each performance indicator of the UAV; a processing module, configured to determine a score for each performance indicator of the drone based on the subjective weight coefficient and the objective weight coefficient and subjective and objective evaluation results of each performance indicator of the drone; The evaluation module is used to determine the comprehensive performance score of the drone based on the scores of each performance indicator of the drone and the weight coefficient assigned to each performance indicator, so as to evaluate the performance of the drone.

9. An electronic device, characterized in that: The electronic device comprises: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer program instructions are stored therein, and when the computer program instructions are executed by a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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