An unmanned aerial vehicle autonomous controllable computing platform credibility evaluation method

Abstract

This invention discloses a reliability evaluation method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs). The evaluation method includes the following steps: Step 1: Establishing a reliability evaluation index model for the autonomous and controllable computing platform for UAVs; Step 2: Determining a test plan based on the reliability evaluation index model in Step 1; Step 3: Selecting test cases based on the test plan in Step 2; Step 4: Evaluating the platform based on the test cases in Step 3 according to the evaluation index in Step 1, and giving a final conclusion. This invention addresses the current lack of reliable measurement and evaluation methods for UAV hardware-in-the-loop (HILL) simulation test platforms.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) evaluation, specifically relating to a method for evaluating the credibility of an autonomous and controllable computing platform for UAVs. Background Technology

[0002] The UAV flight control computing platform is a highly complex, real-time embedded system. It comprises both software systems (flight control software, operating system, etc.) and hardware circuits (high-performance processors, fiber optic communication chips, etc.). During its operation, the combinational and timing logic of the coordinated software and hardware operation is subject to strict constraints. Reliability assessment is particularly important for nearby UAVs, which are characterized by long operating cycles and complex, variable operating environments.

[0003] According to the ISO 9000-2000 definition, product quality refers to the degree to which a set of inherent product components fulfill requirements. Therefore, product quality is a complex combination of various elements, varying depending on the application and the quality requirements specified by the user. Reliability, as an indicator of product quality, has received increasing attention from designers and users in recent years.

[0004] Because there is no standard credibility evaluation index system in the current UAV testing system, and there is a lack of suitable basic quality attributes for credibility evaluation in the field of combinatorial logic and timing logic evaluation of UAV autonomous and controllable computing platforms, in order to achieve a comprehensive evaluation of the combinatorial logic and timing logic of near-space UAV autonomous and controllable computing platforms.

[0005] Currently, there are significant differences in the understanding of the meaning of credibility across various fields both domestically and internationally. Credibility measurement and assessment methods are lacking, established assessment models are unstructured, assessment criteria are unsystematic, and assessment methods lack universality. According to... Figure 1 The classic McCall quality model, as shown, bases its product quality concept on 11 elements, which address the product's operation, correction, and transfer stages. These elements reflect the product's reliability. For the operation stage, correctness, reliability, efficiency (real-time performance), availability, and integrity are the quality attributes characterizing product reliability.

[0006] Correctness: This refers to the degree to which a product meets the design specifications and user expectations under a predetermined environment; it requires that the product be free of errors.

[0007] Reliability: The degree to which a product can operate continuously without failure under specified time and conditions, in accordance with design requirements.

[0008] Real-time performance: This refers to the product's ability to complete a response or deliver output within a specified time.

[0009] Usability: This refers to the amount of work required for users to learn, use, and prepare input for and interpret the output of a product.

[0010] Integrity: The ability of a product to continue working even when subjected to accidental or intentional damage. Summary of the Invention

[0011] This invention provides a method for evaluating the credibility of an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs), addressing the current lack of reliable measurement and evaluation methods for UAV hardware-in-the-loop (HIBL) testing platforms.

[0012] This invention is achieved through the following technical solution:

[0013] A method for evaluating the credibility of an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) includes the following steps:

[0014] Step 1: Establish a credibility evaluation index model for the autonomous and controllable computing platform of unmanned aerial vehicles (UAVs);

[0015] Step 2: Determine the test plan based on the credibility assessment index model in Step 1;

[0016] Step 3: Select test cases based on the test plan in Step 2;

[0017] Step 4: Based on the test cases in Step 3, evaluate them according to the evaluation metrics in Step 1, and give a final conclusion.

[0018] Furthermore, step 1, establishing the credibility evaluation index model for the autonomous and controllable computing platform of the UAV, specifically involves establishing a credibility evaluation index system for the autonomous and controllable computing platform with correctness, real-time performance, and completeness as basic quality attributes; and establishing a credibility decomposition model based on the above system. The credibility decomposition model has four layers, including the credibility of the overall evaluation, the basic quality attributes of credibility, test items, and test cases.

[0019] For the k (k=3) basic quality attributes Attr1, Attr2,...,Attr of the autonomous and controllable computing platform k Any basic quality attribute Attr i Having t i Test Items Any test item Having n i,q test cases

[0020] Furthermore, assuming the evaluation set of the test case set is U≡{u1,u2}, corresponding to pass and fail respectively; the process of quantitatively evaluating the credibility of the autonomous and controllable computing platform includes the following steps:

[0021] Step 1.1: Based on the test case execution results, obtain the evaluation value at the test item level;

[0022] Step 1.2: Determine whether the test item meets the criteria for the specified interval based on its evaluation value.

[0023] Step 1.3: Calculate the evaluation values ​​of the basic quality attribute level based on the evaluation values ​​of the interval test item level;

[0024] Step 1.4: Based on the evaluation values ​​of the basic quality attribute levels, calculate the credibility evaluation results and derive the credibility evaluation index model of the UAV autonomous and controllable computing platform.

[0025] Furthermore, step 1.1 specifically involves, for any test case... Based on its execution results, the evaluation value vector can be obtained as follows: in:

[0026]

[0027] Assuming test items Having n i,q If there are 10 test cases, then its evaluation matrix R is:

[0028]

[0029] Since the weights of all use cases are equal, we can obtain The evaluation value vector is:

[0030] Furthermore, step 1.2 specifically involves, in order to avoid having only two levels when quantifying the final evaluation set, and to make the evaluation results more fair, setting the evaluation values ​​of the test item levels to range conformity;

[0031] Let V≡{v1,v2,v3,v4}={100,80,60,20} correspond to the four levels A, B, C, and D respectively; U≡{u1,u2}={100,0}, which corresponds to the pass / fail of the test case;

[0032] Calculate based on the evaluation values ​​of the test items:

[0033]

[0034] Then, interval matching is performed based on the interval in which the value of v falls, that is, the evaluation value of the test item is converted into:

[0035]

[0036] Furthermore, step 1.3 specifically involves assuming a certain basic quality attribute of credibility, Attr. i Having ti If there are 10 test items, then its evaluation matrix is:

[0037]

[0038] Since the weights of each test item are equal, then Attr i The normalized evaluation value is:

[0039]

[0040] Furthermore, step 1.4 specifically involves assuming the product has k basic quality attributes related to reliability, then its evaluation matrix is:

[0041]

[0042] The credibility assessment result of the autonomous and controllable computing platform is as follows:

[0043] η 1×4 ≡W×D=(y1,y2,y3,y4) (8)

[0044] Where W is the weight matrix of the basic quality attributes. Based on the evaluation set V, the final credibility of the autonomous and controllable computing platform is:

[0045]

[0046] Furthermore, step 2, determining the test plan, specifically involves using the existing test plan design tools of the joint testing platform to retrieve basic resource components from the resource repository, completing the test plan design, and storing it in the test plan library of the data archive. Each test plan corresponds to a product to be verified and evaluated, and each test plan includes several basic quality attribute evaluation plans for reliability verification and evaluation.

[0047] Furthermore, step 3, selecting test cases, specifically involves using the joint testing platform data archive to create a new basic quality attribute evaluation scheme under the test scheme. Each evaluation scheme corresponds to a basic quality attribute that affects the product reliability evaluation, and the evaluation scheme includes several test items for basic quality attribute evaluation.

[0048] For each test item, a test case set is designed using an automatic test case generation tool. The test case set contains several test cases for test item evaluation. The expected correct results of the test cases are generated through a standard comparison model. The generated test case set is stored in the test case database of the data archive.

[0049] Furthermore, the test cases for the basic quality attributes are specifically as follows:

[0050] Correctness test cases: When the combination of input parameter values ​​and the order of input parameters of the autonomous and controllable computing platform are within the legal range, the correctness of the combinational logic of the autonomous and controllable computing platform is verified and evaluated. The execution result of the test cases is determined by the value of the output parameters of the autonomous and controllable computing platform.

[0051] Real-time test cases: When the input time of the parameters of the autonomous and controllable computing platform is within the legal period, verify and evaluate the real-time performance of the timing logic of the autonomous and controllable computing platform. The execution result of the test cases is determined by the output time of the parameters of the autonomous and controllable computing platform.

[0052] Integrity test cases: When the combination of input parameter values, the order of input parameters, or the timing of input parameters are not within the legal range, the integrity of the functions and performance of the autonomous and controllable computing platform under illegal input is verified and evaluated. The execution result of the test cases is comprehensively determined by the values ​​and timing of the output parameters of the autonomous and controllable computing platform.

[0053] The beneficial effects of this invention are:

[0054] This invention can effectively evaluate the autonomous and controllable computing platform of UAVs; it solves the problem of complex platform combination logic and timing logic and the lack of systematic evaluation standards; by establishing a reliability evaluation model, the evaluation process is made clearer and more organized; by selecting basic reliability quality attributes, the evaluation process is simplified and the reliability of the evaluation results is improved. Attached Figure Description

[0055] Figure 1 This is a McCall software quality model diagram.

[0056] Figure 2 This is a hierarchical structure diagram of the reliability decomposition model of the autonomous and controllable computing platform of the present invention.

[0057] Figure 3 This is a basic flowchart of the pre-test preparation stage of the present invention.

[0058] Figure 4 This is a flowchart of the method of the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] The goal of this project is to evaluate the combinational and temporal logic of an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs). The focus is on the correctness of the combinational logic within reasonable sensor parameter ranges, the real-time performance of the temporal logic at reasonable input times, and the integrity of both logics under abnormal input data. Therefore, this project aims to establish a reliability evaluation index system for the autonomous and controllable computing platform, with correctness, real-time performance, and integrity as its basic quality attributes.

[0061] A method for evaluating the credibility of an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) includes the following steps:

[0062] Step 1: Establish a credibility evaluation index model for the autonomous and controllable computing platform of unmanned aerial vehicles (UAVs);

[0063] Step 2: Determine the test plan based on the credibility assessment index model in Step 1;

[0064] Step 3: Select test cases based on the test plan in Step 2;

[0065] Step 4: Based on the test cases in Step 3, evaluate them according to the evaluation metrics in Step 1, and give a final conclusion.

[0066] A method for assessing the credibility of an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) is proposed. Step 1, establishing a credibility assessment index model for the autonomous and controllable computing platform, specifically involves, to quantify the credibility of the autonomous and controllable computing platform, proposing a hierarchical structure for a credibility decomposition model, as follows: Figure 2 As shown, a reliability evaluation index system for an autonomous and controllable computing platform is established, with correctness, real-time performance, and completeness as basic quality attributes. Based on the above system, a reliability decomposition model is established, which consists of four layers including overall reliability assessment, basic reliability quality attributes, test items, and test cases.

[0067] For the k (k=3) basic quality attributes Attr1, Attr2,...,Attr of the autonomous and controllable computing platform k Any basic quality attribute Attr i Having t i Test Items Any test item Having n i,q test cases

[0068] A reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) is proposed. Assuming the evaluation set of the test case set is U≡{u1,u2}, corresponding to pass and fail respectively, the quantitative assessment process of the reliability of the autonomous and controllable computing platform includes the following steps:

[0069] Step 1.1: Based on the test case execution results, obtain the evaluation value at the test item level;

[0070] Step 1.2: Determine whether the test item meets the criteria for the specified interval based on its evaluation value.

[0071] Step 1.3: Calculate the evaluation values ​​of the basic quality attribute level based on the evaluation values ​​of the interval test item level;

[0072] Step 1.4: Based on the evaluation values ​​of the basic quality attribute levels, calculate the credibility evaluation results and derive the credibility evaluation index model of the UAV autonomous and controllable computing platform.

[0073] A reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs), wherein step 1.1 specifically involves, for any test case... Based on its execution results, the evaluation value vector can be obtained as follows: in:

[0074]

[0075] Assuming test items Having n i,q If there are 10 test cases, then its evaluation matrix R is:

[0076]

[0077] Since the weights of all use cases are equal, we can obtain The evaluation value vector is:

[0078] A reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs), wherein step 1.2 specifically involves, to avoid having only two levels in the final evaluation set quantification and to ensure a fairer evaluation result, range conformance is applied to the evaluation values ​​of the test item levels. Let V≡{v1,v2,v3,v4}={100,80,60,20} correspond to the four levels A, B, C, and D respectively; U≡{u1,u2}={100,0}, corresponding to the pass / fail status of the test cases. Based on the evaluation values ​​of the test items, the following calculation is performed:

[0079]

[0080] Then, interval matching is performed based on the interval in which the value of v falls, that is, the evaluation value of the test item is converted into:

[0081]

[0082] A method for evaluating the credibility of an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs), wherein step 1.3 specifically involves assuming a certain basic credibility quality attribute Attr i Having ti If there are 10 test items, then its evaluation matrix is:

[0083]

[0084] Since the weights of each test item are equal, then Attr i The normalized evaluation value is:

[0085]

[0086] A reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs), wherein step 1.4 specifically involves assuming the product has k basic reliability quality attributes, then its evaluation matrix is:

[0087]

[0088] The credibility assessment result of the autonomous and controllable computing platform is as follows:

[0089] η 1×4 ≡W×D=(y1,y2,y3,y4) (8)

[0090] Where W is the weight matrix of the basic quality attributes. Based on the evaluation set V, the final credibility of the autonomous and controllable computing platform is:

[0091]

[0092] A reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) is provided. Step 2, determining the test scheme, specifically involves using the existing test scheme design tools of the joint test platform to retrieve basic resource components from the resource repository, completing the test scheme design, and storing it in the test scheme library of the data archive. Each test scheme corresponds to a product to be verified and evaluated, and the test scheme includes several basic quality attribute evaluation schemes for reliability verification and evaluation.

[0093] A method for evaluating the credibility of an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs), wherein step 3, selecting test cases, specifically involves creating a basic quality attribute evaluation scheme under the test scheme using the joint test platform data archive. Each evaluation scheme corresponds to a basic quality attribute that affects the product credibility evaluation, and the evaluation scheme includes several test items for evaluating the basic quality attributes.

[0094] For each test item (typical processes such as taxiing, takeoff, climb, level flight, descent, and landing), a test case set is designed using an automatic test case generation tool. The test case set contains several test cases for evaluating the test item. The expected correct results of the test cases are generated through a standard comparison model, and the generated test case set is stored in the test case database of the data archive.

[0095] A reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs), wherein the test cases for the basic quality attributes are specifically as follows:

[0096] Correctness test cases: When the combination of input parameter values ​​and the order of input parameters of the autonomous and controllable computing platform are within the legal range, the correctness of the combinational logic of the autonomous and controllable computing platform is verified and evaluated. The execution result of the test cases is determined by the value of the output parameters of the autonomous and controllable computing platform.

[0097] Real-time test cases: When the input time of the parameters of the autonomous and controllable computing platform is within the legal period, verify and evaluate the real-time performance of the timing logic of the autonomous and controllable computing platform. The execution result of the test cases is determined by the output time of the parameters of the autonomous and controllable computing platform.

[0098] Integrity test cases: When the combination of input parameter values, the order of input parameters, or the timing of input parameters are not within the legal range, the integrity of the functions and performance of the autonomous and controllable computing platform under illegal input is verified and evaluated. The execution result of the test cases is comprehensively determined by the values ​​and timing of the output parameters of the autonomous and controllable computing platform.

Claims

1. A method for evaluating the credibility of an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs), characterized in that, The evaluation method includes the following steps: Step 1: Establish a credibility evaluation index model for the autonomous and controllable computing platform of unmanned aerial vehicles (UAVs); Step 2: Determine the test plan based on the credibility assessment index model in Step 1; Step 3: Select test cases based on the test plan in Step 2; Step 4: Based on the test cases in Step 3, evaluate them according to the evaluation metrics in Step 1, and give a final conclusion; Step 1, establishing the credibility evaluation index model for the autonomous and controllable computing platform of the UAV, specifically involves establishing a credibility evaluation index system for the autonomous and controllable computing platform with correctness, real-time performance, and completeness as basic quality attributes; and establishing a credibility decomposition model based on the above system. The credibility decomposition model has four layers, including the overall credibility evaluation, basic credibility quality attributes, test items, and test cases. For an independent and controllable computing platform Basic quality attributes Any basic quality attribute have Test Items , Any test item have test cases , ; Assume the comment set of the test case set is These correspond to passing and failing, respectively; the process of quantitatively assessing the credibility of an autonomous and controllable computing platform includes the following steps: Step 1.1: Based on the test case execution results, obtain the evaluation value at the test item level; Step 1.2: Determine whether the test item meets the criteria for the specified interval based on its evaluation value. Step 1.3: Calculate the evaluation values ​​of the basic quality attribute level based on the evaluation values ​​of the interval test item level; Step 1.4: Based on the evaluation values ​​of the basic quality attribute levels, calculate the credibility evaluation results and derive the credibility evaluation index model of the UAV autonomous and controllable computing platform.

2. The reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) according to claim 1, characterized in that, Step 1.1 specifically involves, for any test case... Based on its execution result, the evaluation value vector can be obtained as follows: ,in: (1) Assuming test items have For each test case, its evaluation matrix is... for: (2) Since the weights of all use cases are equal, we can obtain The evaluation value vector is: .

3. The reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) according to claim 1, characterized in that, Specifically, step 1.2 involves, in order to avoid having only two levels when quantifying the final evaluation set, and to make the evaluation results more fair, setting the evaluation values ​​of the test item levels to range conformity; make These correspond to four levels: A, B, C, and D. This corresponds to the pass / fail status of the test case; based on the evaluation value of the test item, calculate: (3) Then according to The intervals containing the values ​​are matched, that is, the evaluation values ​​of the test items are converted into: (4)。 4. The reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) according to claim 1, characterized in that, Specifically, step 1.3 involves assuming a certain basic quality attribute of credibility. have If there are 10 test items, then its evaluation matrix is: (5) Since the weights of each test item are equal, The normalized evaluation value is: (6)。 5. The reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) according to claim 1, characterized in that, Step 1.4 specifically involves assuming the product has a total of If there are several basic quality attributes for credibility, then the evaluation matrix is ​​as follows: (7) The credibility assessment result of the autonomous and controllable computing platform is as follows: (8) in, The weight matrix for the basic quality attributes; based on the comment set. The final credibility of the independently controllable computing platform is: (9)。 6. The reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) according to claim 1, characterized in that, Step 2, determining the test plan, specifically involves using the existing test plan design tools of the joint testing platform to retrieve basic resource components from the resource repository, completing the test plan design, and storing it in the test plan library of the data archive. Each test plan corresponds to a product to be verified and evaluated, and each test plan includes several basic quality attribute evaluation plans for reliability verification and evaluation.

7. The reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) according to claim 1, characterized in that, Step 3, selecting test cases, specifically involves creating a basic quality attribute evaluation scheme under the test scheme using the joint testing platform data archive. Each evaluation scheme corresponds to a basic quality attribute that affects the product reliability evaluation, and the evaluation scheme includes several test items for basic quality attribute evaluation. For each test item, a test case set is designed using a test case automatic generation tool. The test case set contains several test cases for evaluating the test item. The expected correct results of the test cases are generated through a standard comparison model, and the generated test case set is stored in the test case database of the data archive.

8. The reliability assessment method for an autonomous and controllable computing platform for unmanned aerial vehicles (UAVs) according to claim 7, characterized in that, The specific test cases for the basic quality attributes are as follows: Correctness test cases: When the combination of input parameter values ​​and the order of input parameters of the autonomous and controllable computing platform are within the legal range, the correctness of the combinational logic of the autonomous and controllable computing platform is verified and evaluated. The execution result of the test cases is determined by the value of the output parameters of the autonomous and controllable computing platform. Real-time test cases: When the input time of the parameters of the autonomous and controllable computing platform is within the legal period, verify and evaluate the real-time performance of the timing logic of the autonomous and controllable computing platform. The execution result of the test cases is determined by the output time of the parameters of the autonomous and controllable computing platform. Integrity test cases: When the combination of input parameter values, the order of input parameters, or the timing of input parameters are not within the legal range, the integrity of the functions and performance of the autonomous and controllable computing platform under illegal input is verified and evaluated. The execution result of the test cases is comprehensively determined by the values ​​and timing of the output parameters of the autonomous and controllable computing platform.

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