Intermediate checking method for driving steering robot

Abstract

The invention provides a period checking method for a driving steering robot, and the method comprises the steps: obtaining a plurality of groups of measurement rotation angles corresponding to a plurality of groups of input test rotation angles when the driving steering robot is in a preparation completion state on a test bench; the expansion uncertainty of the measurement corner is determined, the credible interval of the measurement result is quantified, and it is ensured that the error range is controllable. Under the condition that the expansion uncertainty meets a threshold condition, the precision error of the driving steering robot is determined according to the measurement rotation angle and the test rotation angle; and outputting a period checking report according to the precision error and the confidence interval. Therefore, a set of effective period checking scheme is formed from installation preparation, test execution, data verification, error quantification and formation of a checking logic closed loop, the scheme remarkably reduces the inspection cost and time, provides reliable equipment state guarantee for intelligent network connection automobile testing, improves the checking efficiency, defines an optimization path, and improves the test efficiency. And the quality management is more targeted and scientific.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent networked vehicle testing, and particularly to a method for in - period verification of a driving steering robot. Background Art

[0002] As a core device for active safety testing of intelligent networked vehicles, an autonomous driving steering robot verifies the performance, control strategy, and safety compliance of a vehicle's steering system by accurately simulating a driver's steering behavior. To ensure that the device maintains a stable, good state, and high measurement credibility during the interval between two calibrations, in - period verification needs to be performed regularly. That is, it is verified whether the device maintains its original metrological performance indicators (such as steering angle accuracy, repeatability, and dynamic response characteristics, etc.) during the interval between two calibrations.

[0003] However, the research and development and measurement technology of autonomous driving steering robots for intelligent networked vehicle testing in China are still in their infancy. There is no corresponding instruction manual for in - period verification method for imported autonomous driving robots from abroad, making it difficult to effectively conduct in - period verification of the device. Moreover, the current development cycle of intelligent networked vehicles is short. As an essential test instrument for ensuring test consistency and improving the robustness of vehicle performance, the time cost of frequently sending the device to a professional institution for inspection is huge, and the effective delivery of products cannot be guaranteed.

[0004] Therefore, how to implement the in - period verification of a driving robot while not affecting daily test verification work is a key link in the quality assurance system for active safety testing of intelligent networked vehicles. Summary of the Invention

[0005] To overcome the problems existing in the related art, this specification provides a method for in - period verification of a driving steering robot.

[0006] According to the first aspect of the embodiments of this specification, an in - period verification system for a driving steering robot is provided. The system includes:

[0007] A driving steering robot, which includes an inner ring and an outer ring that meshes with and rotates with the inner ring. The inner ring is used to be fixedly connected to the steering wheel of a vehicle to drive the steering wheel to rotate;

[0008] A test bench, including a fixture for clamping the driving steering robot, and the outer ring of the driving steering robot is fixed on the test bench through the fixture;

[0009] Among them, the driving steering robot includes a control unit, and the control unit is connected to the motor of the driving steering robot through a control bus and is used to drive the movement of the driving steering robot according to an instruction;

[0010] A data acquisition unit, connected to the control unit through a data transmission bus, for acquiring and reading data of the driving steering robot; and

[0011] A power supply system for powering the driving steering robot and the data acquisition unit.

[0012] According to a periodic verification system for a driving steering robot provided by the present application, the system further includes:

[0013] A host computer for sending instructions of a corner test program to the control unit through a data transmission bus.

[0014] A periodic verification method for a driving steering robot based on the periodic verification system of the driving steering robot according to any one of the above, the method includes:

[0015] Obtaining a plurality of sets of measured angles corresponding to the test angles obtained by rotating the driving steering robot on a test bench in a ready-to-complete state based on a plurality of sets of input test angles;

[0016] Determining the expanded uncertainty of the measured angle for evaluating the confidence interval of the measured angle of the driving steering robot;

[0017] When the expanded uncertainty meets the threshold condition, determining the accuracy error of the driving steering robot according to the measured angle and the test angle;

[0018] Outputting a periodic verification report according to the accuracy error and the confidence interval.

[0019] According to a periodic verification method for a driving steering robot provided by the present application,

[0020] The determining the expanded uncertainty of the measured angle includes:

[0021] Determining multiple categories of uncertainties according to the uncertainty sources in the periodic verification process;

[0022] According to the multiple categories of uncertainties, synthesizing a combined standard uncertainty for representing the overall influence of the test;

[0023] Based on the combined standard uncertainty, determining the expanded uncertainty of the measured angle.

[0024] According to a periodic verification method for a driving steering robot provided by the present application,

[0025] The uncertainty sources in the periodic verification process include equipment errors in measuring the measured angle and repeatability errors in multiple measurements,

[0026] Determine multiple categories of uncertainties according to the sources of uncertainties in the intermediate verification process, including:

[0027] The multiple categories of uncertainties include a first uncertainty corresponding to the repeatability error and a second uncertainty corresponding to the equipment error.

[0028] According to an intermediate verification method for a driving steering robot provided by the present application,

[0029] The first uncertainty corresponding to the repeatability error is determined according to the average value and standard deviation of the multiple groups of measured rotation angles.

[0030] According to an intermediate verification method for a driving steering robot provided by the present application,

[0031] When the driving steering robot is in a ready state on the test bench, rotate based on multiple input groups of test rotation angles, and obtain multiple groups of measured rotation angles corresponding to the test rotation angles, including:

[0032] When the driving steering robot is in a ready state on the test bench, determine the center of the inner circle of the driving steering robot;

[0033] Use the self-calibration function of the driving steering robot to determine the initial position and mark the initial position;

[0034] Input multiple equally stepped test rotation angles to the control unit of the driving steering robot to control the rotation of the driving steering robot, and mark the position after each test rotation angle runs to obtain test positions;

[0035] Based on the center of the circle, determine the relative angular change of the rotation angle formed between the initial position and the multiple test positions to obtain the measured rotation angle.

[0036] According to an intermediate verification method for a driving steering robot provided by the present application,

[0037] The driving steering robot being in a ready state on the test bench includes the following conditions:

[0038] Fix the outer circle of the driving steering robot on the test bench through the fixture of the test bench. The driving steering robot includes an inner circle and an outer circle that meshes and rotates with the inner circle. The inner circle is used to be fixedly connected to the vehicle's steering wheel to drive the steering wheel to rotate; and the control unit is connected to the motor of the driving steering robot through a control bus, the data acquisition unit is connected to the control unit through a data transmission bus, and the power supply system is connected to the driving steering robot and the data acquisition unit through a power cord.

[0039] A method for interim verification of a driving steering robot provided by the present application further includes: the measured rotation angle covers the full range of the driving steering robot, and the measured rotation angle includes the two-way control requirements of left turn and right turn.

[0040] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the method for interim verification of the driving steering robot as described in any one of the above.

[0041] In the method for interim verification of the driving steering robot in the embodiments of the present specification, when the driving steering robot is in a ready state on the test bench, it rotates based on multiple groups of input test rotation angles, and obtains multiple groups of measured rotation angles corresponding to the test rotation angles; determines the expanded uncertainty of the measured rotation angle, quantifies the confidence interval of the measurement result, and ensures that the error range is controllable. When the expanded uncertainty meets the threshold condition, determines the accuracy error of the driving steering robot according to the measured rotation angle and the test rotation angle; outputs an interim verification report according to the accuracy error and the confidence interval. Furthermore, a verification logic closed-loop is formed from installation preparation, test execution, data verification, and error quantification, forming an effective interim verification scheme. This scheme significantly reduces the inspection cost and time, provides reliable equipment status guarantee for intelligent networked vehicle testing, improves the verification efficiency, and also clarifies the optimization path, making quality management more targeted and scientific.

[0042] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present specification, and are used together with the specification to explain the principles of the present specification.

[0044] Figure 1 is a schematic diagram of an interim verification system of a driving steering robot shown according to an exemplary embodiment of the present specification;

[0045] Figure 2 is a schematic diagram of a driving steering robot shown according to an exemplary embodiment of the present specification;

[0046] Figure 3 is a schematic flowchart of a method for interim verification of a driving steering robot shown according to an exemplary embodiment of the present specification;

[0047] Figure 4 is a schematic flowchart of uncertainty calculation shown according to an exemplary embodiment of the present specification;

[0048] Figure 5It is a schematic diagram of an interim verification device for a driving steering robot shown in accordance with an exemplary embodiment of this specification;

[0049] Figure 6 It is a schematic block diagram of an interim verification device for a driving steering robot shown in accordance with an exemplary embodiment of this specification. Specific embodiments

[0050] Here, the technical solutions in the embodiments (or "embodiment modes") of the present application will be clearly and completely described in conjunction with the accompanying drawings. When the following description involves the accompanying drawings, unless otherwise indicated, the same numerals in different drawings represent the same or similar elements.

[0051] If there are terms related to directional indications or positional relationships in the embodiments of the present application (such as up, down, left, right, front, back, inside, outside, top, bottom, center, vertical, horizontal, longitudinal, transverse, length, width, counterclockwise, clockwise, axial, radial, circumferential, etc.), such terms are only used to explain the relative positional relationships and motion conditions between components in a specific posture (as shown in the accompanying drawings); if this specific posture changes, then the directional indication or positional relationship will also change accordingly. In addition, terms such as "first" and "second" involved in the embodiments of the present application are only for the purpose of convenient description and cannot be understood as indicating or implying relative importance.

[0052] The present application provides an interim verification method for a driving steering robot. The following will describe the present application in detail in conjunction with the accompanying drawings. Without conflict, the features in the following embodiments and embodiment modes can be combined with each other.

[0053] The research and development and measurement technology of autonomous driving steering robots for intelligent network connection testing in China are still in their infancy, and corresponding interim verification method instruction manuals have not been formulated for imported foreign autonomous driving robots, making it difficult to effectively conduct interim verification on the equipment. Moreover, the current development cycle of intelligent network-connected vehicles is short. As an essential test instrument to ensure test consistency and improve the robustness of vehicle performance, the time cost of frequently sending the equipment to professional institutions for inspection is huge, and the effective delivery of products cannot be guaranteed.

[0054] To solve the above technical problems, this specification provides an interim verification method for a driving steering robot.

[0055] The aim is to implement the interim verification of the driving robot while not affecting the daily test and verification work, minimize and reduce the costs and risks caused by equipment or calibration status failures as much as possible, and improve the test efficiency as much as possible.

[0056] Figure 1 It is an interim verification system for a driving steering robot provided by an embodiment of this specification.

[0057] The system includes: a driving steering robot, a control unit, a data acquisition unit, a power supply system, and a test bench.

[0058] Referring to Figure 2 , the driving steering robot includes an inner ring and an outer ring, and the inner and outer rings are connected by rolling bearings and meshed with a pinion. Usually, during the intelligent network connection test, the inner ring is fixedly connected to the vehicle's steering wheel through a steering wheel adapter block to drive the rotation of the vehicle's steering wheel. The outer ring is meshed with the inner ring through rolling bearings by a supporting or adsorbing fixing method and cannot roll or slide.

[0059] The test bench includes a fixture for clamping the driving steering robot. The outer ring of the automatic driving steering robot is firmly installed on the test bench through a fixed fixture to ensure that the outer ring cannot roll or slide. Considering the problem of reference point drift caused by the non-fixability and irregular shape (such as a steering wheel with an airfoil design) of the vehicle's steering wheel, it is difficult to determine the calibration initial reference point. Therefore, a set of fixed fixtures is used to fix the outer ring of the automatic driving steering robot on the test bench to ensure the consistency of the rotation reference and the stability of the rotation axis.

[0060] Subsequently, by powering on and communicating the entire system, a real test environment is simulated to avoid introducing additional errors due to local power failure or signal interruption. Specifically, the power cord, control signal line, and data line are respectively connected to the robot control system and the upper computer to form a complete power supply, control, and data acquisition link.

[0061] Among them, the control unit is connected to the motor of the driving steering robot through a control bus and is used to drive the movement of the driving steering robot according to instructions; the data acquisition unit is connected to the control unit through a data transmission bus and is used to collect and read the data of the driving steering robot; and the power supply system is used to supply power to the driving steering robot and the data acquisition unit.

[0062] The system further includes: an upper computer, which sends instructions for the corner test program to the control unit through a data transmission bus, programs to control multi-angle stepped rotation, and records control instructions, mechanical actions, and sensor data in real time.

[0063] Through the above system, the in-period verification of the driving steering robot is carried out, a real test scenario is simulated, the reliability of the entire link is dynamically verified, and the performance stability of the entire automatic driving steering robot system within two calibration intervals is ensured, including the comprehensive reliability of hardware (such as sensors, mechanical structures), software (control logic), and system integration (connection with the data acquisition unit, power supply system).

[0064] Figure 3It is a schematic flowchart of a method for interim verification of a driving steering robot provided by an embodiment of this specification, and is applied to the interim verification system of the above-mentioned driving steering robot.

[0065] It includes the following steps:

[0066] Step S110, when the driving steering robot is in a ready state on the test bench, rotate it based on multiple groups of input test rotation angles, and obtain multiple groups of measured rotation angles corresponding to the test rotation angles;

[0067] Step S120, determine the expanded uncertainty of the measured rotation angle, which is used to evaluate the confidence interval of the measured rotation angle of the driving steering robot;

[0068] Step S130, when the expanded uncertainty meets the threshold condition, determine the accuracy error of the driving steering robot according to the measured rotation angle and the test rotation angle;

[0069] Step S140, output an interim verification report according to the accuracy error and the confidence interval.

[0070] Through physical fixation, geometric reference, phased testing, and uncertainty quantification, this method forms a set of efficient and low-cost interim verification solutions. The formula design is based on the error propagation theory and statistical principles, ensuring the scientificity and repeatability of each link from data acquisition to result analysis, and ultimately providing high-confidence quality assurance for intelligent networked vehicle testing.

[0071] In step S110, when the fixture of the test bench fixes the outer ring of the driving steering robot on the test bench, and after the full-link connection of the driving steering robot, the control unit, the data acquisition unit, the power supply system, and the test bench, it is determined that the driving steering robot is in a ready state on the test bench.

[0072] In some embodiments, the obtaining of multiple groups of measured rotation angles corresponding to the test rotation angles when the driving steering robot is in a ready state on the test bench and rotates based on multiple groups of input test rotation angles includes:

[0073] Step S111, when the driving steering robot is in a ready state on the test bench, determine the center of the inner ring of the driving steering robot;

[0074] Step S112, use the self-calibration function of the driving steering robot to determine the initial position and mark the initial position;

[0075] Step S113: Input multiple equally stepped test rotation angles into the control unit of the driving steering robot to control the rotation of the driving steering robot, and mark the positions after the operation of each test rotation angle to obtain test positions.

[0076] Step S114: Based on the center of the circle, determine the relative angular change of the rotation angles formed between the initial position and the multiple test positions to obtain the measured rotation angle.

[0077] Specifically, in step S111, cut a cardboard with the same size as the inner circle and fit it to the inner circle of the robot. With the help of a digital angle gauge that has been calibrated, randomly draw two non-parallel chords on the circular cardboard, respectively draw the perpendicular bisectors of the two chords, and the intersection point of the two perpendicular bisectors is the center of the circle O.

[0078] By this geometric method, the influence of the irregular shape of the steering wheel is eliminated, providing an absolute reference for angle measurement.

[0079] After that, in step S112, through the self-calibration function of the autonomous driving steering robot, determine its initial position S0 after returning to "0", so as to determine the rotation angle position. Depict the reference point S0 on the cardboard and make a mark on the outer circle of the driving robot.

[0080] Then, in step S113, edit the test program, and take angles that increase step by step with a set angle to test the left and right steering angles respectively.

[0081] It should be noted that the measured rotation angle covers the full range of the driving steering robot, and the measured rotation angle includes the two-way control requirements of left and right turns. For example, set the angle as equally stepped angles of ±60°, and set the test rotation angles as: 60°, 120°, 180°, 240°, 300°, -60°, -120°, -180°, -240°, -300° (left is "-" and right is "+"). Through multi-angle testing to cover the full range, verify the linearity and repeatability of the robot's rotation angle.

[0082] Finally, in step S114, after the operation of each angle control program is completed, make marks S1, S2... on the paper in contrast to the marked positions on the outer circle, and connect them to the center of the circle O respectively to form a rotation angle. Use a calibrated digital angle gauge to measure the relevant rotation angles respectively to obtain the measured rotation angle. Subsequently, based on the measured rotation angle, calculate whether the relevant precision error is within the acceptable range to evaluate whether the steering angle control precision of the autonomous driving steering robot meets the requirements.

[0083] In step S120, considering the influence of errors during the test on the measurement results, it is necessary to evaluate the confidence interval of the measurement results to quantify the influence of all possible error sources during the measurement process, provide reliable error boundaries, and support decision optimization.

[0084] As an example, referring to Figure 4 , the determination of the expanded uncertainty of the measured rotation angle includes:

[0085] Determine multiple categories of uncertainties according to the uncertainty sources in the intermediate verification process;

[0086] According to the multiple categories of uncertainties, synthesize the combined standard uncertainty representing the overall influence of the test;

[0087] Based on the combined standard uncertainty, determine the expanded uncertainty of the measured rotation angle.

[0088] The identification of the sources of measurement uncertainty for the detection and calibration results in this specification starts from analyzing the measurement process and conducts a detailed study on the measurement method, measurement system, and measurement procedure. The following influencing factors of uncertainty can be abstracted:

[0089] First, the repeatability error of multiple measurements, which is a component from the test method.

[0090] During the inspection process, the control ability of the measurement personnel for equipment operation will inevitably generate random errors, such as the drawing error of the test angle points, the reading error of the results, etc.; the state of the test samples will also generate systematic errors, such as the matching degree between samples, the wear degree between gears, etc. The matching error of the test fixture and the vibration of the equipment during operation caused by environmental factors are also uncontrollable. Therefore, the operations of different test personnel, the laboratory environment, and the matching error between samples, as the uncertainties introduced by the test method itself, are statistically analyzed using type A uncertainty evaluation.

[0091] Second, the equipment error of measuring the measured rotation angle, which is a component from the equipment linear error.

[0092] In this inspection process, a digital display angle gauge is used to collect the rotation angle of the target driving robot, and the uncertainty caused by the influence of the digital display angle gauge instrument on the angle accuracy is considered in the type B evaluation.

[0093] It should be noted that the equipment used to measure the rotation angle after operation in this specification can be but is not limited to a digital display angle gauge, and can also be other calibrated equipment, which will not be limited here.

[0094] In summary, the sources of uncertainty in the above-mentioned intermediate verification process include the equipment error in measuring the measurement rotation angle and the repeatability error in multiple measurements. The multiple categories of uncertainty include the first uncertainty corresponding to the repeatability error and the second uncertainty corresponding to the equipment error.

[0095] As an example, the calculation formula for setting the target driving robot rotation angle S is:

[0096] y = S t + ΔS

[0097] where: y—the actual rotation angle of the target driving steering robot

[0098] S t —the rotation angle measured by the digital display angle gauge

[0099] ΔS—the uncertainty in the measurement by the digital display angle gauge

[0100] Based on the first uncertainty and the second uncertainty during the measurement by the digital display angle gauge, evaluate the confidence interval of the actual rotation angle of the target driving steering robot. It should be noted that the actual rotation angle refers to the measured rotation angle considering the equipment error in measuring the rotation angle and the repeatability error in multiple measurements.

[0101] As an example, evaluate the uncertainty component introduced by the test method. According to the above-mentioned test method, repeat a sufficient number of times, record the measurement results, and conduct n independent and equal-precision measurements on the input test rotation angle S. The results of multiple groups of measured rotation angles obtained are: S1, S2... S n .

[0102] is its arithmetic mean. That is where, S i is the i-th measured value, n is the number of measurements, and the source is the statistical processing requirement of the measurement data. Determine the central tendency of multiple measurements through the mean value to eliminate accidental errors.

[0103] The experimental variance of a single measurement result is:

[0104] It measures the degree of dispersion between a single measured value and the mean value, reflecting the repeatability error of the measurement. (n - 1) is the degree of freedom, which is used for an unbiased estimate of the population variance.

[0105] Standard deviation Quantifies the degree of dispersion of the repeatability error.

[0106] The standard uncertainty of the mean value of the observation series, i.e., the estimated value, is:

[0107] Standard uncertainty

[0108] The standard uncertainty, which is also the first uncertainty corresponding to the repeatability error, takes into account the influence of the number of measurements and the dispersion degree of single measurement on the uncertainty of the average value, and is used to evaluate the uncertainty component introduced by measurement repeatability.

[0109] As an example, the component from the linear error of the equipment. Since the information sources evaluated by different types of measuring instruments can come from calibration certificates, verification certificates, manufacturer's instructions, etc., the solution methods are also diverse.

[0110] If the data (such as a calibration certificate) gives the expanded uncertainty u(s i ) and the coverage factor K, then the standard uncertainty of x i is i

[0111] There are several possible cases as follows:

[0112] a) If the data only gives the expanded uncertainty u(s i ) without specifying k, then k can be considered as 2 (corresponding to a coverage probability of approximately 95%).

[0113] b) If the data only gives u P (s i )(where p is the coverage probability), then the coverage factor k P is related to the distribution of s i . In this case, unless otherwise specified, it is generally considered according to the normal distribution. For p = 0.95, k can be obtained by looking up the table, that is, k P = 1.960.

[0114] c) If the data gives u P and V eff , then k P can be obtained by looking up the table, that is, K P = t p (V eff ).

[0115] The above formula is based on the information provided in data such as calibration certificates, converting the expanded uncertainty into the standard uncertainty, and taking into account the uncertainty introduced by the accuracy of the measuring equipment itself. Different K values are selected for calculation according to the information provided in the data for different cases.

[0116] It depends on the specific application scenario and device characteristics. If the device itself has high precision (Class B / small second uncertainty), while the test environment fluctuates greatly (Class A / large first uncertainty), then Class A may be the main factor; conversely, if the device has limited precision (Class B / large second uncertainty), while the test repeatability is good (Class A / small first uncertainty), then Class B plays a dominant role. If the calculated precision error of the driving steering robot does not meet the requirements in the follow-up, the error analysis of the test process can be carried out according to the above calculation results of the uncertainty, and corresponding improvements can be made.

[0117] In this embodiment, a credible error boundary is provided through the Class A or Class B uncertainty model to support decision optimization.

[0118] Subsequently, according to the first uncertainty and the second uncertainty, a combined standard uncertainty representing the overall impact of the test is synthesized.

[0119] Specifically, the standard uncertainty u(S i ) of the input quantity causes the standard uncertainty component u i (y) of y to be:

[0120]

[0121] Numerically, (also known as the uncertainty propagation coefficient), the sensitivity coefficient can be obtained by taking the partial derivative of the mathematical model with respect to Si, or it can be obtained by experimental measurement. The sensitivity coefficient reflects the sensitivity of the standard uncertainty of this input quantity to the uncertainty of the output quantity.

[0122] In this type of measurement process, since the two standard uncertainty components of the test method and the test equipment are uncorrelated and independent of each other. It can be considered that The combined standard uncertainty can be obtained as:

[0123]

[0124] Since the standard uncertainty components of the test method and the test equipment are uncorrelated, according to the uncertainty propagation law, the Class A and Class B uncertainties (i.e., the first uncertainty and the second uncertainty) are combined to obtain the combined standard uncertainty, which comprehensively reflects the uncertainty degree of the measurement result.

[0125] Next, based on the combined standard uncertainty, the expanded uncertainty of the measured rotation angle is determined.

[0126] The uncertainty of this type of measurement can be estimated as a normal distribution. When choosing a coverage probability of about 95%, the coverage factor can be taken as k = 2, that is, U = u c(y) × k. By multiplying by the coverage factor k, the combined standard uncertainty is expanded into an interval that encompasses most possible measurement results, more intuitively representing the confidence interval of the measurement result of the measured rotation angle.

[0127] Through this embodiment, the calculation method of measurement uncertainty is used to describe the credibility of the measured value, making it easier to intuitively describe the magnitude of the error.

[0128] In step S130, the expanded uncertainty is compared with the threshold. When the expanded uncertainty meets the threshold condition, it means that the measured rotation angle obtained above can be used to determine the precision error of the driving steering robot.

[0129] Under normal circumstances, this threshold is 1 / 3 of the allowable error. That is to say, when the expanded uncertainty is less than 1 / 3 of the allowable error, the precision error of the driving steering robot is determined according to the difference between the measured rotation angle and the test rotation angle, where the test rotation angle is used as the theoretical value.

[0130] When the expanded uncertainty is greater than or equal to 1 / 3 of the allowable error, otherwise the main error sources need to be investigated. It can be but is not limited to investigating according to the above first uncertainty and second uncertainty. For example, if in a certain verification, u c = 0.5° (threshold 0.3°), it exceeds the limit and needs to be investigated. Analysis shows that u a = 0.45° (accounting for 81%), u B = 0.2° (accounting for 19%). Conclusion: The main problem is the repeatability error (type A), and it is necessary to check the shock resistance of the fixture or the operation standardization.

[0131] In step S140, if the precision error is within the acceptable range, it indicates that the steering control of the robot at this angle is relatively accurate; otherwise, it may be necessary to adjust or further check the robot. At the same time, an interim verification report is output, and this output interim verification report includes data on the precision error and the confidence interval.

[0132] The present application provides a method for interim verification of a driving steering robot. When the driving steering robot is in a ready state on a test bench, it rotates based on multiple groups of input test rotation angles, and multiple groups of measured rotation angles corresponding to the test rotation angles are obtained. The expanded uncertainty of the measured rotation angles is determined to quantify the confidence interval of the measurement results and ensure that the error range is controllable. When the expanded uncertainty meets the threshold condition, the accuracy error of the driving steering robot is determined based on the measured rotation angles and the test rotation angles. According to the accuracy error and the confidence interval, an interim verification report is output. Furthermore, a verification logic closed-loop is formed from installation preparation, test execution, data verification, and error quantification, forming an effective interim verification scheme. This scheme significantly reduces the submission inspection cost and time, provides reliable equipment status guarantee for intelligent networked vehicle testing, improves the verification efficiency, and also clarifies the optimization path, making quality management more targeted and scientific.

[0133] Based on the same inventive concept as the above method, an embodiment of the present application also proposes an interim verification device for a driving steering robot, as Figure 5 shown.

[0134] The device includes:

[0135] A data acquisition module 502, which is used to obtain multiple groups of measured rotation angles corresponding to the test rotation angles when the driving steering robot rotates based on multiple groups of input test rotation angles in a ready state on a test bench;

[0136] A data calculation module 504, which is used to determine the expanded uncertainty of the measured rotation angles and evaluate the confidence interval of the measured rotation angles of the driving steering robot;

[0137] An error analysis module 506, which is used to determine the accuracy error of the driving steering robot based on the measured rotation angles and the test rotation angles when the expanded uncertainty meets the threshold condition;

[0138] A verification output module 508, which is used to output an interim verification report according to the accuracy error and the confidence interval.

[0139] The implementation processes of the functions and roles of each module / sub-module / unit in the above device are specifically detailed in the implementation processes of the corresponding steps in the above method, and the same technical effects can be achieved, which will not be elaborated here.

[0140] Figure 6 An example of a schematic diagram of the physical structure of an interim verification device for a driving steering robot is shown in Figure 6As shown, the in-period verification device of the driving steering robot may include: a processor 810, a communications interface 820, a memory 830, and a communication bus 840. Among them, the processor 810, the communications interface 820, and the memory 830 complete mutual communication through the communication bus 840. The processor 810 may call the logical instructions in the memory 830 to execute the in-period verification method of the driving steering robot.

[0141] In addition, when the logical instructions in the above-mentioned memory 830 are implemented in the form of software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, may be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0142] On the other hand, this application also provides a computer program product. The computer program product includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the in-period verification method of the driving steering robot provided by the above-mentioned various methods.

[0143] On yet another hand, this application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to execute the in-period verification method of the driving steering robot provided by the above-mentioned various methods.

[0144] It should be noted that the technical solutions or technical features described in the above embodiments may be combined or supplemented with each other without conflict. The scope of protection of this application is not limited to the precise structures described in the above embodiments and shown in the drawings; all modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A period verification system for driving a steering robot, characterized in that: The system comprises: A driving steering robot, the driving steering robot comprising an inner ring and an outer ring for rotating in mesh with the inner ring, the inner ring being used for fixedly connecting with the steering wheel of the vehicle to drive the steering wheel to rotate; A test bench, comprising a fixture for clamping the driving and steering robot, wherein the outer ring of the driving and steering robot is fixed to the test bench by the fixture; Wherein, the driving steering robot comprises a control unit, which is connected to the motor of the driving steering robot through a control bus and is used to drive the movement of the driving steering robot according to instructions; A data acquisition unit, connected to the control unit via a data transmission bus, for acquiring and reading data of the driving steering robot; and A power supply system is used to supply power to the driving steering robot and the data acquisition unit.

2. The period checking system for driving a steering robot according to claim 1, characterized in that: The system further comprises: The host computer sends the instruction of the corner test program to the control unit through the data transmission bus.

3. A period verification method for a driving steering robot, based on the period verification system for a driving steering robot according to any one of claims 1 to 2, characterized in that: The method comprises: When the driving steering robot is in a ready state on the test bench, the robot rotates based on the input multiple test angles, and obtains multiple sets of measured angles corresponding to the test angles; Determining an expanded uncertainty of the measured turning angle for evaluating a confidence interval of the measured turning angle of the driving steering robot; In a case where the expanded uncertainty satisfies a threshold condition, determining the accuracy error of the driving steering robot according to the measured turning angle and the test turning angle; A period verification report is output based on the precision error and the confidence interval.

4. The period checking method for driving a steering robot according to claim 3, characterized in that: Determining the expanded uncertainty of the measured rotation angle includes: Determine multiple categories of uncertainty based on the sources of uncertainty in the interim verification process; Based on the uncertainties of the multiple categories, a combined standard uncertainty is synthesized to represent the overall effect of the test; Based on the combined standard uncertainty, an expanded uncertainty of the measured rotation angle is determined.

5. The period checking method for driving a steering robot according to claim 4, characterized in that: The sources of uncertainty in the verification process include the equipment error of measuring the measured rotation angle and the repeatability error of multiple measurements. According to the uncertainty sources of the period verification process, multiple categories of uncertainty are determined, including: The multiple categories of uncertainty include a first uncertainty corresponding to a repeatability error and a second uncertainty corresponding to an equipment error.

6. The period checking method for driving a steering robot according to claim 5, characterized in that: The first uncertainty corresponding to the repeatability error is determined according to the average value and standard deviation of the multiple groups of measured rotation angles.

7. The period checking method for driving a steering robot according to claim 3, characterized in that: The obtaining driving steering robot is in a ready state on the test bench, and the robot rotates based on the input multiple groups of test angles, and the obtained multiple groups of measured angles corresponding to the test angles include: When the driving and steering robot is in a ready state on the test bench, determining the center of the inner circle of the driving and steering robot; Using the self-calibration function of the driving and steering robot, determining an initial position and marking the initial position; Inputting a plurality of test turning angles of equal steps into the control unit of the driving and steering robot to control the driving and steering robot to rotate, and marking the position of each test turning angle after operation to obtain a test position; Based on the center of the circle, a relative angle change of a rotation angle formed between the initial position and a plurality of the test positions is determined to obtain the measured rotation angle.

8. The period checking method for driving a steering robot according to claim 7, characterized in that: The driving steering robot is in a ready state on the test bench, including the following conditions: The outer ring of the driving steering robot is fixed on the test bench by the fixture of the test bench, the driving steering robot includes an inner ring and an outer ring meshing and rotating with the inner ring, the inner ring is used to be fixedly connected to the steering wheel of the vehicle to drive the steering wheel to rotate; and the control unit is connected to the motor of the driving steering robot through a control bus, the data acquisition unit is connected to the control unit through a data transmission bus, and the power supply system is connected to the driving steering robot and the data acquisition unit through a power line.

9. The period checking method for driving a steering robot according to claim 7, characterized in that: The measured turning angle covers the full range of the driving steering robot, and the measured turning angle includes left turn and right turn bidirectional control requirements.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a period verification program for a driving steering robot, and when the period verification program for the driving steering robot is executed, the steps of the period verification method for a driving steering robot as described in any one of claims 1-9 are implemented.

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