Attitude angle error determination method and test system

Abstract

This application discloses a method and testing system for determining attitude angle error, belonging to the field of testing technology. The method includes: acquiring test program information, which includes n operating condition identifiers, where n is a positive integer; simulating n operating conditions of the target device based on the test program information; wherein, during the simulated operating conditions, acquiring a set of operating condition test information, which includes first IMU data collected by a reference inertial measurement unit (IMU) and second IMU data collected by the target device; and determining the attitude angle error of the target device based on the n sets of operating condition test information. This application, through automated multi-condition simulation and dual IMU comparison, can improve the scene fit and test realism of the target device's attitude accuracy detection, thus improving the accuracy of the attitude angle error test results. Furthermore, it can achieve fully automated testing without complex external equipment, reducing testing costs while ensuring the objectivity and comprehensiveness of the test results.

Description

Technical Field

[0001] This application relates to the field of testing technology, and in particular to a method and testing system for determining attitude angle error. Background Technology

[0002] With the continuous development of technology, intelligent products such as smart glasses have been integrated into people's lives, providing convenience. Smart glasses generally have a built-in inertial measurement unit (IMU), which determines the user's three-dimensional head posture angles by collecting real-time acceleration and angular velocity data from the smart glasses. The accuracy and stability of these posture angles are key indicators for evaluating the performance of smart glasses. In related technologies, the posture angle error of the device is usually tested in a static, vibration-free, and disturbance-free environment. However, this testing method has relatively low accuracy. Summary of the Invention

[0003] This application provides a method and testing system for determining attitude angle error, which can improve testing accuracy. The technical solution is as follows: Firstly, a method for determining attitude angle error is provided, applied to a test system, the method comprising: Obtain test program information, which includes n working condition identifiers, where n is a positive integer; Based on the test program information, n operating conditions of the target device are simulated; wherein, during the simulation of any operating condition, a set of operating condition test information is acquired, the set of operating condition test information includes first IMU data collected by the reference inertial measurement unit (IMU) and second IMU data collected by the target device; The attitude angle error of the target device is determined based on the obtained n sets of working condition test information.

[0004] In this application, test program information is obtained, which includes n operating condition identifiers. Then, based on this test program information, n operating conditions of the target device are simulated. During the simulation of any operating condition, a set of operating condition test information is acquired. This set of operating condition test information includes first IMU data acquired by a reference IMU and second IMU data acquired by the target device. Finally, the attitude angle error of the target device is determined based on the acquired n sets of operating condition test information. Through automated multi-condition simulation and dual IMU comparison, the scene fit and test realism of the target device attitude accuracy detection can be significantly improved. This not only improves the accuracy of the attitude angle error test results but also enhances the test standardization, consistency, and reproducibility. Furthermore, since no complex external measurement equipment is required and the entire testing process can be automated, testing costs are reduced while ensuring the objectivity and comprehensiveness of the test results, providing a reliable technical means for equipment development and quality control.

[0005] Optionally, the n operating condition identifiers include one or more of the following: low-amplitude, low-frequency stable operating condition identifier, medium-amplitude, medium-frequency motion operating condition identifier, high-amplitude, low-frequency bumpy operating condition identifier, and high-frequency micro-vibration interference operating condition identifier.

[0006] Optionally, the test program information further includes one or more of the following: vibration output mode corresponding to each of the n operating condition identifiers, vibration output parameters corresponding to each operating condition identifier, runtime corresponding to each operating condition identifier, operating condition execution order, operating condition switching interval duration, and operating condition cycle mode. Simulating the n operating conditions of the target device based on the test program information includes: Based on the execution order of the working conditions and / or the working condition cycle mode, the n working condition identifiers are traversed sequentially. For a current operating condition identifier, simulate an operating condition of the target device based on one or more of the vibration output mode, vibration output parameters, and running time corresponding to the operating condition identifier; when the operating condition simulation ends, wait for the operating condition switching interval before continuing to traverse.

[0007] Optionally, the test program information further includes a device attitude identifier corresponding to each of the n working condition identifiers. Before simulating one or more of the vibration output mode, vibration output parameters, and runtime of the target device based on the working condition identifier, the following steps are also included: Adjust the target device to the device posture indicated by the device posture identifier corresponding to the operating condition identifier.

[0008] Optionally, the device attitude identifier can be any one of a neutral attitude identifier, a small-angle deflection attitude identifier, or a large-angle deflection attitude identifier.

[0009] Optionally, obtaining a set of working condition test information includes: The first IMU data is acquired from the reference inertial measurement unit (IMU), and the second IMU data is acquired from the target device; Based on the target operating condition identifier and / or the device attitude identifier corresponding to the target operating condition identifier, the first IMU data and the second IMU data, the set of operating condition test information is generated, wherein the target operating condition identifier is the operating condition identifier of the operating condition being simulated.

[0010] Optionally, determining the attitude angle error of the target device based on the acquired n sets of working condition test information includes: For any set of working condition test information in the n sets of working condition test information, a first attitude angle is determined based on the first IMU data in the set of working condition test information, and a second attitude angle is determined based on the second IMU data in the set of working condition test information. The absolute difference between the first attitude angle and the second attitude angle is defined as the attitude angle error.

[0011] Optionally, after determining the attitude angle error of the target device based on the acquired n sets of working condition test information, the method further includes: Based on the n sets of working condition test information and the attitude angle error corresponding to each set of working condition test information in the n sets of working condition test information, the attitude angle error test result of the target device is generated; The attitude angle error test results are analyzed to obtain an attitude angle error analysis report. The attitude angle error analysis report includes the n sets of test information under operating conditions, the average value of the attitude angle error, one or more of the n first influence weights and n second influence weights. The n first influence weights correspond one-to-one with the n operating conditions, and the first influence weights are the influence weights of the operating conditions on the attitude calculation accuracy of the target device. The n second influence weights correspond one-to-one with the n device attitudes, and the second influence weights are the influence weights of the device attitudes on the attitude calculation accuracy of the target device.

[0012] Optionally, the target device can be any one of smart glasses, an all-in-one augmented reality (AR) head-mounted display, or a split-type head-mounted device.

[0013] Secondly, a testing system is provided, the testing system including a working condition simulation module, a clamping module, a reference inertial measurement unit (IMU), a data acquisition module and an analysis module, the clamping module being used to clamp the target device, and the reference inertial measurement unit (IMU) being fixedly connected to the clamping module; The operating condition simulation module is used to acquire test program information, which includes n operating condition identifiers, where n is a positive integer; and to simulate n operating conditions of the target device based on the test program information. The data acquisition module is used to acquire a set of operating condition test information during the simulation of any operating condition by the operating condition simulation module. The set of operating condition test information includes first IMU data acquired by the reference inertial measurement unit (IMU) and second IMU data acquired by the target device. The analysis module is used to determine the attitude angle error of the target device based on the acquired n sets of working condition test information.

[0014] Thirdly, an attitude angle error determination device is provided, the device comprising: The first acquisition module is used to acquire test program information, which includes n working condition identifiers, where n is a positive integer. The second acquisition module is used to simulate n operating conditions of the target device based on the test program information; wherein, during the simulation of any operating condition, a set of operating condition test information is acquired, the set of operating condition test information including first IMU data collected by the reference inertial measurement unit (IMU) and second IMU data collected by the target device; The determination module is used to determine the attitude angle error of the target device based on the acquired n sets of working condition test information.

[0015] Fourthly, a computer device is provided, the computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the attitude angle error determination method described in the first aspect.

[0016] Fifthly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the attitude angle error determination method described in the first aspect.

[0017] In a sixth aspect, a computer program product is provided, which, when run on a computer device, causes the computer device to execute the attitude angle error determination method described in the first aspect.

[0018] It is understood that the beneficial effects of the second, third, fourth, fifth, and sixth aspects mentioned above can be found in the relevant descriptions in the first aspect above, and will not be repeated here. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the structure of a testing system provided in an embodiment of this application; Figure 2 This is a flowchart of an attitude angle error determination method provided in an embodiment of this application; Figure 3 This is a flowchart of another attitude angle error determination method provided in the embodiments of this application; Figure 4 This is a flowchart of another attitude angle error determination method provided in the embodiments of this application; Figure 5 This is a schematic diagram of the structure of an attitude angle error determination device provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0020] In the following description, specific details such as particular system architectures and technologies are set forth for illustrative purposes and not for limiting purposes, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details.

[0021] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0022] It should be understood that "one or more" as used in this application refers to one, two, or more, and "multiple" as used in this application refers to two or more. In the description of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.

[0023] To facilitate a clear description of the technical solutions of this application, the terms "first" and "second" are used to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that the terms "first" and "second" do not necessarily imply that they are different.

[0024] The terms "one embodiment" or "some embodiments" used in this application mean that one or more embodiments of this application include the specific features, structures, or characteristics described in that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this application do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized.

[0025] The application scenarios involved in the embodiments of this application are described below.

[0026] Currently, smart glasses generally have built-in IMU and attitude calculation algorithms. The IMU collects acceleration and angular velocity data in real time, and the attitude calculation algorithm calculates the user's head attitude angle. The accuracy and stability of the attitude angle directly determine the effectiveness of core functions such as spatial positioning, visual perspective matching, head-following interaction, and body-sensing control, and is a key indicator for evaluating the performance of smart glasses.

[0027] In related technologies, the testing methods for the accuracy of smart glasses' attitude angle calculation are mainly based on static calibration tests. That is, the device's attitude angle error is collected in an ideal environment that is completely still, without vibration or disturbance, in order to determine whether the device's calculation accuracy meets the standard. However, this testing method has the following problems.

[0028] 1. It can only perform static testing and cannot simulate various types of vibration conditions during wear. The test environment is limited and differs significantly from real-world usage scenarios, resulting in low accuracy of test results. Real-world user wear scenarios involve numerous complex dynamic vibration interferences, such as slow walking, brisk walking / running, climbing stairs, road bumps, vehicle vibrations, and high-frequency micro-vibrations of the limbs. These different types of vibration noise can couple into the IMU's raw data through the structural path, causing zero-point drift in acceleration, increased cumulative error in angular velocity integration, and deterioration in filtering performance. This leads to deviations, jitter, and lag in the calculation of head tilt and lateral head angles.

[0029] 2. Static testing lacks standardized posture and vibration matching logic, and only randomly adjusts the angle and applies vibration. It cannot systematically identify which vibration conditions and head postures are most likely to exceed the error limit, resulting in poor test repeatability.

[0030] 3. It cannot distinguish the different impacts of different types of vibration on attitude calculation, and cannot provide accurate data support for the optimization of filtering algorithm parameters and hardware vibration reduction structure. At the same time, most vibration equipment is in a single manual parameter adjustment mode, which cannot realize multi-condition programmable automatic switching and batch cyclic testing, resulting in a lot of manual intervention and low testing efficiency.

[0031] 4. The lack of a systematic dynamic testing scheme of "multi-gradient vibration conditions + multi-posture graded matching + programmable vibration control + dynamic error quantification analysis" makes it impossible to achieve full-condition automated continuous testing, resulting in low product quality inspection efficiency, high missed inspection rate, and lack of effective data basis for R&D iteration.

[0032] Therefore, this application provides a method for determining attitude angle error, applied to a testing system. In this method, test program information is acquired, including n operating condition identifiers, where n is a positive integer. Based on this test program information, n operating conditions of the target device are simulated. During the simulation of any operating condition, a set of operating condition test information is acquired, including first IMU data collected by a reference inertial measurement unit (IMU) and second IMU data collected by the target device. The attitude angle error of the target device is determined based on the acquired n sets of operating condition test information. Through automated multi-condition simulation and dual IMU comparison, the scene fit and test realism of the target device's attitude accuracy detection can be significantly improved. This not only improves the accuracy of attitude angle error test results but also enhances test standardization, consistency, and reproducibility. Furthermore, since no complex external measurement equipment is required and fully automated testing can be achieved, testing costs are reduced while ensuring the objectivity and comprehensiveness of test results, providing a reliable technical means for equipment development and quality control.

[0033] The testing system provided in the embodiments of this application will be described below.

[0034] Figure 1 This is a schematic diagram of the structure of a testing system provided in an embodiment of this application. See also... Figure 1 The test system 10 may include a working condition simulation module 101, a clamping module 102, a reference IMU 103, a data acquisition module 104, and an analysis module 105.

[0035] The clamping module 102 (also known as the eyeglass clamping fixture) can be fixedly installed on the table surface of the working condition simulation module 101 (also known as the vibration excitation table); the reference IMU 103 (also known as the reference six-axis acceleration sensor module) can be rigidly attached to the fixture reference position in the clamping module 102, and remain relatively stationary with the target device. The vibration amplitude, motion trajectory and spatial attitude of the two are completely synchronized, serving as the true reference for the angle of dynamic testing, and used to eliminate the error interference caused by the target device's own sensors.

[0036] It should be noted that the working condition simulation module 101, clamping module 102, reference IMU 103, data acquisition module 104 and analysis module 105 included in the test system 10 provided in this application embodiment may be different modules in the same device or modules set in different devices. This application embodiment does not limit this.

[0037] For example, the target device can be a smart glasses, an all-in-one augmented reality (AR) head-mounted display, a split head-mounted device, or other head-mounted display devices. Of course, it is not limited to these; the target device can also be any device that includes an IMU. This application embodiment does not limit this.

[0038] The working condition simulation module 101 can communicate with the clamping module 102, the data acquisition module 104 and the analysis module 105 via wired or wireless connection.

[0039] The reference IMU103 can communicate with the data acquisition module 104 via a wired or wireless connection.

[0040] The data acquisition module 104 can communicate with the analysis module 105 via a wired or wireless connection.

[0041] The operating condition simulation module 101 is used to acquire test program information (also known as a test program group). This test program information includes n operating condition identifiers, and n operating conditions of the target equipment are simulated based on these n operating condition identifiers. The operating condition simulation module 101, as the core device for dynamic operating condition simulation, has programmable parameter configuration and automatic control functions. It supports custom programming input of vibration output characteristics, vibration duration, and operating condition switching sequence, and can pre-store multiple sets of differentiated test program information. The operating condition simulation module 101 can perform timing logic programming on the execution order, duration of a single operating condition, operating condition switching interval, and number of multiple cycles for each operating condition (also known as a vibration condition). It supports multiple operating modes, such as single-run operation of a single operating condition, sequential loop of multiple operating conditions, and repeated testing of specified operating conditions. The working condition simulation module 101 can automatically output multiple types of vibration excitation signals in sequence according to the test program information, without the need for repeated manual parameter adjustment. It can realize automatic switching of layered gradient working conditions and continuous cyclic testing, meeting different testing needs such as conventional accuracy testing and long-term dynamic stability verification. It accurately reproduces dynamic vibration environments in multiple scenarios and is suitable for standardized and automated batch testing scenarios.

[0042] For example, the n operating condition identifiers may include one or more of the following: low amplitude low frequency stable operating condition identifier, medium amplitude medium frequency motion operating condition identifier, high amplitude low frequency bump operating condition identifier, high frequency micro-vibration interference operating condition identifier, etc. The embodiments of this application do not limit this. Among them, the low-amplitude, low-frequency stable condition is used to simulate scenarios of users walking slowly on flat ground and standing with slight swaying. Under this condition, the overall vibration amplitude and frequency are small, which can test the basic accuracy and stability of the target device under normal wear. The medium-amplitude, medium-frequency motion condition is used to simulate daily exercise scenarios such as brisk walking, jogging, and going up and down stairs. Under this condition, the vibration amplitude and frequency are in the medium range, which can evaluate the posture following accuracy during motion interaction. The high-amplitude, low-frequency bumpy condition is used to simulate strong impact scenarios such as cycling, riding in a car over speed bumps, and bumpy roads. Under this condition, the vibration amplitude is large and the vibration frequency is low, which can test the anti-drift capability of posture calculation under large amplitude vibration interference. The high-frequency micro-vibration interference condition is used to simulate scenarios of fast running and high-frequency limb shaking. Under this condition, the vibration frequency is high and the overall vibration amplitude is small, which can verify the ability of the target device's built-in IMU filtering algorithm to suppress high-frequency vibration noise.

[0043] It should be noted that the above n operating conditions are merely examples of the target equipment's operating conditions and do not constitute a limitation on the n operating conditions. In actual applications, they can be flexibly adjusted according to the needs of the test object and the usage scenario.

[0044] Optionally, the operating condition simulation module 101 may include one or more of a single-axis vibration mode and a multi-axis composite vibration mode. The single-axis mode is used to simulate vibration interference in a single direction, while the multi-axis composite mode can output vibration excitation in multiple directions simultaneously, reproducing the composite vibration environment experienced by the user's head when wearing the device, and can adapt to different stringent testing requirements.

[0045] Optionally, the operating condition simulation module 101 can obtain test program information from other devices or other modules (such as the analysis module 105), or, in response to the user's selection operation, it can obtain the test program information to be executed from a variety of pre-stored test program information. This embodiment of the application does not limit this. Optionally, after simulating the n operating conditions identified by the n operating condition identifiers, the operating condition simulation module 101 can send a test completion message to the other devices or other modules.

[0046] Optionally, the test program information may include the device posture identifier corresponding to each of the n working condition identifiers. Before simulating the operating condition identified by any one of the n working condition identifiers, the working condition simulation module 101 may send a posture adjustment command to the clamping module 102. The posture adjustment command may include the device posture information corresponding to the working condition identifier. After receiving the posture adjustment command, the clamping module 102 may adjust the device posture of the target device based on the device posture information.

[0047] The clamping module 102 is used to clamp the target device; it receives the device posture identifier sent by the working condition simulation module 101, and adjusts the target device to the posture indicated by the device posture identifier. In this case, when the clamping module 102 rotates a certain angle, it can drive the target device to rotate a certain angle, thereby simulating user head tilting, head turning, head nodding, and other actions. The clamping module 102 has a three-axis independent angle adjustment and locking structure for head tilting, head turning, and pitching, which can realize continuous posture adjustment and switch between various head simulation postures such as neutral posture, small-amplitude tilting posture, and large-amplitude tilting posture to simulate different user wearing interaction states; each adjustment axis of the clamping module 102 is equipped with an independent mechanical locking and positioning structure, which can quickly lock after adjustment to the device posture, effectively preventing posture deviation during vibration and ensuring test consistency.

[0048] In some implementations, before the clamping module 102 adjusts the target device to the device posture indicated by the device posture identifier based on the device posture identifier, the user can manually place the target device on the clamping module 102 so that the clamping module 102 clamps the target device, or the clamping module 102 can automatically clamp the target device from the target position.

[0049] Optionally, the clamping module 102 can also integrate an attitude reset structure, which can return to the initial neutral attitude with one click after the n operating conditions simulation is completed, making it convenient to carry out multiple sets of sample tests continuously.

[0050] Optionally, the clamping module 102 can adopt an adaptive clamping structure, which can adaptively clamp devices of different shapes and sizes. For example, the clamping module 102 can clamp different types of devices such as smart glasses, integrated AR headsets, and split-type head-mounted devices, demonstrating strong versatility.

[0051] The reference IMU 103 is used to acquire first IMU data from the target device and send the first IMU data to the data acquisition module 104. For example, the reference IMU 103 can receive a data acquisition request sent by the data acquisition module 104 and send the first IMU data to the data acquisition module 104.

[0052] The data acquisition module 104 is used to acquire a set of working condition test information for each of the n working conditions simulated by the working condition simulation module 101. The working condition test information includes first IMU data and second IMU data. The acquired n sets of working condition test information are sent to the analysis module 105. The second IMU data is the IMU data collected by the IMU in the target device.

[0053] Optionally, the data acquisition module 104 can simultaneously send data acquisition requests to the reference IMU 103 and the target device, receive the first IMU data sent by the reference IMU 103, and receive the second IMU data sent by the target device. In this way, vibration loading and IMU data acquisition can be started and terminated synchronously, thereby eliminating timing deviations and ensuring the validity of the comparison data.

[0054] Optionally, the data acquisition module 104 can establish a hardware trigger linkage relationship with the working condition simulation module 101, using the vibration working condition start signal as the sampling trigger source to realize the synchronous start and synchronous termination of vibration loading and angle data acquisition.

[0055] The analysis module 105 is used to receive n sets of working condition test information sent by the data acquisition module 104, and generate the attitude angle error test result of the target device based on each set of working condition test information in the n sets of working condition test information.

[0056] Optionally, the analysis module 105 can analyze the attitude angle error test results to obtain an attitude angle error analysis report. The attitude angle error analysis report includes one or more of the following: the n sets of working condition test information, the average value of the attitude angle error, n first influence weights, and n second influence weights. The n first influence weights correspond one-to-one with the n operating conditions, and the first influence weight is the influence weight of the operating condition on the attitude calculation accuracy of the target device. The n second influence weights correspond one-to-one with the n device attitudes, and the second influence weight is the influence weight of the device attitude on the attitude calculation accuracy of the target device.

[0057] For example, the analysis module 105 can automatically calculate the absolute angle error, dynamic fluctuation error, etc. based on the attitude angle error test results, statistically analyze the accuracy differences under different working conditions and attitudes, and quantify the influence weight of vibration characteristics and deflection angle on the attitude calculation accuracy.

[0058] Optionally, the analysis module 105 may include an abnormal data identification unit, which can automatically identify and remove atypical abnormal data caused by vibration, impact, instantaneous attitude changes, etc., and complete the analysis and judgment only based on valid and stable data. This can improve the accuracy of the analysis results.

[0059] For example, the analysis module 105 can also have the functions of offline storage of test data, format conversion and automatic generation of test reports. All raw data (i.e. working condition test information), error statistics results and judgment reports can be saved locally or exported externally, which facilitates data traceability, management and product archiving.

[0060] Optionally, the test system 10 may include a host computer for configuring test program information and sending test program information to the operating condition simulation module 101. In some cases, the host computer may include an analysis module 105, that is, the analysis module 105 runs on the host computer; in other cases, the host computer does not include the analysis module 105, and the host computer and the device where the analysis module 105 is located are independent devices. For example, the host computer may be a desktop computer, a laptop computer, etc., and this embodiment of the application does not limit this.

[0061] Optionally, the host computer can also send end test command, pause test command, etc. to the working condition simulation module 101, but this application embodiment does not limit this.

[0062] Optionally, when the host computer includes the analysis module 105, it can have a built-in multi-condition programmable parameter library, attitude matching matrix, error judgment threshold, and data analysis model. When the host computer does not include the analysis module 105, it can have a built-in multi-condition programmable parameter library and attitude matching matrix. The multi-condition programmable parameter library is used for custom editing, storing, and calling test program information, and for one-click command control of the working condition simulation module 101 to automatically complete multi-gradient working condition switching. The attitude matching matrix is ​​a matrix for adjusting the attitude of the target device. The error judgment threshold is a threshold for judging the attitude calculation accuracy of the target device. The data analysis model analyzes the attitude angle error test results. Through the multi-condition programmable parameter library, users can customize test program information according to their needs. This not only meets the configuration requirements of test program information for different scenarios but also satisfies user needs, improving system availability and ease of use.

[0063] It should be noted that, Figure 1 This is merely an example of the test system 10 and does not constitute a limitation on the test system 10. In actual applications, the test system 10 may include more modules, components, or units than shown in the figure, and the embodiments of this application do not limit this.

[0064] The attitude angle error determination method provided in the embodiments of this application will be explained in detail below.

[0065] Figure 2 This is a flowchart illustrating a method for determining attitude angle error provided in an embodiment of this application. For example, this method can be applied to the above... Figure 1 Test system 10 in the embodiment. See also Figure 2 The method may include the following steps: Step 201: The test system obtains test program information, which includes n working condition identifiers, where n is a positive integer.

[0066] The test program information consists of information related to the n working conditions identified by the n working condition identifiers that the test system needs to simulate.

[0067] For example, the test program information may be received by the test system, or, in response to a user's selection operation, the test system may obtain the test program information from multiple preset test program information. This application embodiment does not limit this.

[0068] The n operating condition identifiers are used to identify the n operating conditions under which the target equipment operates under simulated external environmental conditions. Optionally, the n operating condition identifiers may include one or more of the following: low-amplitude, low-frequency stable operating condition identifier, medium-amplitude, medium-frequency motion operating condition identifier, high-amplitude, low-frequency turbulence operating condition identifier, and high-frequency micro-vibration interference operating condition identifier.

[0069] By acquiring test program information, a data foundation is provided for simulating different operating conditions, thereby ensuring the systematic nature of the test and facilitating a comprehensive evaluation of the equipment's performance under various operating conditions. Furthermore, these n operating conditions can cover typical user environments, which helps to quickly expose the accuracy of the attitude angles calculated by the equipment under different motion frequencies and amplitudes.

[0070] Step 202: The test system simulates n operating conditions of the target device based on the test program information; wherein, during the simulation of any operating condition, a set of operating condition test information is acquired, which includes the first IMU data collected by the reference inertial measurement unit (IMU) and the second IMU data collected by the target device.

[0071] The target device is the device that needs to be tested. For example, the target device can be any one of smart glasses, an all-in-one AR head-mounted display, or a split head-mounted device. Of course, it is not limited to these, and the target device can also be other devices including an IMU. This application embodiment does not limit this.

[0072] The reference IMU is a device that collects actual motion data of the target device.

[0073] This test information pertains to the target device under this operating condition. The first IMU data represents the actual motion data of the target device. The second IMU data represents the data collected by the IMUs within the target device.

[0074] By simulating n different operating conditions and obtaining n sets of test information corresponding to these conditions, we can understand the performance of the target device under these n real-world scenarios (i.e., operating conditions), providing accurate data for subsequent determination of the target device's attitude angle error and further analysis. Furthermore, the reference IMU provides a reliable reference for subsequent error calculations, ensuring that attitude angle error calculations are based on solid evidence and avoiding the limitations of relying solely on theoretical models. This improves test accuracy.

[0075] In some implementations, the test program information also includes one or more of the following: vibration output mode corresponding to each of the n operating condition identifiers, vibration output parameters corresponding to each operating condition identifier, runtime corresponding to each operating condition identifier, operating condition execution order, operating condition switching interval duration, and operating condition cycle mode. The test system can simulate the n operating conditions of the target device based on the test program information as follows: based on the operating condition execution order and / or the operating condition cycle mode, the n operating condition identifiers are traversed sequentially; for the currently traversed operating condition identifier, one operating condition of the target device is simulated based on one or more of the vibration output mode, vibration output parameters, and runtime corresponding to the operating condition identifier; when the simulation of the operating condition ends, the traversal continues after waiting for the operating condition switching interval duration.

[0076] The vibration output mode is the mode in which the test system simulates vibration. For example, the vibration output mode may include one or more of a single-axis vibration mode and a multi-axis composite vibration mode, etc., and this application embodiment does not limit this. Specifically, the single-axis vibration mode refers to a vibration mode that outputs vibration excitation only in one direction (e.g., only up and down, only left and right, or only front and back), while remaining stationary in other directions; the multi-axis composite vibration mode refers to a vibration mode that outputs vibration excitation simultaneously in multiple directions.

[0077] The vibration output parameters corresponding to each operating condition identifier refer to the detailed parameters of the system output vibration under each operating condition. For example, these vibration parameters may include one or more of vibration amplitude, vibration frequency, acceleration, etc., but this application embodiment does not limit this.

[0078] The runtime corresponding to each working condition identifier refers to the test duration of each working condition. The working condition execution order refers to the order in which the n working conditions are simulated. The working condition switching interval refers to the waiting time required when switching to the next working condition after the simulation of one working condition has ended.

[0079] The working condition cycle mode refers to the mode of repeatedly executing the n working conditions. For example, the working condition cycle mode may include one or more of the following: single cycle mode, multiple cycle mode, and cycle mode with a specified duration, etc., and the embodiments of this application do not limit it.

[0080] In this way, on the one hand, the movement of the target device in a real-world scenario can be more accurately reproduced, ensuring the accuracy of the test results; on the other hand, by setting different parameters, the entire testing process can be tailored to user needs without requiring manual adjustments. This not only meets user requirements but also improves testing efficiency and accuracy, reducing uncertainties caused by human factors.

[0081] In some implementations, the test program information also includes a device attitude identifier corresponding to each of the n operating condition identifiers. Before the test system simulates an operating condition of the target device based on one or more of the vibration output mode, vibration output parameters, and runtime corresponding to the operating condition identifier, it adjusts the target device to the device attitude identified by the device attitude identifier corresponding to the operating condition identifier.

[0082] The device attitude identifier is an identifier for the attitude that the target device needs to maintain. For example, the device attitude identifier can be any one of a neutral attitude identifier, a small-angle deflection attitude identifier, or a large-angle deflection attitude identifier. Specifically, the neutral attitude identifier indicates that the target device is in a horizontal or designed reference position; the small-angle deflection attitude identifier indicates that the target device deflects slightly, simulating a user's slight head tilt or downward posture; the large-angle deflection attitude identifier indicates that the target device deflects significantly, simulating a user's extremely short-term wearing posture. By setting neutral, small-angle, and large-angle attitudes, not only can the target device's attitude sensitivity be effectively assessed, but the enormous workload of continuous angle testing can also be avoided, simplifying testing complexity and providing accurate and effective data support for IMU filtering algorithm optimization, hardware vibration damping structure improvement, and attitude calculation parameter iteration.

[0083] There is a correspondence between the device attitude identified by the device attitude marker and the operating conditions. This correspondence can be preset. For example, the attitude markers corresponding to the low-amplitude, low-frequency stable operating conditions can include neutral attitude markers, small-angle deflection attitude markers, and large-angle deflection attitude markers to perform basic accuracy verification of all attitudes; the attitude markers corresponding to the medium-amplitude, medium-frequency motion operating conditions can include neutral attitude markers and small-angle deflection attitude markers to simulate high-frequency usage scenarios of slight head turning interaction during user movement; the attitude markers corresponding to the high-amplitude, low-frequency turbulence operating conditions can include neutral attitude markers and small-angle deflection attitude markers to focus on detecting the error amplification problem caused by slight head movements under strong impact vibration; the attitude markers corresponding to the high-frequency micro-vibration interference operating conditions can include large-angle deflection attitude markers to verify the solution drift and stability attenuation caused by high-frequency jitter when the user turns their head or looks up significantly.

[0084] By adjusting the orientation of the target device, the testing dimensions can be increased, allowing error assessment to consider not only the motion conditions but also the device's own orientation. This closely approximates the various angles the device may be in during actual use, improving the accuracy of operational condition simulation and further enhancing the realism and comprehensiveness of the test.

[0085] In some implementations, the operation of the test system to acquire a set of operating condition test information may be as follows: acquiring first IMU data from the reference inertial measurement unit (IMU) and second IMU data from the target device; generating the set of operating condition test information based on the target operating condition identifier and / or the device attitude identifier corresponding to the target operating condition identifier, the first IMU data and the second IMU data, wherein the target operating condition identifier is the operating condition identifier of the operating condition being simulated.

[0086] For example, the testing system can simultaneously acquire data from the first IMU and the second IMU, which can eliminate timing deviations, effectively improve the accuracy and reliability of dynamic test data, ensure the validity of comparative data, and ensure that the attitude accuracy evaluation results are objective and reliable.

[0087] For example, the first IMU data and the second IMU data may be acquired periodically by the test system, or the first IMU data and the second IMU data may be acquired after the test system has simulated the operating conditions identified by the target operating condition identifier. This application embodiment does not limit this.

[0088] By acquiring data from the first IMU and the second IMU, data acquisition synchronization can be ensured. Combining the target operating condition identifier, the corresponding device attitude identifier, the first IMU data, and the second IMU data, structured and self-describing operating condition test information can be generated, which can facilitate subsequent analysis and enhance the manageability and traceability of the data.

[0089] Step 203: The test system determines the attitude angle error of the target device based on the n sets of working condition test information obtained.

[0090] The attitude angle error of the target device is the angle error between the rotation angle measured by the target device itself and the actual rotation angle.

[0091] Since the operating condition test information includes IMU data collected by the target device itself, as well as actual IMU data used for comparison, the attitude angle error of the target device can be determined accordingly.

[0092] By determining the attitude angle error of the target equipment, an intuitive and quantifiable performance indicator, attitude angle error, can be provided. This reflects the overall performance level of the target equipment under n operating conditions, facilitating subsequent qualification assessment and equipment optimization. Furthermore, the attitude angle error under multiple operating conditions provides a data foundation for in-depth analysis of error sources.

[0093] In some implementations, step 203 can be performed as follows: for any set of working condition test information in the n sets of working condition test information, the test system determines a first attitude angle based on the first IMU data in the set of working condition test information, and determines a second attitude angle based on the second IMU data in the set of working condition test information; the absolute difference between the first attitude angle and the second attitude angle is determined as the attitude angle error.

[0094] For example, the test system can determine the first attitude angle and the second attitude angle through an attitude calculation algorithm.

[0095] By determining the attitude angle error, a simple and clear quantitative indicator can be provided, which is convenient for threshold judgment or statistical analysis (such as mean and standard deviation). Moreover, the attitude angle error value can be directly used to evaluate whether the attitude calculation accuracy of the target device meets the design requirements.

[0096] In some implementations, after determining the attitude angle error of the target device based on the acquired n sets of operating condition test information, the testing system generates an attitude angle error test result for the target device based on the n sets of operating condition test information and the attitude angle error corresponding to each set of operating condition test information. The system then analyzes the attitude angle error test result to obtain an attitude angle error analysis report. This report includes the n sets of operating condition test information, the average value of the attitude angle error, one or more of n first influence weights and n second influence weights. The n first influence weights correspond one-to-one with the n operating conditions, and each first influence weight represents the influence of the operating condition on the attitude calculation accuracy of the target device. The n second influence weights correspond one-to-one with the n device attitudes, and each second influence weight represents the influence of the device attitude on the attitude calculation accuracy of the target device.

[0097] By generating attitude angle error test results for the target device, structured test result output can be provided, offering complete information support for subsequent analysis and facilitating archiving, sharing, and further processing. Analyzing these attitude angle error test results to obtain an attitude angle error analysis report can elevate test data into decision support information, enabling technicians to quickly locate the main error sources (such as a specific operating condition or attitude), thereby allowing for targeted improvements to hardware design, algorithm parameters, or calibration procedures.

[0098] The attitude angle error determination method provided in the embodiments of this application will be explained in detail below.

[0099] Figure 3 This is a flowchart illustrating a method for determining attitude angle error provided in an embodiment of this application. For example, this method can be applied to the above... Figure 1The test system in this embodiment includes a working condition simulation module, a clamping module, a reference IMU, a data acquisition module, and an analysis module. The clamping module is used to clamp the target device, and the reference IMU is fixedly connected to the clamping module. (See also...) Figure 3 The method may include the following steps: Step 301: The working condition simulation module obtains the test program information, which includes n working condition identifiers, where n is a positive integer; based on the test program information, it simulates n operating conditions of the target equipment.

[0100] For example, the working condition simulation module can receive test program information sent by the analysis module, or the working condition simulation module can obtain the test program information from multiple preset test program information in response to the user's selection operation. This application embodiment does not limit this.

[0101] Optionally, the n operating condition identifiers include one or more of the following: low-amplitude, low-frequency stable operating condition identifier, medium-amplitude, medium-frequency motion operating condition identifier, high-amplitude, low-frequency bumpy operating condition identifier, and high-frequency micro-vibration interference operating condition identifier.

[0102] In some implementations, the test program information also includes one or more of the following: vibration output mode corresponding to each of the n operating condition identifiers, vibration output parameters corresponding to each operating condition identifier, runtime corresponding to each operating condition identifier, operating condition execution order, operating condition switching interval duration, and operating condition cycle mode. The operation of the operating condition simulation module to simulate n operating conditions of the target device based on the test program information can be as follows: based on the operating condition execution order and / or the operating condition cycle mode, traverse the n operating condition identifiers sequentially; for the currently traversed operating condition identifier, simulate one operating condition of the target device based on one or more of the vibration output mode, vibration output parameters, and runtime corresponding to the operating condition identifier; when the operating condition simulation ends, wait for the operating condition switching interval duration and then continue traversing.

[0103] In some implementations, the test procedure information also includes a device posture identifier corresponding to each of the n working condition identifiers. Before the working condition simulation module simulates a working condition of the target device based on one or more of the vibration output mode, vibration output parameters, and running time corresponding to the working condition identifier, the clamping module adjusts the target device to the device posture identified by the device posture identifier corresponding to the working condition identifier.

[0104] For example, the clamping module can receive the attitude adjustment command sent by the working condition simulation module, and adjust the target device to the device attitude identified by the device attitude identifier based on the device attitude information in the attitude adjustment command.

[0105] Optionally, the device attitude identifier can be any one of a neutral attitude identifier, a small-angle deflection attitude identifier, or a large-angle deflection attitude identifier.

[0106] Step 302: During the simulation of any operating condition by the operating condition simulation module, the data acquisition module acquires a set of operating condition test information, which includes the first IMU data acquired by the reference inertial measurement unit (IMU) and the second IMU data acquired by the target device.

[0107] For example, the target device can be any of the following: smart glasses, an all-in-one augmented reality (AR) head-mounted display, or a split head-mounted device.

[0108] After acquiring a set of operating condition test information, the data acquisition module can send the set of operating condition test information to the analysis module. Alternatively, after acquiring n sets of operating condition test information corresponding to the n operating conditions, the data acquisition module can send the n sets of operating condition test information to the analysis module. This application embodiment does not limit this.

[0109] In some implementations, the data acquisition module may acquire a set of operating condition test information by: acquiring first IMU data from the reference inertial measurement unit (IMU) and second IMU data from the target device; generating the set of operating condition test information based on the target operating condition identifier and / or the device attitude identifier corresponding to the target operating condition identifier, the first IMU data, and the second IMU data, wherein the target operating condition identifier is the operating condition identifier of the operating condition being simulated.

[0110] Specifically, the data acquisition module can receive a start test message sent by the operating condition simulation module. After receiving the start test message, the operating condition simulation module sends a data acquisition message to the reference IMU and the target device. After receiving the data acquisition message, the reference IMU sends first IMU data to the data acquisition module, and the target device sends second IMU data to the data acquisition module. The data acquisition module receives the first IMU data sent by the reference IMU and the second IMU data sent by the target device.

[0111] The target operating condition identifier can be obtained in advance. For example, the target operating condition identifier can be sent to the data acquisition module by the operating condition simulation module before simulating an operating condition.

[0112] Step 303: The analysis module determines the attitude angle error of the target device based on the acquired n sets of working condition test information.

[0113] This analysis module can receive n sets of operating condition test information sent by the data acquisition module.

[0114] For example, the analysis module may determine the attitude angle error of the target device based on the n sets of working condition test information obtained after receiving the test completion message sent by the working condition simulation module.

[0115] In some implementations, the operation of the analysis module to determine the attitude angle error of the target device based on the acquired n sets of working condition test information can be as follows: for any set of working condition test information in the n sets of working condition test information, determine the first attitude angle based on the first IMU data in the set of working condition test information, and determine the second attitude angle based on the second IMU data in the set of working condition test information; and determine the absolute difference between the first attitude angle and the second attitude angle as the attitude angle error.

[0116] In some implementations, after determining the attitude angle error of the target device based on the acquired n sets of operating condition test information, the analysis module generates the attitude angle error test result of the target device based on the n sets of operating condition test information and the attitude angle error corresponding to each set of operating condition test information. The attitude angle error test result is analyzed to obtain an attitude angle error analysis report. The attitude angle error analysis report includes the n sets of operating condition test information, the average value of the attitude angle error, one or more of the following: n first influence weights and n second influence weights. The n first influence weights correspond one-to-one with the n operating conditions, and the first influence weight is the influence weight of the operating condition on the attitude calculation accuracy of the target device. The n second influence weights correspond one-to-one with the n device attitudes, and the second influence weight is the influence weight of the device attitude on the attitude calculation accuracy of the target device.

[0117] To facilitate understanding, the following will be combined with... Figure 4 The method for determining attitude angle error provided in the embodiments of this application is described below.

[0118] Figure 4 This is a flowchart of an attitude angle error determination method provided in an embodiment of this application. Figure 4 As shown, the method includes steps 401 to 405.

[0119] Step 401: Test the system to clamp the target device and adjust and lock the tilt, lateral, and pitch attitudes.

[0120] Step 402: The test system simulates dynamic working conditions based on the acquired test program information, which includes n working condition identifiers.

[0121] Step 403: The test system acquires n sets of working condition test information. Any set of working condition test information in the n sets includes first IMU data and second IMU data. The first IMU data and second IMU data in any set of working condition test information in the n sets are acquired synchronously.

[0122] Step 404: The test system generates the attitude angle error test results of the target device based on the n sets of working condition test information.

[0123] Step 405: The testing system analyzes the attitude angle error test results and obtains an attitude angle error analysis report.

[0124] In this embodiment, the testing system acquires test program information, which includes n operating condition identifiers. Based on this information, it simulates n operating conditions of the target device. During the simulation of any operating condition, a set of operating condition test information is acquired, including first IMU data collected by a reference IMU and second IMU data collected by the target device. Finally, the attitude angle error of the target device is determined based on the acquired n sets of operating condition test information. Through automated multi-condition simulation and dual IMU comparison, the scenario fit and test realism of the target device's attitude accuracy detection can be significantly improved. This not only improves the accuracy of the attitude angle error test results but also enhances test standardization, consistency, and reproducibility. Furthermore, since no complex external measurement equipment is required and the entire testing process can be automated, testing costs are reduced while ensuring the objectivity and comprehensiveness of the test results, providing a reliable technical means for equipment development and quality control.

[0125] Figure 5 This is a schematic diagram of an attitude angle error determination device provided in an embodiment of this application. The device can be implemented as part or all of a computer device by software, hardware, or a combination of both. This computer device can be described below. Figure 6 The computer equipment shown. See also Figure 5 The device includes: a first acquisition module 501, a second acquisition module 502, and a determination module 503.

[0126] The first acquisition module 501 is used to acquire test program information, which includes n working condition identifiers, where n is a positive integer. The second acquisition module 502 is used to simulate n operating conditions of the target device based on the test program information; wherein, during the simulation of any operating condition, a set of operating condition test information is acquired, which includes the first IMU data collected by the reference inertial measurement unit IMU and the second IMU data collected by the target device. The determination module 503 is used to determine the attitude angle error of the target device based on the acquired n sets of working condition test information.

[0127] Optionally, the n operating condition identifiers include one or more of the following: low-amplitude, low-frequency stable operating condition identifier, medium-amplitude, medium-frequency motion operating condition identifier, high-amplitude, low-frequency bumpy operating condition identifier, and high-frequency micro-vibration interference operating condition identifier.

[0128] Optionally, the test program information also includes one or more of the following: vibration output mode corresponding to each of the n working condition identifiers, vibration output parameters corresponding to each working condition identifier, runtime corresponding to each working condition identifier, working condition execution order, working condition switching interval duration, and working condition cycle mode. The second acquisition module 502 is used for: Based on the execution order of the working condition and / or the cyclic mode of the working condition, traverse the n working condition identifiers in sequence; For a current operating condition identifier, simulate an operating condition of the target device based on one or more of the vibration output mode, vibration output parameters, and running time corresponding to the operating condition identifier; when the simulation of the operating condition ends, wait for the operating condition switching interval before continuing to traverse.

[0129] Optionally, the test procedure information also includes the equipment attitude identifier corresponding to each of the n working condition identifiers, and the device further includes: The adjustment module is used to adjust the target device to the device posture indicated by the device posture identifier corresponding to the operating condition identifier.

[0130] Optionally, the device attitude identifier can be any one of a neutral attitude identifier, a small-angle deflection attitude identifier, or a large-angle deflection attitude identifier.

[0131] Optionally, the second acquisition module 502 is used for: Acquire first IMU data from the reference inertial measurement unit (IMU), and acquire second IMU data from the target device; Based on the target operating condition identifier and / or the device attitude identifier corresponding to the target operating condition identifier, the first IMU data and the second IMU data, this set of operating condition test information is generated. The target operating condition identifier is the operating condition identifier of the operating condition being simulated.

[0132] Optionally, the determining module 503 is used for: For any set of working condition test information in the n sets of working condition test information, the first attitude angle is determined based on the first IMU data in the set of working condition test information, and the second attitude angle is determined based on the second IMU data in the set of working condition test information. The absolute difference between the first attitude angle and the second attitude angle is defined as the attitude angle error.

[0133] Optionally, the device further includes: The generation module is used to generate the attitude angle error test results of the target device based on the n sets of working condition test information and the attitude angle error corresponding to each set of working condition test information in the n sets of working condition test information. The analysis module is used to analyze the attitude angle error test results and obtain an attitude angle error analysis report. The attitude angle error analysis report includes the n sets of test information under the operating conditions, the average value of the attitude angle error, one or more of the n first influence weights and n second influence weights. The n first influence weights correspond one-to-one with the n operating conditions, and the first influence weight is the influence weight of the operating condition on the attitude calculation accuracy of the target device. The n second influence weights correspond one-to-one with the n device attitudes, and the second influence weight is the influence weight of the device attitude on the attitude calculation accuracy of the target device.

[0134] Optionally, the target device can be any one of smart glasses, an all-in-one augmented reality (AR) head-mounted display, or a split head-mounted device.

[0135] In this embodiment, test program information is acquired, including n operating condition identifiers. Then, based on this test program information, n operating conditions of the target device are simulated. During the simulation of any operating condition, a set of operating condition test information is acquired, including first IMU data collected by a reference IMU and second IMU data collected by the target device. Finally, the attitude angle error of the target device is determined based on the acquired n sets of operating condition test information. Through automated multi-condition simulation and dual IMU comparison, the scene fit and test realism of the target device's attitude accuracy detection can be significantly improved. This not only improves the accuracy of the attitude angle error test results but also enhances test standardization, consistency, and reproducibility. Furthermore, since no complex external measurement equipment is required and fully automated testing can be achieved, testing costs are reduced while ensuring the objectivity and comprehensiveness of test results, providing a reliable technical means for equipment development and quality control.

[0136] It should be noted that the attitude angle error determination device provided in the above embodiments is only illustrated by the division of the above functional modules when determining the attitude angle error. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0137] The functional modules in the above embodiments can be integrated into one processing unit, or each functional module can exist as a separate physical processing unit, or two or more functional modules can be integrated into one processing unit. The processing unit can be implemented in hardware or software. Furthermore, the specific names of the functional modules are only for easy differentiation and are not intended to limit the scope of protection of the embodiments of this application.

[0138] The attitude angle error determination device and attitude angle error determination method provided in the above embodiments belong to the same concept. The specific working process and technical effects of the functional modules in the above embodiments can be found in the method embodiments section, and will not be repeated here.

[0139] Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Figure 6 As shown, the computer device 6 includes a processor 60, a memory 61, and a computer program 62 stored in the memory 61 and executable on the processor 60. When the processor 60 executes the computer program 62, it implements the steps in the attitude angle error determination method in the above embodiments.

[0140] Computer device 6 can be a testing device. Those skilled in the art will understand that... Figure 6 The computer device 6 is merely an example and does not constitute a limitation on the computer device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0141] Processor 60 can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0142] In some embodiments, memory 61 may be an internal storage unit of the computer device 6, such as a hard disk or RAM of the computer device 6. In other embodiments, memory 61 may be an external storage device of the computer device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on the computer device 6. Furthermore, memory 61 may include both internal and external storage units of the computer device 6. Memory 61 is used to store the operating system, applications, boot loader, data, and other programs. Memory 61 may also be used to temporarily store data that has been output or will be output.

[0143] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0144] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0145] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps in the various method embodiments described above.

[0146] This application provides a computer program product that, when run on a computer, causes the computer to perform the steps described in the various method embodiments above.

[0147] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above method embodiments of this application can be implemented by a computer program. This computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate form. The computer-readable storage medium can include at least: any entity or device capable of carrying computer program code to a computer device, recording media, computer memory, read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage devices. The computer-readable storage medium mentioned in this application can be a non-volatile storage medium; in other words, it can be a non-transient storage medium.

[0148] It should be understood that all or part of the steps of the above embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented in whole or in part as a computer program product. The computer program product includes one or more computer instructions. The computer instructions can be stored in the above-described computer-readable storage medium.

[0149] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0150] In the embodiments provided in this application, it should be understood that the disclosed apparatus / computer devices and methods can be implemented in other ways. For example, the apparatus / computer device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this application according to actual needs.

[0151] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0152] The embodiments described above are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method of determining an attitude angle error, characterized by, Applied to a testing system, the method includes: The test program information includes n operating condition identifiers, the vibration output mode corresponding to each of the n operating condition identifiers, the vibration output parameters corresponding to each operating condition identifier, the runtime corresponding to each operating condition identifier, the equipment attitude identifier corresponding to each operating condition identifier, the operating condition execution sequence, the operating condition switching interval duration, and the operating condition cycle mode. The n operating condition identifiers include low-amplitude, low-frequency stable operating condition identifiers, medium-amplitude, medium-frequency motion operating condition identifiers, high-amplitude, low-frequency bump operating condition identifiers, and high-frequency micro-vibration interference operating condition identifiers. The equipment attitude identifiers corresponding to the low-amplitude, low-frequency stable operating condition identifiers include neutral attitude identifiers, small-angle deflection attitude identifiers, and large-angle deflection attitude identifiers. The equipment attitude identifiers corresponding to the medium-amplitude, medium-frequency motion operating condition identifiers include neutral attitude identifiers and small-angle deflection attitude identifiers. The equipment attitude identifiers corresponding to the high-amplitude, low-frequency bump operating condition identifiers include neutral attitude identifiers and small-angle deflection attitude identifiers. The equipment attitude identifiers corresponding to the high-frequency micro-vibration interference operating condition identifiers include large-angle deflection attitude identifiers. Here, n is a positive integer. Based on the execution order of the operating conditions and / or the cycle mode of the operating conditions, the n operating condition identifiers are traversed sequentially; for the currently traversed operating condition identifier, the target device is adjusted to the device attitude identified by the device attitude identifier corresponding to the operating condition identifier; based on one or more of the vibration output mode, vibration output parameters, and runtime corresponding to the operating condition identifier, a certain operating condition of the target device is simulated; when the simulation of the operating condition ends, the traversal continues after waiting for the operating condition switching interval; wherein, during the simulation of any operating condition, a set of operating condition test information is acquired, the set of operating condition test information including the first IMU data collected by the reference inertial measurement unit IMU and the second IMU data collected by the target device; The attitude angle error of the target device is determined based on the obtained n sets of working condition test information.

2. The method of claim 1, wherein, The acquisition of a set of working condition test information includes: The first IMU data is acquired from the reference inertial measurement unit (IMU), and the second IMU data is acquired from the target device; Based on the target operating condition identifier and / or the device attitude identifier corresponding to the target operating condition identifier, the first IMU data and the second IMU data, the set of operating condition test information is generated, wherein the target operating condition identifier is the operating condition identifier of the operating condition being simulated.

3. The method as described in claim 2, characterized in that, The determination of the attitude angle error of the target device based on the acquired n sets of working condition test information includes: For any set of working condition test information in the n sets of working condition test information, a first attitude angle is determined based on the first IMU data in the set of working condition test information, and a second attitude angle is determined based on the second IMU data in the set of working condition test information. The absolute difference between the first attitude angle and the second attitude angle is defined as the attitude angle error.

4. The method as described in claim 1, characterized in that, After determining the attitude angle error of the target device based on the acquired n sets of working condition test information, the method further includes: Based on the n sets of working condition test information and the attitude angle error corresponding to each set of working condition test information in the n sets of working condition test information, the attitude angle error test result of the target device is generated; The attitude angle error test results are analyzed to obtain an attitude angle error analysis report. The attitude angle error analysis report includes the n sets of test information under operating conditions, the average value of the attitude angle error, one or more of the n first influence weights and n second influence weights. The n first influence weights correspond one-to-one with the n operating conditions, and the first influence weights are the influence weights of the operating conditions on the attitude calculation accuracy of the target device. The n second influence weights correspond one-to-one with the n device attitudes, and the second influence weights are the influence weights of the device attitudes on the attitude calculation accuracy of the target device.

5. The method according to any one of claims 1 to 4, characterized in that, The target device can be any one of smart glasses, an integrated augmented reality (AR) head-mounted display, or a split-type head-mounted device.

6. A testing system, characterized in that, The testing system includes a working condition simulation module, a clamping module, a reference inertial measurement unit (IMU), a data acquisition module, and an analysis module. The clamping module is used to clamp the target device, and the reference inertial measurement unit (IMU) is fixedly connected to the clamping module. The operating condition simulation module is used to: acquire test program information, which includes n operating condition identifiers, vibration output mode corresponding to each of the n operating condition identifiers, vibration output parameters corresponding to each operating condition identifier, runtime corresponding to each operating condition identifier, equipment attitude identifier corresponding to each operating condition identifier, operating condition execution sequence, operating condition switching interval duration, and operating condition cycle mode. The n operating condition identifiers include low-amplitude, low-frequency stable operating condition identifiers, medium-amplitude, medium-frequency motion operating condition identifiers, high-amplitude, low-frequency bumpy operating condition identifiers, and high-frequency micro-vibration interference operating condition identifiers. The equipment attitude identifiers corresponding to the low-amplitude, low-frequency stable operating condition identifiers include neutral attitude identifiers, small-angle deflection attitude identifiers, and large-angle deflection attitude identifiers. The equipment attitude identifiers corresponding to the medium-amplitude, medium-frequency motion operating condition identifiers include neutral attitude identifiers and small-angle deflection attitude identifiers. The equipment attitude identifiers corresponding to the high-amplitude, low-frequency bumpy operating condition identifiers include neutral attitude identifiers and small-angle deflection attitude identifiers. The equipment attitude identifiers corresponding to the high-frequency micro-vibration interference operating condition identifiers include large-angle deflection attitude identifiers. The n is a positive integer. Based on the execution order of the working conditions and / or the working condition cycle mode, the n working condition identifiers are traversed sequentially; for the currently traversed working condition identifier, the target device is adjusted to the device posture identified by the device posture identifier corresponding to the working condition identifier; Simulate one or more of the vibration output mode, vibration output parameters, and running time corresponding to the operating condition identifier for the target device; after the simulation of the operating condition ends, wait for the operating condition switching interval before continuing the iteration; The data acquisition module is used to: acquire a set of operating condition test information during the simulation of any operating condition by the operating condition simulation module, wherein the set of operating condition test information includes first IMU data acquired by the reference inertial measurement unit (IMU) and second IMU data acquired by the target device; The analysis module is used to determine the attitude angle error of the target device based on the acquired n sets of working condition test information.

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