Angular velocity temperature drift compensation value acquisition method, compensation method, medium and equipment

Abstract

The invention provides an angular velocity temperature drift compensation value acquisition method, a compensation method, a medium and equipment, which are applied to head-mounted display equipment. The angular velocity temperature drift compensation value acquisition method comprises the following steps: monitoring the use state of the head-mounted display device; if the use state is a standing state, acquiring real-time temperature data and corresponding real-time angular velocity offset data of the head-mounted display device; according to the real-time temperature data, the real-time angular velocity bias data, the multiple pieces of historical temperature data and the multiple pieces of historical angular velocity bias data, obtaining a target association relationship between the temperature data and the angular velocity bias data; and obtaining target angular velocity offset data corresponding to the real-time temperature data according to the target association relationship, and determining the target angular velocity offset data as an angular velocity temperature drift compensation value. According to the invention, the angular velocity temperature drift compensation value can be accurately obtained so as to obtain the angular velocity data with high accuracy.

Description

Technical Field

[0001] The present application relates to the technical field of obtaining angular velocity, and in particular to a method for obtaining angular velocity temperature drift compensation values, a compensation method, a medium and a device. Background Art

[0002] The head-mounted display device is equipped with an IMU (inertial sensor) that measures the angular velocity (or three-axis attitude angle) and acceleration of an object. In actual use, the head-mounted display device will experience temperature drift due to temperature changes, which causes changes in semiconductor device parameters caused by temperature changes, greatly reducing the accuracy of the angular velocity data obtained by the head-mounted display device. Therefore, how to obtain the angular velocity temperature drift compensation value of the head-mounted display device is the key to improving the accuracy of the angular velocity data. However, the existing related technologies cannot accurately obtain the angular velocity temperature drift compensation value of the head-mounted display device. Summary of the invention

[0003] The purpose of the present application is to overcome the shortcomings and deficiencies in the prior art and to provide a method for obtaining an angular velocity temperature drift compensation value, a compensation method, a medium and a device, which can accurately obtain an angular velocity temperature drift compensation value to obtain angular velocity data with high accuracy.

[0004] A first aspect of an embodiment of the present application provides a method for obtaining an angular velocity temperature drift compensation value, which is applied to a head mounted display device. The temperature drift compensation method includes:

[0005] Monitoring the use state of the head mounted display device; if the use state is a static state, obtaining real-time temperature data and corresponding real-time angular velocity bias data of the head mounted display device;

[0006] Obtaining a target association relationship between the temperature data and the angular velocity bias data according to the real-time temperature data, the real-time angular velocity bias data, a plurality of historical temperature data, and a plurality of historical angular velocity bias data;

[0007] According to the target association relationship, target angular velocity bias data corresponding to the real-time temperature data is obtained, and the target angular velocity bias data is determined as the angular velocity temperature drift compensation value.

[0008] A second aspect of an embodiment of the present application provides an angular velocity temperature drift compensation method, comprising:

[0009] The angular velocity temperature drift compensation value corresponding to the real-time temperature data is obtained by the above-mentioned angular velocity temperature drift compensation value obtaining method;

[0010] The angular velocity data of the head mounted display device is compensated according to the angular velocity temperature drift compensation value to obtain target angular velocity data of the head mounted display device.

[0011] A third aspect of an embodiment of the present application provides an angular velocity temperature drift compensation value acquisition device, which is applied to a head mounted display device, and the temperature drift compensation method includes:

[0012] A real-time data acquisition module, used to monitor the use state of the head-mounted display device; if the use state is a static state, obtain the real-time temperature data and corresponding real-time angular velocity bias data of the head-mounted display device;

[0013] A target association relationship acquisition module, used to obtain a target association relationship between temperature data and angular velocity bias data according to the real-time temperature data, the real-time angular velocity bias data, a plurality of historical temperature data and a plurality of historical angular velocity bias data;

[0014] The angular velocity temperature drift compensation value acquisition module is used to obtain the target angular velocity bias data corresponding to the real-time temperature data according to the target association relationship, and determine the target angular velocity bias data as the angular velocity temperature drift compensation value.

[0015] A fourth aspect of an embodiment of the present application provides an angular velocity temperature drift compensation device, comprising:

[0016] The temperature drift compensation value acquisition module obtains the angular velocity temperature drift compensation value corresponding to the real-time temperature data through the angular velocity temperature drift compensation value acquisition method above;

[0017] The target angular velocity data acquisition module compensates the angular velocity data of the head mounted display device according to the angular velocity temperature drift compensation value to obtain the target angular velocity data of the head mounted display device.

[0018] A fifth aspect of an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the method for obtaining the angular velocity temperature drift compensation value as described above, or the steps of the method for compensating the angular velocity temperature drift as described above.

[0019] A sixth aspect of an embodiment of the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein when the processor executes the computer program, the steps of the method for obtaining the angular velocity temperature drift compensation value as described above, or the steps of the method for compensating the angular velocity temperature drift as described above are implemented.

[0020] Compared with the related art, the present application detects the use state of the head-mounted display device, and when the use state of the head-mounted display device is a static state, obtains real-time temperature data and corresponding real-time angular velocity bias data, and then obtains the target association relationship between the temperature data and the angular velocity bias data according to the real-time temperature data, the real-time angular velocity bias data, multiple historical temperature data, and multiple historical angular velocity bias data, so as to obtain the target angular velocity bias data corresponding to the real-time temperature data according to the target association relationship, thereby accurately obtaining the angular velocity temperature drift compensation value of the head-mounted display device. Among them, since the newly obtained real-time temperature data and real-time angular velocity bias data are obtained when the use state of the head-mounted display device is a static state, they can become historical temperature data and historical angular velocity data, so they can be expanded as the historical temperature data and historical angular velocity data of the head-mounted display device increase with the number of uses, reducing the workload of obtaining the historical temperature data and historical angular velocity data when the head-mounted display device leaves the factory. Moreover, as the number of times the head-mounted display device is used increases, the accuracy of the angular velocity temperature drift compensation value of the head-mounted display device will also be improved due to the expansion of data.

[0021] In order to provide a clearer understanding of the present application, the specific implementation of the present application will be described below in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of a method for obtaining an angular velocity temperature drift compensation value according to an embodiment of the present application.

[0023] Figure 2 A schematic diagram of target association relationships in three directions of a method for obtaining angular velocity temperature drift compensation values ​​according to an embodiment of the present application.

[0024] Figure 3 The flowchart of the angular velocity temperature drift compensation method according to one embodiment of the present application is shown.

[0025] Figure 4 This is a schematic diagram of module connections of a device for acquiring angular velocity temperature drift compensation values ​​according to an embodiment of the present application.

[0026] Figure 5 This is a schematic diagram of module connections of an angular velocity temperature drift compensation device according to an embodiment of the present application.

[0027] 100. angular velocity temperature drift compensation value acquisition device; 101. real-time data acquisition module; 102. target association relationship acquisition module; 103. angular velocity temperature drift compensation value acquisition module; 200. angular velocity temperature drift compensation device; 201. temperature drift compensation value acquisition module; 202. target angular velocity data acquisition module. DETAILED DESCRIPTION

[0028] In order to make the objectives, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0029] It should be clear that the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the embodiments of the present application.

[0030] When the following description relates to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances. The singular forms of "a", "said" and "the" used in the present application and the appended claims are also intended to include the majority form, unless the context clearly indicates other meanings. The words "if" / "if" used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0031] In addition, in the description of this application, unless otherwise specified, "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0032] In order to better understand the technical solution of the present application, the relevant application scenarios of the present application are introduced below.

[0033] The application scenarios of this application include head-mounted display devices. Head-mounted display devices are products that utilize a variety of technology combinations such as simulation technology, computer graphics, human-computer interface technology, multimedia technology, sensor technology, and network technology. They are a new means of human-computer interaction created with the help of computers and the latest sensor technology. Among them, head-mounted display devices rely on a large number of sensors to detect user movements and transmit information to the VR processor. Among all sensors, IMU (inertial sensor) is particularly important. At present, the IMUs used in head-mounted display devices include 3-axis IMU and 6-axis IMU, among which 3-axis IMU refers to a 3-axis gyroscope that can obtain angular velocity. The 6-axis IMU integrates a 3-axis gyroscope and a 3-axis acceleration sensor, which can obtain angular velocity data and acceleration data.

[0034] See also Figure 1, which is a method for obtaining angular velocity temperature drift compensation values ​​according to an embodiment of the present application, and is applied to a head mounted display device. The method for obtaining angular velocity temperature drift compensation values ​​includes:

[0035] S1: Monitor the usage status of the head-mounted display device; if the usage status is a static state, obtain real-time temperature data and corresponding real-time angular velocity bias data of the head-mounted display device.

[0036] If the usage state is not a static state, keep monitoring the usage state of the head mounted display device until the usage state of the head mounted display device is a static state, and obtain real-time temperature data and corresponding real-time angular velocity bias data.

[0037] The usage state refers to the state of the head-mounted display device when the user uses the head-mounted display device after the head-mounted display device leaves the factory. The head-mounted display device of this embodiment may store some historical temperature data and historical angular velocity bias data when it leaves the factory, or may not store any historical temperature data and historical angular velocity bias data. After the head-mounted display device leaves the factory, by monitoring the usage state of the head-mounted display device, when the usage state of the head-mounted display device is restored to a static state after each use by the user, the real-time temperature data and the corresponding real-time angular velocity bias data of the head-mounted display device are acquired. Therefore, the real-time temperature data and the corresponding real-time angular velocity bias data acquired during the use of the head-mounted display device can be stored in the head-mounted display device as new historical temperature data and new historical angular velocity bias data after being used to acquire the angular velocity temperature drift compensation value, thereby expanding the data volume of the head-mounted display device.

[0038] Angular velocity bias data is data including angular velocity bias values ​​in three directions, and generally the angular velocity bias data can be divided into three axes: x, y and z to distinguish the directions of the angular velocity bias values. Among them, real-time angular velocity bias data refers to angular velocity bias data acquired in real time.

[0039] S2: Obtaining a target correlation relationship between the temperature data and the angular velocity bias data according to the real-time temperature data, the real-time angular velocity bias data, a plurality of historical temperature data, and a plurality of historical angular velocity bias data.

[0040] The historical angular velocity bias data refers to the angular velocity bias data stored in the head mounted display device.

[0041] The target association relationship is obtained by fitting a plurality of temperature data and angular velocity bias data, and is used to stably express the relationship between the temperature data and the angular velocity bias data. Specifically, the target association relationship can be obtained by polynomial fitting.

[0042] Specifically, the target association relationship can be expressed as the following formula:

[0043] temperature_gyro_bias

[0044] =A×temperature 4 +B×temperature 3 +C×temperature 2 +D

[0045] ×temperature 1 +E

[0046] Among them, temperature_gyro-bias is the angular velocity bias data, temperature is the corresponding temperature data, and temperature 4 is the fourth power of temperature data, temperature 3 is the cube of temperature data, temperature 2 is the square of temperature data, and A, B, C, D and E are the relationship parameters of the target association relationship respectively.

[0047] See also Figure 2 Since the angular velocity bias data includes the angular velocity bias values ​​in three directions, it is necessary to construct the target association relationship of the angular velocity bias data for the three directions according to the corresponding direction axes of the angular velocity bias data. Among them, temperature_imu_gyr_x, temperature_imu_gyr_y and temperature_imu_gyr_z respectively represent the directions corresponding to the x, z and z axes, radius represents the angular velocity bias value in the corresponding direction, and temperature represents the temperature data.

[0048] Specifically, during the execution of step S2, the validity of the real-time angular velocity bias data is judged, and then, according to the validity of the real-time angular velocity bias data, data for obtaining the target association relationship between the temperature data and the angular velocity bias data is selected from the real-time temperature data, the real-time angular velocity bias data, the multiple historical temperature data, and the multiple historical angular velocity bias data. If the angular velocity bias value in one direction of the real-time angular velocity bias data is invalid data, the real-time angular velocity bias data is determined to be invalid data.

[0049] For example, if the real-time angular velocity bias data is invalid data, only multiple historical temperature data and multiple historical angular velocity bias data are used as data for obtaining the target association relationship. If the real-time angular velocity bias data is valid data, the real-time temperature data, the real-time angular velocity bias data, multiple historical temperature data and multiple historical angular velocity bias data are used as data for obtaining the target association relationship, and the real-time angular velocity bias data as valid data will be stored in the head-mounted display device as historical angular velocity bias data, and the corresponding real-time temperature data will also be stored in the head-mounted display device as historical temperature data.

[0050] In an optional embodiment, if the corresponding real-time temperature data is repeated with a historical temperature data, but the real-time angular velocity bias data is different from the historical angular velocity bias data corresponding to the repeated historical temperature data, then the angular velocity bias data that is closest to the target association relationship among the two angular velocity bias data can be retained as the historical angular velocity bias data.

[0051] S3: According to the target association relationship, the target angular velocity bias data corresponding to the real-time temperature data is obtained, and the target angular velocity bias data is determined as the angular velocity temperature drift compensation value.

[0052] Compared with the real-time angular velocity bias data, the target angular velocity bias data corresponding to the real-time temperature data obtained according to the target association relationship is more stable and reduces the influence of factors other than temperature. Therefore, the accuracy of the target angular velocity bias data is also higher.

[0053] Compared with the related art, the present application detects the use state of the head-mounted display device, and when the use state of the head-mounted display device is a static state, obtains real-time temperature data and corresponding real-time angular velocity bias data, and then obtains the target association relationship between the temperature data and the angular velocity bias data according to the real-time temperature data, the real-time angular velocity bias data, multiple historical temperature data, and multiple historical angular velocity bias data, so as to obtain the target angular velocity bias data corresponding to the real-time temperature data according to the target association relationship, thereby accurately obtaining the angular velocity temperature drift compensation value of the head-mounted display device. Among them, since the newly obtained real-time temperature data and real-time angular velocity bias data are obtained when the use state of the head-mounted display device is a static state, they can become historical temperature data and historical angular velocity data, so they can be expanded as the historical temperature data and historical angular velocity data of the head-mounted display device increase with the number of uses, reducing the workload of obtaining the historical temperature data and historical angular velocity data when the head-mounted display device leaves the factory. Moreover, as the number of times the head-mounted display device is used increases, the accuracy of the angular velocity temperature drift compensation value of the head-mounted display device will also be improved due to the expansion of data.

[0054] In a feasible embodiment, S2: the step of obtaining a target association relationship between temperature data and angular velocity bias data according to real-time temperature data, real-time angular velocity bias data, a plurality of historical temperature data, and a plurality of historical angular velocity bias data comprises:

[0055] S21: Determine the validity of the real-time angular velocity bias data.

[0056] The validity of the real-time angular velocity bias data can be judged based on the distance between the real-time angular velocity bias data and the target association relationship. For example, when the distance is large, the real-time angular velocity bias data may be affected by other factors, resulting in inaccurate data detection, so the real-time angular velocity bias data is judged to be invalid data. When the distance is small, the real-time angular velocity bias data is less affected by other factors, so the real-time angular velocity bias data is judged to be valid data. Among them, the large distance and the small distance can be judged by setting a threshold. The distance described in this embodiment refers to the difference between the real-time angular velocity bias data and the target association relationship at the temperature corresponding to the real-time temperature data, so it can also be understood as the difference between the real-time angular velocity bias data and the target association relationship or the absolute value of the difference.

[0057] S22: If the real-time angular velocity bias data is valid data, a target association relationship is obtained according to the real-time temperature data, the real-time angular velocity bias data, a plurality of historical temperature data and a plurality of historical angular velocity bias data.

[0058] When the real-time angular velocity bias data is valid data, the target association relationship is obtained based on the real-time temperature data, the real-time angular velocity bias data, multiple historical temperature data and multiple historical angular velocity bias data, which increases the amount of data used to obtain the target association relationship and can effectively improve the accuracy of the obtained target association relationship.

[0059] S23: If the real-time angular velocity bias data is invalid data, a target association relationship is obtained according to a plurality of historical temperature data and a plurality of historical angular velocity bias data.

[0060] When the real-time angular velocity bias data is invalid data, the real-time temperature data and the real-time angular velocity bias data are excluded, and the target association relationship is obtained only based on multiple historical temperature data and multiple historical angular velocity bias data. This can prevent invalid data from interfering with the target association relationship and maintain the high accuracy of the target association relationship.

[0061] In this embodiment, through steps S21-S23, data for obtaining target association relationships can be selected in view of the limitation of real-time angular velocity offset data, so as to obtain target association relationships with high accuracy.

[0062] In a feasible embodiment, S21: the step of judging the validity of the real-time angular velocity bias data comprises:

[0063] S211: Determine the data type of the real-time temperature data.

[0064] Among them, the data type of the real-time temperature data can be determined based on the relationship between the real-time temperature data and multiple historical temperature data. For example, one data type indicates that the real-time temperature data is within the temperature value coverage range of multiple historical temperature data, and one data type indicates that the real-time temperature data is outside the temperature value coverage range of multiple historical temperature data.

[0065] S212: Selecting fitting data for obtaining a fitting association relationship from the real-time temperature data, the real-time angular velocity bias data, the plurality of historical temperature data, and the plurality of historical angular velocity bias data according to the data type.

[0066] Since real-time temperature data of different data types have different effects on the fitting correlation relationship, it is necessary to select fitting data according to the data type.

[0067] S213: Perform fitting processing on the fitting data to obtain a fitting correlation relationship.

[0068] The fitting process refers to a polynomial fitting process, and the weight parameters obtained by performing polynomial fitting process on the fitting data can represent the relationship between the temperature data and the angular velocity bias data. Specifically, since the angular velocity bias data is data including angular velocity bias values ​​in three directions, it is also necessary to construct the fitting association relationship of the angular velocity bias data for the three directions according to the corresponding direction axes of the angular velocity bias data.

[0069] S214: judging the validity of the real-time angular velocity bias data according to the real-time temperature data and the fitting correlation relationship.

[0070] In this embodiment, fitting data can be selected according to the data type of the real-time temperature data, and then a fitting correlation relationship can be obtained according to the fitting data, so as to accurately determine the validity of the real-time angular velocity bias data through the fitting data.

[0071] In a feasible embodiment, S211: the step of obtaining the data type of the real-time temperature data includes:

[0072] S2111: Obtain the minimum temperature value and the maximum temperature value from multiple historical temperature data.

[0073] S2112: If the temperature value of the real-time temperature data is greater than the minimum temperature value, and the temperature value of the real-time temperature data is less than the maximum temperature value, determine that the data type of the real-time temperature data is the first type.

[0074] The real-time angular velocity bias data corresponding to the first type of real-time temperature data is data whose validity can be directly judged based on the fitting correlation relationship obtained from a plurality of historical temperature data and a plurality of historical angular velocity bias data.

[0075] S2113: If the temperature value of the real-time temperature data is less than the minimum temperature value, and the temperature difference between the temperature value of the real-time temperature data and the minimum temperature value does not exceed the preset temperature difference range, or if the temperature value of the real-time temperature data is greater than the maximum temperature value, and the temperature difference between the temperature value of the real-time temperature data and the maximum temperature value does not exceed the preset temperature difference range, determine that the data type of the real-time temperature data is the second type.

[0076] The real-time angular velocity bias data corresponding to the second type of real-time temperature data is data whose validity may need to be judged based on the fitting association relationship obtained from the real-time temperature data, the real-time angular velocity bias data, and multiple historical temperature data and multiple historical angular velocity bias data. In this embodiment, in this embodiment, the real-time temperature data is classified according to the relationship between the real-time temperature data and the multiple historical temperature data, which is conducive to selecting the fitting data for obtaining the fitting association relationship according to the data type of the real-time temperature data.

[0077] In a feasible embodiment, S212: selecting, according to the data type, the step of obtaining fitting data for the fitting association relationship from the real-time temperature data, the real-time angular velocity bias data, the plurality of historical temperature data, and the plurality of historical angular velocity bias data, comprises:

[0078] S2121: If the data type of the real-time temperature data is the first type, a plurality of historical temperature data and a plurality of historical angular velocity bias data are determined as fitting data.

[0079] Since the temperature value of the first type of real-time temperature data is greater than the minimum temperature value, and the temperature value of the real-time temperature data is less than the maximum temperature value, the real-time temperature data is within the temperature value coverage range of multiple historical temperature data. At this time, the real-time temperature data and the real-time angular velocity bias data have been covered by the fitting association relationship obtained based on multiple historical temperature data and multiple historical angular velocity bias data. Therefore, in order to prevent the actual temperature data and the real-time angular velocity bias data within the temperature value coverage range of multiple historical temperature data from affecting the validity judgment, so as to improve the accuracy of the validity judgment, the validity of the real-time angular velocity bias data is directly judged based on the fitting association relationship obtained based on multiple historical temperature data and multiple historical angular velocity bias data.

[0080] S2122: If the data type of the real-time temperature data is the second type, the real-time temperature data, the real-time angular velocity bias data, the plurality of historical temperature data, and the plurality of historical angular velocity bias data are determined as fitting data.

[0081] Since the temperature value of the second type of real-time temperature data is less than the minimum temperature value, or the temperature value of the real-time temperature data is greater than the maximum temperature value, the real-time temperature data is outside the temperature value coverage range of multiple historical temperature data, and at this time, the fitting association relationship obtained only based on multiple historical temperature data and multiple historical angular velocity bias data does not cover the real-time temperature data. Therefore, in order to improve the accuracy of the validity judgment based on the real-time temperature data and real-time angular velocity bias data outside the temperature value coverage range of multiple historical temperature data, it is necessary to judge the validity of the real-time angular velocity bias data based on the fitting association relationship obtained from the real-time temperature data, the real-time angular velocity bias data, and multiple historical temperature data and multiple historical angular velocity bias data.

[0082] In this embodiment, fitting data that is beneficial to improving the accuracy of the validity judgment of the real-time angular velocity bias data can be selected according to the data type of the real-time temperature data.

[0083] In a feasible embodiment, S214: the step of judging the validity of the real-time angular velocity bias data according to the real-time temperature data and the fitting association relationship includes:

[0084] S2141: Obtain fitting angular velocity bias data corresponding to the real-time temperature data according to the real-time temperature data and the fitting association relationship.

[0085] S2142: Obtain the data difference between the fitted angular velocity bias data and the real-time angular velocity bias data.

[0086] The data difference includes the angular velocity bias values ​​of the real-time angular velocity bias data in three directions, and the differences between the angular velocity bias values ​​of the fitted angular velocity bias data in the corresponding directions.

[0087] S2143: If the data difference does not exceed a preset data difference range, determine that the real-time angular velocity bias data is valid data; otherwise, determine that the real-time angular velocity bias data is invalid data.

[0088] If, among the data differences, there is a difference in one direction that exceeds a preset data difference range, it is determined that the real-time angular velocity bias data is invalid data.

[0089] In this embodiment, the fitting angular velocity bias data corresponding to the real-time temperature data is obtained according to the fitting association relationship, and then the validity of the real-time angular velocity bias data is judged according to the data difference between the fitting angular velocity bias data and the real-time angular velocity bias data, so that the validity of the real-time angular velocity bias data can be accurately judged.

[0090] In a feasible embodiment, before the step of S21: judging the validity of the real-time angular velocity bias data, the following steps are included:

[0091] S201: Obtaining storage data of a plurality of preset temperature range groups.

[0092] Among them, each temperature range group is used to store corresponding historical temperature data and historical angular velocity bias data respectively, and the storage data status of multiple temperature range groups refers to whether all temperature range groups store corresponding historical temperature data and historical angular velocity bias data.

[0093] The temperature range grouping is to divide the temperature range by using a preset fixed temperature interval, and the fixed temperature interval may be 1°C, 0.5°C, 0.2°C, 0.1°C, and so on.

[0094] S202: If all temperature range groups store historical temperature data and historical angular velocity bias data, obtain a target association relationship based on multiple historical temperature data and multiple historical angular velocity bias data; otherwise, execute a step of determining the validity of real-time angular velocity bias data.

[0095] In this embodiment, when all temperature range groups store historical temperature data and historical angular velocity bias data, it means that there is no need to obtain the target association relationship between temperature data and angular velocity bias data based on real-time angular velocity bias data. Therefore, there is no need to judge the validity of real-time angular velocity bias data. The target association relationship can be directly obtained based on multiple historical temperature data and multiple historical angular velocity bias data, which can improve the efficiency of obtaining angular velocity temperature drift compensation values.

[0096] See also Figure 3 The second embodiment of the present application provides an angular velocity temperature drift compensation method, comprising:

[0097] S100: Obtain an angular velocity temperature drift compensation value corresponding to the real-time temperature data through the above-mentioned angular velocity temperature drift compensation value acquisition method.

[0098] S200: Compensating angular velocity data of the head mounted display device according to the angular velocity temperature drift compensation value to obtain target angular velocity data of the head mounted display device.

[0099] Wherein, step S200 is shown in the following formula:

[0100] refined_gyro=corrected_gyro-temp_gyro_bias(temperature)

[0101] Among them, refined_gyro is the target angular velocity data, corrected_gyro is the angular velocity data of the head-mounted display device, and temp_gyro-bias(temperature) is the angular velocity temperature drift compensation value corresponding to the real-time temperature data.

[0102] The angular velocity data of the head mounted display device may be angular velocity data corrected by a corrected accelerometer, and the corrected angular velocity data may be obtained by the following formula:

[0103] corrected_gyro=Mgyr*(measure_gyro-bias_gyro)

[0104] Among them, mgyr is the matrix for correcting the orthogonal relationship and numerical scale of the accelerometer, measure_gyro is the original angular velocity data after recovery to a static state after use, and bias_gyro is the calibrated original angular velocity data.

[0105] It should be noted that the angular velocity temperature drift compensation method provided in the second embodiment of the present application and the angular velocity temperature drift compensation value acquisition method of the first embodiment of the present application belong to the same concept. The implementation process is detailed in the method embodiment and will not be repeated here.

[0106] See also Figure 4 The third embodiment of the present application provides an angular velocity temperature drift compensation value acquisition device, which is applied to a head mounted display device. The temperature drift compensation method includes:

[0107] The real-time data acquisition module 101 is used to monitor the use state of the head-mounted display device; if the use state is a static state, the real-time temperature data and the corresponding real-time angular velocity bias data of the head-mounted display device are acquired;

[0108] A target association relationship acquisition module 102 is used to obtain a target association relationship between temperature data and angular velocity bias data according to real-time temperature data, real-time angular velocity bias data, a plurality of historical temperature data and a plurality of historical angular velocity bias data;

[0109] The angular velocity temperature drift compensation value acquisition module 103 is used to obtain target angular velocity bias data corresponding to the real-time temperature data according to the target association relationship, and determine the target angular velocity bias data as the angular velocity temperature drift compensation value.

[0110] It should be noted that, when the angular velocity temperature drift compensation value acquisition device 100 provided in the third embodiment of the present application executes the angular velocity temperature drift compensation value acquisition method, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the angular velocity temperature drift compensation value acquisition device 100 provided in the third embodiment of the present application and the angular velocity temperature drift compensation value acquisition method of the first embodiment of the present application belong to the same concept, and the implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0111] See also Figure 5 The fourth embodiment of the present application provides an angular velocity temperature drift compensation device 200, comprising:

[0112] The temperature drift compensation value acquisition module 201 acquires the angular velocity temperature drift compensation value corresponding to the real-time temperature data through the above-mentioned angular velocity temperature drift compensation value acquisition method;

[0113] The target angular velocity data acquisition module 202 compensates the angular velocity data of the head mounted display device according to the angular velocity temperature drift compensation value to obtain the target angular velocity data of the head mounted display device.

[0114] It should be noted that the angular velocity temperature drift compensation device 200 provided in the fourth embodiment of the present application only uses the division of the above-mentioned functional modules as an example when executing the angular velocity temperature drift compensation method. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the angular velocity temperature drift compensation device 200 provided in the fourth embodiment of the present application and the angular velocity temperature drift compensation method of the second embodiment of the present application and the angular velocity temperature drift compensation value acquisition method of the first embodiment belong to the same concept. The implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0115] The fifth embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the method for obtaining the angular velocity temperature drift compensation value as described above, or the steps of the method for compensating the angular velocity temperature drift as described above.

[0116] The sixth embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the steps of the method for obtaining the angular velocity temperature drift compensation value as described above, or the steps of the method for compensating the angular velocity temperature drift as described above when executing the computer program.

[0117] The device embodiments described above are merely illustrative, wherein the components described as separate parts may or may not be physically separated, and the parts displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application. Ordinary technicians in this field can understand and implement it without creative work.

[0118] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0119] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the function selected in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 function selected in a box or multiple boxes.

[0120] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 steps for the function selected in a box or multiple boxes.

[0121] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0122] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0123] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0124] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0125] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for obtaining angular velocity temperature drift compensation value, characterized in that: Applied to a head mounted display device, the temperature drift compensation method includes: Monitoring the use state of the head mounted display device; if the use state is a static state, obtaining real-time temperature data and corresponding real-time angular velocity bias data of the head mounted display device; Obtaining a target association relationship between the temperature data and the angular velocity bias data according to the real-time temperature data, the real-time angular velocity bias data, a plurality of historical temperature data, and a plurality of historical angular velocity bias data; According to the target association relationship, target angular velocity bias data corresponding to the real-time temperature data is obtained, and the target angular velocity bias data is determined as the angular velocity temperature drift compensation value.

2. The method for obtaining the angular velocity temperature drift compensation value according to claim 1, characterized in that: The step of obtaining a target association relationship between temperature data and angular velocity bias data according to the real-time temperature data, the real-time angular velocity bias data, a plurality of historical temperature data, and a plurality of historical angular velocity bias data comprises: Determining the validity of the real-time angular velocity bias data; If the real-time angular velocity bias data is valid data, obtaining the target association relationship according to the real-time temperature data, the real-time angular velocity bias data, the plurality of historical temperature data and the plurality of historical angular velocity bias data; If the real-time angular velocity bias data is invalid data, the target association relationship is obtained according to the plurality of historical temperature data and the plurality of historical angular velocity bias data.

3. The method for obtaining the angular velocity temperature drift compensation value according to claim 2, characterized in that: The step of judging the validity of the real-time angular velocity bias data comprises: Determine the data type of the real-time temperature data; According to the data type, selecting fitting data for obtaining a fitting association relationship from the real-time temperature data, the real-time angular velocity bias data, the plurality of historical temperature data, and the plurality of historical angular velocity bias data; Performing fitting processing on the fitting data to obtain a fitting correlation relationship; The validity of the real-time angular velocity bias data is judged according to the real-time temperature data and the fitting association relationship.

4. The method for obtaining the angular velocity temperature drift compensation value according to claim 3, characterized in that: The step of judging the validity of the real-time angular velocity bias data according to the real-time temperature data and the fitting association relationship comprises: According to the real-time temperature data and the fitting association relationship, obtaining fitting angular velocity bias data corresponding to the real-time temperature data; Acquire a data difference between the fitting angular velocity bias data and the real-time angular velocity bias data; If the data difference does not exceed a preset data difference range, the real-time angular velocity bias data is determined to be valid data; otherwise, the real-time angular velocity bias data is determined to be invalid data.

5. The method for obtaining angular velocity temperature drift compensation value according to claim 3, characterized in that: The step of selecting fitting data for obtaining a fitting association relationship from the real-time temperature data, the real-time angular velocity bias data, the plurality of historical temperature data, and the plurality of historical angular velocity bias data according to the data type comprises: If the data type of the real-time temperature data is the first type, determining the plurality of historical temperature data and the plurality of historical angular velocity bias data as the fitting data; If the data type of the real-time temperature data is the second type, the real-time temperature data, the real-time angular velocity bias data, the multiple historical temperature data and the multiple historical angular velocity bias data are determined as the fitting data.

6. The method for obtaining angular velocity temperature drift compensation value according to claim 5, characterized in that: The step of obtaining the data type of the real-time temperature data comprises: Get the minimum and maximum temperature values ​​from multiple historical temperature data; If the temperature value of the real-time temperature data is greater than the minimum temperature value, and the temperature value of the real-time temperature data is less than the maximum temperature value, determining that the data type of the real-time temperature data is the first type; If the temperature value of the real-time temperature data is less than the minimum temperature value, and the temperature difference between the temperature value of the real-time temperature data and the minimum temperature value does not exceed the preset temperature difference range, or if the temperature value of the real-time temperature data is greater than the maximum temperature value, and the temperature difference between the temperature value of the real-time temperature data and the maximum temperature value does not exceed the preset temperature difference range, it is determined that the data type of the real-time temperature data is the second type.

7. The method for obtaining angular velocity temperature drift compensation value according to claim 2, characterized in that: Before the step of judging the validity of the real-time angular velocity bias data, the method further comprises: Obtain the storage data of multiple preset temperature range groups; If all of the temperature range groups store the historical temperature data and the historical angular velocity bias data, the target association relationship is obtained based on the multiple historical temperature data and the multiple historical angular velocity bias data; otherwise, the step of determining the validity of the real-time angular velocity bias data is performed.

8. A method for compensating angular velocity temperature drift, characterized in that: include: Obtain the angular velocity temperature drift compensation value corresponding to the real-time temperature data by the angular velocity temperature drift compensation value acquisition method described in any one of claims 1 to 7; The angular velocity data of the head mounted display device is compensated according to the angular velocity temperature drift compensation value to obtain target angular velocity data of the head mounted display device.

9. A device for obtaining angular velocity temperature drift compensation value, characterized in that: Applied to a head mounted display device, the temperature drift compensation method includes: A real-time data acquisition module, used to monitor the use state of the head-mounted display device; if the use state is a static state, obtain the real-time temperature data and corresponding real-time angular velocity bias data of the head-mounted display device; A target association relationship acquisition module, used to obtain a target association relationship between temperature data and angular velocity bias data according to the real-time temperature data, the real-time angular velocity bias data, a plurality of historical temperature data and a plurality of historical angular velocity bias data; The angular velocity temperature drift compensation value acquisition module is used to obtain the target angular velocity bias data corresponding to the real-time temperature data according to the target association relationship, and determine the target angular velocity bias data as the angular velocity temperature drift compensation value.

10. An angular velocity temperature drift compensation device, characterized in that: include: A temperature drift compensation value acquisition module, which acquires the angular velocity temperature drift compensation value corresponding to the real-time temperature data through the angular velocity temperature drift compensation value acquisition method described in any one of claims 1 to 7; The target angular velocity data acquisition module compensates the angular velocity data of the head mounted display device according to the angular velocity temperature drift compensation value to obtain the target angular velocity data of the head mounted display device.

11. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for obtaining the angular velocity temperature drift compensation value according to any one of claims 1 to 7, or the steps of the method for compensating the angular velocity temperature drift according to claim 8 are implemented.

12. A computer device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable by the processor. When the processor executes the computer program, the steps of the method for obtaining the angular velocity temperature drift compensation value according to any one of claims 1 to 7, or the steps of the method for compensating the angular velocity temperature drift according to claim 8 are implemented.

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