Data processing method, moving data fusion method, device and storage medium

Abstract

Multiple aspects of the present application provide a data processing method, a traveling data fusion method, a device, and a storage medium. In some embodiments of the present application, the self-mobile device obtains the measurement values ​​of multiple physical IMUs in the IMU array, and the measurement values ​​of multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data; a model relationship between the virtual IMU and physical IMU data considering the time synchronization error is established to eliminate the error caused by the incomplete equality of the timestamps between the multiple IMUs, and the fusion data of the multiple IMUs is more accurate, thereby improving the navigation accuracy of the self-mobile device.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data processing method, a moving data fusion method, a device and a storage medium. Background Art

[0002] IMU (Inertial Measurement Unit) is a device that measures the three-axis attitude angle (or angular rate) and acceleration of an object. Generally, an IMU contains three single-axis accelerometers and three single-axis gyroscopes. The accelerometer detects the acceleration signal of the object in the carrier coordinate system in three independent axes, while the gyroscope detects the angular velocity signal of the carrier relative to the navigation coordinate system, measures the angular velocity and acceleration of the object in three-dimensional space, and uses this to calculate the attitude of the object. It has very important application value in navigation.

[0003] An IMU array includes multiple IMUs, and navigation is performed based on the data fusion results of the multiple IMUs, which is beneficial to improving navigation accuracy. However, the data fusion results of the existing IMU arrays have low accuracy, resulting in low navigation accuracy based on the IMU array. Summary of the invention

[0004] Multiple aspects of the present application provide a data processing method, a travel data fusion method, a device and a storage medium; the present application performs time synchronization processing on the output data of multiple IMUs to improve the accuracy of the travel data obtained after the output data of the IMU array is fused.

[0005] The present application provides a data processing method, including:

[0006] Obtaining measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0007] Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array.

[0008] The present application embodiment provides a data processing method, which is applicable to an IMU array, wherein the IMU array includes multiple physical IMUs, and the method includes:

[0009] Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0010] Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data;

[0011] The state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fusion data.

[0012] The embodiment of the present application further provides an IMU array, comprising: a carrier, and a plurality of IMUs and processors disposed on the carrier, wherein the plurality of IMUs and processors are communicatively connected with each other;

[0013] The multiple IMUs are used to measure the travel data of the mobile device where the IMU array is located;

[0014] The processor obtains measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantities of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data; wherein the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fused data.

[0015] The present application also provides a method for fusion of traveling data, which is applicable to a self-moving device, wherein the self-moving device includes an IMU array, wherein the IMU array includes a plurality of physical IMUs, and the method includes:

[0016] Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0017] Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data;

[0018] The state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fused travel data.

[0019] The embodiment of the present application also provides a travel data processing system, including a self-moving device and a host computer, the self-moving device includes an IMU array, and the IMU array includes multiple physical IMUs;

[0020] The self-moving device is used to obtain the measurement values ​​of multiple physical IMUs in the IMU array, and the measurement values ​​of the multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data; wherein the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fused travel data;

[0021] The host computer, the user controls the self-mobile device to continue moving according to the fused travel data.

[0022] The embodiment of the present application also provides a method for fusion of traveling data, which is applicable to a drone, wherein the drone includes an IMU array, and the IMU array includes a plurality of physical IMUs, and the method includes:

[0023] Obtaining measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0024] Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array;

[0025] The flight of the UAV is controlled according to the fused data.

[0026] The embodiment of the present application also provides a method for fusion of traveling data, which is applicable to a robot, wherein the robot includes an IMU array, and the IMU array includes a plurality of physical IMUs, and the method includes:

[0027] Obtaining measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0028] Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array;

[0029] The robot is controlled to continue moving according to the fused data.

[0030] The embodiment of the present application also provides a self-moving device, including: a memory, an IMU array, and a processor on the IMU array;

[0031] The IMU array includes multiple physical IMUs;

[0032] The memory is used to store one or more computer instructions;

[0033] The processor is configured to execute the one or more computer instructions to:

[0034] Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0035] Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data;

[0036] The state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fusion data.

[0037] The embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer program is executed by one or more processors, the one or more processors are caused to perform the following actions:

[0038] Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0039] Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data;

[0040] The state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fusion data.

[0041] The embodiment of the present application also provides a self-moving device, including: a memory, an IMU array, and a processor on the IMU array;

[0042] The IMU array includes multiple physical IMUs;

[0043] The memory is used to store one or more computer instructions;

[0044] The processor is configured to execute the one or more computer instructions to:

[0045] Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0046] Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data;

[0047] The state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fused travel data.

[0048] The embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer program is executed by one or more processors, the one or more processors are caused to perform the following actions:

[0049] Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0050] Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data;

[0051] The state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fused travel data.

[0052] In some embodiments of the present application, the self-mobile device obtains measurement values ​​of multiple physical IMUs in the IMU array, and the measurement values ​​of multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data; a model relationship between the virtual IMU and physical IMU data considering the time synchronization error is established to eliminate the error caused by the incomplete equality of the timestamps between the multiple IMUs, so that the fused data of the multiple IMUs has higher accuracy, thereby improving the navigation accuracy of the self-mobile device. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0054] Figure 1a A structural diagram of a data processing method system provided for an exemplary embodiment of the present application;

[0055] Figure 1b A schematic diagram of the structure of an IMU array provided for an exemplary embodiment of the present application;

[0056] Figure 1c A schematic diagram of the structure of a traveling data fusion system provided for an exemplary embodiment of the present application;

[0057] Figure 2a A flowchart of a data processing method provided for an exemplary embodiment of the present application;

[0058] Figure 2b A flowchart of a data processing method provided for an exemplary embodiment of the present application;

[0059] Figure 2c A schematic diagram of a flow chart of a method for fusion of traveling data of a UAV provided by an exemplary embodiment of the present application;

[0060] Figure 2d A schematic flow chart of a method for fusion of robot travel data provided by an exemplary embodiment of the present application;

[0061] Figure 3 A flow chart of a method for fusion of traveling data provided by an exemplary embodiment of the present application;

[0062] Figure 4 A schematic diagram of the structure of a self-moving device provided for an exemplary embodiment of the present application;

[0063] Figure 5 A schematic structural diagram of another self-moving device provided for an exemplary embodiment of the present application;

[0064] Figure 6 A schematic structural diagram of another self-moving device provided for an exemplary embodiment of the present application;

[0065] Figure 7 A schematic diagram of the structure of a drone provided for an exemplary embodiment of the present application;

[0066] Figure 8 A schematic diagram of the structure of a robot provided for an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, 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 making creative work are within the scope of protection of the present application.

[0068] The existing IMU array does not consider the issue of IMU calibration parameter compensation during the data fusion process, and the existing IMU calibration parameter compensation method is usually only for a single IMU. The existing IMU array data fusion process needs to first complete the calibration parameter compensation for the gyroscope and accelerometer in a single IMU, and then fuse the compensated data. This serial data processing method does not fully utilize the spatial coupling model between acceleration and angular velocity between multiple IMUs. Due to the incompleteness of the model, the data fusion effect of the IMU array is poor, especially when the motion amplitude of the carrier is large, the impact of this model error is more prominent.

[0069] In addition, the existing IMU array collects data asynchronously and has no data time synchronization mechanism, which leads to inaccurate timestamps. In addition, during the data fusion process, the time deviation between different IMU data is not considered, resulting in time synchronization errors.

[0070] In view of the above-mentioned existing technical problems, the embodiments of the present application provide a solution. In some embodiments of the present application, the measurement values ​​of multiple physical IMUs in the IMU array are obtained from the mobile device, and the measurement values ​​of multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data; a model relationship between the virtual IMU and physical IMU data considering the time synchronization error is established to eliminate the error caused by the incomplete equality of the timestamps between the multiple IMUs, and the fused data of the multiple IMUs has higher accuracy, thereby improving the navigation accuracy of the mobile device.

[0071] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0072] Figure 1a The structure diagram of the data processing method system provided by the exemplary embodiment of the present application is as follows. Figure 1a As shown, the data processing method system 10 includes: a self-mobile device 10a and a host computer 10b. The self-mobile device 10a includes at least one IMU array 101, and the self-mobile device 10a sends the fusion data of at least one IMU array 101 to the host computer 10b; after receiving the fusion data of at least one IMU array 101, the host computer 10b parses the current motion information of the self-mobile device 10a, and sends a control instruction to the self-mobile device 10a to control the motion of the self-mobile device 10a.

[0073] In this embodiment, the self-moving device 10a can be a drone, an unmanned vehicle, a robot, etc., and the type of the robot or the unmanned vehicle is not limited. When the self-moving device 10a is a robot, the robot can be a sweeping robot, a following robot, a welcoming robot, etc. Different types of self-moving devices 10a collect data using the IMU array 101 set thereon, and each IMU array fuses the collected data to generate fused data, and uploads the fused data to the host computer 10b.

[0074] In this embodiment, the host computer 10b is connected to the self-mobile device 10a in communication, and the host computer 10b provides data support, computing services and some management services for the self-mobile device 10a. The host computer 10b sends a control instruction to the self-mobile device 10a to control the movement of the self-mobile device 10a. This embodiment does not limit the specific implementation form of the host computer 10b, and the host computer 10b can be a server. For example, the host computer 10b can be a server device such as a conventional server, a cloud server, a cloud host, a virtual center, etc. Among them, the composition of the server device mainly includes a processor, a hard disk, a memory, a system bus, etc., and a general computer architecture type.

[0075] In this embodiment, the mobile device 10a establishes a communication connection with the host computer 10b. Optionally, the mobile device 10a can establish a communication connection with the host computer 10b by using WIFI, Bluetooth, infrared or other communication methods, or the mobile device 10a can also establish a communication connection with the host computer 10b through a mobile network. The network standard of the mobile network can be any one of 2G (GSM), 2.5G (GPRS), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 5G, etc.

[0076] Figure 1b The schematic diagram of the structure of the IMU array provided by the exemplary embodiment of the present application. Figure 1b As shown, the IMU array 101 includes a carrier and nine IMUs 11a, four temperature sensors 12a, a processor 13a, a time synchronization interface 14a, and a data output interface 15a arranged on the carrier. The carrier is rectangular, the IMUs are evenly spaced on the rectangular carrier, and the multiple temperature sensors are evenly spaced between the multiple IMUs. This application does not limit the number of IMUs 11a and temperature sensors 12a, and the number of IMUs 11a and temperature sensors 12a can be adjusted according to actual conditions.

[0077] In another embodiment of the IMU array, the carrier is in the shape of a regular polygon, the IMUs are evenly spaced on the regular polygon carrier, and the multiple temperature sensors are evenly spaced between the multiple IMUs. For example, the carrier is in the shape of a regular octagon, and four IMUs and four temperature sensors are arranged on the carrier, the four IMUs are spaced at the center of the four faces of the regular octagon, and the four temperature sensors are respectively arranged at the center of the remaining four faces of the regular octagon.

[0078] In the above embodiments, IMU (Inertial Measurement Unit) is a device for measuring the three-axis attitude angle (or angular rate) and acceleration of an object. Generally, an IMU11a includes three single-axis accelerometers and three single-axis gyroscopes. The accelerometer detects the acceleration signal of the object in the independent three axes of the carrier coordinate system, and the gyroscope detects the angular velocity signal of the carrier relative to the navigation coordinate system, measures the angular velocity and acceleration of the object in three-dimensional space, and calculates the attitude of the object. Among them, some IMU11a also include a three-axis magnetometer, with a total of nine axes. A certain distance is maintained between each IMU11a to improve the accuracy of the fusion data.

[0079] In the above embodiment, a plurality of temperature sensors 12a are disposed at different positions of the carrier to collect the temperatures of different positions of the IMU array 101, so as to make a more comprehensive detection of the temperature of the IMU array 101. Preferably, the plurality of temperature sensors 12a are evenly distributed on the carrier to evenly detect the temperatures of various positions of the IMU array 101, thereby improving the accuracy of the temperature of the IMU array 101.

[0080] In the above embodiment, the carrier may be a circuit board. The embodiment of the present application does not limit the type of the circuit board, and may be a ceramic circuit board, an alumina ceramic circuit board, an aluminum nitride ceramic circuit board, and the like.

[0081] In the above embodiment, the time synchronization interface 14a, the user receives the time synchronization notification sent by the host computer 10b, and sends it to the processor 13a, so that the processor 13a performs time synchronization. The process of time synchronization of multiple IMU arrays 101 of the mobile device 10a is as follows: the host computer 10b sends a time synchronization notification to each IMU array 101, and the time synchronization notification carries the time information of the host computer 10b; each IMU array 101 receives the time synchronization notification through its own time synchronization interface 14a, and sends it to its own processor 13a, and the processor 13a adjusts its own clock according to the time synchronization notification to synchronize the time of each IMU array 101.

[0082] In the above embodiment, the data output interface 15a is used to receive the fused data from the processor 13a and send the fused data to the host computer 10b.

[0083] In some embodiments of the IMU array 101, nine IMUs 11a and four temperature sensors 12a are provided on the carrier of the IMU array 101; the carrier is also provided with a processor 13a, a time synchronization interface 14a, and a data output interface 15a. Among them, the nine IMUs 11a are evenly arranged in three rows on one side of the carrier. The even here means that the intervals between each column of IMUs 11a are equal, the intervals between each row of IMUs 11a are equal, and the same distance is maintained between each IMU 11a to improve the accuracy of the fusion data; the four temperature sensors 12a are evenly arranged between the intervals of the nine IMUs 11a to evenly detect the temperature of each position of the IMU array 101 and improve the accuracy of the temperature of the IMU array 101. The time synchronization interface 14a, the processor 13a, and the data output interface 15a are arranged on the other side of the carrier from top to bottom. The embodiments of the present application do not constitute a limitation on the structure of the IMU array, and the structure of the IMU array can be appropriately adjusted according to actual conditions. The structure of the IMU array in this embodiment is simple and compact.

[0084] In some embodiments of the present application, the self-mobile device 10a obtains the measurement value of the physical IMU in the IMU array 101 that needs to be fused in this data fusion process; the self-mobile device 10a performs data fusion on the basis of time synchronization of the measurement values ​​of multiple physical IMUs 11a based on the conversion model to obtain fused data.

[0085] In the above embodiment, the conversion model can be a conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, or can be other forms of conversion models. The conversion model is used to simultaneously perform time synchronization and data fusion on the measurement values ​​of each physical IMU to obtain fused data.

[0086] In this embodiment, based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data. An optional embodiment is that based on the conversion model, the measurement values ​​of multiple physical IMUs are time synchronized to obtain the measurement value increment of the fused data at time t; the fused data is obtained according to the measurement value of the initial moment of the fused data at time t and the measurement value increment of the fused data at time t. Based on the conversion model, the measurement values ​​of multiple physical IMUs are time synchronized to obtain the measurement value increment of the fused data at time t. Optionally, based on the measurement value change rate of the fused data at time t and the measurement value and measurement time of each physical IMU, a synchronization state equation for time synchronization of each physical IMU is established; the conversion model is updated using the synchronization state equation for time synchronization of each physical IMU to obtain the conversion model after the time synchronization error is corrected; according to the measurement value increment equation of the fused data and the conversion model after the time synchronization error is modified, the measurement value increment of the fused data at time t and the measurement value change rate of the fused data at time t are obtained. The conversion model after modifying the time synchronization error is: wherein, the synchronization state equation, the measurement value increment equation of the fusion data, and the conversion model after modifying the time synchronization error can be found in the description of the relevant contents of the subsequent embodiments, and will not be repeated here.

[0087] In other embodiments of the present application, the self-mobile device 10a obtains the measurement values ​​of the physical IMU in the IMU array 101 that need to be fused in this data fusion process; the self-mobile device 10a performs data fusion on the basis of time synchronization of the measurement values ​​of multiple physical IMUs based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity to obtain fused data; the IMU array 101 sends the fused data to the host computer 10b, and after the host computer 10b receives the fused data of the IMU array 101, it generates a control signal according to the fused data, and sends the control signal to the self-mobile device 10a, and the self-mobile device 10a continues to move according to the control signal.

[0088] It should be noted that the virtual IMU is an abstract concept, not a hardware entity. The virtual IMU is an abstraction of multiple physical IMUs in the IMU array. The state quantity of the virtual IMU is used to reflect the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fusion data. That is, assuming that there is a virtual IMU that can reflect the overall motion state of the IMU array, based on this assumption, a conversion relationship between the virtual IMU state quantity and the state quantities of each physical IMU is established, and data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs. The measurement values ​​of each physical IMU are used as the values ​​of the physical IMU state quantity, and are brought into the conversion relationship between the virtual IMU state quantity and the state quantities of each physical IMU to obtain fusion data.

[0089] In the above embodiment, based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data. An optional embodiment is to perform time synchronization on the measurement values ​​of multiple physical IMUs based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU to obtain the measurement value increment of the virtual IMU to time t; wherein time t is the time of this data fusion; and obtain the fused data based on the measurement value of the virtual IMU at the initial time and the measurement value increment of the virtual IMU to time t.

[0090] In the above embodiment, based on the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, the measurement values ​​of multiple physical IMUs are time synchronized to obtain the measurement value increment of the virtual IMU to time t. An optional embodiment is to establish the synchronization state equation of each physical IMU to the virtual IMU based on the measurement value change rate of the virtual IMU at time t and the measurement value and measurement time of each physical IMU; wherein the measurement value change rate of the virtual IMU at time t is the quantity to be determined; according to the synchronization state equation of each physical IMU to the virtual IMU and the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, the conversion relationship after correcting the time synchronization error is obtained; the measurement value increment equation of the virtual IMU and the conversion relationship after correcting the time synchronization error are solved jointly to obtain the measurement value change rate of the virtual IMU at time t and the measurement value increment of the virtual IMU to time t; wherein the measurement value increment of the virtual IMU to time t is the quantity to be determined in the measurement value increment equation, which represents the measurement value increment of the virtual IMU from the initial time to time t.

[0091] For example, the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity.

[0092]

[0093] Where: n is the number of IMU 1 to 9, ω n is the angular velocity output by the gyroscope, M gn is the gyroscope's scale and orthogonality coefficient matrix, is the direction cosine matrix of the gyroscope relative to the accelerometer, is the direction cosine matrix of the accelerometer in the V coordinate system, ω v is the angular velocity output by the virtual IMU, G n is the G sensitivity coefficient of the gyroscope, f v is the specific force output by the virtual IMU, b gn is the gyroscope bias. n is the specific force output by the accelerometer, M an is the scale and orthogonality coefficient matrix of the accelerometer, fv is the specific force output by the virtual IMU, ε v is the angular acceleration of the virtual IMU, r n is the arm from the accelerometer to the virtual IMU, is the accelerometer bias.

[0094] Among them, M gn , G n , b gn 、M an 、r n , Parameters such as are the IMU calibration parameters obtained through calibration, ω v 、f v , ε v is the virtual IMU state parameter to be estimated, ω n With f n The measurement data output by the physical IMU.

[0095] Based on the rate of change of the measurement value of the virtual IMU at time t and the measurement value and measurement time of each physical IMU, the synchronization state equation from each physical IMU to the virtual IMU is established. The synchronization state equation is:

[0096]

[0097] in, is the angular velocity of the virtual IMU at time t, The angular acceleration of the virtual IMU at time t, is the t of the virtual IMU n Angular velocity at the moment, is the virtual IMU’s force at time t, is the first-order derivative of the virtual IMU force with respect to time at time t, t n is the timestamp of the IMU data numbered n, and t is the timestamp of the virtual IMU.

[0098] Substituting Formula 3 and Formula 4 into Formula 1 and Formula 2 respectively, we can obtain the conversion relationship after correcting the time synchronization error:

[0099]

[0100] Linearize Formula 5 and Formula 6, and let and are the initial estimates of the angular velocity and specific force of the virtual IMU, and is the small quantity to be solved, that is, the incremental equation of the measurement value of the virtual IMU:

[0101]

[0102] Substituting Formula 7 and Formula 8 into Formula 5 and Formula 6, we can further obtain:

[0103]

[0104] Let the state parameters to be solved be:

[0105] in, is the measurement increment of the virtual IMU at time t, is the rate of change of the measurement value of the virtual IMU at time t;

[0106] The observed quantity is:

[0107]

[0108] The state matrix is:

[0109]

[0110] Formula 9 and Formula 10 can be organized into least squares form:

[0111]

[0112] Solve formula 11 to obtain the rate of change of the measurement value of the virtual IMU at time t and the measurement value increment of the virtual IMU to time t:

[0113]

[0114] Then according to formula 7 and formula 8, we can get and The calculation result of .

[0115] In an embodiment, multiple temperature sensors 12a provided on the IMU array 101 are used to collect the temperature of the IMU array 101; based on the multiple temperatures collected by the multiple temperature sensors 12a, it is determined whether the temperature of the IMU array 101 is in an abnormal state; if the temperature of the IMU array 101 is in an abnormal state, the abnormal state information is uploaded to the host computer 10b.

[0116] In the above embodiment, it is determined whether the temperature of the IMU array 101 is in an abnormal state based on the multiple temperatures collected by the multiple temperature sensors 12a. One possible embodiment is that if the average value of the multiple temperatures collected by the IMU array 101 is less than the first threshold, it is determined that the temperature of the IMU array 101 is too low; if the average value of the multiple temperatures collected by the IMU array 101 is greater than the second threshold, it is determined that the temperature of the IMU array 101 is too high; if the temperature standard deviation of the multiple temperatures collected by the IMU array 101 is greater than the third threshold, it is determined that the temperature gradient of the IMU array 101 is too large. When the temperature of the IMU array 101 is in an abnormal state, the processor 13a reports the abnormal state information to the host computer 10b, so that the host computer 10b can send a corresponding control signal to the self-mobile device 10a according to the abnormal temperature state information of the IMU array 101.

[0117] For example, let the temperatures output by the four temperature sensors be T 1 , T 2 , T 3 , T 4 , average temperature T m =(T 1 +T 2 +T 3 +T 4 ) / 4, the temperature standard deviation is When T m <T L When T m >T H When T s >T g When , it is determined that the temperature gradient of the IMU array 101 is too large. L 、T H 、T g The first threshold, the second threshold and the third threshold are respectively used. The present application does not limit the first threshold, the second threshold and the third threshold, and the values ​​of the first threshold, the second threshold and the third threshold can be adjusted according to actual conditions.

[0118] Figure 1c The schematic diagram of the structure of the traveling data fusion system provided by the exemplary embodiment of the present application is as follows. Figure 1cAs shown, the travel data fusion system 20 includes: a self-mobile device 20a and a host computer 20b. The self-mobile device 20a includes at least one IMU array, and the self-mobile device 20a sends the fused travel data of at least one IMU array to the host computer 20b; after receiving the fused travel data of at least one IMU array, the host computer 20b parses the current new information of the self-mobile device 10a, and sends a control instruction to the self-mobile device 10a to control the self-mobile device 20a to continue to travel.

[0119] In this embodiment, the self-mobile device 20a obtains the measurement value of the physical IMU in the IMU array that needs to be fused in this data fusion process; the self-mobile device 20a performs data fusion on the basis of time synchronization of the measurement values ​​of multiple physical IMUs based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, and obtains fused travel data; the IMU array sends the fused data to the host computer 20b, and after the host computer 20b receives the fused travel data of the IMU array 101, it generates a control signal according to the fused travel data, and sends the control signal to the self-mobile device 20a, and the self-mobile device 20a continues to move according to the control signal.

[0120] In the above method embodiment of the present application, the self-mobile device obtains the measurement values ​​of multiple physical IMUs in the IMU array, and the measurement values ​​of multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data; a model relationship between the virtual IMU and physical IMU data considering the time synchronization error is established to eliminate the error caused by the incomplete equality of the timestamps between the multiple IMUs, and the fused data of the multiple IMUs has higher accuracy, thereby improving the navigation accuracy of the self-mobile device.

[0121] In addition to the data processing method system 10 and the traveling data fusion system 20 provided above, some embodiments of the present application also provide a data processing method. The data processing method provided by the present application may rely on the above-mentioned data processing method system and the traveling data fusion system, but is not limited to the data processing method system and the traveling data fusion system provided in the above-mentioned embodiments.

[0122] Figure 2a The following is a flow chart of a data processing method provided by an exemplary embodiment of the present application. Figure 2a As shown, the method includes:

[0123] S211: obtaining measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0124] S212: Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantities, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data; wherein, the state quantity of the virtual IMU represents the overall motion state of the IMU array, the overall motion state corresponds to the fused data, and the value of the virtual IMU state quantity is the fused data.

[0125] In this embodiment, the execution subject of the above method is a self-moving device, which can be a drone, an unmanned vehicle, a robot, etc., and the type of the robot and the unmanned vehicle is not limited. When the self-moving device is a robot, the robot can be a sweeping robot, a following robot, a welcoming robot, etc. Different types of self-moving devices collect data using the IMU arrays set thereon, and each IMU array fuses the collected data to generate fused data, and uploads the fused data to the host computer.

[0126] Figure 1b The schematic diagram of the structure of the IMU array provided by the exemplary embodiment of the present application. Figure 1b As shown, the IMU array includes a carrier and nine IMU1s, four temperature sensors, a processor, a time synchronization interface, and a data output interface arranged on the carrier. Among them, this application does not limit the number of IMUs and temperature sensors, and the number of IMUs and temperature sensors can be adjusted according to actual conditions.

[0127] In the above embodiment, IMU (Inertial Measurement Unit) is a device for measuring the three-axis attitude angle (or angular rate) and acceleration of an object. Generally, an IMU includes three single-axis accelerometers and three single-axis gyroscopes. The accelerometer detects the acceleration signal of the object in the independent three axes of the carrier coordinate system, and the gyroscope detects the angular velocity signal of the carrier relative to the navigation coordinate system, measures the angular velocity and acceleration of the object in three-dimensional space, and calculates the attitude of the object. Among them, some IMUs also include three-axis magnetometers, with a total of nine axes. A certain distance is maintained between each IMU to improve the accuracy of the fused data.

[0128] In the above embodiment, multiple temperature sensors are arranged at different positions of the carrier to collect the temperature of different positions of the IMU array, so as to make a more comprehensive detection of the temperature of the IMU array. Preferably, multiple temperature sensors are evenly distributed on the carrier to evenly detect the temperature of each position of the IMU array, thereby improving the accuracy of the temperature of the IMU array.

[0129] In the above embodiment, the carrier may be a circuit board. The embodiment of the present application does not limit the type of the circuit board, and may be a ceramic circuit board, an alumina ceramic circuit board, an aluminum nitride ceramic circuit board, and the like.

[0130] In the above embodiment, the time synchronization interface, the user receives the time synchronization notification sent by the host computer, and sends it to the processor for the processor to perform time synchronization. The process of time synchronization of multiple IMU arrays of the mobile device is as follows: the host computer sends a time synchronization notification to each IMU array, and the time synchronization notification carries the time information of the host computer; each IMU array receives the time synchronization notification through its own time synchronization interface and sends it to its own processor, and the processor adjusts its own clock according to the time synchronization notification to synchronize the time of each IMU array.

[0131] In the above embodiment, the data output interface is used to receive the processor fusion data and send the fusion data to the host computer.

[0132] In some embodiments of the IMU array, nine IMUs and four temperature sensors are provided on the carrier of the IMU array; the carrier is also provided with a processor, a time synchronization interface, and a data output interface. Among them, the nine IMUs are evenly arranged in three rows on one side of the carrier. The uniformity here specifies that the intervals between each column of IMUs are equal, the intervals between each row of IMUs are equal, and the same distance is maintained between each IMU to improve the accuracy of the fusion data; four temperature sensors are evenly arranged between the intervals of the nine IMUs to evenly detect the temperature of each position of the IMU array and improve the temperature accuracy of the IMU array. The time synchronization interface, processor and data output interface are arranged on the other side of the carrier from top to bottom. The embodiments of the present application do not constitute a limitation on the structure of the IMU array, and the structure of the IMU array can be appropriately adjusted according to actual conditions. The structure of the IMU array in this embodiment is simple and compact.

[0133] In this embodiment, the self-mobile device obtains the measurement values ​​of the physical IMU in the IMU array that need to be fused in this data fusion process; the self-mobile device performs data fusion on the basis of time synchronization of the measurement values ​​of multiple physical IMUs based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity to obtain fused data; the IMU array sends the fused data to the host computer, and after the host computer receives the fused data of the IMU array, it generates a control signal according to the fused data, and sends the control signal to the self-mobile device, and the self-mobile device continues to move according to the control signal.

[0134] In the above embodiment, based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data. An optional embodiment is to perform time synchronization on the measurement values ​​of multiple physical IMUs based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU to obtain the measurement value increment of the virtual IMU to time t; wherein time t is the time of this data fusion; and obtain the fused data based on the measurement value of the virtual IMU at the initial time and the measurement value increment of the virtual IMU to time t.

[0135] In the above embodiment, based on the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, the measurement values ​​of multiple physical IMUs are time synchronized to obtain the measurement value increment of the virtual IMU to time t. An optional embodiment is to establish the synchronization state equation of each physical IMU to the virtual IMU based on the measurement value change rate of the virtual IMU at time t and the measurement value and measurement time of each physical IMU; wherein the measurement value change rate of the virtual IMU at time t is the quantity to be determined; according to the synchronization state equation of each physical IMU to the virtual IMU and the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, the conversion relationship after correcting the time synchronization error is obtained; the measurement value increment equation of the virtual IMU and the conversion relationship after correcting the time synchronization error are solved jointly to obtain the measurement value change rate of the virtual IMU at time t and the measurement value increment of the virtual IMU to time t; wherein the measurement value increment of the virtual IMU to time t is the quantity to be determined in the measurement value increment equation, which represents the measurement value increment of the virtual IMU from the initial time to time t.

[0136] For example, the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity.

[0137]

[0138] Where: n is the number of IMU 1 to 9, ω n is the angular velocity output by the gyroscope, M gn is the gyroscope's scale and orthogonality coefficient matrix, is the direction cosine matrix of the gyroscope relative to the accelerometer, is the direction cosine matrix of the accelerometer in the V coordinate system, ω v is the angular velocity output by the virtual IMU, G n is the G sensitivity coefficient of the gyroscope, f v is the specific force output by the virtual IMU, b gn is the gyroscope bias. n is the specific force output by the accelerometer, M an is the scale and orthogonality coefficient matrix of the accelerometer, fv is the specific force output by the virtual IMU, ε v is the angular acceleration of the virtual IMU, r n is the arm from the accelerometer to the virtual IMU, is the accelerometer bias.

[0139] Among them, M gn , G n , b gn 、M an 、r n , Parameters such as are the IMU calibration parameters obtained through calibration, ω v 、f v , ε v is the virtual IMU state parameter to be estimated, ω n With f n The measurement data output by the physical IMU.

[0140] Based on the rate of change of the measurement value of the virtual IMU at time t and the measurement value and measurement time of each physical IMU, the synchronization state equation from each physical IMU to the virtual IMU is established. The synchronization state equation is:

[0141]

[0142] in, is the angular velocity of the virtual IMU at time t, The angular acceleration of the virtual IMU at time t, is the t of the virtual IMU n Angular velocity at the moment, is the virtual IMU’s force at time t, is the first-order derivative of the virtual IMU force with respect to time at time t, t n is the timestamp of the IMU data numbered n, and t is the timestamp of the virtual IMU.

[0143] Substituting Formula 3 and Formula 4 into Formula 1 and Formula 2 respectively, we can obtain the conversion relationship after correcting the time synchronization error:

[0144]

[0145]

[0146] Linearize Formula 5 and Formula 6, and let and are the initial estimates of the angular velocity and specific force of the virtual IMU, and is the small quantity to be solved, that is, the incremental equation of the measurement value of the virtual IMU:

[0147]

[0148] Substituting Formula 7 and Formula 8 into Formula 5 and Formula 6, we can further obtain:

[0149]

[0150] Let the state parameters to be solved be:

[0151] in, is the measurement increment of the virtual IMU at time t, is the rate of change of the measurement value of the virtual IMU at time t;

[0152] The observed quantity is:

[0153]

[0154] The state matrix is:

[0155]

[0156] Formula 9 and Formula 10 can be organized into least squares form:

[0157]

[0158] Solve formula 11 to obtain the rate of change of the measurement value of the virtual IMU at time t and the measurement value increment of the virtual IMU to time t:

[0159]

[0160] Then according to formula 7 and formula 8, we can get and The calculation result of .

[0161] In an embodiment, multiple temperature sensors 12a provided on the IMU array 101 are used to collect the temperature of the IMU array 101; based on the multiple temperatures collected by the multiple temperature sensors 12a, it is determined whether the temperature of the IMU array 101 is in an abnormal state; if the temperature of the IMU array 101 is in an abnormal state, the abnormal state information is uploaded to the host computer 10b.

[0162] In the above embodiment, it is determined whether the temperature of the IMU array 101 is in an abnormal state based on the multiple temperatures collected by the multiple temperature sensors 12a. One possible embodiment is that if the average value of the multiple temperatures collected by the IMU array 101 is less than the first threshold, it is determined that the temperature of the IMU array 101 is too low; if the average value of the multiple temperatures collected by the IMU array 101 is greater than the second threshold, it is determined that the temperature of the IMU array 101 is too high; if the temperature standard deviation of the multiple temperatures collected by the IMU array 101 is greater than the third threshold, it is determined that the temperature gradient of the IMU array 101 is too large. When the temperature of the IMU array 101 is in an abnormal state, the processor 13a reports the abnormal state information to the host computer 10b, so that the host computer 10b can send a corresponding control signal to the self-mobile device 10a according to the abnormal temperature state information of the IMU array 101.

[0163] For example, let the temperatures output by the four temperature sensors be T 1 , T 2 , T 3 , T 4 , average temperature T m =(T 1 +T 2 +T 3 +T 4 ) / 4, the temperature standard deviation is When T m <T L When T m >T H When T s >T g When , it is determined that the temperature gradient of the IMU array 101 is too large. L 、T H 、T g The first threshold, the second threshold and the third threshold are respectively used. The present application does not limit the first threshold, the second threshold and the third threshold, and the values ​​of the first threshold, the second threshold and the third threshold can be adjusted according to actual conditions.

[0164] Figure 2b A flowchart of another data processing method provided for an exemplary embodiment of the present application is shown in FIG. Figure 2b As shown, the method includes:

[0165] S221: Obtain the measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process.

[0166] S222: Based on the conversion model, data fusion is performed on the basis of time synchronization of measurement values ​​of multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array.

[0167] Combined with the description of each embodiment of the above data processing method, Figure 2c A flow chart of a method for fusion of traveling data of a drone provided by an exemplary embodiment of the present application, wherein the drone includes an IMU array, and the IMU array includes multiple physical IMUs, such as Figure 2c As shown, the method includes:

[0168] S231: Acquire measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0169] S232: Based on the conversion model, data fusion is performed on the basis of time synchronization of measurement values ​​of multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array;

[0170] S233: Control the flight of the drone based on the fused data.

[0171] Combined with the description of each embodiment of the above data processing method, Figure 2d A schematic diagram of a process flow of a robot travel data fusion method provided by an exemplary embodiment of the present application, wherein the robot includes an IMU array, and the IMU array includes multiple physical IMUs, such as Figure 2d As shown, the method includes:

[0172] S241: Acquire measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0173] S242: Based on the conversion model, data fusion is performed on the basis of time synchronization of measurement values ​​of multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array;

[0174] S243: Control the robot to continue moving according to the fused data.

[0175] Combined with the description of the above data processing method embodiments, Figure 3 A flow chart of a method for fusion of traveling data provided by an exemplary embodiment of the present application is shown as follows: Figure 3 As shown, the method includes:

[0176] S301: Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​of the travel data that need to be fused in this data fusion process;

[0177] S302: Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused travel data; wherein the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fused travel data.

[0178] In this embodiment, the execution subject of the above method can be a self-moving device, which can be a drone, an unmanned vehicle, a robot, etc., and the type of the robot and the unmanned vehicle is not limited. When the self-moving device is a robot, the robot can be a sweeping robot, a following robot, a welcoming robot, etc. Different types of self-moving devices collect data using the IMU arrays set thereon, and each IMU array fuses the collected data to generate fused data, and uploads the fused data to the host computer.

[0179] In this embodiment, the implementation of the method for fusion of traveling data in the embodiment of the present application can be found in the description of the aforementioned embodiments, which will not be repeated here.

[0180] It should be noted that the execution subject of each step of the method provided in the above embodiment can be the same device, or the method can be executed by different devices. For example, the execution subject of step 301-step 302 can be device A; for another example, the execution subject of step 301 can be device A, and the execution subject of step 302 can be device B; and so on.

[0181] In addition, in some of the processes described in the above embodiments and the accompanying drawings, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel, and the sequence numbers of the operations, such as 301, 302, etc., are only used to distinguish between different operations, and the sequence numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0182] In the above method embodiment of the present application, the self-mobile device obtains the measurement values ​​of multiple physical IMUs in the IMU array, and the measurement values ​​of multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data; a model relationship between the virtual IMU and physical IMU data considering the time synchronization error is established to eliminate the error caused by the incomplete equality of the timestamps between the multiple IMUs, and the fused data of the multiple IMUs has higher accuracy, thereby improving the navigation accuracy of the self-mobile device.

[0183] Figure 4 The schematic diagram of the structure of a self-moving device provided by the exemplary embodiment of the present application is shown in FIG. Figure 4 As shown, the self-moving device includes: a memory 401, an IMU array and a processor 402 on the IMU array. The self-moving device also includes necessary components such as a power supply component 403 and a communication component 404.

[0184] The memory 401 is used to store computer programs and can be configured to store various other data to support operations on the mobile device. Examples of such data include instructions for any application or method used to operate on the mobile device.

[0185] Memory 401 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0186] The communication component 404 is used for data transmission with other devices.

[0187] The processor 402 can execute computer instructions stored in the memory 401 to: obtain measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data; wherein the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fused data.

[0188] Optionally, the processor 402 performs data fusion based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU and on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data. It is specifically used for: based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, time synchronization of the measurement values ​​of multiple physical IMUs is performed to obtain the measurement value increment of the virtual IMU to time t; wherein time t is the time of this data fusion; and fusion data is obtained based on the measurement value of the virtual IMU at the initial time and the measurement value increment of the virtual IMU to time t.

[0189] Optionally, when the processor 402 performs time synchronization on the measurement values ​​of multiple physical IMUs based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity to obtain the measurement value increment of the virtual IMU to time t, it is specifically used to: establish a synchronization state equation from each physical IMU to the virtual IMU based on the measurement value change rate of the virtual IMU at time t and the measurement value and measurement time of each physical IMU; wherein the measurement value change rate of the virtual IMU at time t is the quantity to be determined; according to the synchronization state equation from each physical IMU to the virtual IMU and the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, obtain the conversion relationship after correcting the time synchronization error; jointly solve the measurement value increment equation of the virtual IMU and the conversion relationship after correcting the time synchronization error to obtain the measurement value change rate of the virtual IMU at time t and the measurement value increment from the virtual IMU to time t; wherein the measurement value increment from the virtual IMU to time t is the quantity to be determined in the measurement value increment equation, which represents the measurement value increment of the virtual IMU from the initial time to time t.

[0190] Optionally, the sensor data is travel data of the self-moving device, and the processor 402 may also be used to control the self-moving device to continue moving according to the fused data.

[0191] Optionally, the processor 402 controls the self-mobile device to continue moving according to the fusion data, and is specifically used to: send the fusion data to the host computer so that the host computer can generate a control signal according to the fusion data after the movement data of multiple physical IMUs are fused; receive the control signal sent by the host computer so that the self-mobile device can continue moving according to the control signal.

[0192] Optionally, multiple physical IMUs are set on the IMU array, and the processor 402 can also be used to: use multiple temperature sensors set on the IMU array to collect the temperature of the IMU array; determine whether the temperature of the IMU array is in an abnormal state based on the multiple temperatures collected by the multiple temperature sensors; if the temperature of the IMU array is in an abnormal state, upload the abnormal state information to the host computer.

[0193] Optionally, when the processor 402 determines whether the temperature of the IMU array is in an abnormal state based on multiple temperatures collected by multiple temperature sensors, it is specifically used to: if the average value of the multiple temperatures collected by the IMU array is less than a first threshold, determine that the temperature of the IMU array is too low; if the average value of the multiple temperatures collected by the IMU array is greater than a second threshold, determine that the temperature of the IMU array is too high; if the temperature standard deviation of the multiple temperatures collected by the IMU array is greater than a third threshold, determine that the temperature gradient of the IMU array is too large.

[0194] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors execute Figure 2a Each step in the method embodiment.

[0195] Figure 5 This is a schematic diagram of another self-propelled device provided by an exemplary embodiment of the present application. Figure 5 As shown, the self-moving device includes: a memory 501, an IMU array and a processor 502 on the IMU array. The self-moving device also includes necessary components such as a power supply component 503 and a communication component 504.

[0196] The memory 501 is used to store computer programs and can be configured to store various other data to support operations on the mobile device. Examples of such data include instructions for any application or method used to operate on the mobile device.

[0197] Memory 501 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0198] The communication component 504 is used for data transmission with other devices.

[0199] The processor 502 can execute computer instructions stored in the memory 501 to: obtain measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to the measurement values ​​of the travel data that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data; wherein the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the overall motion state corresponds to the fused travel data.

[0200] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors execute Figure 3 Each step in the method embodiment.

[0201] Figure 6 The schematic diagram of the structure of a self-moving device provided by the exemplary embodiment of the present application is shown in FIG. Figure 6 As shown, the self-moving device includes: a memory 601, an IMU array and a processor 602 on the IMU array. The self-moving device also includes necessary components such as a power supply component 603 and a communication component 604.

[0202] The memory 601 is used to store computer programs and can be configured to store various other data to support operations on the mobile device. Examples of such data include instructions for any application or method used to operate on the mobile device.

[0203] Memory 601 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0204] The communication component 604 is used for data transmission with other devices.

[0205] The processor 602 can execute the computer instructions stored in the memory 601 to: obtain the measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process;

[0206] Based on the conversion model, data fusion is performed on the basis of time synchronization of measurement values ​​of multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array.

[0207] Optionally, the processor 602 performs data fusion based on the conversion model and on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data, specifically for:

[0208] Based on the conversion model, the measurement values ​​of multiple physical IMUs are synchronized in time to obtain the measurement value increment of the fusion data at time t;

[0209] The fused data is obtained according to the measurement value of the fused data at the initial time at the time t and the measurement value increment of the fused data at the time t.

[0210] Optionally, when the processor 602 performs time synchronization on the measurement values ​​of multiple physical IMUs based on the conversion model to obtain the measurement value increment of the fused data at time t, it is specifically used to: establish a synchronization state equation for time synchronization of each physical IMU based on the measurement value change rate of the fused data at time t and the measurement value and measurement time of each physical IMU; use the synchronization state equation for time synchronization of each physical IMU to update the conversion model to obtain the conversion model after correcting the time synchronization error; obtain the measurement value increment of the fused data at time t and the measurement value change rate of the fused data at time t according to the measurement value increment equation of the fused data and the conversion model after modifying the time synchronization error.

[0211] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors execute Figure 2b Each step in the method embodiment.

[0212] Figure 7 The following is a schematic diagram of the structure of a drone provided by an exemplary embodiment of the present application. Figure 7 As shown, the drone includes: a memory 701, an IMU array and a processor 702 on the IMU array. The drone also includes necessary components such as a power supply component 703 and a communication component 704.

[0213] The memory 701 is used to store computer programs and can be configured to store various other data to support the operation of the drone. Examples of such data include instructions for any application or method used to operate on the drone.

[0214] Memory 701 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0215] The communication component 704 is used for data transmission with other devices.

[0216] The processor 702 may execute computer instructions stored in the memory 701 to:

[0217] Obtaining measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0218] Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array;

[0219] The flight of the UAV is controlled according to the fused data.

[0220] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors execute Figure 2c Each step in the method embodiment.

[0221] Figure 8 The schematic diagram of the structure of a robot provided by the exemplary embodiment of the present application is shown in FIG. Figure 8 As shown, the robot includes: a memory 801, an IMU array and a processor 802 on the IMU array. The robot also includes necessary components such as a power supply component 803 and a communication component 804.

[0222] The memory 801 is used to store computer programs and can be configured to store various other data to support the operation of the robot. Examples of such data include instructions for any application program or method operating on the robot.

[0223] Memory 801 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0224] The communication component 804 is used for data transmission with other devices.

[0225] The processor 802 may execute computer instructions stored in the memory 801 to:

[0226] Obtaining measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process;

[0227] Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, wherein the fused data corresponds to the overall motion state of the IMU array;

[0228] The robot is controlled to continue moving according to the fused data.

[0229] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors execute Figure 2d Each step in the method embodiment.

[0230] In the above method embodiment of the present application, the self-mobile device obtains the measurement values ​​of multiple physical IMUs in the IMU array, and the measurement values ​​of multiple physical IMUs refer to the measurement values ​​that need to be fused in this data fusion process; based on the conversion relationship between the virtual IMU state quantity and the state quantity of each physical IMU, data fusion is performed on the basis of time synchronization of the measurement values ​​of multiple physical IMUs to obtain fused data; a model relationship between the virtual IMU and physical IMU data considering the time synchronization error is established to eliminate the error caused by the incomplete equality of the timestamps between the multiple IMUs, and the fused data of the multiple IMUs has higher accuracy, thereby improving the navigation accuracy of the self-mobile device.

[0231] Above Figure 4 , Figure 5 The communication component in is configured to facilitate wired or wireless communication between the device where the communication component is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G / LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0232] Above Figure 4 and Figure 5 The power supply component in the device provides power to various components of the device where the power supply component is located. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device where the power supply component is located.

[0233] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0234] The present invention is described with reference to the flowchart and / or block diagram of the method, device (system), and computer program product according to the embodiment of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the process and / or box 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 produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0235] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0236] These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0237] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0238] The memory may include non-permanent storage 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.

[0239] 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.

[0240] 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.

[0241] The above is only an embodiment of the present application and is 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 in the scope of the claims of the present application.

Claims

1. A data processing method, characterized in that: include: Obtaining measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, wherein the conversion model establishes a conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fused data obtained by data fusion of the measurement values ​​of multiple physical IMUs.

2. The method according to claim 1, characterized in that Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, including: Based on the conversion model, the measurement values ​​of multiple physical IMUs are synchronized in time to obtain the measurement value increment of the fusion data at time t; The fused data is obtained according to the measurement value of the fused data at the initial time at the time t and the measurement value increment of the fused data at the time t.

3. The method according to claim 2, characterized in that Based on the conversion model, the measurement values ​​of multiple physical IMUs are synchronized in time to obtain the measurement value increment of the fusion data at time t, including: Based on the measurement value change rate of the fusion data at time t and the measurement value and measurement time of each physical IMU, a synchronization state equation for time synchronization of each physical IMU is established; The conversion model is updated using the synchronization state equations for time synchronization of each physical IMU to obtain a conversion model after correcting the time synchronization error; According to the measurement value increment equation of the fused data and the conversion model after the time synchronization error is corrected, the measurement value increment of the fused data at time t and the measurement value change rate of the fused data at time t are obtained.

4. A data processing method, applicable to an IMU array, wherein the IMU array comprises a plurality of physical IMUs, characterized in that: The method comprises: Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; Based on the conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data; Among them, the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fusion data obtained by data fusion of the measurement values ​​of multiple physical IMUs.

5. The method according to claim 4, characterized in that Based on the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, including: Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, the measurement values ​​of the multiple physical IMUs are synchronized in time to obtain the measurement value increment of the virtual IMU to time t; wherein time t is the data fusion time of this time; The fusion data is obtained according to the measurement value of the virtual IMU at the initial moment and the measurement value increment of the virtual IMU to the moment t.

6. The method according to claim 5, characterized in that Based on the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, the measurement values ​​of the multiple physical IMUs are synchronized in time to obtain the measurement value increment of the virtual IMU at time t, including: Based on the measurement value change rate of the virtual IMU at time t and the measurement values ​​and measurement times of each physical IMU, a synchronization state equation from each physical IMU to the virtual IMU is established; wherein the measurement value change rate of the virtual IMU at time t is the quantity to be determined; According to the synchronization state equations from each physical IMU to the virtual IMU and the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, a conversion relationship after correcting the time synchronization error is obtained; The measurement value increment equation of the virtual IMU and the conversion relationship after the time synchronization error is corrected are solved simultaneously to obtain the measurement value change rate of the virtual IMU at time t and the measurement value increment of the virtual IMU to time t; Among them, the measurement value increment of the virtual IMU to time t is the quantity to be determined in the measurement value increment equation, which represents the measurement value increment of the virtual IMU from the initial time to time t.

7. The method according to claim 4, characterized in that The fused data is travel data from the mobile device, and the method further includes: The self-moving device is controlled to continue moving according to the fused data.

8. The method according to claim 7, characterized in that Controlling the mobile device to continue moving according to the fused data includes: The fused data is sent to a host computer, so that the host computer generates a control signal according to the fused data after the travel data of multiple physical IMUs are fused; Receive the control signal sent by the host computer so that the mobile device can continue to move according to the control signal.

9. The method according to claim 4, characterized in that The multiple physical IMUs are arranged on an IMU array, and further include: The temperature of the IMU array is collected by using multiple temperature sensors arranged on the IMU array; Determining whether the temperature of the IMU array is in an abnormal state according to the multiple temperatures collected by the multiple temperature sensors; If the temperature of the IMU array is in an abnormal state, the abnormal state information is uploaded to the host computer.

10. The method according to claim 9, characterized in that Judging whether the temperature of the IMU array is in an abnormal state according to the multiple temperatures collected by the multiple temperature sensors includes: If the average value of the multiple temperatures of the IMU array collected is less than the first threshold, it is determined that the temperature of the IMU array is too low; If the average value of the multiple temperatures of the IMU array collected is greater than the second threshold, it is determined that the temperature of the IMU array is too high; If the temperature standard deviation of the multiple temperatures collected of the IMU array is greater than the third threshold, it is determined that the temperature gradient of the IMU array is too large.

11. An IMU array, characterized in that: include: A carrier, and a plurality of IMUs and processors disposed on the carrier, wherein the plurality of IMUs and processors are communicatively connected with each other; The multiple IMUs are used to measure the travel data of the mobile device where the IMU array is located; The processor obtains measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; Based on the conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data; wherein, the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fused data obtained by data fusion of the measurement values ​​of multiple physical IMUs.

12. The IMU array according to claim 11, characterized in that: The processor performs data fusion based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity and on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, specifically for: Based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantity, the measurement values ​​of the multiple physical IMUs are synchronized in time to obtain the measurement value increment of the virtual IMU to time t; wherein time t is the time of data fusion; The fusion data is obtained according to the measurement value of the virtual IMU at the initial moment and the measurement value increment of the virtual IMU to the moment t.

13. The IMU array according to claim 12, characterized in that: The processor performs time synchronization on the measurement values ​​of the multiple physical IMUs based on the conversion relationship between the virtual IMU state quantity and the physical IMU state quantities to obtain the measurement value increment of the virtual IMU to time t, specifically for: Based on the measurement value change rate of the virtual IMU at time t and the measurement values ​​and measurement times of each physical IMU, a synchronization state equation from each physical IMU to the virtual IMU is established; wherein the measurement value change rate of the virtual IMU at time t is the quantity to be determined; According to the synchronization state equations from each physical IMU to the virtual IMU and the conversion relationship between the virtual IMU state quantity and each physical IMU state quantity, a conversion relationship after correcting the time synchronization error is obtained; The measurement value increment equation of the virtual IMU and the conversion relationship after the time synchronization error is corrected are solved simultaneously to obtain the measurement value change rate of the virtual IMU at time t and the measurement value increment of the virtual IMU to time t; Among them, the measurement value increment of the virtual IMU to time t is the quantity to be determined in the measurement value increment equation, which represents the measurement value increment of the virtual IMU from the initial time to time t.

14. The IMU array according to claim 11, characterized in that: Also includes: a plurality of temperature sensors disposed on the carrier; The multiple temperature sensors are used to collect the temperature of the IMU array. The processor is also used to: determine whether the temperature of the IMU array is in an abnormal state based on the multiple temperatures of the IMU array collected; if the temperature of the IMU array is in an abnormal state, upload the abnormal state information to the host computer.

15. The IMU array according to claim 11, characterized in that: Also includes: Time synchronization interface; The time synchronization interface allows the user to receive the time synchronization notification sent by the host computer and send it to the processor for the processor to perform time synchronization.

16. The IMU array according to claim 11, characterized in that: Also includes: Data output interface; The data output interface is used to receive the fused data and send the fused data to a host computer.

17. The IMU array according to claim 14, characterized in that: The multiple IMUs are evenly distributed on the carrier, and the multiple temperature sensors are evenly distributed between the multiple IMUs.

18. The IMU array according to claim 17, characterized in that: The carrier is in a rectangular shape, the IMUs are distributed on the rectangular carrier at equal intervals, and the multiple temperature sensors are distributed between the multiple IMUs at equal intervals.

19. The IMU array according to claim 17, characterized in that: The carrier is in the shape of a regular polygon, the IMUs are distributed on the regular polygon carrier at equal intervals, and the multiple temperature sensors are distributed between the multiple IMUs at equal intervals.

20. The IMU array according to claim 17, characterized in that: The spacing between the multiple IMUs is greater than 10 mm.

21. A method for fusion of traveling data, applicable to a self-moving device, wherein the self-moving device comprises an IMU array, wherein the IMU array comprises a plurality of physical IMUs, characterized in that: The method comprises: Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​of the travel data that need to be fused in this data fusion process; Based on the conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data; Among them, the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fusion data obtained by data fusion of the measurement values ​​of multiple physical IMUs.

22. A traveling data processing system, characterized in that: The self-moving device comprises a host computer, wherein the self-moving device comprises an IMU array, and the IMU array comprises a plurality of physical IMUs; The self-moving device is used to obtain measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; Based on the conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data; wherein the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fused data obtained by data fusion of the measurement values ​​of multiple physical IMUs; The host computer, the user controls the self-mobile device to continue moving according to the fused travel data.

23. A method for fusion of traveling data, applicable to a drone, wherein the drone comprises an IMU array, wherein the IMU array comprises a plurality of physical IMUs, characterized in that: The method comprises: Obtaining measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, wherein the conversion model establishes a conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fused data obtained by data fusion of the measurement values ​​of the multiple physical IMUs; The flight of the UAV is controlled according to the fused data.

24. A method for fusion of traveling data, applicable to a robot, wherein the robot comprises an IMU array, wherein the IMU array comprises a plurality of physical IMUs, wherein: The method comprises: Obtaining measurement values ​​of multiple physical IMUs in the IMU array, wherein the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; Based on the conversion model, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data, wherein the conversion model establishes a conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fused data obtained by data fusion of the measurement values ​​of the multiple physical IMUs; The robot is controlled to continue moving according to the fused data.

25. A self-propelled device, characterized in that: include: Memory, IMU array, and processor on the IMU array; The IMU array includes multiple physical IMUs; The memory is used to store one or more computer instructions; The processor is configured to execute the one or more computer instructions to: Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; Based on the conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data; Among them, the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fusion data obtained by data fusion of the measurement values ​​of multiple physical IMUs.

26. A computer-readable storage medium storing a computer program, which, when executed by one or more processors, causes the one or more processors to perform the following actions: Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​that need to be fused in this data fusion process; Based on the conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused data; in, The state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is fused data obtained by fusing the measurement values ​​of multiple physical IMUs.

27. A self-propelled device, characterized in that: include: Memory, IMU array, and processor on the IMU array; The IMU array includes multiple physical IMUs; The memory is used to store one or more computer instructions; The processor is configured to execute the one or more computer instructions to: Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​of the travel data that need to be fused in this data fusion process; Based on the conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data; Among them, the state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is the fusion data obtained by data fusion of the measurement values ​​of multiple physical IMUs.

28. A computer-readable storage medium storing a computer program, which, when executed by one or more processors, causes the one or more processors to perform the following actions: Acquire measurement values ​​of multiple physical IMUs in the IMU array, where the measurement values ​​of the multiple physical IMUs refer to measurement values ​​of the travel data that need to be fused in this data fusion process; Based on the conversion relationship between the state quantity of the virtual IMU and the state quantity of each physical IMU taking into account the time synchronization error, data fusion is performed on the basis of time synchronization of the measurement values ​​of the multiple physical IMUs to obtain fused travel data; in, The state quantity of the virtual IMU includes the specific force, angular velocity and angular acceleration output by the virtual IMU, the state quantity of the physical IMU includes the angular velocity and specific force output by the physical IMU, the state quantity of the virtual IMU represents the overall motion state of the IMU array, and the value of the state quantity of the virtual IMU is fused data obtained by fusing the measurement values ​​of multiple physical IMUs.

Images