Rapid and convenient IMU calibration system, method and device

Abstract

The embodiment of the invention discloses a rapid and convenient IMU calibration system, method and device, the system comprises a test bench, the test bench is provided with a control module and a test rack, the test rack comprises an outer frame and an inner frame installed on the outer frame, the inner frame is connected with a test area, the control module is connected with the test area, and the control module is connected with the test area. And the control module is used for controlling the test area to rotate according to a preset rotation rule, and the test area is used for installing to-be-tested IMU equipment. The embodiment of the invention overcomes the defect that a high-precision rotary table needs to be used in a traditional calibration scheme, the cost is lower, the operation is more convenient, the multi-angle standing requirement can be met, the IMU calibration time is greatly shortened through a preset rotation rule and an automatic data acquisition and comparison process, and the calibration efficiency is improved by accurately controlling the rotation mode and acquiring data in real time. The internal parameters of the IMU equipment can be accurately calculated, so that the calibration accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of inertial navigation, and particularly relates to a fast and convenient IMU calibration system, method and device. Background Art

[0002] At present, an IMU (Inertial Measurement Unit) generally has six axes, including three-axis accelerometers and three-axis gyroscopes, and is a device for measuring the three-axis linear acceleration and three-axis angular velocity of an object. Among them, MEMS-IMU (Micro-Electro-Mechanical System Inertial Measurement Unit) is a type of IMU, which has small volume, low power consumption and low cost, but also has relatively low accuracy.

[0003] In the existing market, there are generally two methods for calibrating an IMU: one is the method using a turntable, and the other is the method of static measurement in multiple directions. Existing turntables are aimed at high-precision IMUs (such as fiber optic IMUs), and the cost and precision of the turntables are relatively high. If more devices need to be calibrated simultaneously, a larger turntable is required, further increasing the cost. In actual application scenarios, medium and low-precision MEMS IMUs are more commonly used (such as the IMU built into a mobile phone). The high-precision characteristics of using a high-precision turntable for calibration seem to be "using a sledgehammer to crack a nut", and its high cost and complex operation are unnecessary. And the method of static measurement in multiple directions of the second method requires static data at specific angles. Summary of the Invention

[0004] In view of the above-mentioned defects, embodiments of the present invention disclose a fast and convenient IMU calibration system, method and device, which have low cost and high accuracy.

[0005] A first aspect of an embodiment of the present invention discloses a fast and convenient IMU calibration system, including: a test bench, on which a control module and a test rack are provided. The test rack includes an outer frame and an inner frame installed on the outer frame. A test area is connected to the inner frame. The control module is connected to the test area and is used to control the test area to rotate according to a preset rotation mode. The test area is used to install the IMU device to be tested.

[0006] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the control module includes a control MCU, an X-axis position switch, a Y-axis position switch, an X-axis motor driver, a Y-axis motor driver, an X-axis motor, a Y-axis motor and a start switch. The X-axis position switch, the Y-axis position switch, the X-axis motor driver, the Y-axis motor driver, the X-axis motor, the Y-axis motor and the start switch are all connected to the control MCU.

[0007] A second aspect of an embodiment of the present invention discloses a fast and convenient IMU calibration method, including:

[0008] Set the first rotation rule to control the test area to rotate in the Y-axis direction according to the first rotation rule, and collect the Y-axis rotation data of the IMU device in the test area;

[0009] Set the second rotation rule to control the test area to rotate in the X-axis direction according to the second selection rule, and collect the X-axis rotation data of the IMU device in the test area;

[0010] Compare and calculate the Y-axis rotation data with the rotation parameters in the first rotation rule, and compare and calculate the X-axis rotation data with the rotation parameters in the second rotation rule to obtain a comparison error;

[0011] Obtain the internal parameter based on the comparison error, and calibrate the IMU device in combination with the internal parameter.

[0012] As an alternative implementation, in the second aspect of the embodiments of the present invention, the first rotation rule includes the Y-axis angular velocity, the Y-axis rotation angle, and the Y-axis stationary time, and the Y-axis rotation data includes the IMU Y-axis rotation angular velocity, the IMU Y-axis stationary angular velocity, and the IMU Y-axis stationary acceleration.

[0013] As an alternative implementation, in the second aspect of the embodiments of the present invention, the second rotation rule includes the X-axis angular velocity, the X-axis rotation angle, and the X-axis stationary time, and the X-axis rotation data includes the IMU X-axis rotation angular velocity, the IMU X-axis stationary angular velocity, and the IMU X-axis stationary acceleration.

[0014] As an alternative implementation, in the second aspect of the embodiments of the present invention, comparing and calculating the Y-axis rotation data with the rotation parameters in the first rotation rule, and comparing and calculating the X-axis rotation data with the rotation parameters in the second rotation rule to obtain a comparison error includes:

[0015] Calculate the true acceleration value based on the accelerometer error model, and the accelerometer error model is: ||a t || = ||S a M a a m + B a + ε a ||; where a t is the true acceleration value; M a is the cross-axis coupling error of the xyz three axes; a m is the acceleration measurement value, including the IMU Y-axis stationary acceleration and the IMU X-axis stationary acceleration; B a is the sensor zero bias value; ε a is the sensor measurement noise, Sx , S y , S z are the scale factors of the x, y, and z axes of the accelerometer respectively; M yx is the component of the x-axis of the accelerometer acting on the y-axis; M zx is the component of the x-axis of the accelerometer acting on the z-axis; M zy is the component of the y-axis of the accelerometer acting on the z-axis; B x , B y , B z are the zero biases of the x, y, and z axes of the accelerometer respectively;

[0016] Calculate the true angular velocity based on the gyroscope error model, and the gyroscope error model is: ||g t || = ||S g M g g m + B g + ε g ||; where g t is the true angular velocity; M g is the cross-axis coupling error of the xyz axes; g m is the angular velocity measurement value, including the rotational angular velocity of the IMU Y-axis, the static angular velocity of the IMU Y-axis, the rotational angular velocity of the X-axis, and the static angular velocity of the IMU X-axis; B g is the sensor zero bias value; ε g is the sensor measurement noise; S x , S y , S z are the scale factors of the x, y, and z axes of the gyroscope respectively; M yx is the component of the x-axis of the gyroscope acting on the y-axis; M zx is the component of the x-axis of the gyroscope acting on the z-axis; M zy is the component of the y-axis of the gyroscope acting on the z-axis; B x , B y , B z are the zero biases of the x, y, and z axes of the gyroscope respectively.

[0017] As an optional implementation manner, in the second aspect of the embodiments of the present invention, obtaining the internal reference parameters based on the comparison error includes:

[0018] Performing least squares calculations on the comparison errors respectively to obtain the internal reference parameters.

[0019] The third aspect of the embodiments of the present invention discloses a fast and convenient IMU calibration device, including:

[0020] The first rule setting module: used to set the first rotation rule, control the test area to rotate in the Y-axis direction according to the first rotation rule, and collect the Y-axis rotation data of the IMU device in the test area;

[0021] The second rule setting module: used to set the second rotation rule, control the test area to rotate in the X-axis direction according to the second selection rule, and collect the X-axis rotation data of the IMU device in the test area;

[0022] The error calculation module: used to compare and calculate the Y-axis rotation data with the rotation parameters in the first rotation rule, and compare and calculate the X-axis rotation data with the rotation parameters in the second rotation rule to obtain the comparison error;

[0023] The internal parameter calibration module: used to obtain the internal parameter based on the comparison error, and calibrate the IMU device in combination with the internal parameter.

[0024] As an optional implementation manner, in the third aspect of the embodiments of the present invention, the first rotation rule includes the Y-axis angular velocity, the Y-axis rotation angle, and the Y-axis stationary time, and the Y-axis rotation data includes the IMU Y-axis rotation angular velocity, the IMU Y-axis stationary angular velocity, and the IMU Y-axis stationary acceleration.

[0025] As an optional implementation manner, in the third aspect of the embodiments of the present invention, the second rotation rule includes the X-axis angular velocity, the X-axis rotation angle, and the X-axis stationary time, and the X-axis rotation data includes the IMU X-axis rotation angular velocity, the IMU X-axis stationary angular velocity, and the IMU X-axis stationary acceleration.

[0026] As an optional implementation manner, in the third aspect of the embodiments of the present invention, comparing and calculating the Y-axis rotation data with the rotation parameters in the first rotation rule, and comparing and calculating the X-axis rotation data with the rotation parameters in the second rotation rule to obtain the comparison error, includes:

[0027] Calculating the true acceleration value based on the accelerometer error model, and the accelerometer error model is: ||a t || = ||S a M a a m +B a +ε a ||; where, a t is the true acceleration value; M a is the cross-axis coupling error of the xyz three axes; a m is the acceleration measurement value, including the IMU Y-axis stationary acceleration and the IMU X-axis stationary acceleration; B a is the sensor zero bias value; ε a is the sensor measurement noise, S x 、S y 、S z are the scale factors of the x, y, and z axes of the accelerometer respectively; M yx is the component of the x-axis of the accelerometer acting on the y-axis; M zx is the component of the x-axis of the accelerometer acting on the z-axis; M zy is the component of the y-axis of the accelerometer acting on the z-axis; B x 、B y 、B z are the zero biases of the x, y, and z axes of the accelerometer respectively;

[0028] Calculate the true angular velocity based on the gyroscope error model, and the gyroscope error model is: ||g t || = ||S g M g g m +B g +ε g ||; where g t is the true angular velocity; M g is the cross-axis coupling error of the xyz axes; g m is the angular velocity measurement value, including the rotational angular velocity of the IMU Y-axis, the static angular velocity of the IMU Y-axis, the rotational angular velocity of the X-axis, and the static angular velocity of the IMU X-axis; B g is the sensor zero bias value; ε g is the sensor measurement noise; S x 、S y 、S z are the scale factors of the x, y, and z axes of the gyroscope respectively; M yx is the component of the x-axis of the gyroscope acting on the y-axis; M zx is the component of the x-axis of the gyroscope acting on the z-axis; M zy is the component of the y-axis of the gyroscope acting on the z-axis; B x 、B y 、B z are the zero biases of the x, y, and z axes of the gyroscope respectively.

[0029] As an optional implementation manner, in the third aspect of the embodiments of the present invention, obtaining the internal reference parameters based on the comparison error includes:

[0030] Performing least squares calculations on the comparison errors respectively to obtain the internal reference parameters.

[0031] A fourth aspect of an embodiment of the present invention discloses an electronic device, including: a memory storing executable program code; a processor coupled to the memory; the processor invoking the executable program code stored in the memory for executing the fast and convenient IMU calibration method disclosed in the second aspect of the embodiment of the present invention.

[0032] A fifth aspect of an embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the fast and convenient IMU calibration method disclosed in the second aspect of the embodiment of the present invention.

[0033] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0034] In the embodiment of the present invention, a test bench is provided. The test bench is controlled by a control module to rotate according to a set rule, including rotating in the Y-axis direction and the X-axis direction in a control area, and the Y-axis rotation data and X-axis rotation data of an IMU device on the test area are collected in real time. Based on the collected data and a preset rotation rule, comparisons are made respectively, and the difference between the actual rotation of the IMU device and the preset rotation rule, that is, the comparison error, is calculated. Based on the comparison error, the internal parameter of the IMU device is calculated. Combining these internal parameters, the IMU device is calibrated to improve its measurement accuracy. The embodiment overcomes the need to use a high-precision turntable in the traditional calibration scheme, has a lower cost and is more convenient to operate. It can meet the multi-angle static needs. Through the preset rotation rule and the automated data collection and comparison process, the time for IMU calibration is greatly shortened. By precisely controlling the rotation mode and collecting data in real time, the internal parameters of the IMU device can be accurately calculated, thereby improving the calibration accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0036] Figure 1 is a schematic structural diagram of a fast and convenient IMU calibration system disclosed in an embodiment of the present invention;

[0037] Figure 2 is a schematic module structure diagram of a fast and convenient control module disclosed in an embodiment of the present invention;

[0038] Figure 3 is a schematic flowchart of a fast and convenient IMU calibration method disclosed in an embodiment of the present invention;

[0039] Figure 4 It is a schematic structural diagram of a fast and convenient IMU calibration device provided by an embodiment of the present invention;

[0040] Figure 5 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention.

[0041] In the figure, 1 is a test bench; 2 is a control module; 3 is a test rack; 31 is an outer frame; 32 is an inner frame; 33 is a test area. Specific embodiments

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0043] It should be noted that the terms "first", "second", "third", "fourth", etc. in the description and claims of the present invention are used to distinguish different objects, rather than to describe a specific order. The terms "including" and "having" in the embodiments of the present invention and any of their deformations are intended to cover non-exclusive inclusion. Exemplarily, a process, method, system, product or device including a series of steps or units does not necessarily limit to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0044] An embodiment of the present invention discloses a fast and convenient IMU calibration system, method, device, electronic device and storage medium. In the embodiment, a test bench is provided, and the test bench is controlled by a control module to rotate according to a set rule, including rotating in the Y-axis direction and the X-axis direction of the control area, and real-time collecting the Y-axis rotation data and X-axis rotation data of the IMU device on the test area. Based on the collected data and the preset rotation rule, comparisons are made respectively, and the difference between the actual rotation of the IMU device and the preset rotation rule, that is, the comparison error, is calculated. Based on the comparison error, the internal parameter of the IMU device is calculated. Combining these internal parameters, the IMU device is calibrated to improve its measurement accuracy. The embodiment overcomes the traditional calibration scheme that requires the use of a high-precision turntable, with lower cost and more convenient operation. It can meet the multi-angle static requirements. Through the preset rotation rule and the automated data collection and comparison process, the time for IMU calibration is greatly shortened. By precisely controlling the rotation mode and real-time collecting data, the internal parameters of the IMU device can be accurately calculated, thereby improving the calibration accuracy.

[0045] Embodiment 1

[0046] Please refer to Figure 1 and Figure 2 , Figure 1 which shows a structural schematic diagram of a fast and convenient IMU calibration system disclosed in an embodiment of the present invention, Figure 2 and which shows a module structural schematic diagram of the control module disclosed in an embodiment of the present invention. Combining Figure 1 and Figure 2 , the system includes a test bench 1, on which a control module 2 and a test rack 3 are provided. The test rack 3 includes an outer frame 31 and an inner frame 32 mounted on the outer frame 31. A test area 33 is connected to the inner frame 32. The control module 2 is connected to the test area 33 and is used to control the test area 33 to rotate according to a preset rotation rule. The test area 33 is used to mount the IMU device to be tested.

[0047] Among them, the control module 2 includes a control MCU, an X-axis position switch, a Y-axis position switch, an X-axis motor driver, a Y-axis motor driver, an X-axis motor, a Y-axis motor, and a start switch. The X-axis position switch, the Y-axis position switch, the X-axis motor driver, the Y-axis motor driver, the X-axis motor, the Y-axis motor, and the start switch are all connected to the control MCU.

[0048] The test bench 1 is the platform foundation for the entire calibration process, equipped with a control module 2 and a test stand 3. It is responsible for controlling the rotation of the test area 33, connected to the test area 33 to ensure the accurate execution of rotation instructions. The test stand 3 consists of an outer frame 31 and an inner frame 32. The test area 33 is connected to the inner frame 32 and is used to install the IMU device to be tested. The control module 2 is a system integrating various electronic components and devices, aiming to precisely control the rotation of the test area 33. The control MCU is the core of the control module 2, responsible for receiving and processing signals from other components, and sending control signals according to preset programs or instructions. It can respond and process various input signals in real time. The X-axis position switch is used to detect the position of the test area 33 in the X-axis direction. When the test area 33 reaches the preset X-axis position, the X-axis position switch will send a signal to the control MCU so that the control MCU can take corresponding actions. Similarly, the Y-axis position switch is used to detect the position of the test area in the Y-axis direction. When the test area reaches the preset Y-axis position, the Y-axis position switch will also send a signal to the control MCU. The X-axis motor driver is responsible for receiving the control signal from the control MCU and driving the X-axis motor to rotate. By precisely controlling the rotation speed and rotation direction of the X-axis motor, the precise movement of the test area in the X-axis direction can be achieved. The Y-axis motor driver is responsible for receiving the signal from the control MCU and driving the Y-axis motor to rotate. By controlling the rotation of the Y-axis motor, the precise movement of the test area in the Y-axis direction can be achieved. The X-axis motor is the power source for driving the test area to move in the X-axis direction, and the Y-axis motor is the power source for driving the test area to move in the Y-axis direction. Under the control of the X-axis motor driver, the X-axis motor can rotate according to the preset rotation rules and parameters. Under the control of the Y-axis motor driver, the Y-axis motor can rotate according to the preset rotation rules and parameters. The start switch is used to start the working process of the entire control module. When the start switch is pressed, the control MCU will receive the start signal and start to execute the preset program or instructions.

[0049] The working principle is that when the start switch is pressed, the control MCU starts to receive input signals from the X-axis position switch, Y-axis position switch, and other possible sources. According to the preset rotation rules, the control MCU will send control signals to the X-axis motor driver and Y-axis motor driver. After receiving the control signals, the X-axis motor driver and Y-axis motor driver will respectively drive the X-axis motor and Y-axis motor to rotate. By precisely controlling the rotation of the X-axis motor and Y-axis motor, the precise movement and rotation of the test area in the X-axis and Y-axis directions can be achieved.

[0050] Embodiment 2

[0051] Please refer to Figure 3 , Figure 3It is a schematic flowchart of a fast and convenient IMU calibration method disclosed in an embodiment of the present invention. Among them, the execution subject of the method described in the embodiment of the present invention is an execution subject composed of software or / and hardware. This execution subject can receive relevant information through wired or / and wireless means and can send certain instructions. Of course, it can also have certain processing functions and storage functions. This execution subject can control multiple devices, such as remote physical servers or cloud servers and related software, or it can also be a local host or server and related software that performs relevant operations on devices placed somewhere. In some scenarios, it can also control multiple storage devices, and the storage devices can be placed in the same place or different places as the devices. As Figure 3 shown, this fast and convenient IMU calibration method includes the following steps:

[0052] 301. Set the first rotation rule, control the test area to rotate in the Y-axis direction according to the first rotation rule, and collect the Y-axis rotation data of the IMU device in the test area.

[0053] IMU is an inertial measurement unit, usually including an accelerometer and a gyroscope, which is used to measure the angular velocity and acceleration of an object. Calibrating the IMU is usually to correct the errors of its sensors, such as offset, scale factor error, and cross-axis coupling, etc. The test area is equivalent to a platform for installing or placing the IMU device and rotates according to the set rule under the drive of the motor driver in the control module.

[0054] In the embodiment, the IMU device to be calibrated is placed on the turntable test area, the power supply and communication interface of the IMU device to be calibrated are connected, and the start button is pressed. At this time, it will first enter a warming-up stage, and the turntable test area will be static for a period of time to make the temperature of the IMU device reach a stable state, ensuring that it will not be affected by temperature during calibration. After the warming-up stage ends, the test area starts to rotate. The rotation actually consists of two parts, the rotation of the pitch angle and the rotation of the roll angle, that is, the control rotates in the Y-axis and X-axis.

[0055] Specifically, the first rotation rule includes the Y-axis angular velocity, the Y-axis rotation angle, and the Y-axis stationary time, and the Y-axis rotation data includes the IMU Y-axis rotation angular velocity, the IMU Y-axis stationary angular velocity, and the IMU Y-axis stationary acceleration.

[0056] First, rotate the Y-axis pitch angle. According to the requirements of different IMU devices, divide 360 degrees in a week into several equal parts with corresponding angles and rotation angles and start rotating. Each time it rotates, it stops for a certain time. For example, it rotates at an angular velocity of 3° / s for 3° and then stops for 1 second.

[0057] 302. Set the second rotation rule to control the rotation of the test area in the X-axis direction according to the second selection rule, and collect the X-axis rotation data of the IMU device in the test area.

[0058] The way of the X-axis is similar to that of the Y-axis. In the embodiment, the X-axis and the Y-axis can be tested separately to avoid mutual interference. By independently rotating the X-axis and the Y-axis, the gyroscope data of the IMU device is collected. The second rotation rule includes the X-axis angular velocity, the X-axis rotation angle, and the X-axis stationary time. The X-axis rotation data includes the IMU X-axis rotation angular velocity, the IMU X-axis stationary angular velocity, and the IMU X-axis stationary acceleration.

[0059] When the pitch angle completes one full rotation, the X-axis roll angle will also rotate once at the corresponding angular velocity and rotation angle. The device will also collect the IMU angular velocity during rotation and the IMU angular velocity and acceleration at rest during this process. When both the Y-axis pitch angle and the X-axis roll angle complete one full rotation, the turntable will stop moving. At this time, the device will calculate all the collected data.

[0060] 303. Compare and calculate the Y-axis rotation data with the rotation parameters in the first rotation rule, and compare and calculate the X-axis rotation data with the rotation parameters in the second rotation rule to obtain the comparison error.

[0061] The comparison error is also to compare the data collected by the IMU device with the true value of the rotation of the test area. Specifically, in the embodiment, the true value of the acceleration is calculated based on the accelerometer error model. The accelerometer error model is: ||a t || = ||S a M a a m + B a + ε a ||; where a t is the true value of the acceleration. Since it is only affected by gravity at rest, its two-norm is the gravity value; M a is the cross-axis coupling error of the xyz three axes; a m is the acceleration measurement value, including the IMU Y-axis stationary acceleration and the IMU X-axis stationary acceleration; B a is the sensor zero bias value; ε a is the sensor measurement noise, S a is the scale factor between the actual value and the sensor measurement value. S x 、S y 、S z are the scale factors of the x, y, and z axes of the accelerometer respectively; M yx is the component of the accelerometer x-axis acting on the y-axis; M zxis the component of the acceleration along the x-axis acting on the z-axis; M zy is the component of the acceleration along the y-axis acting on the z-axis; B x and B y and B z are the zero biases of the x, y, and z axes of the accelerometer respectively;

[0062] Calculate the true angular velocity based on the angular velocity error model. The angular velocity error model is: ||g t || = ||S g M g g m + B g + ε g ||; where g t is the true angular velocity, and its two-norm is the angular velocity of the motor rotation; M g is the cross-axis coupling error of the xyz axes; g m is the measured angular velocity, including the angular velocity of the IMU Y-axis rotation, the angular velocity of the IMU Y-axis at rest, the angular velocity of the X-axis rotation, and the angular velocity of the IMU X-axis at rest; B g is the sensor zero bias value; ε g is the sensor measurement noise; S g is the scale factor between the actual value and the sensor measurement value, S x and S y and S z are the scale factors of the x, y, and z axes of the angular velocity sensor respectively; M yx is the component of the angular velocity along the x-axis acting on the y-axis; M zx is the component of the angular velocity along the x-axis acting on the z-axis; M zy is the component of the angular velocity along the y-axis acting on the z-axis; B x and B y and B z are the zero biases of the x, y, and z axes of the angular velocity sensor respectively.

[0063] 304. Obtain the internal reference parameters based on the comparison error, and calibrate the IMU device in combination with the internal reference parameters.

[0064] In the embodiment, the least squares calculation is performed on the comparison errors respectively to obtain the internal reference parameters. In the least squares calculation, the scale factor and zero bias can be fitted through multiple groups of different angular velocity data to improve the parameter estimation accuracy.

[0065] To save the calibration time, the angular velocity is recorded during each small rotation. In other examples, a full rotation can be made without stopping in the middle, and the angular velocity during this rotation can be recorded, which can avoid the inaccuracy of the angular velocity caused by the acceleration process at startup and the deceleration process at stop, thereby improving the calculation accuracy.

[0066] Example 3

[0067] Please refer to Figure 4 , Figure 4 , which is a schematic structural diagram of a fast and convenient IMU calibration device disclosed in an embodiment of the present invention. As Figure 4 shown, the fast and convenient IMU calibration device may include: a first rule setting module 401, a second rule setting module 402, an error calculation module 403, and an internal parameter calibration module 404. Among them, the first rule setting module 401: is used to set a first rotation rule, control the test area to rotate in the Y-axis direction according to the first rotation rule, and collect the Y-axis rotation data of the IMU device in the test area; the second rule setting module 402: is used to set a second rotation rule, control the test area to rotate in the X-axis direction according to the second selection rule, and collect the X-axis rotation data of the IMU device in the test area; the error calculation module 403: is used to compare and calculate the Y-axis rotation data with the rotation parameters in the first rotation rule, and compare and calculate the X-axis rotation data with the rotation parameters in the second rotation rule to obtain a comparison error; the internal parameter calibration module 404: is used to obtain internal parameter values based on the comparison error, and calibrate the IMU device in combination with the internal parameter values.

[0068] In the first rule setting module 401, the first rotation rule includes the Y-axis angular velocity, the Y-axis rotation angle, and the Y-axis stationary time, and the Y-axis rotation data includes the IMU Y-axis rotation angular velocity, the IMU Y-axis stationary angular velocity, and the IMU Y-axis stationary acceleration. In the second rule setting module 402, the second rotation rule includes the X-axis angular velocity, the X-axis rotation angle, and the X-axis stationary time, and the X-axis rotation data includes the IMU X-axis rotation angular velocity, the IMU X-axis stationary angular velocity, and the IMU X-axis stationary acceleration. In the error calculation module 403, the true acceleration value is calculated based on the accelerometer error model, and the accelerometer error model is: ||a t || = ||S a M a a m +B a +ε a ||; where a t is the true acceleration value; M a is the cross-axis coupling error of the xyz three axes; a m is the acceleration measurement value, including the IMU Y-axis stationary acceleration and the IMU X-axis stationary acceleration; B a is the sensor zero bias value; ε a is the sensor measurement noise, S x 、S y 、Sz The scale factors of the x, y, and z axes of the accelerometer, respectively; M yx is the component of the x-axis of the accelerometer acting on the y-axis; M zx is the component of the x-axis of the accelerometer acting on the z-axis; M zy is the component of the y-axis of the accelerometer acting on the z-axis; B x 、B y 、B z The zero biases of the x, y, and z axes of the accelerometer, respectively;

[0069] Calculating the true angular velocity based on the angular velocity meter error model, the angular velocity meter error model is: ||g t || = ||S g M g g m +B g +ε g ||; where g t is the true angular velocity; M g is the cross-axis coupling error of the xyz axes; g m is the angular velocity measurement value, including the rotational angular velocity of the IMU Y-axis, the stationary angular velocity of the IMU Y-axis, the rotational angular velocity of the X-axis, and the stationary angular velocity of the IMU X-axis; B g is the sensor zero bias value; ε g is the sensor measurement noise; S x 、S y 、S z The scale factors of the x, y, and z axes of the angular velocity meter, respectively; M yx is the component of the x-axis of the angular velocity meter acting on the y-axis; M zx is the component of the x-axis of the angular velocity meter acting on the z-axis; M zy is the component of the y-axis of the angular velocity meter acting on the z-axis; B x 、B y 、B z The zero biases of the x, y, and z axes of the angular velocity meter, respectively.

[0070] Example 4

[0071] Please refer to Figure 5 , Figure 5 is a schematic structural diagram of an electronic device disclosed in an embodiment of the present invention. The electronic device can be a computer, a server, etc. Of course, in certain cases, it can also be a smart device such as a mobile phone, a tablet computer, and a monitoring terminal, as well as an image acquisition device with a processing function. As Figure 5 shown, the electronic device may include:

[0072] A memory 501 storing executable program code;

[0073] A processor 502 coupled to a memory 501;

[0074] Wherein, the processor 502 calls the executable program code stored in the memory 501 and executes some or all of the steps in the fast and convenient IMU calibration method in the first embodiment.

[0075] An embodiment of the present invention discloses a computer-readable storage medium that stores a computer program, wherein the computer program causes a computer to execute some or all of the steps in the fast and convenient IMU calibration method in the second embodiment.

[0076] An embodiment of the present invention also discloses a computer program product, wherein when the computer program product runs on a computer, it causes the computer to execute some or all of the steps in the fast and convenient IMU calibration method in the second embodiment.

[0077] An embodiment of the present invention also discloses an application publishing platform, wherein the application publishing platform is used to publish a computer program product, and when the computer program product runs on a computer, it causes the computer to execute some or all of the steps in the fast and convenient IMU calibration method in the second embodiment.

[0078] In various embodiments of the present invention, it should be understood that the magnitude of the sequence numbers of the various processes does not necessarily mean the order of execution. The order of execution of the various processes should be determined by their functions and internal logics, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0079] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0080] In addition, in each embodiment of the present invention, the various functional units may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0081] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests for causing a computer device (which can be a personal computer, a server, or a network device, etc., specifically, the processor in the computer device) to execute some or all of the steps of the methods described in the various embodiments of the present invention.

[0082] In the embodiments provided by the present invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0083] Those of ordinary skill in the art can understand that some or all of the steps in the various methods of the embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electrically-erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc memories, magnetic disk memories, tape memories, or any other computer-readable medium that can be used to carry or store data.

[0084] The above has introduced in detail the fast and convenient IMU calibration method, device, electronic device and storage medium disclosed in the embodiments of the present invention. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation on the present invention.

Claims

1. A fast and convenient IMU calibration system, characterized in that: include: A test bench is provided with a control module and a test frame, the test frame includes an outer frame and an inner frame installed on the outer frame, the inner frame is connected to a test area, the control module is connected to the test area and is used to control the test area to rotate according to a preset rotation rule, and the test area is used to install an IMU device to be tested.

2. The IMU calibration system according to claim 1, characterized in that: The control module includes a control MCU, an X-axis position switch, a Y-axis position switch, an X-axis motor driver, a Y-axis motor driver, an X-axis motor, a Y-axis motor and a start switch, and the X-axis position switch, the Y-axis position switch, the X-axis motor driver, the Y-axis motor driver, the X-axis motor, the Y-axis motor and the start switch are all connected to the control MCU.

3. A fast and convenient IMU calibration method, characterized in that: include: Setting a first rotation rule, controlling the test area to rotate in the Y-axis direction according to the first rotation rule, and collecting Y-axis rotation data of the IMU device in the test area; Setting a second rotation rule, controlling the test area to rotate in the X-axis direction according to the second selection rule, and collecting X-axis rotation data of the IMU device in the test area; Compare and calculate the Y-axis rotation data with the rotation parameters in the first rotation rule, and compare and calculate the X-axis rotation data with the rotation parameters in the second rotation rule to obtain a comparison error; Based on the comparison error, an internal reference parameter is obtained, and the IMU device is calibrated in combination with the internal reference parameter.

4. The IMU calibration method according to claim 3, characterized in that: The first rotation rule includes Y-axis angular velocity, Y-axis rotation angle and Y-axis stationary time, and the Y-axis rotation data includes IMU Y-axis rotation angular velocity, IMU Y-axis stationary angular velocity and IMU Y-axis stationary acceleration.

5. The IMU calibration method according to claim 4, characterized in that: The second rotation rule includes X-axis angular velocity, X-axis rotation angle and X-axis stationary time, and the X-axis rotation data includes IMU X-axis rotation angular velocity, IMU X-axis stationary angular velocity and IMU X-axis stationary acceleration.

6. The IMU calibration method according to claim 5, characterized in that: Comparing and calculating the Y-axis rotation data with the rotation parameters in the first rotation rule, and comparing and calculating the X-axis rotation data with the rotation parameters in the second rotation rule, to obtain a comparison error, including: The true value of acceleration is calculated based on the accelerometer error model, where the accelerometer error model is: ||a t ||=||S a M a a m +B a +ε a ||; where a t is the true value of acceleration; M a is the xyz three-axis cross-axis coupling error; a m B is the acceleration measurement value, including IMU Y-axis static acceleration and IMU X-axis static acceleration; a is the sensor zero bias value; ε a is the sensor measurement noise, S x , S y , S z are the scale factors of the accelerometer x, y, and z axes respectively; M yx M is the component of the accelerometer x-axis acting on the y-axis; zx M is the component of the accelerometer x-axis acting on the z-axis; zy B is the component of the accelerometer y-axis acting on the z-axis; x , B y , B z They are the zero bias of the accelerometer's x, y, and z axes respectively; The true value of the angular velocity is calculated based on the angular velocity meter error model, and the angular velocity meter error model is: ||g t ||=||S g M g g m +B g +ε g ||; where g t is the true value of angular velocity; M g is the xyz three-axis cross-axis coupling error; g m B is the angular velocity measurement value, including IMU Y-axis rotation angular velocity, IMU Y-axis static angular velocity, X-axis rotation angular velocity, and IMU X-axis static angular velocity; g is the sensor zero bias value; ε g Measuring noise for sensors; S x , S y , S z are the scale factors of the angular velocity meter x, y, and z axes respectively; M yx M is the component of the angular velocity meter x-axis acting on the y-axis; zx M is the component of the angular velocity meter x-axis acting on the z-axis; zy B is the component of the y-axis of the angular velocity meter acting on the z-axis; x , B y , B z They are the zero bias of the angular velocity sensor on the x, y, and z axes respectively.

7. The IMU calibration method according to claim 6, characterized in that: Based on the comparison error, an internal reference parameter is obtained, including: The internal parameters were obtained by performing least square calculation on the comparison errors.

8. A fast and convenient IMU calibration device, characterized in that: include: A first rule setting module: used to set a first rotation rule, control the test area to rotate in the Y-axis direction according to the first rotation rule, and collect Y-axis rotation data of the IMU device in the test area; A second rule setting module: used to set a second rotation rule, control the test area to rotate in the X-axis direction according to the second selection rule, and collect X-axis rotation data of the IMU device in the test area; Error calculation module: used for comparing and calculating the Y-axis rotation data with the rotation parameters in the first rotation rule, and comparing and calculating the X-axis rotation data with the rotation parameters in the second rotation rule, to obtain a comparison error; Intrinsic parameter calibration module: used to obtain the intrinsic parameter based on the comparison error, and calibrate the IMU device in combination with the intrinsic parameter.

9. An electronic device, characterized in that: include: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the fast and convenient IMU calibration method described in any one of claims 3 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program enables a computer to execute the fast and convenient IMU calibration method described in any one of claims 3 to 7.

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