WO2020258198A1

WO2020258198A1 - Calibration method, calibration device, stabilizer and computer readable storage medium

Info

Publication number: WO2020258198A1
Application number: PCT/CN2019/093489
Authority: WO
Inventors: 张翔; 苏铁; 王文杰
Original assignee: 深圳市大疆创新科技有限公司
Priority date: 2019-06-28
Filing date: 2019-06-28
Publication date: 2020-12-30
Also published as: CN111712688A

Abstract

A calibration method, a calibration device, a stabilizer and a computer readable storage medium. The calibration method comprises: acquiring current measurement information of an inertial sensor; determining, according to the current measurement information of the inertial sensor, whether the current posture of a platform carried by the inertial sensor is abnormal; and automatically calibrating the inertial sensor if the current posture of the platform is abnormal. The calibration method can automatically calibrate the inertial sensor when the current posture of the platform is abnormal, without the need for a user to manually trigger a calibration, thereby reducing the usage difficulty for a user.

Description

Calibration method, calibration equipment, stabilizer and computer readable storage medium

Technical field

The embodiment of the present invention relates to the technical field of inertial sensors, in particular to a calibration method, a calibration device, a stabilizer, and a computer-readable storage medium.

Background technique

Benefiting from the advantages of size and price, coupled with increasing performance and reliability, MEMS (Micro-Electro-Mechanical System) inertial sensors are currently used in handheld stabilizers, drones, mobile robots, consumer electronics and other fields Shine.

However, limited by the level of technology and process development, MEMS inertial sensors have larger measurement errors than high-precision inertial sensors such as laser gyroscopes and fiber optic gyroscopes. Therefore, error calibration is a crucial link in the actual use of MEMS inertial sensors. .

The inventor found that there are at least the following problems in the traditional technology: Although the traditional MEMS inertial sensor calibration method has high calibration accuracy and reliability, it requires professional equipment and operating methods and is only suitable for batch calibration during product production. If it is only calibrated by the factory, in some use environments, the zero bias error of the gyroscope may cause an abnormal attitude of the handheld stabilizer, which manifests as a skewed attitude or slow drift. Although some handheld stabilizer products on the market have opened the sensor calibration interface, for ordinary users, due to lack of understanding of the working principle of the stabilizer, it is difficult to notice the abnormal performance of the tiny sensor and perform sensor calibration consciously. And the calibration function of most products has strict requirements on user operation specifications.

Summary of the invention

The embodiment of the present invention provides a calibration method, a calibration device, a stabilizer, and a computer-readable storage medium.

According to one aspect of the embodiments of the present invention, a calibration method is provided. The calibration method includes: acquiring current measurement information of the inertial sensor; determining whether the current attitude of the platform on which the inertial sensor is mounted is abnormal according to the current measurement information of the inertial sensor; and if the current attitude of the platform is abnormal, then The inertial sensor is automatically calibrated.

According to another aspect of the embodiments of the present invention, a calibration device is provided. The calibration device has one or more processors, and the one or more processors work individually or collectively to execute: obtain current measurement information of the inertial sensor; determine the current measurement information of the inertial sensor; Whether the current attitude of the platform on which the inertial sensor is mounted is abnormal; and if the current attitude of the platform is abnormal, the inertial sensor is automatically calibrated.

According to another aspect of the embodiments of the present invention, a calibration device is provided. The calibration equipment includes a measurement information acquisition device, a determination device and a calibration device. The measurement information obtaining device is configured to obtain current measurement information of the inertial sensor. The determining device is configured to determine whether the current posture of the platform mounted on the inertial sensor is abnormal according to the current measurement information of the inertial sensor. The calibration device is configured to automatically calibrate the inertial sensor if the current attitude of the platform is abnormal.

According to another aspect of the embodiments of the present invention, a stabilizer is provided. The stabilizer includes an inertial sensor and the calibration device for calibrating the inertial sensor as described above, and the inertial sensor includes a gyroscope and an accelerometer.

According to another aspect of the embodiments of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium stores executable instructions. The steps of the calibration method as described above are implemented when the executable instructions are executed by the processor.

The embodiment of the present invention can determine whether the current attitude of the platform mounted on the inertial sensor is abnormal according to the current measurement information of the inertial sensor, and automatically calibrate the inertial sensor when the current attitude of the platform is abnormal, without the need for the user to manually trigger the calibration. Reduce the difficulty of users.

Description of the drawings

In order to more clearly describe the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings used in the description of the embodiments. Obviously, the accompanying 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 labor.

Figure 1 is a schematic block diagram of a calibration device according to an embodiment of the present invention;

Figure 2 is a flowchart of a calibration method according to an embodiment of the present invention;

Fig. 3 reveals the steps of how to determine whether the current attitude of the platform mounted on the inertial sensor is abnormal in Fig. 2;

Figure 4 reveals the steps of how to obtain the zero offset calibration value of the gyroscope at the previous moment in Figure 2;

FIG. 5 reveals the steps of how to detect whether the platform mounted on the inertial sensor is in a stationary state in FIG. 2.

Figure 6 is a schematic block diagram of a calibration device according to another embodiment of the present invention;

Fig. 7 is a schematic block diagram of a stabilizer according to an embodiment of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below 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 a person of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

Here, exemplary embodiments will be described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present invention. Rather, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

The terms used in the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and/or" used herein refers to and includes any or all possible combinations of one or more associated listed items. Unless otherwise indicated, similar words such as "front", "rear", "lower" and/or "upper" are only for convenience of description, and are not limited to one position or one spatial orientation. Similar words such as "connected" or "connected" are not limited to physical or mechanical connections, and may include electrical connections, whether direct or indirect. In the present invention, "ability" can mean having ability. The various embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the case of no conflict, the following embodiments and features in the implementation can be combined with each other.

Fig. 1 is a schematic block diagram of a calibration device 11 according to an embodiment of the present invention. As shown in FIG. 1, the calibration equipment 11 of an embodiment of the present invention includes a measurement information acquisition device 111, a determination device 112 and a calibration device 113. In some embodiments, the calibration device 11 may include, for example, a handheld pan/tilt, a mobile robot, and an unmanned aerial vehicle. The measurement information acquiring device 111 may acquire current measurement information of an inertial sensor (Inertial Measurement Unit, IMU) 12 as shown in FIG. 2. In some embodiments, as shown in FIG. 2, the inertial sensor 12 may include, for example, but is not limited to MEMS inertial sensor, and includes gyroscope 121 and accelerometer 122. The determining device 112 can determine whether the current posture of the platform mounted on the inertial sensor 12 is abnormal according to the current measurement information of the inertial sensor 12. If the determination device 112 determines that the current attitude of the platform is abnormal, the calibration device 113 can automatically calibrate the inertial sensor 12.

The calibration device 11 of the embodiment of the present invention can determine whether the current attitude of the platform mounted on the inertial sensor 12 is abnormal according to the current measurement information of the inertial sensor 12, and automatically calibrate the inertial sensor 12 when the current attitude of the platform is abnormal, and There is no need for the user to manually trigger the calibration, thus reducing the difficulty of the user.

In some embodiments, the determining device 112 can determine the deviation angle θ of the platform's current posture from its ideal posture in the direction of gravity, and determine whether the current posture of the platform is abnormal based on the deviation angle θ, when the deviation angle θ is less than a preset angle threshold When the current posture of the platform is normal; when the deviation angle θ is greater than or equal to the preset angle threshold, it is determined that the current posture of the platform is abnormal.

For example, as shown in the following expression:

When the deviation angle θ is less than the preset angle threshold θ _threshold , the determination result RESULT=PASS, which means that the current attitude of the platform is normal; when the deviation angle θ is greater than or equal to the preset angle threshold θ _threshold , the determination result RESULT= FAULT means that the current attitude of the platform is abnormal.

In a stationary state, the measured value a ^b of the accelerometer 122 in the inertial sensor 12 is the projection of the gravitational acceleration in the body coordinate system {b}. Assuming that the measured value a ^{b of the} accelerometer 122 has no error, the following formula can be obtained:

a ^b = g ^b (2)

Among them, g ^b is the ideal value of gravitational acceleration in the body coordinate system {b}. Therefore, in some embodiments, the measured value a ^{b of the} accelerometer 122 can be regarded as an ideal value of the gravitational acceleration in the body coordinate system {b}.

The determining device 112 may further determine the estimated value of the acceleration of gravity. In one embodiment, the estimated value of the acceleration of gravity is an estimated value of the acceleration of gravity in the body coordinate system {b}

The determining device 112 may be based on the measured value a ^b of the accelerometer 122 in the inertial sensor 12 and the estimated value of gravitational acceleration (specifically, the estimated value of gravitational acceleration in the body coordinate system {b}.

) To determine the deviation angle θ between the current attitude of the platform and the ideal attitude in the direction of gravity. For example, by determining the cosine value of the angle between the measured value a ^{b of the} accelerometer 122 and the estimated value of gravitational acceleration, the deviation angle θ of the current posture of the platform from its ideal posture in the direction of gravity is determined.

For example, the determining device 112 may determine the deviation angle θ between the current attitude of the platform and the ideal attitude in the direction of gravity based on the following formula:

among them,

Is the rotation matrix of the current posture of the platform,

It can be determined by the current measurement information of the inertial sensor 12, g ^e is the gravitational acceleration in the geodetic coordinate system {e}.

Therefore, the rotation matrix of the current attitude of the known platform

And the gravitational acceleration in the geodetic coordinate system {e}, the estimated value of the gravitational acceleration in the airframe coordinate system {b} can be obtained according to formula (4)

The estimated value of the acceleration of gravity under the known body coordinate system {b}

And the measured value a ^{b of the} accelerometer 122, the deviation angle θ can be further obtained according to formula (3).

In order to prevent the influence of measurement noise, the calibration device 11 of the embodiment of the present invention may further include a filtering device 114, and the filtering device 114 may filter the measured value of the accelerometer 122. In this case, the determining device 112 may be based on the filtered measurement value of the accelerometer 122 and the estimated value of the gravitational acceleration (specifically, the estimated value of the gravitational acceleration in the body coordinate system {b}.

) To determine the deviation angle θ between the current attitude of the platform and the ideal attitude in the direction of gravity.

The errors of the inertial sensor 12, such as a MEMS inertial sensor, include deterministic errors and non-deterministic errors. Non-deterministic errors are also called random errors, which cannot be completely eliminated by calibration in theory. The deterministic error mainly includes zero bias error, scale factor error and non-orthogonal error. This part of the error can be compensated by calibration. MEMS inertial sensors include MEMS gyroscopes and MEMS accelerometers.

The error model of MEMS gyroscope has the following mathematical expressions:

ω ^O =T ^g K ^g (ω ^S +b ^g +v ^g ) (5)

Among them, ω ^O represents the ideal angular velocity without error, ω ^S represents the actual measured value of the MEMS gyroscope, T ^g represents the non-orthogonal error, K ^g represents the scale factor error, b ^g represents the zero bias error, and v ^g represents the random error .

Because the structural size of the MEMS gyroscope, the elastic modulus of the material, and the performance of the electronic device in the gyroscope detection circuit will change with temperature, the zero bias and scale factor of the MEMS gyroscope will change. Therefore, the MEMS gyroscope's The error model also needs to consider the influence of temperature. However, if the zero bias and scale factor errors of the MEMS gyroscope are directly temperature compensated, not only an expensive turntable with a temperature box is required, but also the calibration time is greatly increased, which is too costly for mass production. Experiments and studies have shown that the zero bias of MEMS gyroscopes is much more affected by temperature than the scale factor is affected by temperature. Therefore, in the above MEMS gyroscope error model, it can be considered that the non-orthogonal error and the scale factor error are fixed values. The bias error is a function of temperature. In addition to temperature, the zero bias of the MEMS gyroscope is also affected by stress and other factors. With time accumulation and temperature changes, the structure and hardware will inevitably change in size, resulting in changes in the stress on the MEMS inertial sensor, thereby making the gyroscope zero Partial change.

In summary, since the gyroscope 121 in the inertial sensor 12 is greatly affected by temperature, in particular, the zero bias of the gyroscope 121 will change with changes in temperature and stress. Therefore, in some embodiments of the present invention, the automatic calibration of the inertial sensor 12 by the calibration device 11 may include automatic zero-bias calibration of the gyroscope 121 in the inertial sensor 12, thereby simplifying the calibration structure, reducing the calibration time, and Greatly reduce costs. Therefore, when it is determined that the current attitude of the platform on which the inertial sensor 12 is mounted is abnormal, the calibration device 11 can automatically calibrate the gyroscope 121 with zero offset.

Assuming that the gyroscope 121 has been calibrated at the factory, the non-orthogonal error T ^g , the scale factor error K ^g and the initial zero offset have been compensated

Then the output value of the gyroscope 121 after factory calibration compensation is:

Although the gyroscope 121 has been calibrated at the factory, there is still a part of the zero offset of the gyroscope 121 after the gyroscope 121 is calibrated.

It cannot be compensated. According to the error model of the gyroscope 121, the ideal angular velocity without error can be obtained as follows:

Among them, ω ^O is the ideal angular velocity without error, ω ^m is the output value of the gyroscope 121 after factory calibration and compensation, and v ^g is the random error of the gyroscope 121.

Therefore, the calibration device 113 of the embodiment of the present invention can obtain the zero offset calibration value of the gyroscope 121 at the previous moment.

And based on the zero offset calibration value of the gyroscope 121 at the previous moment

To compensate the output value ω ^{m of the} gyroscope 121 at the current moment, so as to perform zero offset calibration on the gyroscope 121. In the case that the gyroscope 121 is calibrated at the factory, the output value ω ^m of the gyroscope 121 at the current time is the output value of the gyroscope 121 at the current time after being compensated by the factory calibration.

The calibration device 11 also includes a calculation device 115, which can obtain the output value of the gyroscope 121 at the previous moment

And the previous measurement value of the accelerometer 122 in the inertial sensor 12

And based on the output value of the gyroscope 121 at the previous moment

To calculate the zero offset calibration value of the gyroscope 121 at the previous moment in real time

Calculate the zero offset calibration value of the gyroscope in real time

Therefore, once it is determined that the current attitude of the platform is abnormal, the zero offset calibration value can be used to compensate the current output value of the gyroscope, so that the zero offset calibration of the gyroscope can be completed quickly and automatically.

Continuing to refer to FIG. 1, the calibration device 11 of the embodiment of the present invention may further include a static detection device 116, and the static detection device 116 may detect whether the platform mounted on the inertial sensor 12 is in a static state. When the platform is in a stationary state, the calibration device 113 can calibrate the inertial sensor 12. When the platform is in a moving state, the calibration device 113 exits the calibration, thereby effectively avoiding calibration errors and reducing the probability of abnormal operation of the stabilizer.

The stationary detection device 116 may further calculate the variance of the accelerometer 122 based on the sampling values of the accelerometer 122 at different moments in a given time interval, and determine whether the platform is in a stationary state based on the variance of the accelerometer 122.

In one embodiment, the sampling value of the accelerometer 122 includes the sampling value of the accelerometer 122 on the x, y, and z axes, respectively. The variance of the accelerometer 122 can be calculated according to the sampling values of the accelerometer 122 on the x, y, and z axes.

For example, the stationary detection device 116 may determine whether the inertial sensor 12 is in a stationary state based on the following formula:

Where σ ² is the variance of the accelerometer 122, and t _w is the given time interval,

Represents the variance of the sampled value of the accelerometer 122 on the x-axis at time t,

Represents the variance of the sampled value of the accelerometer 122 on the y-axis at time t, and

It represents the variance of the sample value of the accelerometer 122 on the z axis at time t.

Since the variance of the accelerometer 122 can reflect the change characteristics of the acceleration of the platform in a given time interval t _w , when the platform is stationary, the variance is the smallest; when the carrier moves more violently, the variance is greater. Therefore, it is possible to detect whether the platform is stationary by comparing the variance σ ^{2 of the} accelerometer 122 with a given variance threshold. For example, when the variance σ ^{2 of the} accelerometer 122 is less than the given variance threshold, the stationary detection device 116 can determine the platform At a standstill. When the variance σ ^{2 of the} accelerometer 122 is greater than or equal to a given variance threshold, the stationary detection device 116 can determine that the platform is in a moving state.

For example, as shown in the following formula:

The variance σ ^{2 of the} accelerometer 122 is less than the given variance threshold

When, the detection result result=STATIC, that is, the static detection device 116 can determine that the platform is in a static state. The variance σ ^{2 of the} accelerometer 122 is greater than or equal to the given variance threshold

When, the detection result result=MOVE, that is, the static detection device 116 can determine that the platform is in a moving state.

The calibration device 11 of the embodiment of the present invention can detect abnormal platform attitude and automatically calibrate the zero offset of the gyroscope 121, thereby effectively reducing the measurement error of the gyroscope 121 and improving the accuracy and reliability of platform attitude estimation.

The calibration device 11 of the embodiment of the present invention can perform temperature calibration on the zero bias of the gyroscope only in a static state, thereby effectively reducing costs and improving calibration efficiency.

The embodiment of the present invention also provides a calibration method. Fig. 2 is a flowchart of a calibration method S1 according to an embodiment of the present invention. As shown in FIG. 2, the calibration method S1 of the embodiment of the present invention may include steps S11 to S13.

In step S11, the current measurement information of the inertial sensor is acquired.

The current measurement information of the inertial sensor may include, for example, the current angular velocity value of the gyroscope and the current acceleration value of the accelerometer. In some embodiments, the current measurement information of the inertial sensor may be automatically acquired, so that the entire calibration method can be automatically executed without the user's participation. Specifically, it may be automatically acquired according to a set time interval. The current measurement information of the inertial sensor. Further, the time interval can be set by the user, so that the inertial sensor can be calibrated according to specific needs. It may also be that the current measurement information of the inertial sensor is acquired after the user's trigger operation is acquired, thereby saving the computing resources of the platform on which the inertial sensor is mounted.

In step S12, according to the current measurement information of the inertial sensor, it is determined whether the current attitude of the platform on which the inertial sensor is mounted is abnormal. If the result of the determination is yes, the process continues to step S13; if the result of the determination is no, the process returns to step S11.

In some embodiments, the calibration method S1 of the embodiment of the present invention may further include step S14. In step S14, it is detected whether the platform mounted on the inertial sensor is in a stationary state? If the result of the detection is yes, the process proceeds to step S13. If the result of the detection is negative, the process proceeds to step S15. In step S15, when the platform is in a non-stationary or moving state, the calibration is exited, thereby effectively avoiding calibration errors and reducing the probability of abnormal operation of the stabilizer. Further, the calibration method of the embodiment of the present invention may further include step S16. In step S16, when the platform is in a non-stationary state, a corresponding alarm signal can also be provided to the user.

In step S13, if the current attitude of the platform is abnormal, the inertial sensor is automatically calibrated.

In some embodiments, automatically calibrating the inertial sensor includes automatically calibrating the gyroscope in the inertial sensor. Therefore, the calibration method of the embodiment of the present invention may further include step S17. In step S17, the zero offset calibration value of the gyroscope at the previous moment can be obtained in real time. Then, in step S13, the automatic zero-bias calibration of the gyroscope includes the compensation of the current output value of the gyroscope based on the zero-bias calibration value of the gyroscope at the previous time to perform the zero-bias calibration on the gyroscope. The output value of the gyroscope at the current time is the output value of the gyroscope at the current time after factory calibration compensation. By obtaining the zero offset calibration value of the gyroscope at the previous moment in real time, once it is determined that the current attitude of the platform is abnormal, the zero offset calibration value can be used to compensate the output value of the gyroscope at the current time, so as to quickly and automatically complete Zero offset calibration of the gyroscope.

For the embodiment in which the inertial sensor is located in the handheld pan/tilt, the calibration method of the embodiment of the present invention may further include step S18 before the step S11 of acquiring the current measurement information of the inertial sensor. In step S18, the control parameters of the handheld pan/tilt are automatically adjusted, so that the handheld pan/tilt can achieve good control performance when adapting to different carriers. After auto-tuning the control parameters of the handheld pan/tilt, the process enters step S11 to start acquiring the current measurement information of the inertial sensor.

When the platform mounted on the inertial sensor is a camera, the step S18 of self-tuning the control parameters of the handheld pan/tilt may include: adjusting the configuration of the control parameters of the handheld pan/tilt based on the camera mounted on the handheld pan/tilt, so that the handheld pan/tilt Good control performance can be achieved when adapting to different cameras. Specifically, adjusting the configuration of the control parameters of the handheld PTZ based on the camera includes: recognizing the frequency domain model parameters of the combination of the handheld PTZ and the camera, and adjusting the configuration of the control parameters of the handheld PTZ according to the identified model .

The self-tuning of control parameters of the handheld pan/tilt in the embodiment of the present invention includes: acquiring a user's operation on the keys of the handheld pan/tilt to trigger the control parameter self-tuning.

The calibration method of the embodiment of the present invention can determine whether the current attitude of the platform on which the inertial sensor is mounted is abnormal according to the current measurement information of the inertial sensor, and automatically calibrate the inertial sensor when the current attitude of the platform is abnormal, without manual triggering by the user Calibration, thus reducing the difficulty of user use.

The calibration method of the embodiment of the present invention can perform temperature calibration on the zero bias of the gyroscope only in a static state, thereby effectively reducing the cost and improving the calibration efficiency.

The calibration method of the embodiment of the present invention can automatically calibrate the zero offset of the gyroscope at any time. Compared with the traditional method of only performing factory calibration, it can effectively eliminate the zero offset error of the gyroscope caused by the installation stress change of the MEMS inertial sensor. Thereby improving the performance of attitude estimation.

Fig. 3 discloses the detailed steps of how to determine whether the current attitude of the platform mounted on the inertial sensor is abnormal according to an embodiment of the present invention. As shown in FIG. 3, the step S12 of determining whether the current posture of the platform mounted on the inertial sensor is abnormal according to an embodiment of the present invention may include step S121 and step S122.

In step S121, the deviation angle between the current posture of the platform mounted on the inertial sensor and its ideal posture in the direction of gravity is determined. Wherein, step S121 may further include steps S1211 to S1213.

In step S1211, the measured value of the accelerometer in the inertial sensor is obtained.

In some embodiments, after step S1211, step S121 may further include step S1214. In step S1214, the measured value of the accelerometer is filtered to prevent the influence of measurement noise.

In step S1212, the estimated value of gravitational acceleration is determined.

In some embodiments, determining the estimated value of the gravitational acceleration includes determining the estimated value of the gravitational acceleration in the body coordinate system, which may include step S1221 and step S1222.

In step S1221, the current measurement information of the inertial sensor is used to determine the rotation matrix of the current posture of the platform.

In step S1222, the estimated value of the gravity acceleration in the body coordinate system is calculated based on the rotation matrix of the current posture of the platform and the gravity acceleration in the geodetic coordinate system.

In step S1213, the deviation angle between the current posture of the platform and its ideal posture in the direction of gravity is calculated based on the measured value of the accelerometer and the estimated value of gravitational acceleration. In the case of filtering the measured value of the accelerometer, in step S1213, the deviation angle between the current attitude of the platform and its ideal attitude in the direction of gravity is calculated based on the measured value of the filtered accelerometer and the estimated value of gravity acceleration .

In step S122, determine whether the current posture of the platform is abnormal based on the deviation angle? Specifically, it is determined whether the deviation angle is greater than or equal to a preset angle threshold? When the result of the determination is yes, that is, when the deviation angle is greater than or equal to the preset angle threshold, it is determined that the current attitude of the platform is abnormal; when the result of the determination is no, that is, when the deviation angle is less than the preset angle threshold, the platform is determined The current posture is normal.

Fig. 4 discloses the detailed steps of how to obtain the zero offset calibration value of the gyroscope at the previous moment according to an embodiment of the present invention. As shown in FIG. 4, the step S17 of obtaining the zero offset calibration value of the gyroscope at the previous moment in an embodiment of the present invention may include steps S171 to S173.

In step S171, the output value of the gyroscope at the previous time is obtained.

In step S172, the previous measurement value of the accelerometer in the inertial sensor is obtained.

In step S173, the zero offset calibration value of the gyroscope at the previous time is calculated based on the output value of the gyroscope at the previous time and the measurement value of the accelerometer at the previous time. Wherein, step S173 may further include steps S1731 to S1734.

In step S1731, the system state equation can be obtained based on the output value of the gyroscope at the previous moment, and according to the gyroscope error model and the quaternion differential equation.

In step S1732, based on the previous measurement value of the accelerometer, an observation model of the attitude can be established and an observation equation of the attitude can be obtained.

In step S1733, the posture solution Kalman filter is designed according to the system state equation and the observation equation.

In step S1734, the Kalman filter is calculated based on the attitude to estimate the zero offset calibration value of the gyroscope at the previous moment.

FIG. 5 discloses the detailed steps of how to detect whether the platform mounted on the inertial sensor is in a static state according to an embodiment of the present invention. As shown in FIG. 5, the step S14 of detecting whether the platform mounted on the inertial sensor is in a stationary state according to an embodiment of the present invention may include steps S141 to S143.

In step S141, the sampled values of the accelerometers at different moments in a given time interval are obtained. The sampling value of the accelerometer may include the sampling value of the accelerometer on the x, y, and z axes, respectively.

In step S142, the variance of the accelerometer is calculated based on the sampled value of the accelerometer.

In step S143, it is determined whether the platform is at a standstill based on the variance of the accelerometer? Specifically, determine whether the variance of the accelerometer is less than a given variance threshold? When the result of the determination is yes, that is, when the variance of the accelerometer is less than the given threshold of variance, the platform is determined to be at rest; when the result of the determination is no, that is, when the variance of the accelerometer is greater than or equal to the given threshold of variance, then Make sure that the platform is not stationary or in motion.

FIG. 6 is a schematic block diagram of a calibration device 21 according to another embodiment of the present invention. As shown in FIG. 6, the calibration device 21 according to another embodiment of the present invention may include one or more processors 211. The one or more processors 211 work individually or together, and may be used to perform the steps of the calibration method as described above.

The specific operation and execution process of the calibration device 21 of the embodiment of the present invention are similar to those of the above-mentioned calibration method, and have beneficial technical effects similar to those of the above-mentioned calibration method, so it will not be repeated here.

The embodiment of the present invention also provides a stabilizer 1. The stabilizer 1 may include, for example, but is not limited to, a handheld stabilizer 1 (ie, a handheld pan/tilt), an unmanned aerial vehicle, a pan/tilt cart, etc. Fig. 7 is a schematic block diagram of a stabilizer 1 according to an embodiment of the present invention. As shown in FIG. 7, the stabilizer 1 of the embodiment of the present invention includes an inertial sensor 12 and the calibration device 11/21 of the embodiment of the present invention described above. The inertial sensor 12 includes a gyroscope 121 and an accelerometer 122. The calibration device 11/21 is used to calibrate the inertial sensor 12, and it may include the calibration device 11 shown in FIG. 1 or the calibration device 21 shown in FIG. 6.

The stabilizer 1 includes a controller 13. In the embodiment where the stabilizer 1 is a handheld pan/tilt, the stabilizer 1 of the embodiment of the present invention may also include a control parameter auto-tuning device 14, which can perform control parameter auto-tuning on the controller 13 of the handheld pan/tilt. Tuning. After auto-tuning the control parameters of the controller 13 of the handheld PTZ, the measurement information acquisition device 111 in the calibration device 11 can start to acquire the current measurement information of the inertial sensor 12, or the processor 211 in the calibration device 21 is used for execution. At the beginning, the current measurement information of the inertial sensor 12 is acquired.

For example, for a camera handheld gimbal, because the camera handheld gimbal needs to be adapted to different cameras, the differences in the size and quality of the combination of various cameras and lenses, as well as the different installation positions and structural stress conditions will lead to different The dynamic model parameters and frequency response characteristics. If the handheld pan/tilt adopts a unified controller, it cannot adapt well to the changes of the controlled object, which will affect the stability enhancement performance of the handheld pan/tilt. The stabilizer 1 of the embodiment of the present invention adds a control parameter self-tuning device 14, which can adjust the configuration of the control parameters of the controller of the handheld pan/tilt based on the camera loaded on the handheld pan/tilt, so that the handheld pan/tilt Good control performance can be achieved when adapting to different cameras.

Specifically, the control parameter self-tuning device 14 can identify the frequency domain model parameters of the combination of the handheld pan/tilt head and the camera, and adjust the configuration of the control parameters of the controller of the handheld pan/tilt head according to the identified model.

The specific operation and execution process of the stabilizer 1 of the embodiment of the present invention is similar to the above-mentioned

calibration equipment

11, 21 and the calibration method, and has similar beneficial technical effects as the above-mentioned

calibration equipment

11, 21 and the calibration method, so it is not here. Repeat it again. In the case of no conflict, the stabilizer 1 of the embodiment of the present invention may use or include the embodiments or implementations of specific operations and execution processes of the

aforementioned calibration devices

11 and 21 and the calibration method.

The embodiment of the present invention also provides a computer-readable storage medium on which executable instructions are stored. When the executable instruction is executed by the processor, the steps of the calibration method as described above are implemented, which will not be repeated here.

It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply these There is any such actual relationship or sequence between entities or operations. The terms "include", "include", or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements that are not explicitly listed. Elements, or also include elements inherent to such processes, methods, articles, or equipment. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other same elements in the process, method, article, or equipment including the element.

The calibration method, calibration equipment, stabilizer, and computer-readable storage medium provided by the embodiments of the present invention have been described in detail above. Specific examples are used in this article to illustrate the principles and implementation of the present invention. The description of the above embodiments It is only used to help understand the method and core idea of the present invention, and the content of this specification should not be construed as a limitation to the present invention. At the same time, for those of ordinary skill in the art, based on the ideas of the present invention, any modification, equivalent replacement or improvement, etc. can be made in the specific implementation and the scope of application, which shall be included in the scope of the claims of the present invention. Inside.

Claims

A calibration method is characterized in that it includes:

Obtain the current measurement information of the inertial sensor;

According to the current measurement information of the inertial sensor, determine whether the current attitude of the platform on which the inertial sensor is mounted is abnormal; and

If the current attitude of the platform is abnormal, the inertial sensor is automatically calibrated.
The calibration method according to claim 1, wherein the determining whether the current attitude of the platform mounted on the inertial sensor is abnormal comprises:

Determine the deviation angle between the current posture of the platform mounted on the inertial sensor and its ideal posture in the direction of gravity, and determine whether the current posture of the platform is abnormal based on the deviation angle.
The calibration method according to claim 2, wherein when the deviation angle is greater than or equal to a preset angle threshold, it is determined that the current attitude of the platform is abnormal.
The calibration method according to claim 2, wherein when the deviation angle is less than the preset angle threshold, it is determined that the current posture of the platform is normal.
The calibration method according to claim 2, wherein the determining the deviation angle of the current attitude of the platform mounted on the inertial sensor from its ideal attitude in the direction of gravity comprises:

Obtaining the measured value of the accelerometer in the inertial sensor;

Determine the estimated value of gravitational acceleration; and

The deviation angle between the current attitude of the platform and its ideal attitude in the direction of gravity is calculated based on the measured value of the accelerometer and the estimated value of the acceleration of gravity.
The calibration method according to claim 5, wherein said determining the estimated value of gravitational acceleration comprises determining the estimated value of gravitational acceleration in the body coordinate system.
7. The calibration method according to claim 6, wherein said determining the estimated value of the acceleration of gravity in the body coordinate system further comprises:

Determine the rotation matrix of the current attitude of the platform from the current measurement information of the inertial sensor; and

The estimated value of the gravity acceleration in the body coordinate system is calculated based on the rotation matrix of the current posture of the platform and the gravity acceleration in the geodetic coordinate system.
The calibration method of claim 5, wherein the determining the deviation angle of the current attitude of the platform mounted on the inertial sensor from its ideal attitude in the direction of gravity further comprises:

Filtering the measured value of the accelerometer,

Wherein, the deviation angle between the current attitude of the platform and its ideal attitude in the direction of gravity is calculated based on the measured value of the filtered accelerometer and the estimated value of the acceleration of gravity.
The calibration method according to claim 1, wherein said automatically calibrating said inertial sensor comprises automatically calibrating a gyroscope in said inertial sensor.
8. The calibration method of claim 9, further comprising:

Acquiring the zero-bias calibration value of the gyroscope at the previous moment;

Wherein, the automatic zero-bias calibration of the gyroscope includes compensating the output value of the gyroscope at the current time based on the zero-bias calibration value of the gyroscope at the previous time to perform the zero-bias calibration on the gyroscope.
The calibration method according to claim 10, wherein said obtaining the zero offset calibration value of the gyroscope at a previous moment comprises:

Obtaining the output value of the gyroscope at the previous time and the measurement value of the accelerometer in the inertial sensor at the previous time; and

The zero offset calibration value of the gyroscope at the previous time is calculated based on the output value of the gyroscope at the previous time and the measured value of the accelerometer at the previous time.
The calibration method according to claim 10 or 11, wherein the output value of the gyroscope is the output value of the gyroscope after factory calibration compensation.
The calibration method according to claim 1, characterized in that it further comprises:

Detect whether the platform mounted on the inertial sensor is in a static state,

Wherein, when the platform is in a stationary state, the inertial sensor is calibrated.
The calibration method of claim 13, wherein when the platform is in a non-stationary state, the calibration is exited.
The calibration method of claim 14, wherein when the platform is in a non-stationary state, a corresponding alarm signal is provided to the user.
The calibration method according to claim 13, wherein said detecting whether the platform is in a stationary state comprises:

Obtaining sampling values of the accelerometer at different times within a given time interval;

Calculating the variance of the accelerometer based on the sampling value of the accelerometer;

Determine whether the platform is at rest based on the variance of the accelerometer.
The calibration method of claim 16, wherein the sampling value of the accelerometer includes the sampling value of the accelerometer on the x, y, and z axes, respectively.
The calibration method according to claim 16, wherein when the variance of the accelerometer is less than a given variance threshold, it is determined that the platform is in a stationary state.
The calibration method according to claim 16, characterized in that: when the variance of the accelerometer is greater than or equal to the given variance threshold, it is determined that the platform is in a non-stationary state.
The calibration method of claim 1, wherein the inertial sensor is located in a handheld pan/tilt, and the method further comprises:

Self-tuning the control parameters of the handheld PTZ,

Wherein, after self-tuning the control parameters of the handheld pan/tilt, it starts to acquire the current measurement information of the inertial sensor.
22. The calibration method of claim 20, wherein the platform mounted on the inertial sensor is a camera, and the self-tuning of the control parameters of the handheld PTZ comprises:

The configuration of the control parameters of the handheld PTZ is adjusted based on the camera mounted on the handheld PTZ.
The calibration method according to claim 21, wherein the configuration of adjusting the control parameters of the handheld PTZ based on the camera comprises:

Identifying the frequency domain model parameters of the combination of the handheld PTZ and the camera;

The configuration of the control parameters of the handheld pan/tilt head is adjusted according to the identified model.
The calibration method according to claim 20, wherein the self-tuning of the control parameters of the handheld PTZ comprises:

Obtain the user's operation on the keys of the handheld pan/tilt head to trigger the control parameter self-tuning.
A calibration device, characterized in that it comprises one or more processors, and the one or more processors work individually or collectively for executing:

Obtain the current measurement information of the inertial sensor;

According to the current measurement information of the inertial sensor, determine whether the current attitude of the platform on which the inertial sensor is mounted is abnormal; and

If the current attitude of the platform is abnormal, the inertial sensor is automatically calibrated.
The calibration device of claim 24, wherein the one or more processors work individually or collectively to perform: determining the current attitude of the platform on which the inertial sensor is mounted and its ideal attitude in gravity The deviation angle in the direction is used to determine whether the current posture of the platform is abnormal based on the deviation angle.
The calibration device according to claim 25, wherein when the deviation angle is greater than or equal to a preset angle threshold, it is determined that the current attitude of the platform is abnormal.
The calibration device according to claim 25, wherein when the deviation angle is less than the preset angle threshold, it is determined that the current posture of the platform is normal.
The calibration device according to claim 25, characterized in that: the one or more processors work individually or collectively to execute:

Obtaining the measured value of the accelerometer in the inertial sensor;

Determine the estimated value of gravitational acceleration; and

The deviation angle between the current attitude of the platform and its ideal attitude in the direction of gravity is calculated based on the measured value of the accelerometer and the estimated value of the acceleration of gravity.
The calibration device according to claim 28, wherein said determining the estimated value of gravitational acceleration comprises determining the estimated value of gravitational acceleration in the body coordinate system.
The calibration device according to claim 29, wherein the one or more processors work individually or collectively to execute:

Determine the rotation matrix of the current attitude of the platform from the current measurement information of the inertial sensor; and

The estimated value of the gravity acceleration in the body coordinate system is calculated based on the rotation matrix of the current posture of the platform and the gravity acceleration in the geodetic coordinate system.
The calibration device of claim 28, wherein the one or more processors work individually or collectively, and are also used to execute:

Filtering the measured value of the accelerometer,

Wherein, the deviation angle between the current attitude of the platform and its ideal attitude in the direction of gravity is calculated based on the measured value of the filtered accelerometer and the estimated value of the acceleration of gravity.
The calibration device according to claim 24, wherein the one or more processors work individually or collectively to execute: automatically perform zero-bias calibration of the gyroscope in the inertial sensor.
The calibration device according to claim 32, wherein the one or more processors work individually or collectively to execute:

Acquiring the zero-bias calibration value of the gyroscope at the previous moment;

Compensating the output value of the gyroscope at the current time based on the zero-bias calibration value of the gyroscope at the previous time to perform the zero-bias calibration of the gyroscope.
The calibration device according to claim 33, characterized in that: the one or more processors work individually or collectively to execute:

Obtaining the output value of the gyroscope at the previous time and the measurement value of the accelerometer in the inertial sensor at the previous time; and

The zero offset calibration value of the gyroscope at the previous time is calculated based on the output value of the gyroscope at the previous time and the measured value of the accelerometer at the previous time.
The calibration device according to claim 33 or 34, wherein the output value of the gyroscope is the output value of the gyroscope after factory calibration compensation.
The calibration device of claim 1, wherein the one or more processors work individually or collectively, and are also used to execute:

Detect whether the platform mounted on the inertial sensor is in a static state,

Wherein, when the platform is in a stationary state, the inertial sensor is calibrated.
The calibration device according to claim 36, wherein the one or more processors work individually or collectively, and are also used to execute: when the platform is in a non-stationary state, exit the calibration.
The calibration device according to claim 37, characterized in that: the one or more processors work individually or collectively, and are also used to execute: when the platform is in a non-stationary state, providing the user with corresponding Alarm.
The calibration device according to claim 36, wherein the one or more processors work individually or collectively to execute:

Obtaining sampling values of the accelerometer at different times within a given time interval;

Calculating the variance of the accelerometer based on the sampling value of the accelerometer;

Determine whether the platform is at rest based on the variance of the accelerometer.
The calibration device according to claim 39, wherein the sampling value of the accelerometer includes the sampling value of the accelerometer on the x, y, and z axes, respectively.
The calibration device according to claim 39, wherein the one or more processors work individually or collectively to execute: when the variance of the accelerometer is less than a given variance threshold, determine The platform is in a static state.
The calibration device of claim 39, wherein the one or more processors work individually or collectively to execute: when the variance of the accelerometer is greater than or equal to the given variance threshold When it is determined that the platform is in a non-stationary state.
The calibration device according to claim 24, wherein the inertial sensor is located in a hand-held pan/tilt, and the one or more processors work individually or collectively to execute:

Self-tuning the control parameters of the handheld PTZ,

Wherein, after self-tuning the control parameters of the handheld pan/tilt, it starts to acquire the current measurement information of the inertial sensor.
The calibration device of claim 43, wherein the platform on which the inertial sensor is mounted is a camera, and the one or more processors work individually or collectively for executing:

The configuration of the control parameters of the handheld PTZ is adjusted based on the camera mounted on the handheld PTZ.
The calibration device of claim 44, wherein the one or more processors work individually or collectively to execute:

Identifying the frequency domain model parameters of the combination of the handheld PTZ and the camera;

The configuration of the control parameters of the handheld pan/tilt head is adjusted according to the identified model.
The calibration device of claim 43, wherein the one or more processors work individually or collectively to execute:

Obtain the user's operation on the keys of the handheld pan/tilt head to trigger the control parameter self-tuning.
A calibration equipment, which is characterized in that it comprises:

A measurement information acquisition device, which is configured to acquire current measurement information of the inertial sensor;

A determining device, which is configured to determine whether the current attitude of the platform on which the inertial sensor is mounted is abnormal according to the current measurement information of the inertial sensor; and

The calibration device is configured to automatically calibrate the inertial sensor if the current attitude of the platform is abnormal.
The calibration device according to claim 47, wherein the determining device is configured to:

Determine the deviation angle between the current posture of the platform and its ideal posture in the direction of gravity, and determine whether the current posture of the platform is abnormal based on the deviation angle.
The calibration device of claim 48, wherein when the deviation angle is greater than or equal to a preset angle threshold, it is determined that the current attitude of the platform is abnormal.
The calibration device according to claim 48, wherein when the deviation angle is less than the preset angle threshold, it is determined that the current posture of the platform is normal.
The calibration device of claim 48, wherein the determining device is further configured to:

Determine the estimated value of gravitational acceleration; and

The deviation angle between the current attitude of the platform and its ideal attitude in the direction of gravity is determined based on the measured value of the accelerometer in the inertial sensor and the estimated value of the acceleration of gravity.
The calibration device according to claim 51, wherein the estimated value of the acceleration of gravity is an estimated value of the acceleration of gravity in the body coordinate system.
The calibration equipment according to claim 51, characterized in that it further comprises:

A filtering device, which is used to filter the measured value of the accelerometer,

Wherein, the determining device is configured to determine the deviation angle of the current attitude of the platform from its ideal attitude in the direction of gravity based on the measured value of the filtered accelerometer and the estimated value of the acceleration of gravity.
The calibration device according to claim 47, wherein the calibration device is configured to automatically calibrate the gyroscope in the inertial sensor.
The calibration device according to claim 54, wherein the calibration device is further configured to: obtain the zero-bias calibration value of the gyroscope at the previous time, and calibrate it based on the zero-bias calibration value of the gyroscope at the previous time Value to compensate the output value of the gyroscope at the current moment to calibrate the gyroscope.
The calibration device according to claim 55, characterized in that it further comprises:

A calculation device configured to obtain the output value of the gyroscope at the previous time and the measured value of the accelerometer in the inertial sensor at the previous time, and calculate the output value of the gyroscope at the previous time The zero offset calibration value of the gyroscope at the previous moment.
The calibration device according to claim 55 or 56, wherein the output value of the gyroscope at the current time is the output value of the gyroscope at the current time after factory calibration compensation.
The calibration device according to claim 47, which further comprises:

A stationary detection device configured to detect whether the platform mounted on the inertial sensor is in a stationary state,

Wherein, when the platform is in a stationary state, the calibration device calibrates the inertial sensor.
The calibration device according to claim 58, wherein the static detection device is further configured to:

Calculating the variance of the accelerometer based on the sampled values of the accelerometer at different moments in a given time interval;

Determine whether the platform is at rest based on the variance of the accelerometer.
The calibration device of claim 59, wherein the sampling value of the accelerometer includes the sampling value of the accelerometer on the x, y, and z axes, respectively.
The calibration device according to claim 59, wherein the static detection device is configured to determine that the platform is in a static state when the variance of the accelerometer is less than a given variance threshold.
The calibration device according to claim 59, wherein the static detection device is configured to determine that the platform is in a non-stationary state when the variance of the accelerometer is greater than or equal to the given variance threshold .
A stabilizer, characterized in that it comprises:

Inertial sensors, which include gyroscopes and accelerometers; and

The calibration device according to any one of claims 47 to 62, which is used to calibrate the inertial sensor.
The stabilizer according to claim 63, wherein the stabilizer includes at least one of the following: a handheld pan/tilt, an unmanned aerial vehicle, and a pan/tilt cart.
The stabilizer according to claim 64, wherein the stabilizer is a handheld pan/tilt, which further comprises:

A control parameter self-tuning device, which is configured to perform control parameter self-tuning on the controller of the handheld PTZ,

Wherein, after auto-tuning the control parameters of the controller of the handheld pan/tilt, the measurement information acquisition device is configured to start acquiring the current measurement information of the inertial sensor.
The stabilizer of claim 65, wherein the platform on which the inertial sensor is mounted is a camera, and the control parameter self-tuning device is configured as:

The configuration of the control parameters of the controller of the handheld PTZ is adjusted based on the camera mounted on the handheld PTZ.
The stabilizer of claim 66, wherein the control parameter self-tuning device is further configured to:

Identifying the frequency domain model parameters of the combination of the handheld PTZ and the camera;

The configuration of the control parameters of the controller of the handheld pan/tilt head is adjusted according to the identified model.
A computer-readable storage medium having executable instructions stored thereon, characterized in that: when the executable instructions are executed by a processor, the calibration method according to any one of claims 1 to 23 is implemented step.