CN111928844A - Model system of general MEMS gyroscope applied to AGV - Google Patents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
- G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
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Abstract
The invention discloses a model system of a general MEMS gyroscope applied to an AGV, which comprises: the gyro data acquisition module: the system comprises a data acquisition module, a data acquisition module and a data processing module, wherein the data acquisition module is used for acquiring angular velocity data of an MEMS gyroscope installed on an AGV; the gyro data compensation module: compensating the acquired gyro data, wherein the compensation method sequentially comprises temperature compensation, calibration and zero offset subtraction; a state judgment module: comparing the compensated gyro data with a dynamic and static state switching threshold A, if the gyro data is greater than the dynamic and static state switching threshold A, judging that the AGV is in a motion state, and judging that the AGV is in a static state; course angle YAW calculation module: and respectively calculating the course angle YAW in the motion state and the course angle YAW in the static state by adopting a dynamic course angle YAW calculation method and a static course angle YAW calculation method. The invention enables the general MEMS gyroscope to be applied to the AGV, and the performance of the MEMS gyroscope is equivalent to or even better than that of a gyroscope with high price, thereby greatly reducing the cost of the AGV application development.
Description
Technical Field
The invention relates to the technical field of MEMS, in particular to application of a general MEMS gyroscope in AGV.
Background
The AGV trolley is an automatic carrying trolley for short, and nowadays, the AGV trolley becomes one of important devices for modern intelligent logistics, movement and storage, and is gradually accepted and introduced.
The indoor AGV has various navigation modes including visual navigation, laser navigation, electromagnetic navigation and inertial navigation. The navigation modes can be used independently or cooperatively, and the task of high measurement precision and accurate navigation is completed. The visual and laser navigation modes have high precision but high price, which is 4000-tens of thousands yuan different; the traditional inertial navigation needs a high-precision gyroscope to provide accurate navigation, but the price is more than thousand yuan, the gyroscope suppliers are few, and the problem is caused by price or stable supply; the navigation features of electromagnetic navigation generally need to be used in conjunction with inertial navigation.
The general MEMS gyroscope which is easily available in the market has low price, the price is less than one hundred yuan, the choice of suppliers is large, and the supply is sufficient. However, the performance of the gyroscope has the defects of large zero offset, poor zero offset repeatability, large temperature drift, poor nonlinearity and the like, so that the gyroscope can have angle drift and inaccurate course angle in AGV application, so that the AGV cannot be accurately positioned, and the gyroscope is not adopted by the AGV industry.
In summary, the navigation technology of today is very expensive in the application of providing high-precision navigation, and the use and popularization are seriously affected.
Disclosure of Invention
The invention aims to provide a model system of a general MEMS gyroscope applied to an AGV, and the AGV trolley is accurately positioned through the general MEMS gyroscope.
In order to solve the technical problems, the invention adopts the following technical scheme: a model system of a general MEMS gyroscope for AGV application comprises:
the gyro data acquisition module: the system comprises a data acquisition module, a data acquisition module and a data processing module, wherein the data acquisition module is used for acquiring angular velocity data of an MEMS gyroscope installed on an AGV;
the gyro data compensation module: compensating the acquired gyro data, wherein the compensation method sequentially comprises temperature compensation, precision calibration and zero offset subtraction;
a state judgment module: comparing the compensated gyro data with a dynamic and static state switching threshold A, if the gyro data is greater than the dynamic and static state switching threshold A, judging that the AGV is in a motion state, and judging that the AGV is in a static state;
course angle YAW calculation module: and respectively calculating the course angle YAW in the motion state and the course angle YAW in the static state by adopting a dynamic course angle YAW calculation method and a static course angle YAW calculation method.
Preferably, the gyro zero offset calculation method during power-on is as follows:
firstly, a system is electrified to collect static 20 gyro data and stores the static gyro data into a cache Gyro Buff;
secondly, sequencing the cached Gyro Buff to obtain Gyro Buff 1;
and thirdly, taking 16 middle data of the cached Gyro Buff1 to perform average processing to obtain zero-offset BIAS of the gyroscope.
Preferably, the gyroscope is subjected to full-temperature compensation at-40 ℃ to 85 ℃:
the first step, carrying out second-order least square fitting on the collected full-temperature gyro data and the temperature:
Gyro＝AtTemp2+Bt·Temp+Ct
wherein, Gyro is Gyro data, Temp is temperature data, At is a second-order coefficient, Bt is a first-order coefficient, and Ct is a constant;
calculating the numerical values of At, Bt and Ct through fitting;
secondly, calculating a temperature curve value Gyro1 at the current temperature:
Gyro1＝At·Temp2+Bt·Temp+Ct
wherein Temp is a current temperature value;
thirdly, calculating a temperature curve value Gyro2 at 25 ℃:
Gyro2＝At·252+Bt·25+Ct
fourthly, temperature compensation is carried out on the gyro data:
GyroOut＝GyroRead-(Gyro1-Gyro2)
wherein, GyroOut is the gyro value after temperature compensation, and gyrorand is the reading gyro value.
Preferably, the method for calibrating the gyro precision comprises the following steps:
acquiring n groups of data of the gyroscope under +/-x DEG/s, wherein n is more than or equal to 7, averaging each group of data, fitting the data by using a least square method, finally obtaining scale factors, zero offset and cross coupling parameters of each group of gyroscope data, and compensating the acquired gyroscope data:
wherein, GyrosXOut, GyrosyOut and GyrosZOut are compensated gyro values, GyrosXRead, GyrosYREAD and GyrosZRead are read gyro values, and Data 0-Data 11 are fitting parameters.
Preferably, the method for calculating the dynamic and static state switching threshold value a comprises the following steps: a is GNoise + GTemp + GData, wherein GNoise is 1/2 noise fluctuation peak-to-peak value when the gyroscope is static; GTemp is the zero offset change value of the gyroscope within the working temperature range of the system; GData is a reserved threshold value.
Preferably, the calculation method of the course angle YAW in the motion state is as follows: YAW is YAWl + Gyro Time, wherein YAW is the current course angle, YAWl is the last course angle, Gyro is angular velocity data acquired by the gyroscope, and Time is system integration Time 10 ms.
Preferably, the method for calculating the YAW angle YAW in the stationary state includes: YAW is the current heading angle, YAWd is the heading angle when the dynamic enters static, and RandomNoise is the noise estimate of the system and is limited to ± 0.1.
Preferably, after the angular velocity data of the gyroscope is collected, the singular points of the gyroscope are removed, and then the gyroscope data are compensated.
Preferably, the compensated gyro data is subjected to amplitude limiting filtering by a digital filter, and then the dynamic heading angle is calculated through integral operation.
By adopting the technical scheme, when the general MEMS gyroscope is applied to the AGV, the course angle is not judged by only depending on the performance of the gyroscope, but an adaptive algorithm is invented after temperature, parameter calibration and digital filtering so as to carry out integral processing on the gyroscope according to the current motion state of the AGV.
Therefore, the following beneficial effects are achieved:
make general MEMS top also can use and the performance is equivalent even better with the top of high price on the AGV, great reduction AGV application development's cost, also for the AGV application provides more choices, opened the market of general MEMS top in AGV application, alleviateed AGV manufacturer to gyroscope cost and the burden on the lectotype.
The following detailed description of the present invention will be provided in conjunction with the accompanying drawings.
Drawings
The invention is further described with reference to the accompanying drawings and the detailed description below:
FIG. 1 is a schematic diagram of a typical MEMS gyroscope applied to an AGV;
FIG. 2 is a flowchart of a typical MEMS gyroscope algorithm for AGV application;
Detailed Description
The technical solutions of the embodiments of the present invention are explained and illustrated below, but the following embodiments are only preferred embodiments of the present invention, and not all of them. Based on the embodiments in the implementation, other embodiments obtained by those skilled in the art without any creative effort belong to the protection scope of the present invention.
Referring to fig. 1 and 2, a model system of a general MEMS gyroscope for AGV application, which uses the general MEMS gyroscope to realize positioning of an AGV cart, includes:
the gyro data acquisition module: the method is used for collecting the angular velocity data of the MEMS gyroscope installed on the AGV.
And singular points of the angular velocity data need to be rejected.
The gyro data compensation module: compensating the acquired gyro data, wherein the compensation method sequentially comprises temperature compensation, precision calibration and zero offset subtraction;
a state judgment module: comparing the compensated gyro data with a dynamic and static state switching threshold A, if the gyro data is greater than the dynamic and static state switching threshold A, judging that the AGV is in a motion state, and judging that the AGV is in a static state;
course angle YAW calculation module: and respectively calculating the course angle YAW in the motion state and the course angle YAW in the static state by adopting a dynamic course angle YAW calculation method and a static course angle YAW calculation method.
Processing zero offset of the gyroscope during power-on:
firstly, a system is electrified to collect static 20 gyro data and stores the static gyro data into a cache Gyro Buff;
secondly, sequencing the cached Gyro Buff to obtain Gyro Buff 1;
and thirdly, taking the middle 16 data of the cached Gyro Buff1 to perform average processing to obtain the zero-offset BIAS of the gyroscope.
It will be appreciated by those skilled in the art that more than 20 static gyroscopic data may be acquired at power-up. And once stationary, the zero offset needs to be recalculated.
And carrying out full-temperature compensation of-40-85 ℃ on the gyroscope. Since the AGV car of the present invention is directed to an industrial level application, the temperature compensation corresponds to an industrial level temperature.
The first step, carrying out second-order least square fitting on the collected full-temperature gyro data and the temperature:
Gyro＝At·Temp2+Bt·Temp+Ct
wherein, Gyro is Gyro data, Temp is temperature data, At is a second-order coefficient, Bt is a first-order coefficient, and Ct is a constant;
the At, Bt and Ct values can be determined in the first step.
Secondly, calculating a temperature curve value Gyro1 at the current temperature:
Gyro1＝At·Temp2+Bt.Temp+Ct
wherein Temp is a current temperature value;
thirdly, calculating a temperature curve value Gyro2 at 25 ℃:
Gyro2＝At·252+Bt·25+Ct
fourthly, temperature compensation is carried out on the gyro data:
GyroOut＝GyroRead-(Gyro1-Gyro2)
wherein, GyroOut is the gyro value after temperature compensation, and gyrorand is the reading gyro value.
And calibrating the gyroscope.
The system collects multiple groups of data (each group comprises positive values and negative values) of the gyroscope within +/-5 DEG/s, +/-30 DEG/s, +/-50 DEG/s, +/-75 DEG/s, +/-85 DEG/s, +/-100 DEG/s and the like, averages each group of data respectively, and performs fitting processing on the data by a least square method to finally obtain scale factors, zero offset coefficients and cross coupling parameters of each group of gyroscope data. The specific calculation method can refer to the prior art, for example, the thesis document < the technical research of an attitude and heading measurement system based on the MEMS-IMU >, the university of harbinge engineering, the major research student: liukun, teacher: liu Yin Fang Ming.
According to the scale factor, the zero offset coefficient and the cross coupling parameter, compensating the acquired gyro data:
wherein, GyrosXOut, GyrosyOut and GyrosZOut are compensated gyro values, GyrosXRead, GyrosYREAD and GyrosZRead are read gyro values, and Data 0-Data 11 are fitting parameters. Data0, Data4, Data8 are scale factor coefficients of the tri-axial gyroscope, Data9, Data10, Data11 are zero bias coefficients of the tri-axial gyroscope, and the rest are cross coupling coefficients.
Real-time judgment of motion state of AGV
Step one, calculating a threshold value A of system dynamic and static state switching:
A＝GNoise+GTemp+GData
wherein, GNoise is 1/2 noise fluctuation peak value when the gyroscope is static; GTemp is the zero-bias change value of the gyroscope in the working temperature range of the system, and GData reserves a threshold value for software.
Secondly, calculating the integral of the course angle YAW under the dynamic condition:
YAW＝YAWl+Gyro·Time
where YAW is the current course angle, YAWl is the last course angle, Gyro is angular velocity data collected by the Gyro, and Time is the system integration Time 10 ms.
And if the dynamic situation is determined, digital filtering processing needs to be carried out on the compensated data through a digital filter before integral calculation is carried out. The motion state will use temperature calibration, precision calibration, zero offset subtraction, digital filtering.
Thirdly, calculating a course angle YAW under a static condition:
YAW＝YAWd+RandomNoise
YAW is the current course angle, YAWd is the course angle when the dynamic state enters the static state, RandomNoise is the noise estimation value of the system and is limited within +/-0.1, and the noise estimation value is obtained by accumulating the random numerical value added by the system to the output value. The angle noise itself is random and irregular, and thus a random number is used, which is generated by a random function.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that the invention is not limited thereto, and may be embodied in other forms without departing from the spirit or essential characteristics thereof. Any modification which does not depart from the functional and structural principles of the present invention is intended to be included within the scope of the claims.
Claims (9)
1. A model system of a general MEMS gyroscope on an AGV application is characterized by comprising:
the gyro data acquisition module: the system comprises a data acquisition module, a data acquisition module and a data processing module, wherein the data acquisition module is used for acquiring angular velocity data of an MEMS gyroscope installed on an AGV;
the gyro data compensation module: compensating the acquired gyro data, wherein the compensation method sequentially comprises temperature compensation, precision calibration and zero offset subtraction;
a state judgment module: comparing the compensated gyro data with a dynamic and static state switching threshold A, if the gyro data is greater than the dynamic and static state switching threshold A, judging that the AGV is in a motion state, and judging that the AGV is in a static state;
course angle YAW calculation module: and respectively calculating the course angle YAW in the motion state and the course angle YAW in the static state by adopting a dynamic course angle YAW calculation method and a static course angle YAW calculation method.
2. The model system of claim 1, wherein said model system comprises: the gyro zero-offset calculation method during power-on is as follows:
firstly, a system is electrified to collect static 20 gyro data and stores the static gyro data into a cache Gyro Buff;
secondly, sequencing the cached Gyro Buff to obtain Gyro Buff 1;
and thirdly, taking 16 middle data of the cached Gyro Buff1 to perform average processing to obtain zero-offset BIAS of the gyroscope.
3. The model system of claim 2, wherein said model system comprises: carrying out full-temperature compensation of-40-85 ℃ on the gyroscope:
the first step, carrying out second-order least square fitting on the collected full-temperature gyro data and the temperature:
Gyro＝At·Temp2+Bt·Temp+Ct
wherein, Gyro is Gyro data, Temp is temperature data, At is a second-order coefficient, Bt is a first-order coefficient, and Ct is a constant;
calculating the numerical values of At, Bt and Ct through fitting;
secondly, calculating a temperature curve value Gyro1 at the current temperature:
Gyro1＝At·Temp2+Bt·Temp+Ct
wherein Temp is a current temperature value;
thirdly, calculating a temperature curve value Gyro2 at 25 ℃:
Gyro2＝At·252+Bt·25+Ct
fourthly, temperature compensation is carried out on the gyro data:
GyroOut＝GyroRead-(Gyro1-Gyro2)
wherein, GyroOut is the gyro value after temperature compensation, and gyrorand is the reading gyro value.
4. A model system of a general MEMS gyroscope for AGV applications according to any of claims 1 to 3, wherein: the method for calibrating the gyro precision comprises the following steps:
acquiring n groups of data of the gyroscope under +/-x DEG/s, wherein n is more than or equal to 7, averaging each group of data, fitting the data by using a least square method, finally obtaining scale factors, zero offset and cross coupling parameters of each group of gyroscope data, and compensating the acquired gyroscope data:
wherein, GyrosXOut, GyrosyOut and GyrosZOut are compensated gyro values, GyrosXRead, GyrosYREAD and GyrosZRead are read gyro values, and Data 0-Data 11 are fitting parameters.
5. A model system of a general MEMS gyroscope for AGV application according to any of claims 1 to 4, wherein:
the calculation method of the dynamic and static state switching threshold A comprises the following steps: a is GNoise + GTemp + GData,
wherein, GNoise is 1/2 noise fluctuation peak value when the gyroscope is static; GTemp is the zero offset change value of the gyroscope within the working temperature range of the system; GData is a reserved threshold value.
6. The model system of claim 5 for a generic MEMS gyroscope for AGV application, wherein: the calculation method of the course angle YAW in the motion state comprises the following steps: YAW is YAWl + Gyro Time,
where YAW is the current course angle, YAWl is the last course angle, Gyro is angular velocity data collected by the Gyro, and Time is the system integration Time 10 ms.
7. The model system of claim 5 for a generic MEMS gyroscope for AGV application, wherein: the method for calculating the course angle YAW in the static state comprises the following steps: YAW is YAWd + RandomNoise,
where YAW is the current course angle, YAWd is the course angle when the dynamic state enters the static state, and RandomNoise is the noise estimation value of the system and is limited within + -0.1.
8. The model system of claim 1, wherein said model system comprises: after the angular velocity data of the gyroscope is collected, the singular points of the gyroscope are removed at first, and then the gyroscope data are compensated.
9. The model system of claim 1, wherein said model system comprises: and carrying out amplitude limiting and filtering on the compensated gyro data by adopting a digital filter, and then calculating the dynamic course angle by integral operation.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000180462A (en) * | 1998-12-17 | 2000-06-30 | Tokin Corp | Posture angle detecting device |
| CN101236083A (en) * | 2008-03-06 | 2008-08-06 | 浙江大学 | A Method of Quickly Switching Dynamic and Static Output Data of Fiber Optic Gyroscope |
| CN103808331A (en) * | 2014-03-05 | 2014-05-21 | 北京理工大学 | MEMS (micro-electromechanical system) three-axis gyroscope error calibration method |
| CN104567931A (en) * | 2015-01-14 | 2015-04-29 | 华侨大学 | Course-drifting-error elimination method of indoor inertial navigation positioning |
| US20150276783A1 (en) * | 2014-03-31 | 2015-10-01 | Stmicroelectronics S.R.I. | Positioning apparatus comprising an inertial sensor and inertial sensor temperature compensation method |
| CN105675015A (en) * | 2016-01-08 | 2016-06-15 | 中国电子科技集团公司第二十六研究所 | MEMS gyroscope zero-offset automatic elimination method |
| CN108507572A (en) * | 2018-05-28 | 2018-09-07 | 清华大学 | A kind of attitude orientation error correcting method based on MEMS Inertial Measurement Units |
| CN108680189A (en) * | 2018-07-09 | 2018-10-19 | 无锡凌思科技有限公司 | A kind of MEMS gyroscope Z axis zero bias dynamic compensation method based on Kalman filtering |
| CN109696183A (en) * | 2019-01-28 | 2019-04-30 | 北京华捷艾米科技有限公司 | The scaling method and device of Inertial Measurement Unit |
| CN109827596A (en) * | 2019-04-02 | 2019-05-31 | 北京理工大学 | A Zero Bias Estimation Method for MEMS Gyroscopes under Discontinuous Motion Condition |
| CN110221302A (en) * | 2019-05-24 | 2019-09-10 | 上海高智科技发展有限公司 | Environmental detection device and its modification method, system, portable equipment and storage medium |
| DE102018115428A1 (en) * | 2018-06-27 | 2020-01-02 | Valeo Schalter Und Sensoren Gmbh | Method for determining an offset value for an inertial measuring unit in a stationary state of motion of a motor vehicle |
-
2020
- 2020-06-11 CN CN202010529726.XA patent/CN111928844B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000180462A (en) * | 1998-12-17 | 2000-06-30 | Tokin Corp | Posture angle detecting device |
| CN101236083A (en) * | 2008-03-06 | 2008-08-06 | 浙江大学 | A Method of Quickly Switching Dynamic and Static Output Data of Fiber Optic Gyroscope |
| CN103808331A (en) * | 2014-03-05 | 2014-05-21 | 北京理工大学 | MEMS (micro-electromechanical system) three-axis gyroscope error calibration method |
| US20150276783A1 (en) * | 2014-03-31 | 2015-10-01 | Stmicroelectronics S.R.I. | Positioning apparatus comprising an inertial sensor and inertial sensor temperature compensation method |
| CN104567931A (en) * | 2015-01-14 | 2015-04-29 | 华侨大学 | Course-drifting-error elimination method of indoor inertial navigation positioning |
| CN105675015A (en) * | 2016-01-08 | 2016-06-15 | 中国电子科技集团公司第二十六研究所 | MEMS gyroscope zero-offset automatic elimination method |
| CN108507572A (en) * | 2018-05-28 | 2018-09-07 | 清华大学 | A kind of attitude orientation error correcting method based on MEMS Inertial Measurement Units |
| DE102018115428A1 (en) * | 2018-06-27 | 2020-01-02 | Valeo Schalter Und Sensoren Gmbh | Method for determining an offset value for an inertial measuring unit in a stationary state of motion of a motor vehicle |
| CN108680189A (en) * | 2018-07-09 | 2018-10-19 | 无锡凌思科技有限公司 | A kind of MEMS gyroscope Z axis zero bias dynamic compensation method based on Kalman filtering |
| CN109696183A (en) * | 2019-01-28 | 2019-04-30 | 北京华捷艾米科技有限公司 | The scaling method and device of Inertial Measurement Unit |
| CN109827596A (en) * | 2019-04-02 | 2019-05-31 | 北京理工大学 | A Zero Bias Estimation Method for MEMS Gyroscopes under Discontinuous Motion Condition |
| CN110221302A (en) * | 2019-05-24 | 2019-09-10 | 上海高智科技发展有限公司 | Environmental detection device and its modification method, system, portable equipment and storage medium |
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