CN113984090B - Wheel type robot IMU error online calibration and compensation method and device - Google Patents
Wheel type robot IMU error online calibration and compensation method and device Download PDFInfo
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Abstract
The invention discloses a wheel robot IMU error online calibration and compensation method and device, wherein the method comprises the following steps: acquiring first correction data; the first correction data are a section of continuous data collected by the IMU when the wheeled robot provided with the IMU is in a standing state on a horizontal plane, and the continuous data comprise acceleration and angular velocity in the X, Y, Z direction; acquiring second correction data; the second correction data is a section of continuous data collected by the IMU in the in-situ rotation process of the wheeled robot, and comprises the angular speed in the X, Y, Z direction; establishing an accelerometer and gyroscope online calibration error model, and calculating calibration parameters; and compensating the output of the IMU through the calculated parameters. According to the invention, the condition that the IMU has an installation error is considered, and the IMU of the wheeled robot can be calibrated and compensated on line through simple operation, so that the measurement accuracy of the IMU is improved.
Description
Technical Field
The invention relates to the technical field of automatic control of wheeled robots, in particular to a method and a device for calibrating and compensating an IMU error of a wheeled robot on line.
Background
Today, where service robots are becoming more and more popular, wheeled robots take up a significant role, while during their travel inertial measurement units (Inertial Measurement Unit, IMU) are a key sensor for the wheeled robots to achieve positioning, speed measurement, and attitude estimation. The IMU is used as a measuring element, and is sensitive to interference generated by unavoidable external factors such as impact, vibration, stress, temperature and the like in the processes of factory installation, transportation and user use, so that time-varying and non-negligible IMU errors can be caused. If the accumulation of the errors of the IMU is not processed, the gesture and navigation precision of the robot can be seriously reduced, so that the performance of the robot is affected. Therefore, on-line calibration and compensation are required for the IMU error, so that the measurement accuracy of the IMU is ensured, and the performance of the robot is ensured.
Before the IMU is installed on the wheeled robot, the IMU is generally fixed on a turntable for factory calibration, and calibration parameters comprise a scale factor and zero offset. Through testing, after the IMU leaves the factory and installs on the robot, the scale factors of the accelerometer and gyroscope are very small in change caused by factors such as installation, transportation, temperature change and aging, and the like, so that online calibration is not needed; however, the zero offset factors of gyroscopes and accelerometers can be greatly changed due to the factors, and online calibration and compensation are needed.
Generally, in the prior art, in order to perform on-line calibration on zero offset of a gyroscope and an accelerometer installed in a wheeled robot, the zero offset can be calculated by only allowing the robot to stand on a horizontal ground, and since the theoretical output of the gyroscope is 0 and the theoretical output of the accelerometer is the gravitational acceleration g.
However, considering that the mounting of the IMU on the wheeled robot is not horizontal, there is an installation error angle between the IMU and the robot, so even if the robot is placed on a horizontal ground, it is difficult for the theoretical horizontal axis in the IMU to remain parallel to the ground. And because of the existence of the gravity acceleration g, components of the gravity acceleration g exist on 3 axes of the accelerometer, which brings difficulty to the calculation of the zero offset of the accelerometer. It is difficult to estimate the accelerometer zero offset simply by resting on a level ground. Therefore, the existing method for calibrating the zero offset of the IMU installed in the wheeled robot cannot accurately realize the calibration and compensation of the IMU error of the wheeled robot.
Disclosure of Invention
The invention provides a method and a device for on-line calibration and compensation of an IMU error of a wheeled robot, which are used for solving the technical problem that the existing method for calibrating the zero offset of the IMU installed in the wheeled robot cannot accurately realize the calibration and compensation of the IMU error of the wheeled robot.
In order to solve the technical problems, the invention provides the following technical scheme:
in one aspect, the invention provides a wheel robot IMU error online calibration and compensation method, which comprises the following steps:
acquiring first correction data; the first correction data are a section of continuous data collected by the Inertial Measurement Unit (IMU) in a first preset time period when the wheeled robot provided with the IMU is in a standing state on a horizontal plane, and the first correction data comprise acceleration and angular velocity in the X, Y, Z direction;
acquiring second correction data; the second correction data is a section of continuous data collected by the IMU in the process that the wheeled robot rotates in situ for a preset angle on a horizontal plane at a preset speed within a second preset time period, and the second correction data comprises an angular speed in the X, Y, Z direction;
establishing an accelerometer and gyroscope online calibration error model;
based on the first correction data and the second correction data, calculating zero offset of the gyroscope and the accelerometer through an online calibration error model of the accelerometer and the gyroscope, and completing online calibration of the IMU error;
and compensating the output data of the IMU through the calculated zero offset of the gyroscope and the accelerometer.
Further, the expression of the accelerometer and gyroscope online calibration error model is as follows:
wherein,,
represents the angular velocity measurement value, ω represents the angular velocity theoretical value, w g Representing gyro noise of the type Gaussian white noise +.>
Represents the measured acceleration value, a represents the theoretical acceleration value, w a Representing accelerometer noise of the type Gaussian white noise, b g Indicating zero bias of gyroscope, b a Indicating the accelerometer zero offset.
Further, the calculating, based on the first correction data and the second correction data, zero offset of the gyroscope and the accelerometer through the accelerometer and the gyroscope on-line calibration error model includes:
calculating an average value of accelerations in the first correction data
And the average value of the angular velocity in the first correction data +.>
Since the IMU is in a rest state and gaussian white noise mathematical expectation is 0, ω=0, gyroscope noise average +.>
Accelerometer noise mean>
This gives:
wherein,,
representing the average value of zero offset of the gyroscope within a first preset duration;
calculating an average value of the angular velocity in the second correction data
Since the robot rotates on the horizontal plane, the rotation axis direction is the same as the gravity direction, and there are:
and because:
so that:
further, the compensating the output data of the IMU by the calculated zero offset of the gyroscope and the accelerometer includes:
based on the calculated zero offset of the gyroscope and the accelerometer and the online calibration error model of the accelerometer and the gyroscope, the output data of the IMU is compensated by using the following formula:
wherein omega 2 A, outputting data for the compensated gyroscope 2 And outputting data for the compensated accelerometer.
On the other hand, the invention also provides a wheel type robot IMU error on-line calibration and compensation device, which comprises:
the first correction data acquisition module is used for acquiring first correction data; the first correction data are a section of continuous data collected by the Inertial Measurement Unit (IMU) in a first preset time period when the wheeled robot provided with the IMU is in a standing state on a horizontal plane, and the first correction data comprise acceleration and angular velocity in the X, Y, Z direction;
a second correction data acquisition module configured to acquire second correction data; the second correction data is a section of continuous data collected by the IMU in the process that the wheeled robot rotates in situ for a preset angle on a horizontal plane at a preset speed within a second preset time period, and the second correction data comprises an angular speed in the X, Y, Z direction;
the calibration error model construction module is used for establishing an accelerometer and gyroscope online calibration error model;
the on-line calibration module is used for calculating zero offset of the gyroscope and the accelerometer through the on-line calibration error model of the accelerometer and the gyroscope established by the calibration error model establishment module based on the first correction data acquired by the first correction data acquisition module and the second correction data acquired by the second correction data acquisition module, so as to complete on-line calibration of the IMU error;
and the compensation module is used for compensating the output data of the IMU through the zero offset of the gyroscope and the accelerometer calculated by the online calibration module.
Further, the expression of the online calibration error model established by the calibration error model establishing module is as follows:
wherein,,
represents the angular velocity measurement value, ω represents the angular velocity theoretical value, w g Representing gyro noise of the type Gaussian white noise +.>
Represents the measured acceleration value, a represents the theoretical acceleration value, w a Representing accelerometer noise of the type Gaussian white noise, b g Indicating zero bias of gyroscope, b a Indicating the accelerometer zero offset.
Further, the online calibration module is specifically configured to:
calculating an average value of accelerations in the first correction data
And the average value of the angular velocity in the first correction data +.>
Since the IMU is in a rest state and gaussian white noise mathematical expectation is 0, ω=0, gyroscope noise average +.>
Accelerometer noise mean>
This gives:
wherein,,
representing the average value of zero offset of the gyroscope within a first preset duration;
calculating an average value of the angular velocity in the second correction data
Since the robot rotates on the horizontal plane, the rotation axis direction is the same as the gravity direction, and there are:
and because:
so that:
further, the compensation module is specifically configured to:
based on the calculated zero offset of the gyroscope and the accelerometer and the online calibration error model of the accelerometer and the gyroscope, the output data of the IMU is compensated by using the following formula:
wherein omega 2 A, outputting data for the compensated gyroscope 2 And outputting data for the compensated accelerometer.
In yet another aspect, the present invention also provides an electronic device including a processor and a memory; wherein the memory stores at least one instruction that is loaded and executed by the processor to implement the above-described method.
In yet another aspect, the present invention also provides a computer readable storage medium having at least one instruction stored therein, the instruction being loaded and executed by a processor to implement the above method.
The technical scheme provided by the invention has the beneficial effects that at least:
1. according to the invention, the on-line calibration of the IMU of the wheeled robot can be completed through real-time acquisition calculation, the calibration result is good, and the positioning and attitude-fixing performance can be effectively improved.
2. The mathematical formula in the invention is simple and easy to understand, and the program is convenient to realize; the implementation and operation are simple, the implementation is easy, and the operation time is short. Only one horizontal ground is needed for operation, and other specialized tools are not needed.
3. The wheel type robot IMU error online calibration and compensation method provided by the invention is suitable for the condition of larger IMU installation error and has good practicability.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an execution flow of a method for on-line calibration and compensation of an IMU error of a wheeled robot according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the embodiments of the present invention will be described in further detail with reference to the accompanying drawings.
First embodiment
The embodiment provides a wheel robot IMU error online calibration and compensation method, which can be realized by electronic equipment. The execution flow of the method is shown in fig. 1, and comprises the following steps:
s1, acquiring first correction data; the first correction data are a section of continuous data collected by the Inertial Measurement Unit (IMU) in a first preset time period when the wheeled robot provided with the IMU is in a standing state on a horizontal plane, and the first correction data comprise acceleration and angular velocity in the X, Y, Z direction;
in this embodiment, the first correction data is obtained by: placing the wheeled robot provided with the IMU on a horizontal plane, enabling the wheeled robot to be in a standing state, and then acquiring data output by the IMU; the data output by the IMU is IMU data corrected by the factory calibration coefficient.
S2, acquiring second correction data; the second correction data is a section of continuous data collected by the IMU in the process that the wheeled robot rotates in situ for a preset angle on a horizontal plane at a preset speed within a second preset time period, and the second correction data comprises an angular speed in the X, Y, Z direction;
in this embodiment, the second correction data is obtained by: placing a wheeled robot provided with an IMU on a horizontal plane, driving the robot to rotate in situ at a certain angle on the horizontal plane clockwise (or anticlockwise) at a certain speed, and acquiring a section of continuous data collected by the IMU in a in-situ rotation state; the data output by the IMU is IMU data corrected by the factory calibration coefficient.
S3, establishing an accelerometer and gyroscope online calibration error model;
in the embodiment, when modeling the error models of the accelerometer and the gyroscope, the calibration factors of the gyroscope and the accelerometer are considered to be calibrated when leaving the factory, and the changes caused by factors such as installation, transportation, temperature change, aging and the like after leaving the factory are very small, so that online calibration is not needed; however, the zero offset factors of gyroscopes and accelerometers can cause large changes due to the factors, and online calibration is needed.
Based on the above, the present embodiment builds an accelerometer and gyroscope error model as follows:
wherein,,
represents the angular velocity measurement value, ω represents the angular velocity theoretical value, w g Representing gyro noise of the type Gaussian white noise +.>
Represents the measured acceleration value, a represents the theoretical acceleration value, w a Representing accelerometer noise of the type Gaussian white noise, b g Indicating zero bias of gyroscope, b a Indicating the accelerometer zero offset.
S4, based on the first correction data and the second correction data, calculating zero offset of the gyroscope and the accelerometer through an online calibration error model of the accelerometer and the gyroscope, and completing online calibration of IMU errors;
specifically, in the present embodiment, the error parameter solving process of the accelerometer and the gyroscope is as follows:
and respectively averaging the acceleration and the angular velocity in the first correction data to obtain: average value of acceleration in first correction data
And an average value +.of the angular velocity in the first correction data>
Since the IMU is in a rest state and gaussian white noise mathematical expectation is 0, ω=0, gyroscope noise average +.>
Accelerometer noise average
This gives:
Wherein,,
and representing the average value of the zero offset of the gyroscope in the first preset time period.
Averaging the angular velocity of the second correction data to obtain an average value of the angular velocity in the second correction data
Since the robot rotates on the horizontal plane, the rotation axis direction is the same as the gravity direction, and there are:
and because gaussian white noise is mathematically expected to be 0,
the error model is brought into the above equation:
and because:
so that:
so far, the zero offset of the gyroscope and the accelerometer is solved, and the online calibration of the IMU error of the robot is completed.
And S5, compensating the output data of the IMU through the calculated zero offset of the gyroscope and the accelerometer.
Specifically, when the robot operates in practical application, the IMU error compensation method is as follows:
wherein omega 2 A, outputting data for the compensated gyroscope 2 Outputting data for the compensated accelerometer; b g B is zero offset error of gyroscope a For zero offset error of the accelerometer, w g Data noise of gyroscope is Gaussian white noise, w a The data noise of the accelerometer is Gaussian white noise;
output data for the factory corrected gyroscope and accelerometer, respectively, can be represented by the following formulas:
wherein K is g Is 3-order square matrix, B g The 3-dimensional column vectors are respectively a factory calibrated gyroscope scale coefficient and zero offset; k (K) a Is 3-order square matrix, B a And 3-dimensional column vectors are respectively the calibration coefficient and zero offset of the factory calibrated accelerometer.
Raw data output by the gyroscope and the accelerometer respectively.
In summary, in the method for calibrating and compensating the wheel robot IMU error online in the embodiment, zero offset is solved by using the average value of the output of the gyroscope when the robot stands still; the zero offset of the accelerometer is solved by utilizing the characteristic that the direction of the rotation axis is the same as the direction of gravity when the robot rotates on the horizontal plane. The method can complete on-line calibration and compensation of the IMU of the wheeled robot through simple operation and real-time acquisition calculation, has good result and can effectively improve the positioning and attitude-fixing performance; the mathematical formula is simple and easy to understand, the program is convenient to realize, the implementation and operation are simple and easy to realize, the operation time is short, the operation can be performed only by a horizontal ground, and other professional tools are not needed. Moreover, the calibration and compensation method is suitable for the condition of large IMU installation error, and has good practicability.
Second embodiment
The embodiment provides an on-line calibration and compensation device for IMU errors of a wheeled robot, which comprises:
the first correction data acquisition module is used for acquiring first correction data; the first correction data are a section of continuous data collected by the Inertial Measurement Unit (IMU) in a first preset time period when the wheeled robot provided with the IMU is in a standing state on a horizontal plane, and the first correction data comprise acceleration and angular velocity in the X, Y, Z direction;
a second correction data acquisition module configured to acquire second correction data; the second correction data is a section of continuous data collected by the IMU in the process that the wheeled robot rotates in situ for a preset angle on a horizontal plane at a preset speed within a second preset time period, and the second correction data comprises an angular speed in the X, Y, Z direction;
the calibration error model construction module is used for establishing an accelerometer and gyroscope online calibration error model;
the on-line calibration module is used for calculating zero offset of the gyroscope and the accelerometer through the on-line calibration error model of the accelerometer and the gyroscope established by the calibration error model establishment module based on the first correction data acquired by the first correction data acquisition module and the second correction data acquired by the second correction data acquisition module, so as to complete on-line calibration of the IMU error;
and the compensation module is used for compensating the output data of the IMU through the zero offset of the gyroscope and the accelerometer calculated by the online calibration module.
The wheel type robot IMU error online calibration and compensation device of the embodiment corresponds to the wheel type robot IMU error online calibration and compensation method of the first embodiment; the functions realized by the functional modules in the wheel robot IMU error online calibration and compensation device in the embodiment are in one-to-one correspondence with the flow steps in the wheel robot IMU error online calibration and compensation method; therefore, the description is omitted here.
Third embodiment
The embodiment provides an electronic device, which comprises a processor and a memory; wherein the memory stores at least one instruction that is loaded and executed by the processor to implement the method of the first embodiment.
The electronic device may vary considerably in configuration or performance and may include one or more processors (central processing units, CPU) and one or more memories having at least one instruction stored therein that is loaded by the processors and performs the methods described above.
Fourth embodiment
The present embodiment provides a computer-readable storage medium having stored therein at least one instruction that is loaded and executed by a processor to implement the method of the first embodiment described above. The computer readable storage medium may be, among other things, ROM, random access memory, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. The instructions stored therein may be loaded by a processor in the terminal and perform the methods described above.
Furthermore, it should be noted that the present invention can be provided as a method, an apparatus, or a computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the invention may take the form of a computer program product on one or more computer-usable storage media having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.
It is finally pointed out that the above description of the preferred embodiments of the invention, it being understood that although preferred embodiments of the invention have been described, it will be obvious to those skilled in the art that, once the basic inventive concepts of the invention are known, several modifications and adaptations can be made without departing from the principles of the invention, and these modifications and adaptations are intended to be within the scope of the invention. It is therefore intended that the following claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Claims (4)
1. The method for calibrating and compensating the wheel type robot IMU error on line is characterized by comprising the following steps:
acquiring first correction data; the first correction data are a section of continuous data collected by the Inertial Measurement Unit (IMU) in a first preset time period when the wheeled robot provided with the IMU is in a standing state on a horizontal plane, and the first correction data comprise acceleration and angular velocity in the X, Y, Z direction;
acquiring second correction data; the second correction data is a section of continuous data collected by the IMU in the process that the wheeled robot rotates in situ for a preset angle on a horizontal plane at a preset speed within a second preset time period, and the second correction data comprises an angular speed in the X, Y, Z direction;
establishing an accelerometer and gyroscope online calibration error model;
based on the first correction data and the second correction data, calculating zero offset of the gyroscope and the accelerometer through an online calibration error model of the accelerometer and the gyroscope, and completing online calibration of the IMU error;
compensating the output data of the IMU through the calculated zero offset of the gyroscope and the accelerometer;
the expression of the accelerometer and gyroscope on-line calibration error model is as follows:
wherein,,
represents the angular velocity measurement value, ω represents the angular velocity theoretical value, w g Representing gyro noise of the type Gaussian white noise +.>
Represents the measured acceleration value, a represents the theoretical acceleration value, w a Representing accelerometer noise of the type Gaussian white noise, b g Indicating zero bias of gyroscope, b a Indicating the accelerometer zero offset;
based on the first correction data and the second correction data, calculating zero offset of the gyroscope and the accelerometer through the accelerometer and the gyroscope on-line calibration error model, including:
calculating an average value of accelerations in the first correction data
And the average value of the angular velocity in the first correction data +.>
Since the IMU is in a rest state and gaussian white noise mathematical expectation is 0, ω=0, gyroscope noise average +.>
Accelerometer noise mean>
This gives:
wherein,,
representing the average value of zero offset of the gyroscope within a first preset duration;
calculating an average value of the angular velocity in the second correction data
Since the robot rotates on the horizontal plane, the rotation axis direction is the same as the gravity direction, and there are:
and because:
so that:
2. the method for on-line calibration and compensation of an IMU error of a wheeled robot according to claim 1, wherein said compensating the output data of said IMU by the calculated zero offset of the gyroscope and the accelerometer comprises:
based on the calculated zero offset of the gyroscope and the accelerometer and the online calibration error model of the accelerometer and the gyroscope, the output data of the IMU is compensated by using the following formula:
wherein omega 2 A, outputting data for the compensated gyroscope 2 To compensate forThe latter accelerometer outputs data.
3. The utility model provides a wheeled robot IMU error is demarcating and compensation arrangement on line which characterized in that includes:
the first correction data acquisition module is used for acquiring first correction data; the first correction data are a section of continuous data collected by the Inertial Measurement Unit (IMU) in a first preset time period when the wheeled robot provided with the IMU is in a standing state on a horizontal plane, and the first correction data comprise acceleration and angular velocity in the X, Y, Z direction;
a second correction data acquisition module configured to acquire second correction data; the second correction data is a section of continuous data collected by the IMU in the process that the wheeled robot rotates in situ for a preset angle on a horizontal plane at a preset speed within a second preset time period, and the second correction data comprises an angular speed in the X, Y, Z direction;
the calibration error model construction module is used for establishing an accelerometer and gyroscope online calibration error model;
the on-line calibration module is used for calculating zero offset of the gyroscope and the accelerometer through the on-line calibration error model of the accelerometer and the gyroscope established by the calibration error model establishment module based on the first correction data acquired by the first correction data acquisition module and the second correction data acquired by the second correction data acquisition module, so as to complete on-line calibration of the IMU error;
the compensation module is used for compensating the output data of the IMU through the zero offset of the gyroscope and the accelerometer calculated by the online calibration module;
the expression of the online calibration error model established by the calibration error model construction module is as follows:
wherein,,
represents the angular velocity measurement value, ω represents the angular velocity theoretical value, w g Representing gyro noise of the type Gaussian white noise +.>
Represents the measured acceleration value, a represents the theoretical acceleration value, w a Representing accelerometer noise of the type Gaussian white noise, b g Indicating zero bias of gyroscope, b a Indicating the accelerometer zero offset;
the on-line calibration module is specifically used for:
calculating an average value of accelerations in the first correction data
And the average value of the angular velocity in the first correction data +.>
Since the IMU is in a rest state and gaussian white noise mathematical expectation is 0, ω=0, gyroscope noise average +.>
Accelerometer noise mean>
This gives:
wherein,,
representing the average value of zero offset of the gyroscope within a first preset duration;
calculating the angle in the second correction dataAverage value of speed
Since the robot rotates on the horizontal plane, the rotation axis direction is the same as the gravity direction, and there are:
and because:
so that:
4. the on-line calibration and compensation device for the error of the IMU of the wheeled robot according to claim 3, wherein the compensation module is specifically configured to:
based on the calculated zero offset of the gyroscope and the accelerometer and the online calibration error model of the accelerometer and the gyroscope, the output data of the IMU is compensated by using the following formula:
wherein omega 2 A, outputting data for the compensated gyroscope 2 And outputting data for the compensated accelerometer.
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