CN116659481A - Outdoor robot course angle calibration method, system and medium based on RTK and odometer - Google Patents
Outdoor robot course angle calibration method, system and medium based on RTK and odometer Download PDFInfo
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Classifications
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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
- G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C1/00—Measuring angles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/40—Correcting position, velocity or attitude
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/53—Determining attitude
Abstract
The application discloses a method, a system and a medium for calibrating an outdoor robot course angle based on RTK and an odometer, wherein the method comprises the following steps: in the calibration stage, controlling the robot to rotate, and acquiring a course angle acquired by a wheel type odometer and a course angle output by RTK equipment; and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot. The application can solve the problem that the current pure RTK robot has unstable course angle in open outdoor environment.
Description
Technical Field
The application relates to the field of robot navigation, in particular to a method, a system and a medium for calibrating an outdoor robot course angle based on RTK and an odometer.
Background
RTK (Real-Time Kinematic) and IMU (Inertial Measurement Unit ) sensors are two very important parts in robot positioning and control, and are widely applied to various robot scenes, such as autonomous navigation, unmanned driving, aerospace, industrial automation and the like. RTK can realize high accuracy position location, and IMU sensor can acquire the gesture information of robot, such as angle, speed, acceleration etc. and both combine and can realize fine motion control and location.
In order to reduce the manufacturing costs of robots, some manufacturers have proposed solutions for pure RTK robots. Pure RTK robots achieve high precision positioning by GPS-based RTK technology and do not use IMU sensors. The advantages of a pure RTK robot are lower cost, simpler construction, easier maintenance and use.
However, in an open outdoor environment, the RTK signal may be affected by various interference factors, which may cause unstable quality of the RTK signal, and thus cause unstable heading angle of the pure RTK robot.
Disclosure of Invention
The application mainly aims to provide a method, a system and a medium for calibrating a course angle of an outdoor robot based on RTK and an odometer, and aims to solve the problem that the course angle of the existing pure RTK robot is unstable in an open outdoor environment.
To achieve the above object, the present application provides a heading angle calibration method for an outdoor robot based on an RTK and an odometer, the robot being configured with an apparatus using a real-time dynamic differential measurement technique RTK, the method comprising:
in the calibration stage, controlling the robot to rotate, and acquiring a course angle acquired by a wheel type odometer and a course angle output by RTK equipment;
and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
Optionally, the step of calibrating the robot course angle based on the course angle acquired by the wheel type odometer and the course angle output by the RTK device to obtain calibration parameters of the robot course angle includes:
and correcting the course angle output by the RTK equipment based on the calibration parameters of the course angle of the robot to obtain the course angle of the robot.
Optionally, in the calibration stage, the step of controlling the robot to rotate and acquiring the heading angle acquired by the wheel type odometer and the heading angle output by the RTK device includes:
and controlling the robot to point to a preset direction, rotating the robot anticlockwise according to a preset rotation angle, and recording the course angle acquired by the wheel type odometers and the course angle output by the RTK equipment.
Optionally, the step of calibrating the robot course angle based on the course angle acquired by the wheel type odometer and the course angle output by the RTK device to obtain calibration parameters of the robot course angle includes:
and fitting calibration parameters in a pre-constructed conversion formula by a linear regression algorithm based on the course angle acquired by the plurality of groups of wheel type odometers and the course angle output by the RTK equipment to obtain the calibration parameters of the robot course angle.
Optionally, the step of correcting the heading angle output by the RTK device based on the calibration parameter of the heading angle of the robot to obtain the heading angle of the robot includes:
substituting the calibration parameters of the course angle of the robot into a pre-constructed conversion formula to obtain a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer;
in the moving process of the robot, acquiring a course angle output by the RTK;
correcting the course angle output by the RTK acquired in the moving process of the robot based on a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer to obtain a corrected course angle output by RTK equipment;
and taking the heading angle output by the corrected RTK equipment as the heading angle of the robot.
Optionally, before the step of controlling the robot to point to a preset direction, rotating the robot counterclockwise according to a preset rotation angle and recording the heading angles acquired by the wheel type odometers and the heading angles output by the RTK device, the method comprises the following steps:
reading a course angle output by RTK equipment, and detecting whether the course angle output by the RTK equipment is effective;
and if the course angle output by the RTK equipment is effective, acquiring the course angle output by the RTK equipment.
Alternatively, the linear regression algorithm may be a least squares method.
The embodiment of the application also provides a robot course angle calibration device, which comprises:
the data acquisition module is used for controlling the robot to rotate in a calibration stage to acquire a course angle acquired by the wheel type odometer and a course angle output by the RTK equipment;
and the calibration module is used for calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
The embodiment of the application also provides a system which comprises a memory, a processor and a robot course angle calibration program which is stored in the memory and can run on the processor, wherein the robot course angle calibration program is executed by the processor to realize the robot course angle calibration method.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium is stored with a robot course angle calibration program, and the robot course angle calibration program realizes the robot course angle calibration method when being executed by a processor.
According to the outdoor robot course angle calibration method, system and medium based on RTK and odometer, in the calibration stage, the robot is controlled to rotate, and the course angle acquired by the wheel type odometer and the course angle output by the RTK device are acquired; and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
According to the embodiment of the application, the course angle of the robot is calibrated based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment, so that the calibration parameter of the course angle of the robot is obtained, then the course angle output by the RTK equipment is corrected based on the calibration parameter, so that the course angle of the robot is obtained, and the course angle of the robot obtained after correction is more stable and accurate. In addition, the robot in the embodiment of the application can realize high-precision positioning only by relying on RTK technology and a wheel type odometer without using an IMU sensor, so that the robot has lower cost, simpler structure and easier maintenance and use.
Drawings
FIG. 1 is a schematic diagram of functional modules of terminal equipment to which a robot course angle calibration device of the present application belongs;
FIG. 2 is a flowchart of a first embodiment of a robot heading angle calibration method according to the present application;
FIG. 3 is a schematic diagram of a calibration flow in an embodiment of a robot course angle calibration method according to the present application;
fig. 4 is a diagram of calibration results in an embodiment of the robot course angle calibration method of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The main solutions of the embodiments of the present application are: in the calibration stage, controlling the robot to rotate, and acquiring a course angle acquired by a wheel type odometer and a course angle output by RTK equipment; and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot. According to the embodiment of the application, under an open outdoor environment, the course angle of the robot is calibrated based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment, so that the calibration parameters of the course angle of the robot are obtained, then the course angle output by the RTK equipment is corrected based on the calibration parameters, so that the course angle of the robot is obtained, and the course angle of the robot obtained after correction is more stable and accurate. In addition, the robot in the embodiment of the application can realize high-precision positioning only by relying on RTK technology and a wheel type odometer without using an IMU sensor, so that the robot has lower cost, simpler structure and easier maintenance and use.
Technical terms related to the embodiment of the application:
RTK: RTK (Real-Time Kinematic) is a high-precision GNSS positioning technology. In RTK, a receiver receives two or more satellite signals simultaneously, and errors are eliminated by calculating errors in the satellite signal propagation process, thereby improving positioning accuracy.
IMU sensor: the IMU (Inertial Measurement Unit ) is a sensor for acquiring information such as the position, direction and angle of a mechanically moving object in space by measuring information such as the acceleration, angular velocity and magnetic field strength of the mechanically moving object.
Wheel type odometer: the wheel type odometer is a sensor for estimating displacement of a robot in a horizontal direction by measuring the speed and displacement of the rotation of a wheel of the robot, and further, for calculating position and posture information of the robot in the horizontal direction. The course angle of the wheel type odometer can be obtained through the wheel type odometer.
Heading angle: in the field of robots, heading angle generally refers to the angle of orientation of a robot relative to a fixed coordinate system, i.e. the angle between the axis of rotation of the robot and the horizontal plane of the coordinate system, which angle is generally the angle of rotation about the Z-axis, also referred to as the Z-axis rotation angle. The course angle of the robot can be used for describing the direction and the rotation state of the robot, and has important significance in the aspects of outdoor robot positioning, navigation, path planning, obstacle avoidance and the like.
Calibrating: in the field of robots, calibration refers to measuring and calibrating parameters of various sensors and actuators of the robot to improve positioning and control accuracy of the robot.
Specifically, referring to fig. 1, fig. 1 is a schematic diagram of functional modules of a device to which a heading angle calibration device for a robot of the present application belongs. The robot course angle calibration device can be a device which is independent of equipment and can perform data processing, and can be loaded on the equipment in a hardware or software mode. The device can be an intelligent mobile terminal with a data processing function such as a mobile phone and a tablet personal computer, and can also be a fixed device or a server with a data processing function.
In this embodiment, the apparatus to which the robot heading angle calibration device belongs at least includes an output module 110, a processor 120, a memory 130, and a communication module 140.
The memory 130 stores an operating system and a robot course angle calibration program; the output module 110 may be a display screen or the like. The communication module 140 may include a WIFI module, a bluetooth module, and the like, and communicate with an external device or a server through the communication module 140.
Wherein the robot heading angle calibration program in the memory 130 when executed by the processor performs the steps of:
in the calibration stage, controlling the robot to rotate, and acquiring a course angle acquired by a wheel type odometer and a course angle output by RTK equipment;
and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
Further, the robot heading angle calibration program in the memory 130, when executed by the processor, further performs the steps of:
and correcting the course angle output by the RTK equipment based on the calibration parameters of the course angle of the robot to obtain the course angle of the robot.
Further, the robot heading angle calibration program in the memory 130, when executed by the processor, further performs the steps of:
and controlling the robot to point to a preset direction, rotating the robot anticlockwise according to a preset rotation angle, and recording the course angle acquired by the wheel type odometers and the course angle output by the RTK equipment.
Further, the robot heading angle calibration program in the memory 130, when executed by the processor, further performs the steps of:
and fitting calibration parameters in a pre-constructed conversion formula by a linear regression algorithm based on the course angle acquired by the plurality of groups of wheel type odometers and the course angle output by the RTK equipment to obtain the calibration parameters of the robot course angle.
Further, the robot heading angle calibration program in the memory 130, when executed by the processor, further performs the steps of:
substituting the calibration parameters of the course angle of the robot into a pre-constructed conversion formula to obtain a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer;
in the moving process of the robot, acquiring a course angle output by the RTK;
correcting the course angle output by the RTK acquired in the moving process of the robot based on a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer to obtain a corrected course angle output by RTK equipment;
and taking the heading angle output by the corrected RTK equipment as the heading angle of the robot.
Further, the robot heading angle calibration program in the memory 130, when executed by the processor, further performs the steps of:
reading a course angle output by RTK equipment, and detecting whether the course angle output by the RTK equipment is effective;
and if the course angle output by the RTK equipment is effective, acquiring the course angle output by the RTK equipment.
Further, the robot heading angle calibration program in the memory 130, when executed by the processor, further performs the steps of:
the linear regression algorithm may be a least squares method.
According to the scheme, specifically, in the calibration stage, the robot is controlled to rotate, and the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment are acquired; and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot. In an open outdoor environment, the embodiment of the application calibrates the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot, then corrects the course angle output by the RTK equipment based on the calibration parameters to obtain the course angle of the robot, and the course angle of the robot obtained after correction is more stable and accurate. In addition, the robot in the embodiment of the application can realize high-precision positioning only by relying on RTK technology and a wheel type odometer without using an IMU sensor, so that the robot has lower cost, simpler structure and easier maintenance and use.
Based on the above device architecture, but not limited to the above architecture, the method embodiments of the present application are presented.
The execution body of the method of the embodiment may be a robot course angle calibration device, which may be a device independent of the apparatus and capable of performing data processing, and may be carried on the apparatus in a form of hardware or software. The apparatus may be a robot using a real-time dynamic differential measurement technique RTK. The embodiment uses a robot using a real-time dynamic differential measurement technique RTK as an example, and realizes the calibration of the course angle of the robot by using the real-time dynamic differential measurement technique RTK, so as to obtain a more stable and more accurate course angle of the robot.
Referring to fig. 2, fig. 2 is a flowchart illustrating a first embodiment of a robot heading angle calibration method according to the present application. The robot course angle calibration method comprises the following steps:
and S10, controlling the robot to rotate in a calibration stage, and acquiring a course angle acquired by the wheel type odometer and a course angle output by the RTK equipment.
In the navigation and positioning process of the robot, the course angle of the robot is an important parameter, which determines the running direction and posture of the robot. In the embodiment of the application, the course angle of the robot using the real-time dynamic differential measurement technology RTK uses the course angle output by the RTK equipment, but the course angle output by the RTK equipment can be interfered by various factors to generate errors, so that the course angle of the robot needs to be calibrated.
Specifically, when the course angle of the robot is calibrated, the robot is controlled to face a preset direction, then the robot is rotated according to a preset rotation angle, and the course angle acquired by the wheel type odometer in the rotation process of the robot and the course angle output by the RTK equipment are recorded.
After the robot is started up each time, the wheel type odometer is initialized, so that the position provided by the wheel type odometer is the relative position. The pose information of the robot can be acquired through the wheel type odometer, and the pose information comprises x and y coordinates and course angles under a self coordinate system.
The absolute position information of the robot in a world coordinate system is output to the robot through a serial port of the RTK equipment, wherein the absolute position information comprises x, y coordinates and course angles under the world coordinate system.
The course angle acquired by the wheel type odometer and the course angle output by the RTK equipment are both 0-360 degrees, so that certain conversion can be carried out between the two.
And step S20, calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
The method comprises the steps of constructing a conversion formula of a course angle acquired by a wheel type odometer and a course angle output by RTK equipment in advance.
The parameters of the conversion formula are unknown, and the parameters of the conversion formula are calibration parameters of the course angle of the robot.
And then, fitting parameters in a pre-constructed conversion formula based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
And step S30, correcting the course angle output by the RTK equipment based on the calibration parameters of the course angle of the robot to obtain the course angle of the robot.
Substituting calibration parameters of the course angle of the robot into a pre-constructed conversion formula to obtain a course angle acquired by a wheel type odometer with known parameter values and a course angle conversion formula output by RTK equipment.
After the calibration process is finished, continuously reading a course angle output by the RTK equipment in the motion process of the robot;
after the course angle output by the RTK equipment is read each time, correcting the course angle output by the RTK equipment by using a conversion formula of the course angle acquired by a wheel type odometer with known parameter values and the course angle output by the RTK equipment to obtain the course angle of the robot.
According to the scheme, the robot is controlled to rotate in the calibration stage, so that the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment are acquired; and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot. And correcting the course angle output by the RTK equipment based on the calibration parameters of the course angle of the robot to obtain the course angle of the robot. In an open outdoor environment, the embodiment of the application calibrates the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot, then corrects the course angle output by the RTK equipment based on the calibration parameters to obtain the course angle of the robot, and the course angle of the robot obtained after correction is more stable and accurate. In addition, the robot in the embodiment of the application can realize high-precision positioning only by relying on RTK technology and a wheel type odometer without using an IMU sensor, so that the robot has lower cost, simpler structure and easier maintenance and use.
Further, the present embodiment refines the above steps S10, S20 and S30 based on the embodiment shown in fig. 2.
In this embodiment, in the step S10, in the calibration stage, controlling the robot to rotate, the obtaining the heading angle collected by the wheel type odometer and the heading angle output by the RTK device may include:
and S11, controlling the robot to point to a preset direction, rotating the robot anticlockwise according to a preset rotation angle, and recording the course angles acquired by the wheel type odometers and the course angles output by the RTK equipment.
Specifically, as an implementation mode, the robot is controlled to face in the forward direction, the robot is rotated anticlockwise by one circle by taking a right hand coordinate system as a reference, and the course angles acquired by a plurality of groups of wheel type odometers and the course angles output by the RTK equipment in the rotation process of the robot are recorded.
The robot is controlled to face the forward direction, so that the x axis and the y axis of the robot on the coordinate system of the robot can be kept consistent with the x axis and the y axis of the world coordinate system, and the robot can conveniently calculate during positioning and navigation.
The right-hand coordinate system is a common coordinate system standard. The positive directions of the x-axis, y-axis and z-axis in the right-hand coordinate system are specified as follows: the right hand is placed at the original point, so that the thumb, the index finger and the middle finger are mutually right-angled, and when the thumb points to the positive direction of the x axis and the index finger points to the positive direction of the y axis, the direction pointed by the middle finger is the positive direction of the z axis. In calibrating the heading angle of a robot, an x-axis is generally defined as a robot forward direction, a y-axis is defined as a robot right direction, and a z-axis is defined as a direction perpendicular to the ground upward.
The robot rotates in the anticlockwise direction, so that the calibration flow can be unified, the calibration modes of all schemes are consistent, and the comparison and reproduction of the schemes are convenient.
In one specific implementation manner, the validity of the course angle output by the RTK device can be detected before the course angles acquired by the wheel type odometers and the course angle output by the RTK device are recorded.
The method comprises the steps of reading a course angle output by RTK equipment, and detecting whether the course angle output by the RTK equipment is effective;
specifically, detecting whether the heading angle output by the RTK apparatus is valid may, but is not limited to, take the following ways: checking whether the course angle output by the RTK device is within the normal range of 0-360 degrees, using other conventional navigation devices, observing whether the course angle is consistent with the course angle output by the RTK device, and the like.
And if the course angle output by the RTK equipment is effective, acquiring the course angle output by the RTK equipment.
Then, the effective course angle output by the RTK equipment is used as input data of a robot calibration stage.
And if the course angle output by the RTK equipment is invalid, continuing to read the course angle output by the RTK equipment.
And then, continuing to read the course angle output by the RTK device until the read course angle output by the RTK device is valid.
In this embodiment, step S20, calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK device, where obtaining calibration parameters of the course angle of the robot may include:
and S21, fitting calibration parameters in a pre-constructed conversion formula through a linear regression algorithm based on the course angles acquired by the wheel type odometers and the course angles output by the RTK equipment to obtain the calibration parameters of the course angle of the robot.
Wherein, the course angle collected by the wheel type odometer is made to beThe course angle output by the RTK device is +.>The calibration parameters are a and b, and a conversion formula which can be constructed is shown as (1):
（1）
a linear regression algorithm is a statistical method for analyzing the relationship between two or more variables, such as analyzing the relationship between a set of independent variables and a dependent variable. In the calibration of the course angle of the robot, the course angle acquired by the wheel type odometer and the course angle output by the RTK device can be used as independent variables, and the calibration parameters a and b can be used as the dependent variables for fitting.
The goal of the linear regression algorithm is to find a best fit line that best describes the linear relationship between the two variables.
The linear regression algorithm can be a least square method, a ridge regression algorithm, a guy cable regression algorithm, an elastic network regression algorithm and the like, and different linear regression algorithms can be flexibly selected according to actual conditions.
In this embodiment, the linear regression algorithm is a least square method.
Wherein. The least square method is a method of achieving parameter fitting by minimizing the sum of squares of errors between measurement data and fitting results. During the calibration parameter fitting process, we need to find an optimal set of calibration parameters to minimize the sum of squares error between the calculated values and the measured data. The core idea of the least square method is to continuously optimize the calculation result by adjusting the calibration parameters until the best fitting effect is achieved.
Specifically, a two-dimensional rectangular coordinate system is established by taking a course angle acquired by a wheel type odometer as a y-axis and taking a course angle output by RTK equipment as an x-axis.
Then, the course angle acquired by the wheel type odometers and the course angle output by the RTK equipment are used as a plurality of data points (yaw r1 , yaw w1 ), (yaw r2 , yaw w2 ), ...(yaw rn , yaw wn ) From these data points, a straight line can be foundSo that the sum of the distances of all data points from this line is minimized. Through the calculation of the least square method, a linear formula with the smallest sum of the distances can be obtained, namely the value a of a and b can be fitted 1 , b 1 。
In this embodiment, the step S30, based on the calibration parameters of the robot course angle, corrects the course angle output by the RTK apparatus, where obtaining the robot course angle may include:
and S31, substituting the calibration parameters of the course angle of the robot into a pre-constructed conversion formula to obtain a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer.
Wherein the known calibration parameter a obtained by fitting 1 , b 1 Substituting a pre-built conversion formulaIn (3) obtaining yaw w =a 1 ×yaw r +b 1 。
Step S32, acquiring a heading angle output by the RTK in the movement process of the robot.
Wherein, the course angle of RTK output obtained in the robot movement process is made to be yaw rr1 ,yaw rr2 ,yaw rr3 , ... yaw rrn 。
And step S33, correcting the course angle output by the RTK acquired in the robot movement process based on the conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer, and obtaining the corrected course angle output by the RTK equipment.
Wherein, a conversion formula yaw of a course angle output by RTK based on known calibration parameters and a course angle acquired by a wheel type odometer w =a 1 ×yaw r +b 1 Course angle yaw for RTK output acquired during robot motion rr1 ,yaw rr2 ,yaw rr3 , ... yaw rrn Correcting to obtain a heading angle yaw output by the corrected RTK equipment ww1 ,yaw ww2 ,yaw ww3 , ... yaw wwn 。
And step S34, taking the course angle output by the corrected RTK equipment as the course angle of the robot.
Wherein, the corrected heading angle yaw output by the RTK device ww1 ,yaw ww2 ,yaw ww3 , ... yaw wwn As the robot heading angle.
Referring to fig. 3, fig. 3 is a schematic diagram of a calibration flow in an embodiment of a robot course angle calibration method according to the present application.
The process for obtaining the conversion formula of the heading angle output by the RTK and the heading angle acquired by the wheel type odometer comprises the following steps:
in step S1000, it is detected whether the read RTK data is valid.
If the read RTK data are invalid, the course angle output by the RTK device is continuously read until the course angle output by the RTK device is valid.
Step S1001, the robot is oriented in the forward direction.
In step S1002, the robot is rotated counterclockwise by one turn according to the right-hand coordinate system.
Step S1003, collecting a heading angle of the robot wheel type odometer.
Step S1004, collecting a course angle output by the RTK equipment.
Step S1005, calculating parameters in a conversion formula of the course angle acquired by the wheel type odometer and the course angle output by the RTK device by using a least square method.
Step S1006, the calibration procedure is exited.
Step S1007, substituting the calculated parameter into the conversion formula.
Referring to fig. 4, fig. 4 is a diagram of calibration results in an embodiment of a robot heading angle calibration method according to the present application.
Wherein the abscissa represents time (frame), the ordinate represents angle of course angle, the thick and light black solid line represents RTK course angle before calibration, the thin and dark black solid line represents RTK course angle after calibration, and the thick and dark black dotted line represents course angle of robot.
The dotted line representing the course angle of the robot coincides with the solid line representing the RTK course angle after calibration, and the calibration result is proved to be correct.
According to the scheme, the robot is controlled to rotate in the calibration stage, so that the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment are acquired; and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot. And correcting the course angle output by the RTK equipment based on the calibration parameters of the course angle of the robot to obtain the course angle of the robot. The method comprises the steps of reading a course angle output by RTK equipment, and detecting whether the course angle output by the RTK equipment is effective; and if the course angle output by the RTK equipment is effective, acquiring the course angle output by the RTK equipment. And then, controlling the robot to point to a preset direction, rotating the robot anticlockwise according to a preset rotation angle, and recording the course angles acquired by the wheel type odometers and the course angles output by the RTK equipment. And then, fitting calibration parameters in a pre-constructed conversion formula through a linear regression algorithm based on the course angle acquired by the wheel type odometers and the course angle output by the RTK equipment to obtain the calibration parameters of the robot course angle. Wherein the linear regression algorithm may be a least squares method. Then substituting the calibration parameters of the course angle of the robot into a conversion formula constructed in advance to obtain a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer; in the moving process of the robot, acquiring a course angle output by the RTK; correcting the course angle output by the RTK acquired in the moving process of the robot based on a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer to obtain a corrected course angle output by RTK equipment; and taking the heading angle output by the corrected RTK equipment as the heading angle of the robot.
In an open outdoor environment, the embodiment of the application calibrates the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot, then corrects the course angle output by the RTK equipment based on the calibration parameters to obtain the course angle of the robot, and the course angle of the robot obtained after correction is more stable and accurate. In addition, the robot in the embodiment of the application can realize high-precision positioning only by relying on RTK technology and a wheel type odometer without using an IMU sensor, so that the robot has lower cost, simpler structure and easier maintenance and use. Before fitting the calibration parameters, validity detection is performed on the course angle output by the RTK device, so that the course angle output by the RTK device can be ensured to be valid, and the calibration parameters obtained by calculating the course angle output by the RTK device can be ensured to be reliable. And then, the calibration parameters are fitted through a linear regression algorithm, so that uncertainty of debugging the calibration parameters based on experience can be reduced to a certain extent, and the stability and reliability of calibration are improved. When the linear regression algorithm is used for carrying out calibration parameter fitting, the least square method is specifically adopted for carrying out calibration parameter fitting, so that the calculated amount during fitting is small, the accuracy of the obtained result is relatively high, and the operation is relatively simple.
In addition, the embodiment of the application also provides a robot course angle calibration device, which comprises:
the data acquisition module is used for controlling the robot to rotate in a calibration stage to acquire a course angle acquired by the wheel type odometer and a course angle output by the RTK equipment;
and the calibration module is used for calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
The principle and implementation process of calibrating the course angle of the robot are realized in this embodiment, please refer to the above embodiments, and are not described herein.
In addition, the embodiment of the application also provides a system which comprises a memory, a processor and a robot course angle calibration program stored in the memory and capable of running on the processor, wherein the robot course angle calibration program realizes the steps of the robot course angle calibration method when being executed by the processor.
Because all the technical schemes of all the embodiments are adopted when the course angle calibration program of the robot is executed by the processor, the course angle calibration program at least has all the beneficial effects brought by all the technical schemes of all the embodiments and is not described in detail herein.
In addition, the embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium is stored with a robot course angle calibration program, and the robot course angle calibration program realizes the steps of the robot course angle calibration method when being executed by a processor.
Because all the technical schemes of all the embodiments are adopted when the course angle calibration program of the robot is executed by the processor, the course angle calibration program at least has all the beneficial effects brought by all the technical schemes of all the embodiments and is not described in detail herein.
According to the scheme, the robot is controlled to rotate in the calibration stage, so that the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment are acquired; and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot. And correcting the course angle output by the RTK equipment based on the calibration parameters of the course angle of the robot to obtain the course angle of the robot. In an open outdoor environment, the embodiment of the application calibrates the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot, then corrects the course angle output by the RTK equipment based on the calibration parameters to obtain the course angle of the robot, and the course angle of the robot obtained after correction is more stable and accurate. In addition, the robot in the embodiment of the application can realize high-precision positioning only by relying on RTK technology and a wheel type odometer without using an IMU sensor, so that the robot has lower cost, simpler structure and easier maintenance and use.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or method 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 method. 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 method that comprises the element.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, a controlled terminal, or a network device, etc.) to perform the method of each embodiment of the present application.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the application, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. An outdoor robot heading angle calibration method based on an RTK and an odometer, wherein the robot is configured with equipment using a real-time dynamic differential measurement technique RTK, the method comprising the steps of:
in the calibration stage, controlling the robot to rotate, and acquiring a course angle acquired by a wheel type odometer and a course angle output by RTK equipment;
and calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
2. The method according to claim 1, wherein the step of calibrating the robot heading angle based on the heading angle acquired by the wheel type odometer and the heading angle output by the RTK device to obtain the calibration parameter of the robot heading angle comprises:
and correcting the course angle output by the RTK equipment based on the calibration parameters of the course angle of the robot to obtain the course angle of the robot.
3. The method of claim 1, wherein the step of controlling the robot to rotate during the calibration phase to obtain the heading angle collected by the wheel odometer and the heading angle output by the RTK device comprises:
and controlling the robot to point to a preset direction, rotating the robot anticlockwise according to a preset rotation angle, and recording the course angle acquired by the wheel type odometers and the course angle output by the RTK equipment.
4. The method of claim 3, wherein the step of calibrating the robot heading angle based on the heading angle acquired by the wheel odometer and the heading angle output by the RTK device to obtain calibration parameters of the robot heading angle comprises:
and fitting calibration parameters in a pre-constructed conversion formula by a linear regression algorithm based on the course angle acquired by the plurality of groups of wheel type odometers and the course angle output by the RTK equipment to obtain the calibration parameters of the robot course angle.
5. The method of claim 2, wherein the step of correcting the heading angle output by the RTK apparatus based on the calibration parameter of the heading angle of the robot to obtain the heading angle of the robot comprises:
substituting the calibration parameters of the course angle of the robot into a pre-constructed conversion formula to obtain a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer;
in the moving process of the robot, acquiring a course angle output by the RTK;
correcting the course angle output by the RTK acquired in the moving process of the robot based on a conversion formula of the course angle output by the RTK and the course angle acquired by the wheel type odometer to obtain a corrected course angle output by RTK equipment;
and taking the heading angle output by the corrected RTK equipment as the heading angle of the robot.
6. The method of claim 3, wherein the step of controlling the robot to point in a predetermined direction, rotating the robot counterclockwise according to a predetermined rotation angle, and recording the heading angles collected by the plurality of sets of wheel odometers and the heading angle output by the RTK apparatus comprises, before:
reading a course angle output by RTK equipment, and detecting whether the course angle output by the RTK equipment is effective;
and if the course angle output by the RTK equipment is effective, acquiring the course angle output by the RTK equipment.
7. The method of claim 4, wherein the linear regression algorithm is a least squares method.
8. A robot heading angle calibration device, the device comprising:
the data acquisition module is used for controlling the robot to rotate in a calibration stage to acquire a course angle acquired by the wheel type odometer and a course angle output by the RTK equipment;
and the calibration module is used for calibrating the course angle of the robot based on the course angle acquired by the wheel type odometer and the course angle output by the RTK equipment to obtain calibration parameters of the course angle of the robot.
9. A robot heading angle calibration system, characterized in that the robot heading angle calibration system comprises a memory, a processor and a computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, implements the robot heading angle calibration method according to any one of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the robot heading angle calibration method according to any of claims 1-7.
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