CN112945266B - Laser navigation robot and odometer calibration method thereof - Google Patents
Laser navigation robot and odometer calibration method thereof Download PDFInfo
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Abstract
The application discloses a laser navigation robot and an odometer calibration method of the robot, wherein the odometer and a laser radar detect the movement of the robot from a first position to a second position at the same time, and odometer data and laser radar data are respectively obtained; constructing residual errors according to the position relation information of the odometer and the laser radar and the data of the odometer and the data of the laser radar, and solving to obtain the minimum solution of the parameters of the odometer; and calibrating the initial value of the parameter of the odometer by using the minimum solution, thereby solving the problem that the calibration accuracy of the odometer is reduced due to wheel abrasion or mechanical structure transformation of the odometer.
Description
Technical Field
The application relates to the technical field of laser navigation systems, in particular to a laser navigation robot and an odometer calibration method of the laser navigation robot.
Background
Existing laser navigation schemes on robots all involve the application of wheel odometers. Typically, the calibration of the odometer is done at the factory. However, with time, the calibration accuracy of the odometer may be lowered due to wear of the wheels, change of mechanical structure, etc. When the accuracy of the odometer is reduced to a certain extent, the effect of laser navigation may be seriously affected.
Content of the application
Therefore, it is necessary to provide a laser navigation robot and a calibration method of an odometer of the laser navigation robot, so as to solve the technical problem that the laser navigation is affected due to the reduction of the calibration precision of the odometer caused by the abrasion of wheels of the odometer or the change of a mechanical structure.
To achieve the above object, the present application provides a laser odometer calibration method of a robot for laser navigation, the odometer for counting movement of a traveling wheel, the robot further comprising a horizontal scanning laser radar for detecting a moving position of the robot, the method comprising:
The odometer and the laser radar detect the movement of the robot from the first position to the second position at the same time, and odometer data and laser radar data are obtained respectively;
constructing residual errors according to the position relation information of the odometer and the laser radar and the data of the odometer and the data of the laser radar, and solving to obtain the minimum solution of the parameters of the odometer;
and calibrating the initial value of the odometer parameter with the minimum solution.
In some embodiments, the method further comprises:
Establishing an odometer coordinate system, and establishing a laser radar coordinate system, wherein the odometer parameters comprise traveling wheel parameters, rotation of an X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and coordinates of an origin O of the laser radar coordinate system under the odometer coordinate system;
the step of simultaneously detecting the movement of the robot from the first position to the second position by the odometer and the laser radar to respectively obtain odometer data and laser radar data, and the step of constructing residual errors according to the position relation information of the odometer and the laser radar and the odometer data and the laser radar data and solving to obtain the minimum solution of the odometer parameters specifically comprises the following steps:
controlling the robot to move from a first position to a second position, calculating the relative pose of the two positions through laser radar splicing, and converting the relative pose into an odometer coordinate system according to the position relation information to obtain a first estimated value; while the odometer detects a second estimate of the relative position of the computing robot moving from the first position to the second position; calculating the first and second estimates and their differences;
The robot moves for multiple times to generate multiple groups of first positions and second positions, and multiple groups of first estimated values, second estimated values and difference values of the first estimated values and the second estimated values are obtained through calculation;
and combining and solving the plurality of differences to obtain a group of solutions which minimize the optimization objective.
In some embodiments, after the step of combining the plurality of differences to obtain a set of solutions that minimize the optimization objective, the method further comprises:
and comparing the initial value of the odometer parameter with the minimum solution, and if the comparison result is in a preset range, calibrating the traveling wheel parameter of the laser odometer, the rotation of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system by using the minimum solution.
In some embodiments, the establishing the odometer coordinate system specifically includes:
the origin of the odometer coordinate system is the position o of the center of the two wheels, and the positive direction of the x axis is the direction in which the vertical line perpendicular to the connecting line between the two wheels points to the forward rolling of the wheels; the y-axis direction is the direction of the connecting line of the two-wheel straight line, the y-axis positive direction is the direction that the x-axis direction rotates 90 degrees anticlockwise around the origin o, the z-axis direction is vertical to the ground, and the z-axis positive direction is the direction vertical to the ground upwards;
the establishing a laser radar coordinate system specifically comprises the following steps:
The origin of the laser radar coordinate system is the origin O measured by a laser of the laser radar, the positive direction of the Z axis coincides with the positive direction of the Z axis of the odometer coordinate system, the positive direction of the X axis of the laser radar coordinate system is the positive direction of the laser, the positive direction of the Y axis is deduced through a right hand rule, the direction of the thumb of the right hand is the positive direction of the X axis of the laser radar coordinate system, and the directions pointed by the four fingers of the right hand are the positive direction of the Y axis.
In some embodiments of the present invention, in some embodiments,
The travelling wheels comprise left wheels and right wheels, the travelling wheel parameters comprise a left wheel radius, a right wheel radius and a wheel base between the two wheels, the initial value alpha=1 of the left wheel radius is defined, the initial value beta=1 of the right wheel radius is defined, and the wheel base gamma=1 between the two wheels; the rotation angle theta of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinates (X, y) of the origin O of the laser radar coordinate system in the odometer coordinate system are obtained according to the installation data of the laser radar; the optimization function used to solve the minimum solution is:
where N is the total number of observations and C is the covariance matrix of the laser splice.
In some embodiments of the present invention, in some embodiments,
The optimization function is solved using gauss newton's method or linear approximation.
In some embodiments of the present invention, in some embodiments,
The method further comprises the steps of:
a difference k i is calculated for each set of first and second estimates:
And deleting the data which are far from the distribution center point by a preset proportion according to the distribution of k i so as to ensure the data consistency.
In some embodiments of the present invention, in some embodiments,
The minimum solution calibrates a left wheel radius, a right wheel radius, an wheelbase between two wheels of the laser odometer, a rotation of an X-axis of a laser radar coordinate system relative to the X-axis of the odometer coordinate system, and a coordinate of an origin O of the laser radar coordinate system under the odometer coordinate system, the method further comprising:
And screening the minimum solution by a preset inspection standard to calibrate the radius of the left wheel, the radius of the right wheel, the wheel distance between the two wheels of the laser odometer, the rotation of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system, so as to ensure that the distance between the laser points of the laser radar is within a high-precision area of the laser radar.
In some embodiments of the present invention, in some embodiments,
The method further comprises the steps of:
Calculating a first rotation parameter of a double wheel of the odometer using inertial measurement unit integration; simultaneously calculating a second rotation parameter of the odometer in the same time; and comparing the first rotation parameter with the second rotation parameter, and deleting the odometer data and the laser radar data in the corresponding time period if the first rotation parameter and the second rotation parameter are inconsistent.
In order to achieve the above purpose, the application also provides a processor, a laser odometer and a horizontal scanning laser radar, which are arranged on the robot, wherein the processor is used for executing the laser odometer calibration method of the robot.
In some embodiments, an inertial measurement unit is mounted on the robot, and a first rotation parameter of the two wheels of the odometer is calculated using the inertial measurement unit integral; simultaneously calculating a second rotation parameter of the odometer in unit time in the same time; and comparing the first rotation parameter with the second rotation parameter, and deleting the odometer data and the laser radar data in the corresponding time period if the first rotation parameter and the second rotation parameter are inconsistent.
To achieve the above object, the present application also proposes a computer-readable storage medium having stored thereon a screen display program which, when executed by the processor, implements the steps of the laser odometer calibration method of a robot as described above.
According to the laser navigation robot and the odometer calibration method of the laser navigation robot, provided by the embodiment of the application, the odometer and the laser radar detect the movement of the robot from the first position to the second position at the same time, and odometer data and laser radar data are respectively obtained; constructing residual errors according to the position relation information of the odometer and the laser radar and the data of the odometer and the data of the laser radar, and solving to obtain the minimum solution of the parameters of the odometer; and calibrating the initial value of the parameter of the odometer by using the minimum solution, thereby solving the problem that the calibration accuracy of the odometer is reduced due to wheel abrasion or mechanical structure transformation of the odometer.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic view of a robot configuration according to an embodiment of the present application;
FIG. 2 is a flow chart of a laser odometer calibration method for a robot in accordance with an embodiment of the application;
FIG. 3 is a flow chart of a laser odometer calibration method for a robot in accordance with another embodiment of the application;
FIG. 4 is a flow chart of a laser odometer calibration method for a robot in accordance with yet another embodiment of the application;
FIG. 5 is a schematic view of an odometer coordinate system of a laser odometer calibration method for a robot according to an embodiment of the application;
FIG. 6 is a schematic view of a laser radar coordinate system of a laser odometer calibration method for a robot according to an embodiment of the application;
fig. 7 is a block diagram of a laser navigation robot according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that all directional indicators (such as up, down, left, right, front, and rear … …) in the embodiments of the present application are merely used to explain the relative positional relationship, movement, etc. between the components in a particular posture (as shown in the drawings), and if the particular posture is changed, the directional indicator is changed accordingly.
Furthermore, the description of "first," "second," etc. in this disclosure is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present application.
In the present application, unless specifically stated and limited otherwise, the terms "connected," "affixed," and the like are to be construed broadly, and for example, "affixed" may be a fixed connection, a removable connection, or an integral body; can be mechanically or electrically connected; either directly or indirectly, through intermediaries, or both, may be in communication with each other or in interaction with each other, unless expressly defined otherwise. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art according to the specific circumstances.
The method is applicable to most existing laser navigation systems as long as they have the following components: the automatic navigation system comprises (1) an odometer 1005 and a double-wheel differential motor with the odometer, (2) a single-line laser radar 1004 for horizontal scanning, and (3) an SLAM robot (SLAM (simultaneous localization AND MAPPING) for real-time positioning and map construction) which can estimate the pose of the user in a scene in real time, so that the automatic navigation can be realized. The scene may be indoor or outdoor, as illustrated in fig. 1 as an example of a robot. The robot 100 further includes an inertial measurement unit 1006 thereon.
Example 1
According to the laser odometer calibration method for the robot, the robot is used for laser navigation, and the odometer is used for counting the movement of the travelling wheel. As shown in fig. 1, if the robot is two-wheeled, a two-wheeled differential motor is provided. In fact, the embodiment of the application can calibrate not only a two-wheel odometer, but also other types of wheels, such as a single-wheel odometer (outputting rotation quantity and translation quantity), so long as the odometer can deduce a pose transformation. In the embodiments described below, the road wheel parameters include the left wheel radius, the right wheel radius, and the wheelbase between the wheels, but other types of odometers may be other parameters, as well as calibration, without limitation of the application.
The robot further comprises a horizontal scanning lidar for detecting a movement position of the robot, the method comprising:
optionally, in some embodiments, the odometer coordinate system and the lidar coordinate system are established in advance.
As shown in fig. 2, the method includes:
step 1, the odometer and the laser radar detect the movement of the robot from a first position to a second position at the same time, and odometer data and laser radar data are respectively obtained;
Specifically, the first position may be defined as an initial position of the robot, and the second position is defined as a target position of the robot.
Step 2, constructing residual errors according to the position relation information of the odometer and the laser radar and the data of the odometer and the data of the laser radar, and solving to obtain the minimum solution of the parameters of the odometer;
And 3, calibrating the initial value of the odometer parameter by the minimum solution.
Further, as shown in fig. 3 and 4, the method further includes:
Step 4, establishing an odometer coordinate system, and establishing a laser radar coordinate system, wherein the odometer parameters comprise traveling wheel parameters, rotation of an X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and coordinates of an origin O of the laser radar coordinate system under the odometer coordinate system;
The step 2 and the step3 specifically comprise:
Step 20, controlling the robot to move from a first position to a second position, calculating the relative pose of the two positions through horizontal scanning laser radar splicing, and converting the relative pose into an odometer coordinate system according to the position relation information to obtain a first estimated value; while the odometer detects a second estimate of the relative position of the computing robot moving from the first position to the second position; calculating the first and second estimates and their differences;
The relative pose of the first position and the second position calculated by laser radar splicing can be obtained by using the existing calculation method.
Specifically, the information of the positional relationship between the laser radar and the robot can be obtained according to an installation drawing of the laser navigation system. The mounting position of the lidar on the robot is illustrated in fig. 1.
The odometer detects movement of the computing robot from the first position to the second position, requiring various parameter settings in conjunction with the odometer's two-wheel differential motor.
Further, the method further comprises:
Step 5, the robot moves for many times to generate a plurality of groups of first positions and second positions, and a plurality of groups of first estimated values, second estimated values and difference values of the first estimated values and the second estimated values are obtained through calculation;
specifically, the first estimate may also be referred to as a first calculated estimate, and the second estimate may also be referred to as a second calculated estimate.
Step 6, combining and solving a plurality of difference values to obtain a group of solutions which minimize the optimization objective;
After the minimum solution is calculated, the travelling wheel parameters of the laser odometer, the rotation of the laser radar coordinate system X axis relative to the odometer coordinate system X axis and the coordinates of the origin O of the laser radar coordinate system in the odometer coordinate system are calibrated by the minimum solution.
Specifically, establishing the odometer coordinate system specifically includes: the origin of the odometer coordinate system is the position o of the center of the two wheels, and the positive direction of the x axis is the direction in which the vertical line perpendicular to the connecting line between the two wheels points to the forward rolling of the wheels; the y-axis direction is the direction of the connecting line of the two-wheel straight line, the y-axis positive direction is the direction that the x-axis direction rotates 90 degrees anticlockwise around the origin o, the z-axis direction is vertical to the ground, and the z-axis positive direction is the direction vertical to the ground upwards;
Specifically, establishing a lidar coordinate system specifically includes: the origin of the laser radar coordinate system is the origin O measured by a laser of the laser radar, the positive direction of the Z axis coincides with the positive direction of the Z axis of the odometer coordinate system, the positive direction of the X axis of the laser radar coordinate system is the positive direction of the laser, the positive direction of the Y axis is deduced through a right hand rule, the direction of the thumb of the right hand is the positive direction of the X axis of the laser radar coordinate system, and the directions pointed by the four fingers of the right hand are the positive direction of the Y axis.
The odometer coordinate system is shown in fig. 5, and the laser radar coordinate system is shown in fig. 6.
According to the method for calibrating the odometer of the robot, provided by the embodiment of the application, the second estimated value is obtained through detection and calculation of the movement of the robot by the laser odometer, the splicing calculation of the movement of the robot from the first position to the second position by means of the horizontal scanning laser radar is converted into the odometer coordinate system to obtain the first estimated value, the two calculated estimated values are obtained through one-time movement of the robot, a plurality of groups of first estimated values, second estimated values and difference values thereof are calculated through optimization, and the solution for minimizing the optimization target is obtained through combination and solution, and the minimum solution comprises the odometer parameters; and calibrating the traveling wheel parameters, the rotation of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinates of the origin O of the laser radar coordinate system under the odometer coordinate system by the minimum solution, and solving the problem that the calibration precision of the odometer is reduced due to the wheel abrasion or mechanical structure transformation of the odometer as well as the rotation of the X axis of the odometer coordinate system and the coordinates of the origin O of the laser radar coordinate system under the odometer coordinate system due to the recalibration/calibration of the odometer parameters.
Further, after the step of combining the plurality of differences to obtain a set of solutions that minimize the optimization objective, the method further comprises:
and step 31, comparing the initial value of the odometer parameter with the minimum solution, and if the comparison result is within a preset range, calibrating the travelling wheel parameter of the laser odometer, the rotation of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system by using the minimum solution.
That is, the odometer parameter is not calibrated by directly comparing the minimum solution with the radius of the left wheel, the radius of the right wheel, the wheel base between the two wheels, the rotation of the X-axis of the laser radar coordinate system relative to the X-axis of the odometer coordinate system and the initial value of the coordinates of the origin O of the laser radar coordinate system in the odometer coordinate system, and the comparison result is calibrated by using the minimum solution within the preset range.
The preset range comprises:
the radius of the left wheel in the smallest solution is 0.9-1.1 times of the initial value alpha of the radius of the left wheel;
The right wheel radius in the minimum solution is 0.9-1.1 times of the right wheel radius initial value beta;
The wheelbase between two wheels in the minimum solution is 0.9-1.1 times of the initial value gamma of the wheelbase between two wheels;
The rotation angle of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system in the minimum solution is 10 degrees up and down of an initial value theta of the rotation angle of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system;
The coordinates of the origin O of the laser radar coordinate system in the minimum solution under the odometer coordinate system are 5 cm above and below x and 5 cm above and below y in the initial value (x, y) of the coordinates of the origin O of the laser radar coordinate system under the odometer coordinate system.
The odometer includes the following three parameters: (1) left wheel radius alpha x l, (2) right wheel radius beta x r, (3) wheel base between two wheels gamma x d. The three parameters of l, r and d are determined by a physical model. However, each parameter is not accurate due to wear and the like, and alpha, beta, gamma are used to describe such errors in embodiments of the present application.
The initial value of the left wheel radius of the odometer is alpha=1, the initial value of the right wheel radius is beta=1, and the wheelbase gamma=1 between two wheels; the rotation angle theta of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinates (X, y) of the origin O of the laser radar coordinate system in the odometer coordinate system are obtained according to the installation data of the laser radar;
namely, the odometer parameters to be calibrated (calibrated) by the method are:
(1)α；
(2)β；
(3)γ；
(4) Rotation θ of the laser radar coordinate system X-axis relative to the odometer coordinate system X-axis (Z/Z-axis coincides so there is only 1 dimension of rotation);
(5) The laser radar coordinate system origin O coincides with x and y (Z/Z axis so there is only x, y) in the odometer coordinate system.
Wherein, define the initial value of the mileometer parameter as:
α＝1；
β＝1；
γ＝1；
θ=derived from the installation drawing (installation data of the lidar);
x: obtaining an initial value from an installation drawing;
y: deriving from an installation drawing;
the embodiment of the application constructs a residual error containing the parameters, and then uses an optimization algorithm to solve each corresponding physical quantity when the residual error is minimum.
Constructing residual errors: when the robot moves from a first position (Pi) to a second position (Pi +1), the relative pose of the two positions can be calculated by splicing the laser radars, and can be converted into the odometer coordinate by the parameters (4) and (5)Meanwhile, the odometer can also directly estimate the relative position of the two positionsThus we have two different estimates for the same physical quantity, and the residual may be defined as the difference between these two physical quantities.
Wherein N is the total observation times, and C is the covariance matrix of laser splicing; in practice, a set of solutions that minimize the optimization objective is sought by combining multiple measurements. Since the initial values are generally accurate, the optimization function can be solved by a general optimization algorithm such as gauss-newton method, and the like, and can also be solved by a linear approximation method.
In some embodiments, in consideration of actual operation, the laser odometer calibration method of the robot of the embodiment of the present invention needs to consider numerous practical problems, and the following provides a corresponding solution to the problems that may be encountered:
Problem (1) odometer slip problem: in a real world scenario, for some ground and wheel combinations, the wheels may slip. In the mathematical model, the slipping causes an outlier which is fatal to the least squares construction, so that accurate data for slipping is needed. We propose to add an IMU (inertial measurement unit) to solve this problem. The rotation calculated by the odometry during the unit time and the rotation integrated by the IMU during the same time are not consistent due to wheel slip, and the odometry data and lidar data during this time period should not be added to the optimization.
The method further comprises the steps of:
Calculating a first rotation parameter of a double wheel of the odometer using inertial measurement unit integration; simultaneously calculating a second rotation parameter of the odometer in the same time; and comparing the first rotation parameter with the second rotation parameter, and deleting the odometer data detected in the time if the first rotation parameter and the second rotation parameter are inconsistent.
The odometer calculates the rotation by means of parameter settings of the odometer.
Problem (2) inaccurate laser splicing and wrong splicing problem. C is used as a covariance matrix to reflect the quality degree of laser splicing, and data with better laser splicing is selected in data screening. But the covariance matrix C does not reflect erroneous splices. That is, the wrong splice may also have a better covariance matrix C. In order to solve the problem (2), it is proposed that:
the method further comprises the steps of:
a difference k i is calculated for each set of first and second estimates:
The distribution of k i is then calculated and then a proportion (e.g. 15% -30%, in particular 20% or 25%) of the data which is far from the centre point of the distribution is removed. This approach effectively guarantees substantial consistency of the data, thus addressing laser splice errors.
Problem (3) measurement error of laser: lasers on the market have relatively large errors at certain distances. For example, the error of the laser radar based on the TOF principle is relatively large within 10 cm, and the error of the laser radar of the small triangular ranging is large outside 10 m. The magnitude of these errors will not be reflected into the C matrix, so an additional check of the recorded calibration data is required to ensure that the distance of the laser points inside is within the high-precision region of the laser radar.
To solve this problem, the method further comprises:
the minimum solution calibrates a left wheel radius, a right wheel radius, an wheelbase between two wheels of the laser odometer, a rotation of an X-axis of a laser radar coordinate system relative to the X-axis of the odometer coordinate system, and a coordinate of an origin O of the laser radar coordinate system under the odometer coordinate system, the method further comprising:
And screening the minimum solution by a preset inspection standard to calibrate the radius of the left wheel, the radius of the right wheel, the wheel distance between the two wheels of the laser odometer, the rotation of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system, so as to ensure that the distance between the laser points of the laser radar is within a high-precision area of the laser radar.
Since commercial lasers have relatively large errors at certain distances. Laser light such as TOF laser radar has relatively large errors within 10 cm (with highest accuracy within 10 cm-20 m), and small-sized triangular ranging laser radar has large errors outside 10m (with highest accuracy within 0-8 m). The magnitude of these errors will not be reflected in the covariance matrix C of the laser splice, so that an additional check needs to be made on the recorded calibration data, ensuring that the distance of the laser points inside is within the high-precision area of the laser radar.
Taking the laser radar of the triangle method as an example, the accuracy is highest within 0-8m, so if a certain piece of data contains the measured distance of 10m, by judging whether the certain piece of data contains the measurement beyond the accuracy range, the piece of data (the odometer data and the laser radar data) is not added to the optimization, because the data are not accurate enough. The detection standard is set according to specific situations because the detection standard is specifically determined by combining specific laser radar models.
In some embodiments, a method of calibrating an odometer of a robot of a laser navigation system, the laser navigation system including a robot on which a laser odometer and a horizontal scanning lidar are mounted, the method comprising:
Starting the robot to automatically navigate;
recording odometer data and laser radar data of preset time in the course of travel, detecting the stopping state of the robot, and suspending recording in the stopping state; stopping recording data after recording the threshold times for 2-4 seconds within the preset time range; the threshold number of times ranges from 100 to 10000 times.
Screening and removing the recorded data (avoiding measurement errors caused by the accuracy problem of the mechanical radar), and continuing recording if the data quantity is less than 100.
Starting to calculate the first estimation value and the second estimation value and the difference value thereof;
The robot moves for multiple times to generate multiple groups of first positions and second positions, and multiple groups of first estimated values, second estimated values and difference values of the first estimated values and the second estimated values are obtained through calculation;
And after the calculation is completed, comparing the first estimated value and the second estimated value of the plurality of groups and the difference value and the initial value of the first estimated value and the second estimated value, and if the difference value is not large, receiving calibration (six parameters alpha, beta, gamma, theta, x and y of the calibration odometer), otherwise, judging that the calibration fails.
Repeating the steps after a period of time, wherein the interval time can be adjusted according to the use rate of the robot. The laser odometer parameter is calibrated by the minimum solution, and the problem that the calibration accuracy of the odometer is reduced due to the fact that the wheel of the odometer is worn or the mechanical structure is changed is solved.
Example two
As shown in fig. 7, the embodiment of the present invention further provides a laser navigation robot 200, on which a processor 201, a laser odometer 202 and a horizontal scanning laser radar 203 are mounted, the processor 201 being configured to perform the laser odometer calibration method of the robot according to the first embodiment.
Specifically, an inertial measurement unit is installed on the robot, and the inertial measurement unit is used for integrating and calculating a first rotation parameter of a double wheel of the odometer; simultaneously calculating a second rotation parameter of the odometer in unit time in the same time; and comparing the first rotation parameter with the second rotation parameter, and deleting the odometer data and the laser radar data in the corresponding time period if the first rotation parameter and the second rotation parameter are inconsistent.
It should be noted that, the laser navigation robot of the present embodiment belongs to the same concept as the method of the first embodiment, the specific implementation process of the laser navigation robot is detailed in the method embodiment, and the technical features of the method embodiment are correspondingly applicable in the present embodiment, which is not repeated herein.
According to the laser navigation robot provided by the embodiment of the application, the movement of the robot from the first position to the second position is detected by the odometer and the laser radar simultaneously, and odometer data and laser radar data are respectively obtained; constructing residual errors according to the position relation information of the odometer and the laser radar and the data of the odometer and the data of the laser radar, and solving to obtain the minimum solution of the parameters of the odometer; and calibrating the initial value of the odometer parameter with the minimum solution. The parameters of the odometer are recalibrated, so that the problem that the calibration accuracy of the odometer is reduced due to abrasion of wheels or change of a mechanical structure of the odometer is solved.
Example III
A third embodiment of the present application provides a computer-readable storage medium having stored thereon a program for odometer calibration of a robot, which when executed by a processor is configured to implement the steps of the method for odometer calibration of a robot described in the first embodiment.
It should be noted that, the computer readable storage medium of the present embodiment belongs to the same concept as the method of the first embodiment, the specific implementation process of the computer readable storage medium is detailed in the method embodiment, and the technical features of the method embodiment are correspondingly applicable in the present embodiment, which is not repeated herein.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
The foregoing description of the preferred embodiments of the present application should not be construed as limiting the scope of the application, but rather as utilizing equivalent structural changes made in the description and drawings of the present application or directly/indirectly applied to other related technical fields under the application concept of the present application.
Claims (11)
1. A laser odometer calibration method for a robot for laser navigation, wherein the odometer is used for counting the movement of a travelling wheel, the robot further comprising a horizontal scanning laser radar for detecting the movement position of the robot, the method comprising:
Establishing an odometer coordinate system, and establishing a laser radar coordinate system, wherein the odometer parameters comprise traveling wheel parameters, rotation of an X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and coordinates of an origin O of the laser radar coordinate system under the odometer coordinate system;
controlling the robot to move from a first position to a second position, calculating the relative pose of the two positions through laser radar splicing, and converting the relative pose into an odometer coordinate system according to the position relation information to obtain a first estimated value; while the odometer detects a second estimate of the relative position of the computing robot moving from the first position to the second position; calculating the first and second estimates and their differences;
The robot moves for multiple times to generate multiple groups of first positions and second positions, and multiple groups of first estimated values, second estimated values and difference values of the first estimated values and the second estimated values are obtained through calculation;
combining and solving a plurality of difference values to obtain a group of solutions which minimize the optimization objective;
and calibrating the initial value of the odometer parameter with the minimum solution.
2. The method of claim 1, wherein after the step of combining the plurality of differences to obtain a set of solutions that minimize the optimization objective, the method further comprises:
and comparing the initial value of the odometer parameter with the minimum solution, and if the comparison result is in a preset range, calibrating the traveling wheel parameter of the laser odometer, the rotation of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system by using the minimum solution.
3. The method according to claim 2, wherein said establishing said odometer coordinate system comprises in particular:
the origin of the odometer coordinate system is the position o of the center of the two wheels, and the positive direction of the x axis is the direction in which the vertical line perpendicular to the connecting line between the two wheels points to the forward rolling of the wheels; the y-axis direction is the direction of the connecting line of the two-wheel straight line, the y-axis positive direction is the direction that the x-axis direction rotates 90 degrees anticlockwise around the origin o, the z-axis direction is vertical to the ground, and the z-axis positive direction is the direction vertical to the ground upwards;
the establishing a laser radar coordinate system specifically comprises the following steps:
The origin of the laser radar coordinate system is the origin O measured by a laser of the laser radar, the positive direction of the Z axis coincides with the positive direction of the Z axis of the odometer coordinate system, the positive direction of the X axis of the laser radar coordinate system is the positive direction of the laser, the positive direction of the Y axis is deduced through a right hand rule, the direction of the thumb of the right hand is the positive direction of the X axis of the laser radar coordinate system, and the directions pointed by the four fingers of the right hand are the positive direction of the Y axis.
4. A method according to claim 3, wherein the travelling wheels comprise a left wheel and a right wheel, the travelling wheel parameters comprise a left wheel radius, a right wheel radius, a wheelbase between the two wheels, the left wheel radius initial value α = 1, the right wheel radius initial value β = 1, the wheelbase γ = 1; the rotation angle theta of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinates (X, y) of the origin O of the laser radar coordinate system in the odometer coordinate system are obtained according to the installation data of the laser radar; the optimization function used to solve the minimum solution is:
Where N is the total number of observations, C is the covariance matrix of the laser splice, Is the relative pose of the first position and the second position in the odometer coordinates,Is the relative position of the first and second positions estimated by the odometer.
5. The method of claim 4, wherein the optimization function is solved using gauss newton's method or linear approximation.
6. The method of claim 5, wherein the method further comprises:
a difference k i is calculated for each set of first and second estimates:
And deleting the data which are far from the distribution center point by a preset proportion according to the distribution of k i so as to ensure the data consistency.
7. The method of claim 5, wherein the minimum solution calibrates a left wheel radius, a right wheel radius, a wheelbase between two wheels of the laser odometer, a rotation of a laser radar coordinate system X-axis relative to the odometer coordinate system X-axis, and a coordinate of a laser radar coordinate system origin O under the odometer coordinate system, the method further comprising:
And screening the minimum solution by a preset inspection standard to calibrate the radius of the left wheel, the radius of the right wheel, the wheel distance between the two wheels of the laser odometer, the rotation of the X axis of the laser radar coordinate system relative to the X axis of the odometer coordinate system and the coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system, so as to ensure that the distance between the laser points of the laser radar is within a high-precision area of the laser radar.
8. The method of claim 5, wherein the method further comprises:
Calculating a first rotation parameter of a double wheel of the odometer using inertial measurement unit integration; simultaneously calculating a second rotation parameter of the odometer in the same time; and comparing the first rotation parameter with the second rotation parameter, and deleting the odometer data and the laser radar data in the corresponding time period if the first rotation parameter and the second rotation parameter are inconsistent.
9. A laser navigation robot, characterized in that a processor, a laser odometer and a horizontal scanning laser radar are mounted on the robot, the processor being adapted to perform the laser odometer calibration method of the robot according to any of the claims 1-8.
10. The laser navigation robot of claim 9, wherein an inertial measurement unit is mounted on the robot, and wherein the inertial measurement unit is used to integrate and calculate a first rotation parameter of the two wheels of the odometer; simultaneously calculating a second rotation parameter of the odometer in unit time in the same time; and comparing the first rotation parameter with the second rotation parameter, and deleting the odometer data and the laser radar data in the corresponding time period if the first rotation parameter and the second rotation parameter are inconsistent.
11. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a screen display program, which when executed by a processor, implements the steps of the laser odometer calibration method of a robot according to any of the claims 1-8.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105628026A (en) * | 2016-03-04 | 2016-06-01 | 深圳大学 | Positioning and posture determining method and system of mobile object |
| CN106123890A (en) * | 2016-06-14 | 2016-11-16 | 中国科学院合肥物质科学研究院 | A kind of robot localization method of Fusion |
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| CN109974742A (en) * | 2017-12-28 | 2019-07-05 | 沈阳新松机器人自动化股份有限公司 | A kind of laser Method for Calculate Mileage and map constructing method |
| CN110263675B (en) * | 2019-06-03 | 2024-02-20 | 武汉联一合立技术有限公司 | Garbage target identification system and method of community security robot |
| CN110293563B (en) * | 2019-06-28 | 2022-07-26 | 炬星科技（深圳）有限公司 | Method, apparatus, and storage medium for estimating pose of robot |
| CN110411462B (en) * | 2019-07-22 | 2021-05-18 | 武汉大学 | GNSS/inertial navigation/lane line constraint/milemeter multi-source fusion method |
| CN110515088B (en) * | 2019-08-27 | 2021-07-09 | 中国人民解放军国防科技大学 | Odometer estimation method and system for intelligent robot |
| CN110530399B (en) * | 2019-09-06 | 2023-03-24 | 苏州寻迹智行机器人技术有限公司 | Wheel spacing correction method for odometer calibration of double-wheel differential mobile robot |
-
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105628026A (en) * | 2016-03-04 | 2016-06-01 | 深圳大学 | Positioning and posture determining method and system of mobile object |
| CN106123890A (en) * | 2016-06-14 | 2016-11-16 | 中国科学院合肥物质科学研究院 | A kind of robot localization method of Fusion |
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