CN112945266A - Laser navigation robot and odometer calibration method thereof - Google Patents
Laser navigation robot and odometer calibration method thereof Download PDFInfo
- Publication number
- CN112945266A CN112945266A CN201911261789.5A CN201911261789A CN112945266A CN 112945266 A CN112945266 A CN 112945266A CN 201911261789 A CN201911261789 A CN 201911261789A CN 112945266 A CN112945266 A CN 112945266A
- Authority
- CN
- China
- Prior art keywords
- odometer
- coordinate system
- laser radar
- laser
- robot
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 69
- 238000005457 optimization Methods 0.000 claims description 17
- 238000005259 measurement Methods 0.000 claims description 16
- 238000003860 storage Methods 0.000 claims description 11
- 238000009434 installation Methods 0.000 claims description 8
- 239000011159 matrix material Substances 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000007689 inspection Methods 0.000 claims description 5
- 238000012216 screening Methods 0.000 claims description 5
- 230000010354 integration Effects 0.000 claims description 4
- 230000009977 dual effect Effects 0.000 claims description 3
- 210000003811 finger Anatomy 0.000 claims description 3
- 238000005096 rolling process Methods 0.000 claims description 3
- 210000003813 thumb Anatomy 0.000 claims description 3
- 238000009826 distribution Methods 0.000 claims description 2
- 230000008859 change Effects 0.000 abstract description 5
- 230000006870 function Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 3
- 238000005299 abrasion Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
- 230000007723 transport mechanism Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
Landscapes
- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The application discloses a laser navigation robot and a method for calibrating an odometer of the robot, wherein the odometer and a laser radar simultaneously detect the movement of the robot from a first position to a second position to respectively obtain odometer data and laser radar data; constructing a residual error 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 a minimum solution of the odometer parameters; and calibrating the initial value of the odometer parameter with the minimum solution, thereby solving the problem that the wheel wear or the mechanical structure change of the odometer causes the calibration precision of the odometer to be reduced.
Description
Technical Field
The application relates to the technical field of laser navigation systems, in particular to a laser navigation robot and a method for calibrating a milemeter of the robot.
Background
Existing laser navigation solutions on robots all involve the application of wheel odometers. Typically, calibration of the odometer is done at the factory. However, over time, the accuracy of the odometer calibration may be degraded by wear of the wheels, changes in mechanical structure, etc. When the accuracy of the odometer drops to a certain degree, the effect of laser navigation can be severely affected.
Content of application
Therefore, it is necessary to provide a laser navigation robot and an odometer calibration method for the robot thereof, so as to solve the technical problem that the laser navigation is affected due to the fact that the calibration accuracy of the odometer is reduced due to wheel wear or mechanical structure change of the odometer.
To achieve the above object, the present application proposes a laser odometer calibration method for a robot, the robot being used for laser navigation, the odometer being used for counting movements of a travel wheel, the robot further including a horizontal scanning lidar for detecting a movement position of the robot, the method including:
the odometer and the laser radar simultaneously detect the movement of the robot from a first position to a second position, and odometer data and laser radar data are respectively obtained;
constructing a residual error 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 a minimum solution of the odometer parameters;
calibrating the initial values of the odometry parameters with the minimum solution.
In some embodiments, the method further comprises:
establishing a coordinate system of the odometer, and establishing a coordinate system of the laser radar, wherein the parameters of the odometer comprise a traveling wheel parameter, the rotation of an X axis of the coordinate system of the laser radar relative to an X axis of the coordinate system of the odometer, and the coordinate of an origin O of the coordinate system of the laser radar under the coordinate system of the odometer;
the method comprises the steps of simultaneously detecting the movement of the robot from a first position to a second position by the odometer and the laser radar, and respectively obtaining odometer data and laser radar data, and the steps of constructing a residual error according to the position relation information of the odometer and the laser radar, the odometer data and the laser radar data, and solving to obtain a minimum solution of the odometer parameters specifically comprise:
controlling the robot to move from a first position to a second position, calculating the relative poses of the two positions through laser radar splicing, and converting the relative poses into a first estimated value under a coordinate system of the odometer according to the position relation information; simultaneously 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 difference;
the robot moves for multiple times to generate multiple groups of first positions and second positions, and multiple groups of first estimated values, multiple groups of second estimated values and differences of the first estimated values and the second estimated values are obtained through calculation;
the multiple differences are combined and solved and a set of solutions is obtained that minimizes the optimization objective.
In some embodiments, after the step of merging the solutions to the plurality of differences and obtaining a set of solutions that minimizes the optimization objective, the method further comprises:
and comparing the initial value of the odometer parameter with the minimum solution, and calibrating the travel 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 if the comparison result is within a preset range.
In some embodiments, the establishing the odometer coordinate system comprises:
the origin of the coordinate system of the odometer is the position o of the center of the two wheels, and the positive direction of the x axis is the direction in which a vertical line perpendicular to a connecting line between the two wheels points to the positive rolling direction of the wheels; the y-axis direction is the direction of a connecting line of two straight lines, the positive direction of the y-axis is the direction of rotating 90 degrees anticlockwise around an origin o in the x-axis direction, the direction of the z-axis is vertical to the ground, and the positive direction of the z-axis is the upward direction vertical to the ground;
the establishing of the laser radar coordinate system comprises:
the original point of laser radar coordinate system is laser radar's the measured original point O of laser instrument, Z axle positive direction with odometer coordinate system Z axle positive direction coincidence, the X axle positive direction of laser radar coordinate system does the positive direction of laser instrument, Y axle positive direction are derived out through the right-hand rule, and right hand thumb direction does the X axle positive direction of laser radar coordinate system, the direction that the four fingers of the right hand indicate is Y axle positive direction.
In some embodiments of the present invention, the,
the travelling wheel comprises a left wheel and a right wheel, the travelling wheel parameters comprise a left wheel radius, a right wheel radius and a wheelbase between the two wheels, the initial value alpha of the left wheel radius is 1, the initial value beta of the right wheel radius is 1, and the wheelbase gamma between the two wheels is 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 and C is the covariance matrix of the laser stitching.
In some embodiments of the present invention, the,
the optimization function is solved using gauss-newton method or linear approximation.
In some embodiments of the present invention, the,
the method further comprises the following steps:
calculating a difference k for each set of the first estimate and the second estimatei：
According to kiAnd deleting data far away from the distribution central point in a preset proportion to ensure data consistency.
In some embodiments of the present invention, the,
the minimum solution calibrates the laser odometer for a left wheel radius, a right wheel radius, a wheelbase between two wheels, a rotation of a laser radar coordinate system X-axis relative to an odometer coordinate system X-axis, and before coordinates of a laser radar coordinate system origin O under the odometer coordinate system, the method further comprising:
and screening the minimum solution according to a preset inspection standard to calibrate the radius of a left wheel, the radius of a right wheel, the wheel base between 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 coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system so as to ensure that the distance of the laser point of the laser radar is within the high-precision area of the laser radar.
In some embodiments of the present invention, the,
the method further comprises the following steps:
calculating a first rotation parameter of a dual wheel of the odometer using inertial measurement unit integration; simultaneously calculating a second rotation parameter of the odometer at the same time; and comparing the first rotation parameter with the second rotation parameter, and if the first rotation parameter is inconsistent with the second rotation parameter, deleting the odometry data and the laser radar data in the corresponding time period.
In order to achieve the above object, the present application further proposes that the robot is provided with a processor, a laser odometer and a horizontal scanning lidar, wherein the processor is used for executing the laser odometer calibration method of the robot.
In some embodiments, the robot has an inertial measurement unit mounted thereon, and 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 if the first rotation parameter is inconsistent with the second rotation parameter, deleting the odometry data and the laser radar data in the corresponding time period.
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 robot, the odometer and the laser radar simultaneously detect movement of the robot from a first position to a second position, and odometer data and laser radar data are respectively obtained; constructing a residual error 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 a minimum solution of the odometer parameters; and calibrating the initial value of the odometer parameter with the minimum solution, thereby solving the problem that the wheel wear or the mechanical structure change of the odometer causes the calibration precision of the odometer to be reduced.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a schematic view of a robot according to an embodiment of the present application;
FIG. 2 is a flow chart of a laser odometer calibration method of a robot of an embodiment of the present application;
FIG. 3 is a flow chart of a laser odometer calibration method of a robot according to another embodiment of the present application;
FIG. 4 is a flow chart of a laser odometer calibration method of a robot according to yet another embodiment of the present application;
FIG. 5 is a schematic odometer coordinate system of a laser odometer calibration method of a robot according to an embodiment of the application;
FIG. 6 is a laser radar coordinate system schematic of a laser odometer calibration method of a robot according to an embodiment of the present application;
fig. 7 is a block diagram of a laser navigation robot according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that all the directional indications (such as up, down, left, right, front, and rear … …) in the embodiment of the present application are only used to explain the relative position relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indication is changed accordingly.
In addition, the descriptions referred to as "first", "second", etc. in this application are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicit ly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present application.
In this application, unless expressly stated or limited otherwise, the terms "connected," "secured," and the like are to be construed broadly, and for example, "secured" may be a fixed connection, a removable connection, or an integral part; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.
The method is applicable to most existing laser navigation systems as long as they have the following components: (1) the system comprises an odometer 1005 and a double-wheel differential motor with the odometer, (2) a horizontal scanning single-line laser radar 1004, and (3) the self pose in the scene can be estimated in real time through a SLAM robot (SLAM) for instant positioning and mapping, so that autonomous navigation can be realized. The scene can be indoor or outdoor, as an example of a robot is illustrated in fig. 1. The robot 100 also includes an inertial measurement unit 1006 thereon.
Example one
The embodiment of the application provides a laser odometer calibration method of a robot, the robot is used for laser navigation, and the odometer is used for counting the movement of a traveling wheel. If the robot is two-wheeled, a two-wheeled differential motor would be provided, as shown in fig. 1. 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 (output rotation amount and translation amount) odometer, and can calibrate the odometer as long as a posture change can be derived through the odometer. In the following embodiments, two-wheel odometer is used, and the travel wheel parameters include left wheel radius, right wheel radius and wheelbase between two wheels, but other types of odometer may be other parameters and may be calibrated as well, and the application is not limited thereto.
The robot further comprises a horizontal scanning lidar for detecting a robot movement position, 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:
in particular, the first position may be defined as an initial position of the robot and the second position as a target position of the robot.
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:
the step 2 and the step 3 specifically comprise:
the relative poses of the first position and the second position calculated by laser radar splicing can be obtained by using the existing calculation method.
Specifically, the positional relationship information between the laser radar and the robot can be obtained according to an installation drawing of a laser navigation system. The mounting position of the lidar on the robot is illustrated in fig. 1.
The odometer detects that the computing robot moves from a first position to a second position and needs to be combined with various parameter settings of a two-wheel differential motor of the odometer.
Further, the method further comprises:
in particular, 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.
after the minimum solution is calculated, the travel wheel parameters 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 coordinates of the origin O of the laser radar coordinate system under the odometer coordinate system are calibrated with the minimum solution.
Specifically, establishing the odometer coordinate system comprises: the origin of the coordinate system of the odometer is the position o of the center of the two wheels, and the positive direction of the x axis is the direction in which a vertical line perpendicular to a connecting line between the two wheels points to the positive rolling direction of the wheels; the y-axis direction is the direction of a connecting line of two straight lines, the positive direction of the y-axis is the direction of rotating 90 degrees anticlockwise around an origin o in the x-axis direction, the direction of the z-axis is vertical to the ground, and the positive direction of the z-axis is the upward direction vertical to the ground;
specifically, the establishing of the lidar coordinate system comprises: the original point of laser radar coordinate system is laser radar's the measured original point O of laser instrument, Z axle positive direction with odometer coordinate system Z axle positive direction coincidence, the X axle positive direction of laser radar coordinate system does the positive direction of laser instrument, Y axle positive direction are derived out through the right-hand rule, and right hand thumb direction does the X axle positive direction of laser radar coordinate system, the direction that the four fingers of the right hand indicate is Y axle positive direction.
The coordinate system of the odometer is shown in figure 5, and the coordinate system of the laser radar is shown in figure 6.
The method for calibrating the odometer of the robot comprises the steps of obtaining a second estimated value through detection and calculation of the laser odometer on the movement of the robot, splicing and calculating the movement of the robot from a first position to a second position by means of a horizontal scanning laser radar, converting the spliced and calculated values into an odometer coordinate system to obtain a first estimated value, obtaining two calculated estimated values through one movement of the robot, and obtaining a group of solutions enabling an optimization target to be minimum through optimizing and calculating a plurality of groups of first estimated values, second estimated values and difference values of the first estimated values and the second estimated values and solving the solutions, wherein the minimum solution comprises the odometer parameters; and calibrating the travelling 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, so that the problems that the calibration precision of the odometer is reduced due to 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 caused by the wheel wear or the mechanical structure transformation of the odometer and the calibration precision of the odometer is reduced due to the re-calibration/calibration of the odometer parameters are solved.
Further, after the step of merging the plurality of differences and obtaining a set of solutions that minimizes the optimization objective, the method further comprises:
and 31, comparing the initial value of the odometer parameter with the minimum solution, and calibrating the travel 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 if the comparison result is within a preset range.
That is, the minimum solution is not directly used to calibrate the odometer parameters, or the minimum solution is used to calibrate the odometer parameters only when the minimum solution is within a preset range by 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.
The preset range includes:
the radius of the left wheel in the minimum 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 the right wheel radius initial value beta;
the wheelbase between two wheels in the minimum solution is 0.9-1.1 times 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 above and below the 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 lidar coordinate system in the minimum solution in 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 lidar coordinate system in 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) axle distance between the two wheels gamma x d. The three parameters l, r, 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 in the embodiments of the present application to describe such errors.
The initial value alpha of the radius of the left wheel of the odometer is 1, the initial value beta of the radius of the right wheel of the odometer is 1, and the wheelbase gamma between two wheels is 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;
namely, the odometer parameters to be calibrated (calibrated) by the method are as follows:
(1)α；
(2)β；
(3)γ；
(4) rotation theta of the X-axis of the lidar coordinate system relative to the X-axis of the odometer coordinate system (the Z/Z axes coincide and so have only 1-dimensional rotation);
(5) the lidar coordinate system origin O is x and y (the Z/Z axes coincide so there is only x, y) in the odometer coordinate system.
Wherein, the initial values of the odometer parameters are defined as:
α＝1；
β＝1；
γ＝1；
θ is derived from the installation drawing (installation data of the lidar);
x: obtaining an initial value from an installation drawing;
y: obtaining from an installation drawing;
in the embodiment of the application, a residual error containing the parameters is constructed, and then each physical quantity corresponding to the minimum residual error is solved by using an optimization algorithm.
Constructing a residual error: 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 radar, and can be converted into the coordinate of the odometer through the parameter (4) and the parameter (5)
Meanwhile, the odometer can also directly estimate the relative position of the two positions
Thus we have two different estimates for the same physical quantity and the residual can be defined as the difference between the two physical quantities.
In the formula, N is the total observation times, and C is a covariance matrix of laser splicing; in practice, a set of solutions is sought that minimizes the optimization objective by combining multiple measurements. Since the initial value is generally accurate, the optimization function can be solved by a general optimization algorithm such as a gauss-newton method, and the like, and can also be solved by a linear approximation method.
In some embodiments, considering practical operation, the laser odometer calibration method of the robot of the embodiment of the invention also needs to consider a plurality of practically occurring problems, and corresponding solutions are proposed for the problems possibly encountered:
problem (1) odometer slip problem: in a real-world scenario, for some ground and wheel combinations, wheel slippage may occur. Reflecting the mathematical model, the slip causes an outlier, which is fatal to the least square construction, so we need to accurately remove the data of the slip. We propose to add an IMU (inertial measurement unit) to solve this problem. As the wheel slips, the odometer-calculated rotation per unit time and the rotation integrated by the IMU at the same time are not identical, and the odometer data and lidar data during this time period should not be added to the optimization.
The method further comprises the following steps:
calculating a first rotation parameter of a dual wheel of the odometer using inertial measurement unit integration; simultaneously calculating a second rotation parameter of the odometer at 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 is inconsistent with the second rotation parameter.
The odometer calculates the rotation by parameter setting of the odometer.
Problem (2) laser splicing inaccuracy and splicing error problems. 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 the wrong stitching. I.e. a wrong concatenation may also have a better covariance matrix C. To solve the problem (2):
the method further comprises the following steps:
calculating a difference k for each set of the first estimate and the second estimatei：
Then calculate kiThen a certain proportion (e.g. 15% -30%, in particular 20% or 25%) of the data that is far from the distribution center point is removed. The method actually ensures the general consistency of data, thereby solving the problem of laser splicing errors.
Problem (3) measurement error of laser: lasers on the market can have relatively large errors at a particular distance. 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 based on the small-sized triangular distance measurement is large beyond 10 m. The size of these errors will not be reflected in 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 lidar.
To solve this problem, the method further comprises:
the minimum solution calibrates the laser odometer for a left wheel radius, a right wheel radius, a wheelbase between two wheels, a rotation of a laser radar coordinate system X-axis relative to an odometer coordinate system X-axis, and before coordinates of a laser radar coordinate system origin O under the odometer coordinate system, the method further comprising:
and screening the minimum solution according to a preset inspection standard to calibrate the radius of a left wheel, the radius of a right wheel, the wheel base between 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 coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system so as to ensure that the distance of the laser point of the laser radar is within the high-precision area of the laser radar.
Since lasers on the market have a relatively large error at a certain distance. For example, the laser of TOF lidar has relatively large error within 10 cm (with the highest accuracy within 10 cm-20 m), and the laser of small triangulation ranging has large error outside 10m (with the highest accuracy within 0-8 m). The size of the errors cannot be reflected in the covariance matrix C of laser splicing, so that additional inspection needs to be performed on recorded calibration data once, and the distance of laser points in the calibration data is ensured to be within the high-precision area of the laser radar.
Taking the laser radar of the trigonometry as an example, the accuracy is the highest within 0-8m, so if a certain piece of data includes a measured distance of 10m, by judging whether a certain piece of data includes a measurement beyond the accuracy range, the piece of data (the mileage count data and the laser radar data) is not added to the optimization because the data are not accurate enough. The specific type of the laser radar is used for judgment, so that the preset inspection standard is set according to specific conditions.
In some embodiments, a method for odometer calibration of a robot of a laser navigation system is provided, the laser navigation system comprising a robot having a laser odometer and a horizontal scanning lidar mounted thereon, the method comprising:
starting the automatic navigation of the robot;
recording mileage counting data and laser radar data of preset time in the process of travel, detecting the stop state of the robot, and pausing recording in the stop state; stopping recording data after the preset time range is 2-4 seconds and the threshold times are recorded; the threshold number of times ranges from 100 to 10000.
And (4) screening and eliminating the recorded data (avoiding measurement errors caused by the accuracy problem of the mechanism radar), and continuing recording if the data quantity is less than 100.
Starting to calculate the first and second estimates and their difference;
the robot moves for multiple times to generate multiple groups of first positions and second positions, and multiple groups of first estimated values, multiple groups of second estimated values and differences of the first estimated values and the second estimated values are obtained through calculation;
and comparing the plurality of groups of first estimation values and second estimation values and the difference values and the initial values after the calculation is finished, and accepting calibration (calibrating six parameters alpha, beta, gamma, theta, x and y of the odometer) if the difference is not large, otherwise, judging that the calibration fails.
The steps are repeated after a period of time, and the interval time can be adjusted according to the use rate of the robot. The laser odometer parameters are calibrated by the minimum solution, and the odometer parameters are calibrated continuously, so that the problem of low calibration precision of the odometer caused by wheel abrasion or mechanical structure transformation of the odometer is solved.
Example two
As shown in fig. 7, an embodiment of the present invention further provides a laser navigation robot 200, where the robot is mounted with a processor 201, a laser odometer 202, and a horizontal scanning lidar 203, and the processor 201 is configured to perform a laser odometer calibration method of the robot according to the first embodiment.
Specifically, an inertia measurement unit is installed on the robot, and a first rotation parameter of a double wheel of the odometer is calculated by integration of the inertia measurement unit; 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 if the first rotation parameter is inconsistent with the second rotation parameter, deleting the odometry data and the laser radar data in the corresponding time period.
It should be noted that the laser navigation robot of this embodiment has the same concept as the method of the first embodiment, and the specific implementation process thereof is described in detail in the method embodiment, and the technical features in the method embodiment are all correspondingly applicable in this embodiment, which is not described herein again.
According to the laser navigation robot provided by the embodiment of the application, the odometer and the laser radar simultaneously detect the movement of the robot from the first position to the second position, and odometer data and laser radar data are respectively obtained; constructing a residual error 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 a minimum solution of the odometer parameters; calibrating the initial values of the odometry parameters with the minimum solution. The odometer parameters are calibrated again, so that the problem that the calibration precision of the odometer is reduced due to wheel abrasion or mechanical structure change of the odometer is solved.
EXAMPLE III
A third embodiment of the present application provides a computer-readable storage medium having a program for odometer calibration of a robot stored thereon, the program for odometer calibration of a robot being adapted to be executed by a processor for implementing the steps of the method for odometer calibration of a robot according to the first embodiment.
It should be noted that the computer-readable storage medium of this embodiment belongs to the same concept as the method of the first embodiment, and specific implementation processes thereof are detailed in the method embodiment, and technical features in the method embodiment are all correspondingly applicable in this embodiment, which is not described herein again.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between 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 by several physical components in cooperation. 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 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 is well known to those of ordinary skill 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 accessed by a computer. In addition, 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 as known to those skilled in the art.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications and equivalents of the subject matter of the present application, which is intended to be covered by the claims and their equivalents, or which are directly or indirectly applicable to other related arts are intended to be included within the scope of the present application.
Claims (12)
1. Method for laser odometer calibration of a robot, said robot being intended for laser navigation, characterized in that said odometer is intended for counting the movements of a travelling wheel, said robot further comprising a horizontal scanning lidar intended for detecting the robot's movement position, said method comprising:
the odometer and the laser radar simultaneously detect the movement of the robot from a first position to a second position, and odometer data and laser radar data are respectively obtained;
constructing a residual error 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 a minimum solution of the odometer parameters;
calibrating the initial values of the odometry parameters with the minimum solution.
2. The method of claim 1, further comprising:
establishing a coordinate system of the odometer, and establishing a coordinate system of the laser radar, wherein the parameters of the odometer comprise a traveling wheel parameter, the rotation of an X axis of the coordinate system of the laser radar relative to an X axis of the coordinate system of the odometer, and the coordinate of an origin O of the coordinate system of the laser radar under the coordinate system of the odometer;
the method comprises the steps of simultaneously detecting the movement of the robot from a first position to a second position by the odometer and the laser radar, and respectively obtaining odometer data and laser radar data, and the steps of constructing a residual error according to the position relation information of the odometer and the laser radar, the odometer data and the laser radar data, and solving to obtain a minimum solution of the odometer parameters specifically comprise:
controlling the robot to move from a first position to a second position, calculating the relative poses of the two positions through laser radar splicing, and converting the relative poses into a first estimated value under a coordinate system of the odometer according to the position relation information; simultaneously 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 difference;
the robot moves for multiple times to generate multiple groups of first positions and second positions, and multiple groups of first estimated values, multiple groups of second estimated values and differences of the first estimated values and the second estimated values are obtained through calculation;
the multiple differences are combined and solved and a set of solutions is obtained that minimizes the optimization objective.
3. The method of claim 2, wherein after the step of merging the solution differences and obtaining a set of solutions that minimizes the optimization objective, the method further comprises:
and comparing the initial value of the odometer parameter with the minimum solution, and calibrating the travel 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 if the comparison result is within a preset range.
4. The method of claim 3, wherein the establishing the odometer coordinate system comprises:
the origin of the coordinate system of the odometer is the position o of the center of the two wheels, and the positive direction of the x axis is the direction in which a vertical line perpendicular to a connecting line between the two wheels points to the positive rolling direction of the wheels; the y-axis direction is the direction of a connecting line of two straight lines, the positive direction of the y-axis is the direction of rotating 90 degrees anticlockwise around an origin o in the x-axis direction, the direction of the z-axis is vertical to the ground, and the positive direction of the z-axis is the upward direction vertical to the ground;
the establishing of the laser radar coordinate system comprises:
the original point of laser radar coordinate system is laser radar's the measured original point O of laser instrument, Z axle positive direction with odometer coordinate system Z axle positive direction coincidence, the X axle positive direction of laser radar coordinate system does the positive direction of laser instrument, Y axle positive direction are derived out through the right-hand rule, and right hand thumb direction does the X axle positive direction of laser radar coordinate system, the direction that the four fingers of the right hand indicate is Y axle positive direction.
5. The method according to claim 4, wherein the traveling wheels comprise a left wheel and a right wheel, the traveling wheel parameters comprise a left wheel radius, a right wheel radius, and a wheelbase between two wheels, the left wheel radius initial value α is 1, the right wheel radius initial value β is 1, and the wheelbase γ between two wheels is 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 and C is the covariance matrix of the laser stitching.
6. The method of claim 5, wherein the optimization function is solved using gauss-newton or linear approximation.
7. The method of claim 6, further comprising:
calculating a difference k for each set of the first estimate and the second estimatei：
According to kiAnd deleting data far away from the distribution central point in a preset proportion to ensure data consistency.
8. The method of claim 6, wherein the minimum solution calibrates the laser odometer for a left wheel radius, a right wheel radius, a wheelbase between two wheels, a rotation of a lidar coordinate system X-axis relative to an odometer coordinate system X-axis, and before coordinates of a lidar coordinate system origin O under the odometer coordinate system, the method further comprising:
and screening the minimum solution according to a preset inspection standard to calibrate the radius of a left wheel, the radius of a right wheel, the wheel base between 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 coordinate of the origin O of the laser radar coordinate system under the odometer coordinate system so as to ensure that the distance of the laser point of the laser radar is within the high-precision area of the laser radar.
9. The method of claim 6, further comprising:
calculating a first rotation parameter of a dual wheel of the odometer using inertial measurement unit integration; simultaneously calculating a second rotation parameter of the odometer at the same time; and comparing the first rotation parameter with the second rotation parameter, and if the first rotation parameter is inconsistent with the second rotation parameter, deleting the odometry data and the laser radar data in the corresponding time period.
10. Laser navigation robot, characterized in that it is equipped with a processor, a laser odometer and a horizontal scanning lidar, said processor being adapted to perform a laser odometer calibration method of the robot according to any of the claims 1-8.
11. The laser navigation robot of claim 10, wherein the robot has an inertial measurement unit mounted thereon, and wherein the inertial measurement unit is used to integrate and calculate a first rotation parameter of 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 if the first rotation parameter is inconsistent with the second rotation parameter, deleting the odometry data and the laser radar data in the corresponding time period.
12. Computer readable storage medium, characterized in that it has stored thereon a screen display program which, when executed by the processor, carries out the steps of the laser odometer calibration method of a robot according to any one of claims 1 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911261789.5A CN112945266A (en) | 2019-12-10 | 2019-12-10 | Laser navigation robot and odometer calibration method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911261789.5A CN112945266A (en) | 2019-12-10 | 2019-12-10 | Laser navigation robot and odometer calibration method thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112945266A true CN112945266A (en) | 2021-06-11 |
Family
ID=76226123
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911261789.5A Pending CN112945266A (en) | 2019-12-10 | 2019-12-10 | Laser navigation robot and odometer calibration method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112945266A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114440928A (en) * | 2022-01-27 | 2022-05-06 | 杭州申昊科技股份有限公司 | Combined calibration method for laser radar and odometer, robot, equipment and medium |
| CN116148824A (en) * | 2023-04-17 | 2023-05-23 | 机科发展科技股份有限公司 | Automatic calibration system and method for navigation parameters of laser unmanned forklift |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104848851A (en) * | 2015-05-29 | 2015-08-19 | 山东鲁能智能技术有限公司 | Transformer substation patrol robot based on multi-sensor data fusion picture composition and method thereof |
| 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 |
| 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 |
| CN110263675A (en) * | 2019-06-03 | 2019-09-20 | 武汉联一合立技术有限公司 | Garbage target recognition system and recognition method of community security robot |
| CN110293563A (en) * | 2019-06-28 | 2019-10-01 | 炬星科技（深圳）有限公司 | Estimate method, equipment and the storage medium of robot pose |
| CN110411462A (en) * | 2019-07-22 | 2019-11-05 | 武汉大学 | A kind of GNSS/ inertia/lane line constraint/odometer multi-source fusion method |
| CN110515088A (en) * | 2019-08-27 | 2019-11-29 | 中国人民解放军国防科技大学 | Odometer estimation method and system for intelligent robot |
| CN110530399A (en) * | 2019-09-06 | 2019-12-03 | 苏州寻迹智行机器人技术有限公司 | The wheel spacing modification method of two-wheel differential mobile robot odometer calibration |
-
2019
- 2019-12-10 CN CN201911261789.5A patent/CN112945266A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104848851A (en) * | 2015-05-29 | 2015-08-19 | 山东鲁能智能技术有限公司 | Transformer substation patrol robot based on multi-sensor data fusion picture composition and method thereof |
| 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 |
| 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 |
| CN110263675A (en) * | 2019-06-03 | 2019-09-20 | 武汉联一合立技术有限公司 | Garbage target recognition system and recognition method of community security robot |
| CN110293563A (en) * | 2019-06-28 | 2019-10-01 | 炬星科技（深圳）有限公司 | Estimate method, equipment and the storage medium of robot pose |
| CN110411462A (en) * | 2019-07-22 | 2019-11-05 | 武汉大学 | A kind of GNSS/ inertia/lane line constraint/odometer multi-source fusion method |
| CN110515088A (en) * | 2019-08-27 | 2019-11-29 | 中国人民解放军国防科技大学 | Odometer estimation method and system for intelligent robot |
| CN110530399A (en) * | 2019-09-06 | 2019-12-03 | 苏州寻迹智行机器人技术有限公司 | The wheel spacing modification method of two-wheel differential mobile robot odometer calibration |
Non-Patent Citations (2)
| Title |
|---|
| 安雷;张国良;张维平;敬斌;: "移动机器人扩展卡尔曼滤波定位与传感器误差建模", 信息与控制, no. 04 * |
| 纪嘉文;杨明欣;: "一种基于多传感融合的室内建图和定位算法", 成都信息工程大学学报, no. 04 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114440928A (en) * | 2022-01-27 | 2022-05-06 | 杭州申昊科技股份有限公司 | Combined calibration method for laser radar and odometer, robot, equipment and medium |
| CN116148824A (en) * | 2023-04-17 | 2023-05-23 | 机科发展科技股份有限公司 | Automatic calibration system and method for navigation parameters of laser unmanned forklift |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112254741B (en) | Abnormality detection method for mileage sensor, self-moving robot, and storage medium | |
| CN109752003B (en) | Robot vision inertia point-line characteristic positioning method and device | |
| CN110986988B (en) | Track calculation method, medium, terminal and device integrating multi-sensor data | |
| EP3845989A1 (en) | Method for detecting straight side by robot, and method for screening reference wall side by cleaning robot | |
| CN108981687B (en) | Indoor positioning method with vision and inertia integration | |
| US11486988B2 (en) | Method for calibrating the alignment of a moving object sensor | |
| CN110530399B (en) | Wheel spacing correction method for odometer calibration of double-wheel differential mobile robot | |
| CN113933818A (en) | Method, device, storage medium and program product for calibrating laser radar external parameter | |
| CN114179825B (en) | Method for obtaining confidence of measurement value through multi-sensor fusion and automatic driving vehicle | |
| CN112945266A (en) | Laser navigation robot and odometer calibration method thereof | |
| CN112748421A (en) | Laser radar calibration method based on automatic driving of straight road section | |
| CN115200572B (en) | Three-dimensional point cloud map construction method and device, electronic equipment and storage medium | |
| CN110637209B (en) | Method, apparatus and computer readable storage medium having instructions for estimating a pose of a motor vehicle | |
| CN114241062A (en) | Camera external parameter determination method and device for automatic driving and computer readable storage medium | |
| CN110850882A (en) | Charging pile positioning method and device of sweeping robot | |
| CN114943952A (en) | Method, system, device and medium for obstacle fusion under multi-camera overlapped view field | |
| CN112967393B (en) | Correction method and device for vehicle movement track, electronic equipment and storage medium | |
| CN110118571A (en) | A kind of method of the setting angle error of laser sensor in acquisition mobile device | |
| CN112346037B (en) | Calibration method, device and equipment of vehicle-mounted laser radar and vehicle | |
| CN115685153A (en) | Laser radar calibration method, device, equipment and storage medium | |
| CN115540875B (en) | Method and system for high-precision detection and positioning of train vehicles in station track | |
| WO2022237375A1 (en) | Positioning apparatus calibration method, odometer calibration method, program product, and calibration apparatus | |
| CN117233784A (en) | Underwater robot tunnel positioning method, system, computer equipment and storage medium | |
| CN116448146A (en) | Inertial navigation system self-calibration method, device, equipment and storage medium | |
| EP4269044A1 (en) | Slope location correction method and apparatus, robot and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 518000 Room 401, block D, building 7, Shenzhen International Innovation Valley, Dashi 1st Road, Xili community, Xili street, Nanshan District, Shenzhen, Guangdong Applicant after: Juxing Technology (Shenzhen) Co., Ltd Address before: 518000 building 101, building R3b, Gaoxin industrial village, No.018, Gaoxin South 7th Road, community, high tech Zone, Yuehai street, Nanshan District, Shenzhen City, Guangdong Province Applicant before: Juxing Technology (Shenzhen) Co., Ltd |