CN116576884A - System, method and machine-readable storage medium for calibrating parameters of multiple sensors - Google Patents

System, method and machine-readable storage medium for calibrating parameters of multiple sensors Download PDF

Info

Publication number
CN116576884A
CN116576884A CN202310472013.8A CN202310472013A CN116576884A CN 116576884 A CN116576884 A CN 116576884A CN 202310472013 A CN202310472013 A CN 202310472013A CN 116576884 A CN116576884 A CN 116576884A
Authority
CN
China
Prior art keywords
calibration
inertial navigation
coordinate
camera
laser radar
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
Application number
CN202310472013.8A
Other languages
Chinese (zh)
Inventor
方浩
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hubei Ecarx Technology Co Ltd
Original Assignee
Hubei Ecarx Technology Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Hubei Ecarx Technology Co Ltd filed Critical Hubei Ecarx Technology Co Ltd
Priority to CN202310472013.8A priority Critical patent/CN116576884A/en
Publication of CN116576884A publication Critical patent/CN116576884A/en
Pending legal-status Critical Current

Links

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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G01C21/1652—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments with ranging devices, e.g. LIDAR or RADAR
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/497—Means for monitoring or calibrating
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The invention provides a system, a method and a machine-readable storage medium for calibrating parameters of multiple sensors. The multi-sensor parameter calibration method comprises the following steps: establishing a first coordinate system through a total station, and acquiring coordinate values of a plurality of sensors; converting the first coordinate system into a second coordinate system taking inertial navigation as an origin; calculating a lever arm value between the sensor and inertial navigation in a second coordinate system; calculating an L2I calibration parameter according to the lever arm value; calculating camera internal parameter; calculating an L2C calibration parameter according to the camera internal parameter; calculating a C2I calibration parameter according to the L2I calibration parameter and the L2C calibration parameter; calculating primary and secondary laser radar calibration parameters according to the primary laser point cloud and the secondary laser point cloud; and calculating the calibration parameters between the auxiliary laser radar and the inertial navigation according to the L2I calibration parameters and the main and auxiliary laser radar calibration parameters. According to the scheme, the calibration parameters among the sensors are calculated, so that the collected road information can be integrated in a unified coordinate system by a subsequent information collection vehicle, and map production and quality inspection can be performed.

Description

System, method and machine-readable storage medium for calibrating parameters of multiple sensors
Technical Field
The present invention relates to the field of map navigation and autopilot, and in particular, to a system, method and machine-readable storage medium for calibrating parameters with multiple sensors.
Background
In the field of map navigation and automatic driving, in the running process of an information acquisition vehicle, road surface information in the running process is collected through a plurality of sensors on the vehicle, such as a laser radar, a camera, a GNSS antenna, an inertial navigation system (Inertial Navigation Syste, INS or inertial navigation for short), and the like.
Disclosure of Invention
It is an object of the present invention to fuse the positions between different sensors in the same inertial navigation coordinate system.
It is a further object of the invention to calibrate the relative positional relationship between different sensors.
It is yet a further object of the present invention to integrate road information collected by an information collecting vehicle in a unified coordinate system.
In particular, the present invention provides a multi-sensor calibration system comprising:
an information collection vehicle, carrying a plurality of sensors, the sensor includes: the sensor can record and collect peripheral data by using a self coordinate system;
the calibration device is used for fusing the relative position relation of the sensors in the same inertial navigation coordinate system and comprises the following components:
the lever arm value measurement calculation module is used for calculating inertial navigation coordinates from the GNSS antenna and the laser radar
A lever arm value of the center;
the L2I calibration module is used for calibrating the relative position relation between the laser radar and the inertial navigation;
the camera internal parameter calibration module is used for determining specific parameter configuration in the camera;
the L2C calibration module is used for calibrating the relative position relationship between the main laser radar and the camera;
the C2I calibration module is used for calibrating the relative position relation between the camera and the inertial navigation;
the main and auxiliary laser radar calibration module is used for calibrating the relative position relationship between the main laser radar and the auxiliary laser radar;
the auxiliary laser radar and inertial navigation calibration module is used for calibrating the relative position relationship between the auxiliary laser radar and the inertial navigation.
Optionally, the lever arm value measurement calculation module is further configured to:
establishing a first coordinate system with the total station as an origin by the total station, and acquiring coordinate values of a plurality of sensors, wherein the plurality of sensors comprise: the coordinate values comprise an X value, a Y value and a Z value of the sensor in a first coordinate system;
converting the first coordinate system into a second coordinate system taking inertial navigation as an original point, wherein a target coordinate value generated by converting coordinate values in the second coordinate system is recorded in the second coordinate system, the target coordinate value comprises a first target coordinate value of a laser radar, a second target coordinate value of inertial navigation, a third target coordinate value of a GNSS antenna and a fourth target coordinate value of a camera, and the target coordinate value comprises X values, Y values and Z values of various sensors in the second coordinate system;
and calculating lever arm values between one or more of the first target coordinate value, the second target coordinate value, the third target coordinate value and the fourth target coordinate value and inertial navigation coordinate values, wherein the inertial navigation coordinate values are origins in the second coordinate system.
Optionally, the L2I calibration module is further configured to: acquiring route information, and converting the route information and lever arm values of the GNSS antenna into coordinate track information files; converting the coordinate track information file and the lever arm value of the laser radar into L2I calibration parameters;
the camera internal parameter calibration module is further configured to: obtaining a calibration plate photo generated by a camera; the photo of the calibration plate is led into a preset tool to be calculated to obtain camera internal parameter, and the camera internal parameter comprises: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection error;
the L2C calibration module is further configured to: acquiring camera internal parameter of a camera; filling in a configuration file according to the camera intrinsic parameters; importing the photo, the laser point cloud and the configuration file into a preset calibration program to obtain an L2C calibration parameter through calculation;
the C2I calibration module is further configured to: acquiring an L2C calibration parameter; importing the L2I calibration parameters and the L2C calibration parameters into preset program software, and generating the C2I calibration parameters through a preset formula; and is also provided with
The preset formula comprises: c2i=l2i×l2c (-1).
Optionally, the primary and secondary lidar calibration module is further configured to: collecting a main laser point cloud and a secondary laser point cloud generated by the main laser radar and the secondary laser radar facing the same scene at the same moment; leading the main laser point cloud and the auxiliary laser point cloud into a preset calibration program for resolving to obtain main and auxiliary laser radar calibration parameters;
The secondary lidar and inertial navigation calibration module is further configured to: and importing the L2I calibration parameters and the main and auxiliary laser radar calibration parameters into a preset calibration program to perform calculation so as to obtain the calibration parameters between the auxiliary laser radar and the inertial navigation.
According to another aspect of the present invention, there is also provided a method of calibrating parameters of a multi-sensor, comprising:
establishing a first coordinate system with the total station as an origin by the total station, and acquiring coordinate values of a plurality of sensors, wherein the plurality of sensors comprise: the coordinate values comprise an X value, a Y value and a Z value of the sensor in a first coordinate system;
converting the first coordinate system into a second coordinate system taking inertial navigation as an original point, wherein a target coordinate value generated by converting coordinate values in the second coordinate system is recorded in the second coordinate system, the target coordinate value comprises a first target coordinate value of a laser radar, a second target coordinate value of inertial navigation, a third target coordinate value of a GNSS antenna and a fourth target coordinate value of a camera, and the target coordinate value comprises X values, Y values and Z values of various sensors in the second coordinate system;
Calculating lever arm values between one or more target coordinate values of the first target coordinate value, the second target coordinate value, the third target coordinate value and the fourth target coordinate value and inertial navigation coordinate values, wherein the inertial navigation coordinate values are origins in a second coordinate system;
calculating an L2I calibration parameter according to the lever arm value, wherein the L2I calibration parameter is used for calibrating the relative position relation between the laser radar and the inertial navigation;
calculating camera internal parameter of the camera according to the data acquired by the camera;
calculating an L2C calibration parameter according to the camera internal parameter, wherein the L2C calibration parameter is used for calibrating the relative position relationship between the main laser radar and the camera;
C2I calibration parameters are obtained through calculation according to the L2I calibration parameters and the L2C calibration parameters, and the C2I calibration parameters are used for calibrating the relative position relationship between the camera and the inertial navigation;
collecting a main laser point cloud and a secondary laser point cloud generated by the main laser radar and the secondary laser radar facing the same scene at the same moment;
leading the main laser point cloud and the auxiliary laser point cloud into a first preset calibration program for resolving to obtain main and auxiliary laser radar calibration parameters, wherein the main and auxiliary laser radar calibration parameters are used for calibrating the relative position relationship between the main laser radar and the auxiliary laser radar;
The L2I calibration parameters and the main and auxiliary laser radar calibration parameters are led into a second preset calibration program to be resolved, so that the calibration parameters between the auxiliary laser radar and the inertial navigation are obtained, and the calibration parameters between the auxiliary laser radar and the inertial navigation are used for calibrating the relative position relationship between the auxiliary laser radar and the auxiliary inertial navigation.
Optionally, the first coordinate system and the second coordinate system further include: information acquisition vehicle front wheel points and rear wheel points;
the step of converting the first coordinate system into a second coordinate system having inertial navigation as an origin comprises:
importing the first coordinate system into a preset program;
connecting the front wheel point and the rear wheel point in the first coordinate system;
making a vertical line along the rear wheel, and measuring an included angle between the connecting line and the vertical line;
rotating all the measuring points in the first coordinate system by taking the rear wheel points as centers along the connecting line until the measuring points coincide with the vertical line;
redefining coordinate axes in the first coordinate system, generating a second coordinate system by taking the inertial navigation point as a coordinate origin, wherein a vertical line is a Y-axis positive direction, and a vertical right side is an X-axis positive direction;
and calculating coordinates and Z values of a plurality of sensor points in the second coordinate system to generate a first target coordinate value, a second target coordinate value, a third target coordinate value and a fourth target coordinate value.
Optionally, the step of calculating a lever arm value from the first coordinate to the center of the inertial navigation coordinate system includes:
calculating a first azimuth angle from the rear wheel to the front wheel in the first coordinate by using an azimuth angle calculation formula, and calculating a second azimuth angle from the inertial navigation to each measuring point in the first coordinate;
calculating a linear distance from the inertial navigation to the measuring point by the following formula:
△S inertial navigation-measuring point ＝√(△X 2 Inertial navigation-measuring point +△Y 2 Inertial navigation-measuring point ) Wherein DeltaX 2 Inertial navigation-measuring point Representing the square of the X-axis distance from inertial navigation to the measurement point, ΔY 2 Inertial navigation-measuring point Representing the square of the Y-axis distance that is inertial to the measurement point;
obtaining an azimuth angle difference delta alpha by subtracting the first azimuth angle from the second azimuth angle 1 ；
With inertial navigation coordinates as origin, i.e. X Inertial navigation ＝0，Y Inertial navigation =0; calculating a measurement point by the following formulaCoordinate values of (2):
X measuring point ＝X Inertial navigation +S Inertial navigation-measuring point *sin△α 1 ；
Y Measuring point ＝Y Inertial navigation +S Inertial navigation-measuring point *cos△α 1 ；
Z Measuring point ＝Z Center of measuring point -Z Inertial navigation axis center ；
Wherein X is Measuring point, Y Measuring point Z is as follows Measuring point Representing the coordinate value of the measurement point in a coordinate system with inertial navigation coordinates as the origin, S Inertial navigation-measuring point Representing the linear distance of inertial navigation to the measurement point.
Optionally, the step of calculating camera intrinsic parameters of the camera from the data collected by the camera comprises:
obtaining a calibration plate photo generated by a camera;
importing the calibration plate photo into a preset tool to obtain camera internal parameter by means of calculation;
the camera intrinsic parameters include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection errors.
Optionally, the step of calculating the L2C calibration parameter according to the camera internal parameter includes:
acquiring calibration plate data of different preset positions, heights and angle rotation postures by a camera and a laser radar, wherein the calibration plate data comprise photos and laser point clouds;
acquiring camera internal parameter of a camera;
filling in a configuration file according to the camera intrinsic parameters;
and importing the photo, the laser point cloud and the configuration file into a preset calibration program to obtain the L2C calibration parameters through calculation.
Optionally, the step of calculating the C2I calibration parameter according to the L2I calibration parameter and the L2C calibration parameter includes:
importing the L2I calibration parameters and the L2C calibration parameters into preset program software, and generating the C2I calibration parameters through a preset formula;
the preset formula comprises: c2i=l2i×l2c (-1).
According to another aspect of the present invention, there is also provided a machine-readable storage medium having stored thereon a machine-executable program which, when executed by a processor, implements a method of calibrating parameters for a multisensor of any of the above.
According to yet another aspect of the present invention, there is also provided a computer device comprising a memory, a processor and a machine executable program stored on the memory and running on the processor, and a method for implementing any of the above-mentioned multi-sensor calibration parameters when the processor executes the machine executable program.
In the scheme of the invention, a first coordinate system taking the total station as an origin is established through the total station, and coordinate values of a plurality of sensors are obtained, wherein the coordinate values comprise a first coordinate value of a laser radar, a second coordinate value of inertial navigation, a third coordinate value of a GNSS antenna and a fourth coordinate value of a camera; converting the first coordinate system into a second coordinate system taking inertial navigation as an original point, wherein a target coordinate value generated by converting the coordinate values in the second coordinate system is recorded in the second coordinate system, the target coordinate value comprises a first target coordinate value of a laser radar, a second target coordinate value of inertial navigation, a third target coordinate value of a GNSS antenna and a fourth target coordinate value of a camera, and a lever arm value between one or more target coordinate values and the inertial navigation coordinate values in the first target coordinate value, the second target coordinate value, the third target coordinate value and the fourth target coordinate value is calculated; calculating to obtain an L2I calibration parameter according to the route information collected by the information collection vehicle and the lever arm value of the sensor; calculating to obtain camera internal parameter according to the calibration plate photo generated by the camera; acquiring calibration plate data of different preset positions, heights and angle rotation postures through a camera and a laser radar, and calculating according to the calibration plate data and camera internal parameters to obtain L2C calibration parameters; importing the L2I calibration parameters and the L2C calibration parameters into preset program software, and generating C2I calibration parameters through a preset conversion formula; collecting a main laser point cloud and a secondary laser point cloud generated by the main laser radar and the secondary laser radar facing the same scene at the same moment; leading the main laser point cloud and the auxiliary laser point cloud into a first preset calibration program for resolving to obtain main and auxiliary laser radar calibration parameters; and importing the L2I calibration parameters and the main and auxiliary laser radar calibration parameters into a second preset calibration program to perform calculation so as to obtain the calibration parameters between the auxiliary laser radar and the inertial navigation. By the method, the position relations between the sensors and inertial navigation on the information acquisition vehicle can be determined through the calibration parameters, and the relative position relations among different sensors are fused in the same inertial navigation coordinate system, so that the acquired road information is conveniently integrated in a unified coordinate system by the subsequent information acquisition vehicle, and map production and quality inspection are carried out.
The above, as well as additional objectives, advantages, and features of the present invention will become apparent to those skilled in the art from the following detailed description of a specific embodiment of the present invention when read in conjunction with the accompanying drawings.
Drawings
Some specific embodiments of the invention will be described in detail hereinafter by way of example and not by way of limitation with reference to the accompanying drawings. The same reference numbers will be used throughout the drawings to refer to the same or like parts or portions. It will be appreciated by those skilled in the art that the drawings are not necessarily drawn to scale. In the accompanying drawings:
FIG. 1 is a schematic diagram of a plurality of sensor locations and coordinate axes in a vehicle according to one embodiment of the invention;
FIG. 2 is a schematic diagram of the mounting locations of a plurality of sensors on an information collecting vehicle in a method of calibrating parameters of a multi-sensor according to one embodiment of the invention;
FIG. 3 is a schematic view of the installation location of the total station when measuring the sensor information shown in FIG. 2;
FIG. 4 is a schematic architecture diagram of a multi-sensor calibration system according to one embodiment of the invention;
FIG. 5 is a flow chart of a method of calibrating parameters for multiple sensors according to one embodiment of the invention;
FIG. 6 is a schematic diagram of a total station of a method for calibrating parameters of multiple sensors after the coordinates are imported into computer aided design software according to one embodiment of the present invention;
FIG. 7 is a schematic diagram of the transformed coordinates of FIG. 6 with computer aided design software;
FIG. 8 is a schematic diagram of a machine-readable storage medium in a method of calibrating parameters for multiple sensors according to one embodiment of the invention; and
FIG. 9 is a schematic diagram of a computer device in a method of calibrating parameters for multiple sensors according to one embodiment of the invention.
Detailed Description
It should be understood by those skilled in the art that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention, and the some embodiments are intended to explain the technical principles of the present invention and are not intended to limit the scope of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive effort, based on the embodiments provided by the present invention, shall still fall within the scope of protection of the present invention.
FIG. 1 is a schematic diagram of a plurality of sensor coordinate axes according to one embodiment of the invention. Among them, 11, 12 and 13 are cameras, and one optional example of the coordinate axes is: the X axis is right along the vehicle traveling direction, the Y axis is right above the vehicle, and the Z axis is used for indicating the position of the camera and is consistent with the vehicle traveling direction.
14 is a lidar, an alternative example of the coordinate axis of which is such that the X-axis is to the left in the direction of travel of the vehicle, the Y-axis is coincident with or opposite to the direction of travel of the vehicle, and the Z-axis is directly above the vehicle; 15 is inertial navigation, and an alternative example of the coordinate axis thereof is that the X axis is rightward along the traveling direction of the vehicle, the Y axis is consistent with or opposite to the traveling direction of the vehicle, and the Z axis is directly above the vehicle.
It should be noted that, for the coordinate system of each sensor, those skilled in the art may set the coordinate system according to the actual situation, and fig. 1 is only an example.
Because the sensors have a set of own coordinate system, the coordinate values of the sensors are required to be finally unified into the set of coordinate system in the process of statistics, the method provides a method for fusing the coordinates of the sensors in the same inertial navigation coordinate system, namely a method for calibrating the position relation of different sensors relative to the inertial navigation.
FIG. 2 is a schematic diagram of the mounting locations of a plurality of sensors on an information collecting vehicle in a method of calibrating parameters of a multi-sensor according to one embodiment of the invention.
Fig. 3 is a schematic view of an installation position when the total station measures the sensor information shown in fig. 2. The total station is a total station type electronic distance meter (Electronic Total Station), is a high-technology measuring instrument integrating light, machine and electricity, and is a surveying instrument system integrating the functions of measuring horizontal angle, vertical angle, distance (inclined distance and flat distance) and height difference. It should be noted that, the setup position of the total station in fig. 3 is only a specific example, and when the total station is set up, first, a position setting apparatus capable of observing as many reference points of each sensor as possible is found, and the apparatus is leveled, and the error is required to be less than 10″ during leveling. Then, the operator enters the operation interface, freely establishes a station at the position, then performs coordinate measurement by aligning any position, and stores the coordinates of each point. The measuring point positions are the inertial navigation coordinate axis center, the main laser coordinate axis center, the antenna phase center and the same side of the front wheel and the rear wheel.
FIG. 4 is a schematic architecture diagram of a multi-sensor calibration system according to one embodiment of the invention. The multi-sensor calibration system may include an information acquisition vehicle 410 and a calibration device 420, where the information acquisition vehicle 410 may be a vehicle or other mobile acquisition device with various sensors, including: laser radar, inertial navigation, GNSS antenna, camera, etc., and the above mentioned sensors can record and collect peripheral data by their own coordinate system.
The calibration device 420 can calibrate the position relation among the plurality of sensors through the data acquired by the plurality of sensors in the information acquisition vehicle 410, so that the data acquired by the plurality of sensors are fused in a unified coordinate system, and preparation is provided for the production and quality inspection of the subsequent high-precision map.
The calibration device 420 may include: the system comprises a lever arm value measurement and calculation module 421, an L2I calibration module 422, a camera internal parameter calibration module 423, an L2C calibration module 424, a C2I calibration module 425, a main and auxiliary laser radar calibration module 426 and an auxiliary laser radar and inertial navigation calibration module 427.
The lever arm value measurement calculation module 421 is configured to measure and calculate a lever arm value from the sensor to the target position. Establishing a first coordinate system with the total station as an origin by the total station, and acquiring coordinate values of a plurality of sensors, wherein the plurality of sensors comprise: the coordinate values comprise an X value, a Y value and a Z value of the sensor in a first coordinate system;
Converting the first coordinate system into a second coordinate system taking inertial navigation as an original point, wherein a target coordinate value generated by converting coordinate values in the second coordinate system is recorded in the second coordinate system, the target coordinate value comprises a first target coordinate value of a laser radar, a second target coordinate value of inertial navigation, a third target coordinate value of a GNSS antenna and a fourth target coordinate value of a camera, and the target coordinate value comprises X values, Y values and Z values of various sensors in the second coordinate system;
and calculating lever arm values between one or more of the first target coordinate value, the second target coordinate value, the third target coordinate value and the fourth target coordinate value and inertial navigation coordinate values, wherein the inertial navigation coordinate values are origins in the second coordinate system.
The L2I calibration module 422 is configured to calibrate a relative positional relationship between the lidar and the inertial navigation. The information acquisition vehicle acquires the selected route information, the route information and the lever arm value of the GNSS antenna calculated in the lever arm value measurement calculation module 421 are converted into a coordinate track information file, and then the coordinate track information file and the lever arm value of the laser radar are converted into L2I calibration parameters.
The camera internal parameter calibration module 423 is configured to determine a specific parameter configuration in the camera, capture a calibration board at a preset position through a camera installed on the information acquisition vehicle, and obtain specific internal parameter of each camera according to the captured photo. An alternative embodiment of the module is as follows: the photo of the calibration plate is led into a preset tool to obtain the internal parameters of the camera by means of calculation, and one specific example of the preset tool is as follows: camera calibration (camera calibration) tool in MATLAB, camera parameters include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection errors.
The L2C calibration module 424 is configured to calibrate a relative positional relationship between the main lidar and the camera, collect, by using the camera and the lidar installed on the information collecting vehicle, a preset number of calibration board data, where the calibration board data may include a photo and a laser point cloud, and then calculate to obtain an L2C calibration parameter according to the camera internal parameter obtained by the camera internal parameter calibration module 423 and the calibration board data. An alternative embodiment of the module is as follows: filling in a configuration file according to the camera internal parameter obtained by the camera internal parameter calibration module 423; and importing the photo, the laser point cloud and the configuration file in the calibration plate data into a preset calibration program to obtain the L2C calibration parameters through calculation.
The C2I calibration module 425 is configured to calibrate a relative positional relationship between the camera and the inertial navigation, and calculate a C2I calibration parameter from the L2I calibration parameter obtained by the L2I calibration module 422 and the L2C calibration parameter obtained by the L2C calibration module 424. An alternative embodiment of the module is as follows: and importing the L2I calibration parameters and the L2C calibration parameters into MATLAB software to perform calibration parameter conversion through a preset formula, so as to obtain the C2I calibration parameters.
The primary and secondary laser radar calibration module 426 is an L2L (secondary) calibration module, and is configured to calibrate a relative positional relationship between a primary laser radar and a secondary laser radar, and collect, by using a primary and secondary laser radar installed on an information collecting vehicle, a primary laser point cloud and a secondary laser point cloud generated by facing the same scene at the same moment; and leading the main laser point cloud and the auxiliary laser point cloud into a preset calibration program for resolving to obtain L2L (auxiliary) calibration parameters.
The auxiliary laser radar and inertial navigation calibration module 427 is an L (auxiliary) 2I calibration module, and the L (auxiliary) 2I calibration parameter is calculated by the L2I calibration parameter obtained by the L2I calibration module 422 and the L2L (auxiliary) calibration parameter obtained by the main and auxiliary laser radar calibration module 426.
The L2I calibration parameter, the C2I calibration parameter and the L (auxiliary) 2I calibration parameter can be calculated according to the data acquired by the sensors on each information acquisition vehicle through the processing of the multi-sensor calibration system, namely, the relative position relation among the main laser radar, the camera and the auxiliary laser radar relative to inertial navigation is determined, so that when the data are acquired by the main laser radar, the camera and the auxiliary laser radar subsequently, the data can be converted into a coordinate system taking inertial navigation as an origin according to the calibration parameters, and finally, the high-precision map is manufactured and quality inspected.
FIG. 5 is a flow chart of a method for calibrating parameters for multiple sensors according to one embodiment of the invention. The process may include:
in step S501, a first coordinate system with the total station as an origin is established by the total station, and coordinate values of a plurality of sensors are acquired. The plurality of sensors may include: the coordinate values may include a first coordinate value of the laser radar, a second coordinate value of the inertial navigation, a third coordinate value of the GNSS antenna, and a fourth coordinate value of the camera, and the coordinate values include an X value, a Y value, and a Z value of the corresponding sensor in the first coordinate system.
It should be noted that: when the total station is used for measurement, firstly, a position setting instrument capable of observing the reference points of each sensor as many as possible is found, the instrument is leveled, and the error requirement during leveling is less than 10'; then, the operator enters the operation interface, freely establishes a station at the position, then performs coordinate measurement by aligning any position, and stores the coordinates of each point. The measuring point position comprises an inertial navigation coordinate axis center, a main laser coordinate axis center, an antenna phase center and the same side of the front wheel and the rear wheel.
In step S502, the first coordinate system is converted into a second coordinate system with inertial navigation as an origin. The second coordinate system records a target coordinate value generated by converting the coordinate value in the second coordinate system, wherein the target coordinate value comprises a first target coordinate value of the laser radar, a second target coordinate value of inertial navigation, a third target coordinate value of the GNSS antenna and a fourth target coordinate value of the camera, and the target coordinate value comprises X values, Y values and Z values of various sensors in the second coordinate system.
In some embodiments of the present step, the method of calculating may select a graph, and the step of graph may include: counting the coordinate values of the plurality of sensors measured in the step S501 into a table; the X and Y coordinates of the table data are exchanged and imported into computer aided design software, wherein the purpose of the XY coordinate exchange is to convert a mapping coordinate system generated by the total station into a mathematical coordinate system in the computer aided design software; connecting the front wheel points and the rear wheel points in the computer aided design software; making a vertical line along the rear wheel, and measuring an included angle between the connecting line and the vertical line; rotating all the measuring points along the connecting line by taking the rear wheel point as the center until the measuring points coincide with the vertical line; redefining coordinate axes, generating a second coordinate system by taking an inertial navigation point as a coordinate origin, wherein a vertical line is a Y-axis positive direction, and a vertical right side is an X-axis positive direction; and calculating coordinates and Z values of a plurality of sensor points in the second coordinate system to generate a first target coordinate value, a second target coordinate value, a third target coordinate value and a fourth target coordinate value.
Among other things, an alternative example of computer aided design software is: CAD, a person skilled in the art can choose the computer aided design software to be used according to the actual situation. FIG. 6 is a schematic diagram of a total station of a method for calibrating parameters of multiple sensors after the coordinates are imported into computer aided design software according to one embodiment of the present invention; the position of the inertial navigation, lidar, antenna and front and rear wheels of the vehicle in a mathematical coordinate system is shown in the schematic diagram.
FIG. 7 is a schematic diagram of the transformed coordinates of FIG. 8 through the computer aided design software.
In other embodiments of this step, the method of calculation may select a table calculation method, and the step of the table calculation method may include: calculating a first azimuth angle from the rear wheel to the front wheel in the first coordinate by using an azimuth angle calculation formula, and calculating a second azimuth angle from the inertial navigation to each measuring point in the first coordinate; one specific application of the azimuth angle estimation formula is as follows:
α rear wheel-front wheel O→rear wheel azimuth + & lt O rear wheel front wheel ± 180 °, the formula is used for calculating the azimuth angle from the rear wheel to the front wheel;
the application of a second azimuth angle centered on inertial navigation to each measurement point in the first coordinate is illustrated as:
In calculating the azimuth angle that is inertial to GNSS1 (antenna 1), the formula is as follows:
α inertial navigation-GNSS 1 =o1→inertial navigation azimuth angle ++o1 inertial navigation GNSS1±180°; wherein O1 is the right front of inertial navigation and is parallel to the connecting line of O-rear wheel.
The linear distance that is inertial to each measurement point is then calculated by the following formula:
△S inertial navigation-measuring point ＝√(△X 2 Inertial navigation-measuring point +△Y 2 Inertial navigation-measuring point ) Wherein DeltaX 2 Inertial navigation-measuring point Representing the square of the X-axis distance from inertial navigation to the measurement point, ΔY 2 Inertial navigation-measuring point Representing the square of the Y-axis distance that is inertial to the measurement point; obtaining an azimuth angle difference delta alpha by subtracting the first azimuth angle from the second azimuth angle 1 The method comprises the steps of carrying out a first treatment on the surface of the With inertial navigation coordinates as origin, i.e. X Inertial navigation ＝0，Y Inertial navigation =0; calculating the coordinate value of the measurement point by the following formula:
X measuring point ＝X Inertial navigation +S Inertial navigation-measuring point *sin△α 1 ；
Y Measuring point ＝Y Inertial navigation +S Inertial navigation-measuring point *cos△α 1 ；
Z Measuring point ＝Z Center of measuring point -Z Inertial navigation axis center ；
Wherein X is Measuring point, Y Measuring point Z is as follows Measuring point Representing the coordinate value of the measurement point in a coordinate system with inertial navigation coordinates as the origin, S Inertial navigation-measuring point Representing the linear distance of inertial navigation to the measurement point.
In step S503, lever arm values between one or more of the first, second, third, and fourth target coordinate values and the inertial navigation coordinate value are calculated. The inertial navigation coordinate value is the origin in the second coordinate system.
And step S504, calculating according to the lever arm value to obtain the L2I calibration parameter. The method comprises the following steps: and acquiring route information acquired by the information acquisition vehicle, and converting the route information and the lever arm value of the GNSS antenna into a coordinate track information file. And converting the coordinate track information file and the lever arm value of the laser radar into L2I calibration parameters.
One embodiment of collecting route information is as follows: selecting more than a preset number of 90-degree turns, wherein planar block-shaped objects such as flat building walls, signs and the like are required to be arranged at the turns; the GPS satellite information in the acquisition route is strong, and the signal shielding scenes such as tunnels, under an overhead and the like are avoided; one example of the preset number is 20, which can reduce resource consumption without affecting data accuracy.
Some embodiments of translating the route information and lever arm values of the GNSS antenna into a coordinate track information file are as follows: after the collected engineering gps file is subjected to track calculation, the antenna lever arm value generated in the step S503 is used as a configuration file to be input into a model calculation program; and outputting a result nav track file.
The coordinate track information file and the lever arm value of the laser radar are converted into L2I calibration parameters, such as: performing calibration calculation by using a preset calibration program; inputting the main laser lever arm value generated in the step S503 as a configuration file into a preset calibration program, and resolving after correlating the nav track file; and outputting the L2I calibration parameters by the final result.
Wherein, the L2I calibration parameter format is a 4x4 matrix, and one specific example of the 4x4 matrix is shown in table 1:
TABLE 1
-0.998112 -0.061413 -0.000595 -0.005000
0.061408 -0.998091 -0.006532 1.123000
0.000995 -0.006483 0.999978 1.388000
0.000000 0.000000 0.000000 1.000000
The number of 3x3 in the matrix records the rotation angle of the main laser relative to the inertial navigation at X, Y, Z axis, the 4 th column records the lever arm value of the main laser, and the 4 th number represents the identity matrix, and it should be noted that the expression mode of the L2I calibration parameter can be set by a person skilled in the art according to the actual situation.
In step S505, camera intrinsic parameters of the camera are calculated from the data collected by the camera. The method comprises the following steps: obtaining a calibration plate photo generated by a camera; the photo of the calibration plate is led into a preset tool to obtain the internal parameters of the camera by means of calculation, and one specific example of the preset tool is as follows: camera calibration (camera calibration) tool in MATLAB; the camera intrinsic parameters include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection errors.
It should be noted that, the process of obtaining the photo of the calibration plate needs to pay attention to the following requirements:
1. shooting photos of the calibration plates with different angles by using a camera, wherein the included angle between the calibration plates and the plane of the camera is not more than 70 degrees, so that the overlarge angle is avoided, the cross points of the black-white plates are blurred, and the program cannot be identified;
2. the shooting calibration plate needs that the black-and-white frames are all in the view angle of the camera, and the middle is free from shielding;
3. The calibration plate is positioned at the center of the camera visual field, and the checkerboard is kept to be maximized in the camera visual field;
4. the four sides of the four corners of the photo are covered by the calibration plates.
And S506, calculating to obtain L2C calibration parameters according to the camera internal parameter. The method comprises the following steps: acquiring preset number of calibration plate data through a camera and a laser radar installed on an information acquisition vehicle, wherein the calibration plate data can comprise photos and laser point clouds; filling in a configuration file according to the camera intrinsic parameters; importing the photo, the laser point cloud and the configuration file into a preset calibration program to obtain an L2C calibration parameter through calculation;
the following requirements need to be paid attention to in the process of collecting calibration plate data:
1. the calibration plates are distributed at different positions and distances from the front, the back, the left and the right of the camera and the laser radar;
2. the calibration plate performs angle rotation postures with different heights at different position points;
3. when the camera, the laser radar and the calibration plate are relatively static at the same time, data are collected;
4. sequentially and uniformly acquiring data of different preset positions, heights and angle rotation postures. Wherein, an optional example of the preset number is 69, through practical verification, 69 data are collected, and the resource loss can be reduced while the data are kept accurate.
And S507, calculating to obtain the C2I calibration parameters according to the L2I calibration parameters and the L2C calibration parameters. The L2I calibration parameters obtained in the step S504 and the L2C calibration parameters obtained in the step S506 are imported into preset program software, and C2I calibration parameters are generated through a preset formula.
An alternative example of a preset formula is: c2i=l2i×l2c (-1), where L2I represents the L2I parameter matrix generated in step S504 and L2C represents the L2C parameter matrix generated in step S506.
Step S508, collecting a primary laser point cloud and a secondary laser point cloud generated by the primary laser radar and the secondary laser radar facing the same scene at the same time. The process of collecting the main laser point cloud and the auxiliary laser point cloud generated by the main laser radar and the auxiliary laser radar facing the same scene at the same moment needs to pay attention to the following requirements:
1. in a remote road section without vehicle and pedestrian interference, a secondary road is added within four lanes, and the center is free of isolation belts. Two sides are provided with more rods such as street lamps, trunks and the like;
2. during collection, no vehicles, electric vehicles, pedestrians and the like pass through basically, so that the easily disturbed factors of shrubs, flourishing leaves and other scenes are avoided;
3. the S-shaped collection process is carried out, and the replacement position is started after the collection process is carried out for 15 seconds by standing at one roadside.
The requirements can accurately collect the laser point cloud generated when the main laser and the auxiliary laser face the same object, and other interference factors are avoided.
Step S509, the primary laser point cloud and the secondary laser point cloud are led into a first preset calibration program for calculation, and primary and secondary laser radar calibration parameters are obtained.
Step S510, the L2I calibration parameters and the main and auxiliary laser radar calibration parameters are imported into a second preset calibration program for resolving, and the calibration parameters between the auxiliary laser radar and the inertial navigation are obtained.
According to the method, the L2I calibration parameters, the C2I calibration parameters and the L (auxiliary) 2I calibration parameters are finally obtained, and the relative position relationship between the main laser radar and the auxiliary laser radar as well as between the camera and the inertial navigation is determined, so that the relative position relationship between different sensors is fused under the same inertial navigation coordinate system, road information which is integrated and collected by a subsequent information collecting vehicle is conveniently integrated into a unified coordinate system, and map production and quality inspection are performed.
The present implementation also provides a machine-readable storage medium and a computer device. Fig. 8 is a schematic diagram of a machine-readable storage medium 801 according to one embodiment of the invention, and fig. 9 is a schematic diagram of a computer device 903 according to one embodiment of the invention.
The machine-readable storage medium 801 has stored thereon a machine-executable program 802, which when executed by a processor, implements the method of multi-sensor calibration parameters of any of the embodiments described above.
The computer device 903 may include a memory 901, a processor 902, and a machine executable program 802 stored on the memory 901 and running on the processor 902, and the processor 902 implements the method of any of the embodiments described above when executing the machine executable program 802.
It should be noted that the logic and/or steps represented in the flow diagrams or otherwise described herein, e.g., calculating a lever arm value, may be embodied in any machine-readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
For the purposes of this description of the embodiment, a machine-readable storage medium 801 can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the machine-readable storage medium 801 include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the machine-readable storage medium 801 may even be paper or other suitable medium upon which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system.
The computer device 903 may be, for example, a server, a desktop computer, a notebook computer, a tablet computer, or a smartphone. In some examples, the computer device 903 may be a cloud computing node. The computer device 903 may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc. that perform particular tasks or implement particular abstract data types. The computer device 903 may be implemented in a distributed cloud computing environment where remote processing devices, linked through a communications network, perform tasks. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
The computer device 903 may comprise a processor 902 adapted to execute stored instructions, a memory 901 providing temporary storage for the operation of the instructions during operation. The processor 902 may be a single core processor, a multi-core processor, a computing cluster, or any number of other configurations. Memory 901 may include Random Access Memory (RAM), read only memory, flash memory, or any other suitable storage system.
The processor 902 may be connected via a system interconnect (e.g., PCI-Express, etc.) to an I/O interface (input/output interface) adapted to connect the computer device 903 to one or more I/O devices (input/output devices). The I/O devices may include, for example, a keyboard and a pointing device, which may include a touch pad or touch screen, among others. The I/O device may be a built-in component of the computer device 903 or may be a device externally connected to the computing device.
The processor 902 may also be linked by a system interconnect to a display interface adapted to connect the computer device 903 to a display device. The display device may include a display screen as a built-in component of the computer device 903. The display device may also include a computer monitor, television, projector, or the like, which is externally connected to the computer device 903. Further, a network interface controller (network interface controller, NIC) may be adapted to connect the computer device 903 to a network through a system interconnect. In some embodiments, the NIC may use any suitable interface or protocol (such as an internet small computer system interface, etc.) to transfer data. The network may be a cellular network, a radio network, a Wide Area Network (WAN), a Local Area Network (LAN), or the internet, among others. The remote device may be connected to the computing device through a network.
The flowcharts provided by this embodiment are not intended to indicate that the operations of the method are to be performed in any particular order, or that all of the operations of the method are included in all of each case. Furthermore, the method may include additional operations. Additional variations may be made to the above-described methods within the scope of the technical ideas provided by the methods of the present embodiments.
By now it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been shown and described herein in detail, many other variations or modifications of the invention consistent with the principles of the invention may be directly ascertained or inferred from the present disclosure without departing from the spirit and scope of the invention. Accordingly, the scope of the present invention should be understood and deemed to cover all such other variations or modifications.

Claims (12)

1. A multi-sensor calibration system, comprising:
an information collection vehicle, carrying a plurality of sensors, the sensor includes: the sensor can record and collect peripheral data by using a self coordinate system;
the calibration device is used for fusing the relative position relation of the sensors into the same inertial navigation coordinate system and comprises the following components:
The lever arm value measurement calculation module is used for calculating lever arm values from the GNSS antenna and the laser radar to the center of the inertial navigation coordinate system;
the L2I calibration module is used for calibrating the relative position relationship between the laser radar and the inertial navigation;
the camera internal parameter calibration module is used for determining specific parameter configuration in the camera;
the L2C calibration module is used for calibrating the relative position relationship between the main laser radar and the camera;
the C2I calibration module is used for calibrating the relative position relationship between the camera and the inertial navigation;
the main and auxiliary laser radar calibration module is used for calibrating the relative position relationship between the main laser radar and the auxiliary laser radar;
the auxiliary laser radar and inertial navigation calibration module is used for calibrating the relative position relationship between the auxiliary laser radar and the inertial navigation.
2. The multi-sensor calibration system of claim 1, wherein,
the lever arm value measurement calculation module is further configured to:
establishing a first coordinate system with the total station as an origin by the total station, and acquiring coordinate values of a plurality of sensors, wherein the plurality of sensors comprise: the system comprises a laser radar, inertial navigation, a GNSS antenna and a camera, wherein the coordinate values comprise a first coordinate value of the laser radar, a second coordinate value of the inertial navigation, a third coordinate value of the GNSS antenna and a fourth coordinate value of the camera, and the coordinate values comprise an X value, a Y value and a Z value of the sensor in the first coordinate system;
Converting the first coordinate system into a second coordinate system taking the inertial navigation as an origin, wherein a target coordinate value generated by converting the coordinate value in the second coordinate system is recorded in the second coordinate system, the target coordinate value comprises a first target coordinate value of the laser radar, a second target coordinate value of the inertial navigation, a third target coordinate value of the GNSS antenna and a fourth target coordinate value of the camera, and the target coordinate value comprises X values, Y values and Z values of the various sensors in the second coordinate system;
and calculating lever arm values between one or more target coordinate values of the first target coordinate value, the second target coordinate value, the third target coordinate value and the fourth target coordinate value and inertial navigation coordinate values, wherein the inertial navigation coordinate values are origins in the second coordinate system.
3. The multi-sensor calibration system of claim 2, wherein,
the L2I calibration module is further configured to: acquiring route information, and converting the route information and a lever arm value of the GNSS antenna into a coordinate track information file; converting the coordinate track information file and the lever arm value of the laser radar into L2I calibration parameters;
The camera internal parameter calibration module is further configured to: obtaining a calibration plate photo generated by the camera; the calibration plate photo is led into a preset tool to be calculated to obtain the camera internal parameter, and the camera internal parameter comprises: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection error;
the L2C calibration module is further configured to: acquiring camera internal parameter of the camera; filling in a configuration file according to the camera intrinsic parameters; importing the photo, the laser point cloud and the configuration file into a preset calibration program to obtain the L2C calibration parameters through calculation;
the C2I calibration module is further configured to: acquiring an L2C calibration parameter; importing the L2I calibration parameters and the L2C calibration parameters into preset program software, and generating C2I calibration parameters through a preset formula; and is also provided with
The preset formula comprises: c2i=l2i×l2c (-1).
4. The multi-sensor calibration system of claim 3 wherein,
the primary and secondary laser radar calibration module is further configured to: collecting a main laser point cloud and a secondary laser point cloud generated by the main laser radar and the secondary laser radar facing the same scene at the same moment; the main laser point cloud and the auxiliary laser point cloud are led into a preset calibration program to be resolved, and main and auxiliary laser radar calibration parameters are obtained;
The secondary lidar and inertial navigation calibration module is further configured to: and importing the L2I calibration parameters and the main and auxiliary laser radar calibration parameters into a preset calibration program to perform calculation so as to obtain the calibration parameters between the auxiliary laser radar and the inertial navigation.
5. A method of calibrating parameters for a multi-sensor, comprising:
establishing a first coordinate system with the total station as an origin by the total station, and acquiring coordinate values of a plurality of sensors, wherein the plurality of sensors comprise: the system comprises a laser radar, inertial navigation, a GNSS antenna and a camera, wherein the coordinate values comprise a first coordinate value of the laser radar, a second coordinate value of the inertial navigation, a third coordinate value of the GNSS antenna and a fourth coordinate value of the camera, and the coordinate values comprise an X value, a Y value and a Z value of the sensor in the first coordinate system;
converting the first coordinate system into a second coordinate system taking the inertial navigation as an origin, wherein a target coordinate value generated by converting the coordinate value in the second coordinate system is recorded in the second coordinate system, the target coordinate value comprises a first target coordinate value of the laser radar, a second target coordinate value of the inertial navigation, a third target coordinate value of the GNSS antenna and a fourth target coordinate value of the camera, and the target coordinate value comprises X values, Y values and Z values of the various sensors in the second coordinate system;
Calculating lever arm values between one or more target coordinate values of the first target coordinate value, the second target coordinate value, the third target coordinate value and the fourth target coordinate value and inertial navigation coordinate values, wherein the inertial navigation coordinate values are origins in the second coordinate system;
calculating an L2I calibration parameter according to the lever arm value, wherein the L2I calibration parameter is used for calibrating the relative position relationship between the laser radar and the inertial navigation;
calculating camera internal parameter of the camera according to the data acquired by the camera;
calculating an L2C calibration parameter according to the camera internal parameter, wherein the L2C calibration parameter is used for calibrating the relative position relationship between the main laser radar and the camera;
calculating a C2I calibration parameter according to the L2I calibration parameter and the L2C calibration parameter, wherein the C2I calibration parameter is used for calibrating the relative position relationship between a camera and the inertial navigation;
collecting a main laser point cloud and a secondary laser point cloud generated by the main laser radar and the secondary laser radar facing the same scene at the same moment;
the main laser point cloud and the auxiliary laser point cloud are led into a first preset calibration program to be resolved, so that main and auxiliary laser radar calibration parameters are obtained, and the main and auxiliary laser radar calibration parameters are used for calibrating the relative position relationship between the main laser radar and the auxiliary laser radar;
And importing the L2I calibration parameters and the main and auxiliary laser radar calibration parameters into a second preset calibration program to perform calculation so as to obtain the calibration parameters between the auxiliary laser radar and the inertial navigation, wherein the calibration parameters between the auxiliary laser radar and the inertial navigation are used for calibrating the relative position relationship between the auxiliary laser radar and the auxiliary inertial navigation.
6. The method for calibrating parameters of claim 5 wherein,
the first coordinate system and the second coordinate system further comprise: the information acquisition vehicle comprises a front wheel point and a rear wheel point;
the step of converting the first coordinate system into a second coordinate system having the inertial navigation as an origin includes:
importing the first coordinate system into a preset program;
connecting the front wheel points and the rear wheel points in the first coordinate system;
making a vertical line along the rear wheel, and measuring an included angle between the connecting line and the vertical line;
rotating all measurement points in the first coordinate system around the rear wheel point as a center along the connecting line until the measurement points coincide with the vertical line;
redefining coordinate axes in the first coordinate system, and generating the second coordinate system by taking an inertial navigation point as a coordinate origin, wherein the vertical line is a Y-axis positive direction, and the vertical right side is an X-axis positive direction;
And calculating coordinates and Z values of the plurality of sensor points in the second coordinate system to generate the first target coordinate value, the second target coordinate value, the third target coordinate value and the fourth target coordinate value.
7. The method for calibrating parameters of claim 5 wherein,
the step of calculating the lever arm value from the sensor to the center of the inertial navigation coordinate system according to the first coordinate comprises the following steps:
calculating a first azimuth angle from a rear wheel to a front wheel in the first coordinate and a second azimuth angle from inertial navigation to each measuring point in the first coordinate by an azimuth angle calculation formula;
calculating the linear distance from the inertial navigation to the measuring point by the following formula:
△S inertial navigation-measuring point ＝√(△X 2 Inertial navigation-measuring point +△Y 2 Inertial navigation-measuring point ) Wherein DeltaX 2 Inertial navigation-measuring point Representing the square of the X-axis distance from the inertial navigation to the measurement point, ΔY 2 Inertial navigation-measuring point Representing the square of the Y-axis distance from the inertial navigation to the measurement point;
subtracting the first azimuth from the second azimuth to obtain an azimuth difference Deltaalpha 1 ；
Taking the inertial navigation coordinate as an origin, namely X Inertial navigation ＝0，Y Inertial navigation =0; calculating the coordinate value of the measurement point by the following formula:
X Measuring point ＝X Inertial navigation +S Inertial navigation-measuring point *sin△α 1 ；
Y Measuring point ＝Y Inertial navigation +S Inertial navigation-measuring point *cos△α 1 ；
Z Measuring point ＝Z Center of measuring point -Z Inertial navigation axis center ；
Wherein X is Measuring point, Y Measuring point Z is as follows Measuring point Representing the coordinate value of the measurement point in a coordinate system with the inertial navigation coordinate as an origin, S Inertial navigation-measuring point Representing the linear distance of the inertial navigation to the measurement point.
8. The method for calibrating parameters of claim 5 wherein,
the step of calculating the camera intrinsic parameters of the camera from the data acquired by the camera comprises the following steps:
obtaining a calibration plate photo generated by the camera;
importing the calibration plate photo into a preset tool to obtain the camera intrinsic parameter through calculation;
the camera intrinsic parameters include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection errors.
9. The method for calibrating parameters of claim 5 wherein,
the step of calculating the L2C calibration parameter according to the camera internal parameter comprises the following steps:
acquiring calibration plate data of different preset positions, heights and angle rotation postures through the camera and the laser radar, wherein the calibration plate data comprise photos and laser point clouds;
Acquiring camera internal parameter of the camera;
filling in a configuration file according to the camera intrinsic parameters;
and importing the photo, the laser point cloud and the configuration file into a preset calibration program to obtain the L2C calibration parameters through calculation.
10. The method for calibrating parameters of claim 5 wherein,
the step of calculating the C2I calibration parameter according to the L2I calibration parameter and the L2C calibration parameter includes:
importing the L2I calibration parameters and the L2C calibration parameters into preset program software, and generating C2I calibration parameters through a preset formula;
the preset formula comprises: c2i=l2i×l2c (-1).
11. A machine readable storage medium having stored thereon a machine executable program which when executed by a processor implements a method of multi-sensor calibration parameters according to any of claims 5 to 10.
12. A computer device comprising a memory, a processor and a machine executable program stored on the memory and running on the processor, and the processor when executing the machine executable program implements a method of calibrating parameters of a multi-sensor according to any of claims 5 to 10.
CN202310472013.8A 2023-04-27 2023-04-27 System, method and machine-readable storage medium for calibrating parameters of multiple sensors Pending CN116576884A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310472013.8A CN116576884A (en) 2023-04-27 2023-04-27 System, method and machine-readable storage medium for calibrating parameters of multiple sensors

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310472013.8A CN116576884A (en) 2023-04-27 2023-04-27 System, method and machine-readable storage medium for calibrating parameters of multiple sensors

Publications (1)

Publication Number Publication Date
CN116576884A true CN116576884A (en) 2023-08-11

Family

ID=87538849

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310472013.8A Pending CN116576884A (en) 2023-04-27 2023-04-27 System, method and machine-readable storage medium for calibrating parameters of multiple sensors

Country Status (1)

Country Link
CN (1) CN116576884A (en)

Similar Documents

Publication Publication Date Title
CN108613628B (en) Overhead transmission line sag measurement method based on binocular vision
Fraser et al. Metric exploitation of still video imagery
CN100458359C (en) Small-displacement measuring system in long-distance plane
US20140336928A1 (en) System and Method of Automated Civil Infrastructure Metrology for Inspection, Analysis, and Information Modeling
CN109918977B (en) Method, device and equipment for determining idle parking space
CN111322994A (en) Large-scale cadastral survey method for intensive house area based on unmanned aerial vehicle oblique photography
CN108221603A (en) Road surface three-dimensional information detection device, the method and system of a kind of road
CN107356244B (en) Calibration method and device for road side unit antenna
CN111383279A (en) External parameter calibration method and device and electronic equipment
CN110044266B (en) Photogrammetry system based on speckle projection
CN109990703A (en) A kind of size detecting method and system of prefabricated components
WO2022025283A1 (en) Measurement processing device, method, and program
CN103389072A (en) An image point positioning precision assessment method based on straight line fitting
CN112990168B (en) Illegal land monitoring method and system
CN113592951A (en) Method and device for calibrating external parameters of vehicle-road cooperative middle-road side camera and electronic equipment
TWM552589U (en) Laser rangefinder with full-section scanning
CN109631841B (en) Method and device for measuring cross section of expressway based on laser projection
TW201907136A (en) Stereo image and laser scanning ranging integration method
CN116386373A (en) Vehicle positioning method and device, storage medium and electronic equipment
CN116576884A (en) System, method and machine-readable storage medium for calibrating parameters of multiple sensors
CN114754695B (en) Multi-view-field bridge deflection measuring device and method and storage medium
CN110058211B (en) Method and device for acquiring calibration initial value of vehicle-mounted LiDAR measurement system
CN115523929B (en) SLAM-based vehicle-mounted integrated navigation method, device, equipment and medium
CN113763463B (en) Method for determining position of acquisition equipment based on image data processing
CN113810591B (en) High-precision map operation system and cloud platform

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