CN113932835B - Calibration method and device for positioning lever arm of automatic driving vehicle and electronic equipment - Google Patents
Calibration method and device for positioning lever arm of automatic driving vehicle and electronic equipment Download PDFInfo
- Publication number
- CN113932835B CN113932835B CN202111546068.6A CN202111546068A CN113932835B CN 113932835 B CN113932835 B CN 113932835B CN 202111546068 A CN202111546068 A CN 202111546068A CN 113932835 B CN113932835 B CN 113932835B
- Authority
- CN
- China
- Prior art keywords
- information
- positioning
- positioning information
- lever arm
- center
- 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.)
- Active
Links
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
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Navigation (AREA)
Abstract
The application discloses a calibration method and device for a positioning lever arm of an automatic driving vehicle and electronic equipment, wherein the method comprises the following steps: acquiring initial lever arm information and positioning information of an inertial navigation system, wherein the lever arm information comprises distance information from the inertial navigation system to the center of a rear axle of the automatic driving vehicle; compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain initial positioning information of the center of a rear shaft; under the condition that the center of a rear axle of the automatic driving vehicle is positioned at the reference positioning point, acquiring positioning information of the reference positioning point and current positioning information of the center of the rear axle according to the initial positioning information of the center of the rear axle; and determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear shaft so as to finish the calibration of the positioning lever arm of the automatic driving vehicle. According to the method and the device, the lever arm information of the automatic driving vehicle is calibrated on line, so that the calibration efficiency of mass lever arm information is improved, and the subsequent fusion positioning precision is improved.
Description
Technical Field
The application relates to the technical field of automatic driving, in particular to a calibration method and device for a positioning lever arm of an automatic driving vehicle and electronic equipment.
Background
In an automatic driving scene, high-precision positioning is often required to be achieved through an integrated navigation positioning mode, namely, an error is controlled within a centimeter-level range as much as possible, so that accurate calibration needs to be performed on an integrated navigation positioning device in advance.
For an automatic driving control system, real-time high-precision positioning information of the center of a rear axle of an automatic driving vehicle needs to be known, an existing algorithm only compensates an inner lever arm, namely the distance from an inertial navigation system to a rear antenna, the inertial navigation system cannot be usually installed at the position of the center of the rear axle of the automatic driving vehicle due to design and structure reasons of the automatic driving vehicle, an outer lever arm needs to be compensated at the moment, namely the three-dimensional distance from the inertial navigation system to the center of the rear axle, lever arm compensation of the existing algorithm is performed off-line, real-time requirements cannot be met, and labor cost and time can be increased under a large-batch scene.
In addition, when the existing algorithm is used for combined navigation, only the position information of Real-time kinematic (RTK) is considered to be converted into the center of the rear axle, the position information of an Inertial Measurement Unit (IMU) is not considered, but is still the position information of the position of the Inertial navigation system, if the positioning is directly performed in a fusion mode, the fusion positioning precision is affected, and especially under the working conditions of turning and the like, the positioning error is rapidly increased.
Disclosure of Invention
The embodiment of the application provides a calibration method and device for a positioning lever arm of an automatic driving vehicle and electronic equipment, so that the calibration accuracy and the real-time performance of the positioning lever arm of the automatic driving vehicle are improved.
The embodiment of the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides a calibration method for a positioning lever arm of an autonomous vehicle, where the method includes:
acquiring initial lever arm information and positioning information of an inertial navigation system, wherein the lever arm information comprises distance information from the inertial navigation system to the center of a rear axle of an automatic driving vehicle, and the inertial navigation system is pre-installed on the automatic driving vehicle;
compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain initial positioning information of the center of the rear shaft;
under the condition that the center of a rear axle of the automatic driving vehicle is located at a reference positioning point, acquiring positioning information of the reference positioning point and current positioning information of the center of the rear axle according to initial positioning information of the center of the rear axle;
and determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear shaft so as to finish the calibration of the positioning lever arm of the automatic driving vehicle.
Optionally, the positioning information of the inertial navigation system includes first fusion positioning information output by the inertial navigation system and positioning information of a real-time differential positioning RTK device, and the obtaining the initial positioning information of the rear axle center by compensating the positioning information of the inertial navigation system using the initial lever arm information includes:
converting the first fusion positioning information output by the inertial navigation system and the positioning information of the RTK equipment to a target coordinate system;
based on extended Kalman filtering, performing fusion positioning processing on fusion positioning information output by an inertial navigation system under the target coordinate system and positioning information of the RTK equipment to obtain second fusion positioning information;
and compensating the second fusion positioning information by using the initial lever arm information to obtain the initial positioning information of the center of the rear axle.
Optionally, the first fusion positioning information output by the inertial navigation system refers to positioning information of a fused inertial measurement unit IMU, and the positioning information of the fused inertial measurement unit IMU is obtained by fusing the positioning information of the RTK device, the positioning information originally output by the IMU, and speed information of the chassis of the autonomous vehicle based on the extended kalman filter.
Optionally, the second fused positioning information includes a fused position and a fused speed, and the obtaining the initial positioning information of the rear axle center by using the initial lever arm information to compensate the second fused positioning information includes:
compensating the fused position according to the initial lever arm information to obtain the compensated position;
compensating the fused speed according to the initial lever arm information to obtain the compensated speed;
and taking the compensated position and the compensated speed as initial positioning information of the center of the rear shaft.
Optionally, the at least one reference positioning point is included, and the determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear axle includes:
determining a residual error between the positioning information of each datum positioning point and the corresponding current positioning information of the rear axle center;
constructing a lever arm information optimization algorithm according to the residual errors;
and determining the optimal lever arm information according to the lever arm information optimization algorithm.
Optionally, the positioning information of the reference positioning point is obtained by:
and acquiring positioning information of one or more positioning points in advance through the RTK equipment to serve as the positioning information of the reference positioning point.
Optionally, after determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the rear axle center, the method further includes:
and compensating the positioning information of the inertial navigation system by using the optimal lever arm information to obtain the final positioning information of the center of the rear axle.
In a second aspect, an embodiment of the present application further provides a calibration apparatus for a positioning lever arm of an autonomous vehicle, where the apparatus includes:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring initial lever arm information and positioning information of an inertial navigation system, the lever arm information comprises distance information from the inertial navigation system to the center of a rear axle of an automatic driving vehicle, and the inertial navigation system is pre-installed on the automatic driving vehicle;
the first compensation unit is used for compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain the initial positioning information of the center of the rear axle;
the second acquisition unit is used for acquiring positioning information of a reference positioning point and current positioning information of the rear axle center according to the initial positioning information of the rear axle center under the condition that the rear axle center of the automatic driving vehicle is positioned at the reference positioning point;
and the determining unit is used for determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear shaft so as to finish the calibration of the positioning lever arm of the automatic driving vehicle.
In a third aspect, an embodiment of the present application further provides an electronic device, including:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform any of the methods described above.
In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium storing one or more programs that, when executed by an electronic device including a plurality of application programs, cause the electronic device to perform any of the methods described above.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects: according to the calibration method of the positioning lever arm of the automatic driving vehicle, initial lever arm information and positioning information of an inertial navigation system are obtained firstly, wherein the lever arm information refers to distance information from the inertial navigation system to the center of a rear shaft of the automatic driving vehicle; then, compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain the initial positioning information of the center of the rear shaft; then, under the condition that the center of the rear axle of the automatic driving vehicle is positioned at the reference positioning point, acquiring positioning information of the reference positioning point and current positioning information of the center of the rear axle according to the initial positioning information of the center of the rear axle; and finally, determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear shaft so as to finish the calibration of the positioning lever arm of the automatic driving vehicle. According to the calibration method of the positioning lever arm of the automatic driving vehicle, the lever arm information of the automatic driving vehicle is calibrated on line, so that the calibration efficiency of mass lever arm information is improved, and the subsequent fusion positioning precision is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic flow chart illustrating a method for calibrating a lever arm of an autonomous vehicle in an embodiment of the present application;
FIG. 2 is a schematic diagram illustrating positioning accuracy before calibration of a lever arm of an autonomous vehicle in an embodiment of the present application;
FIG. 3 is a schematic diagram illustrating the calibrated positioning accuracy of a lever arm of an autonomous vehicle in an embodiment of the present application;
FIG. 4 is a schematic diagram of a calibration apparatus for a lever arm of an autonomous vehicle in an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some 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.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
The embodiment of the present application provides a method for calibrating a lever arm of a positioning lever of an autonomous vehicle, as shown in fig. 1, a schematic flow chart of the method for calibrating a lever arm of a positioning lever of an autonomous vehicle in the embodiment of the present application is provided, and the method at least includes the following steps S110 to S140:
step S110, obtaining initial lever arm information and positioning information of an inertial navigation system, wherein the lever arm information comprises distance information from the inertial navigation system to the center of a rear axle of an automatic driving vehicle, and the inertial navigation system is installed on the automatic driving vehicle in advance.
The calibration method of the positioning lever arm of the automatic driving vehicle can be executed by the automatic driving positioning system, the inertial navigation system is pre-installed on the automatic driving vehicle, the positioning lever arm can be understood as an outer lever arm and is used for representing the distance from the inertial navigation system to the center of a rear shaft of the automatic driving vehicle, in an actual scene, due to the fact that the automatic driving vehicle is different in driving working conditions and the like, information of the lever arm is not a fixed value, calibration of the lever arm is needed, and the situation that fusion positioning accuracy is reduced due to the existence of the lever arm is avoided as far as possible.
Based on this, when calibrating the positioning lever arm of the automatic driving vehicle, the embodiment of the application needs to acquire initial lever arm information and positioning information of the inertial navigation system, and the initial lever arm information can be determined according to an installation design drawing of the inertial navigation system. The inertial navigation system comprises an RTK device and an IMU inertial measurement unit, so that the positioning information of the inertial navigation system can be IMU positioning information fused and output by the inertial navigation system, and can also comprise positioning information output by the RTK device.
And step S120, compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain the initial positioning information of the center of the rear axle.
After the initial lever arm information is obtained, lever arm compensation can be performed on the positioning information output by the inertial navigation system by using the initial lever arm information, namely, the position of the center of the rear shaft is compensated, so that rough initial positioning information of the center of the rear shaft can be obtained.
Since the rough positioning information of the rear axle center is continuously changed along with the traveling of the autonomous vehicle, the rough positioning information can be updated and acquired in real time subsequently.
Step S130, under the condition that the center of the rear shaft of the automatic driving vehicle is located at a reference positioning point, acquiring positioning information of the reference positioning point and current positioning information of the center of the rear shaft according to the initial positioning information of the center of the rear shaft.
After the above steps are completed, a calibration process of the positioning lever arm may be performed, specifically, the automatic driving vehicle may be controlled to travel to a position of a reference positioning point, where the reference positioning point is a position point calibrated in advance, the rear axle center of the automatic driving vehicle is controlled to align with the reference positioning point, corresponding positioning point information is searched according to the rough positioning information of the rear axle center obtained in the above steps, and the positioning information of the rear axle center at this time is recorded.
And step S140, determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear axle so as to finish the calibration of the positioning lever arm of the automatic driving vehicle.
The positioning information corresponding to the reference positioning point can be regarded as positioning information with high positioning precision, the current positioning information of the center of the rear shaft compensated by the lever arm information at present is compared with the positioning information of the reference positioning point, and the lever arm information can be optimized according to the deviation between the current positioning information and the positioning information of the reference positioning point, so that the optimal lever arm information is obtained, and in the subsequent real-time positioning process, the calibrated optimal lever arm information can be utilized for lever arm compensation, so that the fusion positioning precision is improved.
According to the calibration method of the positioning lever arm of the automatic driving vehicle, the lever arm information of the automatic driving vehicle is calibrated on line, so that the calibration efficiency of mass lever arm information is improved, and the subsequent fusion positioning precision is improved.
In an embodiment of the present application, the positioning information of the inertial navigation system includes first fusion positioning information output by the inertial navigation system and positioning information of a real-time differential positioning RTK device, and the compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain the initial positioning information of the rear axle center includes: converting the first fusion positioning information output by the inertial navigation system and the positioning information of the RTK equipment to a target coordinate system; based on extended Kalman filtering, performing fusion positioning processing on fusion positioning information output by an inertial navigation system under the target coordinate system and positioning information of the RTK equipment to obtain second fusion positioning information; and compensating the second fusion positioning information by using the initial lever arm information to obtain the initial positioning information of the center of the rear axle.
In an embodiment of the application, the first fusion positioning information output by the inertial navigation system refers to positioning information of a fused inertial measurement unit IMU, and the positioning information of the fused inertial measurement unit IMU is obtained by fusing positioning information of the RTK device, positioning information originally output by the IMU, and speed information of an autonomous driving vehicle chassis based on extended kalman filtering.
The positioning information of the inertial navigation system in the embodiment of the application may specifically include first fusion positioning information output by the inertial navigation system and positioning information output by an RTK device, where the first fusion positioning information specifically refers to fused IMU positioning information output by the inertial navigation system itself, and may specifically be obtained by fusing positioning information output by the RTK device, positioning information originally output by the IMU, and speed information of an autonomous driving vehicle chassis through Extended Kalman Filtering (EKF).
According to the embodiment of the application, on the basis of the fusion of the inertial navigation system, the positioning information is secondarily fused through the automatic driving positioning system. Firstly, because the first fused positioning information output by the inertial navigation system is located in an East-North-ENU (East-North-Up) coordinate system, and the positioning information originally output by the IMU is located under a vehicle body coordinate system, namely, a front-left-upper coordinate system (marked as a b system), before the second fusion, the positioning information under the East-North-ENU coordinate system needs to be converted into a North-East-next (North-East-Down) coordinate system (marked as an n system), the positioning information originally output by the IMU under the vehicle body coordinate system needs to be converted into a front-right-lower coordinate system to realize the unification of the coordinate system, then the EKF second fused positioning is performed to obtain second fused positioning information, and finally the second fused positioning information is compensated by using the initial lever arm information to obtain the initial positioning information of the center of the rear axle.
In an embodiment of the present application, the second fused positioning information includes a fused position and a fused speed, and the compensating the second fused positioning information by using the initial lever arm information to obtain the initial positioning information of the center of the rear axle includes: compensating the fused position according to the initial lever arm information to obtain the compensated position; compensating the fused speed according to the initial lever arm information to obtain the compensated speed; and taking the compensated position and the compensated speed as initial positioning information of the center of the rear shaft.
When the lever arm information is used for compensation, the compensation method mainly comprises two dimensions of position and speed, and specifically can adopt the following mode:
1) position compensation:
X~ = X - rx * cos(ori_yaw) +ry * sin(ori_yaw);
Y~ = Y - rx * sin(ori_yaw) - ry * cos(ori_yaw);
Z~ = Z-rz；
wherein X, Y and Z are positions after the secondary fusion, rx, ry and rz are positions of initial lever arms, ori _ yaw is a yaw angle of the automatic driving vehicle, and X, Y and Z are positions of compensated rear axle centers.
2) Speed compensation:
Rvb(0,0)=(gyro_b.z()*ry+gyro_b.x()*rz);
Rvb(1,0)=(-gyro_b.z()*rx-gyro_b.y()*rz);
Rvb(2,0)=(-gyro_b.x()*rx+gyro_b.y()*ry);
Rvn=Tbn*Rvb
es = ekf.result_vel[1]+Rvn(0,0); //east speed and calibrate vel arm err
ns = ekf.result_vel[0]+Rvn(1,0); //north speed and calibrate vel arm err
ss = -ekf.result_vel[2]+Rvn(2,0); //sky speed and calibrate vel arm err
wherein, Rvb represents a b-system conversion matrix, Rvn represents an n-system conversion matrix, Tbn represents a b-system to n-system conversion matrix, gyro _ b.x (), gyro _ b.y (), gyro _ b.z () respectively represent the original output of the fused IMU on the x-axis, y-axis and z-axis, ekf.
In an embodiment of the present application, the positioning information of the reference positioning point is obtained as follows: and acquiring positioning information of one or more positioning points in advance through the RTK equipment to serve as the positioning information of the reference positioning point.
The embodiment of the application can utilize the RTK equipment of the high-precision positioning equipment to acquire the positioning information of the reference positioning points in the preset road section in advance, the number of the reference positioning points can be one or multiple, if the reference positioning points are multiple, the distance between every two adjacent reference positioning points is not less than 10m, the lever arm calibration effect is guaranteed, and finally the acquired positioning information of the reference positioning points is recorded into an automatic driving positioning system for calibration.
In an embodiment of the present application, the determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the rear axle center includes: determining a residual error between the positioning information of each datum positioning point and the corresponding current positioning information of the rear axle center; constructing a lever arm information optimization algorithm according to the residual errors; and determining the optimal lever arm information according to the lever arm information optimization algorithm.
The current positioning information of the center of the rear axle in the embodiment of the application may be represented as f (rx, ry, rz) = (x, y, z, vx, vy, vz), where rx, ry, rz is initial outer lever arm information, x, y, z is the position of the rear axle obtained after the outer lever arm is converted, vx, vy, vz is the speed of the rear axle obtained after the outer lever arm is converted, and the lever arm information may be optimized according to the size of the residual error by calculating the residual error between the current positioning information of the center of the rear axle and the positioning information of the reference positioning point.
The residual error may be represented as Δ n = f (rx, ry, rz) - (xn, yn, zn), where xn, yn, zn are positioning information corresponding to the reference positioning point acquired by the nth RTK device.
Specifically, when the lever arm calibration is performed based on the first reference positioning point, a residual Δ 1= f (rx, ry, rz) - (x1, y1, z1) can be calculated, after the calibration of the first reference positioning point is completed, the autonomous vehicle is rotated, the vehicle head is made to face different directions or run to other reference positioning points, the center of the rear axle of the autonomous vehicle is made to coincide with the positioning points, and the above steps are repeated, so that residuals Δ 2, Δ 3, … …, and Δ n can be calculated respectively.
After obtaining the plurality of residual values, a lever arm information optimization model can be constructed based on the plurality of residual values, and the optimization model can be realized by adopting the existing optimization algorithm such as gradient descent, least square and the like, so that the optimal lever arm information can be obtained through multiple iterations.
In an embodiment of the present application, after determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the rear axle center, the method further includes: and compensating the positioning information of the inertial navigation system by using the optimal lever arm information to obtain the final positioning information of the center of the rear axle.
After the optimal lever arm information is obtained, the optimal lever arm information can be input into the inertial navigation system, so that real-time compensation is carried out on the fusion positioning result of the inertial navigation system, and the fusion positioning precision is improved.
In order to verify the calibration effect of the calibration method of the positioning lever arm of the autonomous vehicle, as shown in fig. 2, a schematic diagram of positioning accuracy before calibration of the positioning lever arm of the autonomous vehicle in the embodiment of the present application is provided, as shown in fig. 3, a schematic diagram of positioning accuracy after calibration of the positioning lever arm of the autonomous vehicle in the embodiment of the present application is provided, wherein both the left half parts in fig. 2 and fig. 3 represent the driving route of the autonomous vehicle, and in order to more comprehensively restore the real scene, the driving route simulates the route forms as many as possible.
As can be seen from comparing fig. 2 and fig. 3, the maximum positioning error can reach about 7-8 m before the calibration method of the embodiment of the present application is adopted, and the maximum positioning error is only about 0.2 m after the calibration method of the embodiment of the present application is adopted, which greatly improves the positioning accuracy.
The embodiment of the present application further provides a calibration apparatus 400 for a positioning lever arm of an autonomous vehicle, as shown in fig. 4, which provides a schematic structural diagram of the calibration apparatus for a positioning lever arm of an autonomous vehicle in the embodiment of the present application, where the apparatus 400 includes: a first obtaining unit 410, a first compensation unit 420, a second obtaining unit 430, and a determination unit 440, wherein:
a first obtaining unit 410, configured to obtain initial lever arm information and positioning information of an inertial navigation system, where the lever arm information includes distance information from the inertial navigation system to a center of a rear axle of an autonomous vehicle, and the inertial navigation system is pre-installed on the autonomous vehicle;
a first compensation unit 420, configured to compensate the positioning information of the inertial navigation system by using the initial lever arm information, so as to obtain initial positioning information of the center of the rear axle;
a second obtaining unit 430, configured to obtain, when a rear axle center of the autonomous vehicle is located at a reference positioning point, positioning information of the reference positioning point and current positioning information of the rear axle center according to initial positioning information of the rear axle center;
the determining unit 440 is configured to determine optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear axle, so as to complete calibration of a positioning lever arm of an autonomous driving vehicle.
In an embodiment of the present application, the positioning information of the inertial navigation system includes first fusion positioning information output by the inertial navigation system and positioning information of a real-time differential positioning RTK device, and the first compensation unit 420 is specifically configured to: converting the first fusion positioning information output by the inertial navigation system and the positioning information of the RTK equipment to a target coordinate system; based on extended Kalman filtering, performing fusion positioning processing on fusion positioning information output by an inertial navigation system under the target coordinate system and positioning information of the RTK equipment to obtain second fusion positioning information; and compensating the second fusion positioning information by using the initial lever arm information to obtain the initial positioning information of the center of the rear axle.
In an embodiment of the application, the first fusion positioning information output by the inertial navigation system refers to positioning information of a fused inertial measurement unit IMU, and the positioning information of the fused inertial measurement unit IMU is obtained by fusing positioning information of the RTK device, positioning information originally output by the IMU, and speed information of an autonomous driving vehicle chassis based on extended kalman filtering.
In an embodiment of the present application, the second fused positioning information includes a fused position and a fused speed, and the first compensation unit 420 is specifically configured to: compensating the fused position according to the initial lever arm information to obtain the compensated position; compensating the fused speed according to the initial lever arm information to obtain the compensated speed; and taking the compensated position and the compensated speed as initial positioning information of the center of the rear shaft.
In an embodiment of the present application, the reference positioning point includes at least one, and the determining unit 440 is specifically configured to: determining a residual error between the positioning information of each datum positioning point and the corresponding current positioning information of the rear axle center; constructing a lever arm information optimization algorithm according to the residual errors; and determining the optimal lever arm information according to the lever arm information optimization algorithm.
In an embodiment of the present application, the positioning information of the reference positioning point is obtained by: and acquiring positioning information of one or more positioning points in advance through the RTK equipment to serve as the positioning information of the reference positioning point.
In one embodiment of the present application, the apparatus further comprises: and the second compensation unit is used for compensating the positioning information of the inertial navigation system by using the optimal lever arm information to obtain the final positioning information of the center of the rear axle.
It can be understood that the calibration device for the lever arm of the autonomous vehicle can implement the steps of the calibration method for the lever arm of the autonomous vehicle provided in the foregoing embodiments, and the explanations related to the calibration method for the lever arm of the autonomous vehicle are applicable to the calibration device for the lever arm of the autonomous vehicle, and are not repeated herein.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 5, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 5, but this does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads a corresponding computer program from the non-volatile memory into the memory and runs the computer program to form a calibration device of the positioning lever arm of the automatic driving vehicle on a logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
acquiring initial lever arm information and positioning information of an inertial navigation system, wherein the lever arm information comprises distance information from the inertial navigation system to the center of a rear axle of an automatic driving vehicle, and the inertial navigation system is pre-installed on the automatic driving vehicle;
compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain initial positioning information of the center of the rear shaft;
under the condition that the center of a rear axle of the automatic driving vehicle is located at a reference positioning point, acquiring positioning information of the reference positioning point and current positioning information of the center of the rear axle according to initial positioning information of the center of the rear axle;
and determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear shaft so as to finish the calibration of the positioning lever arm of the automatic driving vehicle.
The method performed by the calibration apparatus of the lever arm of the autopilot vehicle disclosed in the embodiment of fig. 1 of the present application may be implemented in or by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute the method executed by the calibration device of the positioning lever arm of the autonomous driving vehicle in fig. 1, and implement the functions of the calibration device of the positioning lever arm of the autonomous driving vehicle in the embodiment shown in fig. 1, which are not described herein again in this application.
Embodiments of the present application further provide a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by an electronic device including a plurality of application programs, enable the electronic device to perform the method performed by the calibration apparatus for an autopilot vehicle lever arm in the embodiment shown in fig. 1, and are specifically configured to perform:
acquiring initial lever arm information and positioning information of an inertial navigation system, wherein the lever arm information comprises distance information from the inertial navigation system to the center of a rear axle of an automatic driving vehicle, and the inertial navigation system is pre-installed on the automatic driving vehicle;
compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain initial positioning information of the center of the rear shaft;
under the condition that the center of a rear axle of the automatic driving vehicle is located at a reference positioning point, acquiring positioning information of the reference positioning point and current positioning information of the center of the rear axle according to initial positioning information of the center of the rear axle;
and determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear shaft so as to finish the calibration of the positioning lever arm of the automatic driving vehicle.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (8)
1. A method of calibrating a lever arm of an autonomous vehicle, wherein the method comprises:
acquiring initial lever arm information and positioning information of an inertial navigation system, wherein the lever arm information comprises distance information from the inertial navigation system to the center of a rear axle of an automatic driving vehicle, and the inertial navigation system is pre-installed on the automatic driving vehicle;
compensating the positioning information of the inertial navigation system by using the initial lever arm information to obtain initial positioning information of the center of the rear shaft so as to compensate the positioning information of the inertial navigation system to the position of the center of the rear shaft;
the positioning information of the inertial navigation system comprises first fusion positioning information output by the inertial navigation system and positioning information of real-time differential positioning RTK equipment, and the step of utilizing the initial lever arm information to compensate the positioning information of the inertial navigation system to obtain the initial positioning information of the center of the rear axle comprises the following steps:
converting the first fusion positioning information output by the inertial navigation system and the positioning information of the RTK equipment to a target coordinate system;
based on extended Kalman filtering, performing fusion positioning processing on first fusion positioning information output by an inertial navigation system under the target coordinate system and positioning information of the RTK equipment to obtain second fusion positioning information;
compensating the second fusion positioning information by using the initial lever arm information to obtain initial positioning information of the center of the rear axle, wherein the compensation comprises position compensation and speed compensation;
under the condition that the center of a rear axle of the automatic driving vehicle is located at a reference positioning point, acquiring positioning information of the reference positioning point and current positioning information of the center of the rear axle according to initial positioning information of the center of the rear axle;
determining optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear shaft so as to complete the online calibration of a large batch of positioning lever arms of the automatic driving vehicle;
the determining of the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear axle comprises the following steps:
determining a residual error between the positioning information of each datum positioning point and the corresponding current positioning information of the rear axle center;
constructing a lever arm information optimization algorithm according to the residual errors;
and determining the optimal lever arm information according to the lever arm information optimization algorithm.
2. The method of claim 1, wherein the first fused positioning information output by the inertial navigation system is positioning information of a fused Inertial Measurement Unit (IMU), and the positioning information of the fused IMU is obtained by fusing positioning information of the RTK device, positioning information originally output by the IMU, and speed information of a chassis of the autonomous vehicle based on extended Kalman filtering.
3. The method of claim 1, wherein the second fused positioning information comprises a fused position and a fused velocity, and the compensating the second fused positioning information with the initial lever arm information to obtain the initial positioning information of the rear axle center comprises:
compensating the fused position according to the initial lever arm information to obtain the compensated position;
compensating the fused speed according to the initial lever arm information to obtain the compensated speed;
and taking the compensated position and the compensated speed as initial positioning information of the center of the rear shaft.
4. The method as claimed in claim 1, wherein the positioning information of the positioning reference point is obtained by:
and acquiring positioning information of one or more positioning points in advance through the RTK equipment to serve as the positioning information of the reference positioning point.
5. The method of claim 1, wherein after determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the rear axle center, the method further comprises:
and compensating the positioning information of the inertial navigation system by using the optimal lever arm information to obtain the final positioning information of the center of the rear axle.
6. A calibration apparatus for a positioning lever arm of an autonomous vehicle, wherein the apparatus comprises:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring initial lever arm information and positioning information of an inertial navigation system, the lever arm information comprises distance information from the inertial navigation system to the center of a rear axle of an automatic driving vehicle, and the inertial navigation system is pre-installed on the automatic driving vehicle;
the first compensation unit is configured to compensate the positioning information of the inertial navigation system by using the initial lever arm information to obtain initial positioning information of the rear axle center, where the positioning information of the inertial navigation system includes first fusion positioning information output by the inertial navigation system and positioning information of a real-time differential positioning RTK device, and the first compensation unit is further configured to:
converting the first fusion positioning information output by the inertial navigation system and the positioning information of the RTK equipment to a target coordinate system;
based on extended Kalman filtering, performing fusion positioning processing on first fusion positioning information output by an inertial navigation system under the target coordinate system and positioning information of the RTK equipment to obtain second fusion positioning information;
compensating the second fusion positioning information by using the initial lever arm information to obtain initial positioning information of the center of the rear axle, wherein the compensation comprises position compensation and speed compensation;
the second acquisition unit is used for acquiring positioning information of a reference positioning point and current positioning information of the rear axle center according to the initial positioning information of the rear axle center under the condition that the rear axle center of the automatic driving vehicle is positioned at the reference positioning point;
the determining unit is used for determining the optimal lever arm information according to the positioning information of the reference positioning point and the current positioning information of the center of the rear shaft so as to complete the online calibration of a large batch of positioning lever arms of the automatic driving vehicle;
the reference positioning point includes a plurality of reference positioning points, and the determining unit is specifically configured to:
determining a residual error between the positioning information of each reference positioning point and the current positioning information of the corresponding rear axle center;
constructing a lever arm information optimization algorithm according to the residual errors;
and determining the optimal lever arm information according to the lever arm information optimization algorithm.
7. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method of any of claims 1 to 5.
8. A computer readable storage medium storing one or more programs which, when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method of any of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111546068.6A CN113932835B (en) | 2021-12-17 | 2021-12-17 | Calibration method and device for positioning lever arm of automatic driving vehicle and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111546068.6A CN113932835B (en) | 2021-12-17 | 2021-12-17 | Calibration method and device for positioning lever arm of automatic driving vehicle and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113932835A CN113932835A (en) | 2022-01-14 |
| CN113932835B true CN113932835B (en) | 2022-05-17 |
Family
ID=79289254
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111546068.6A Active CN113932835B (en) | 2021-12-17 | 2021-12-17 | Calibration method and device for positioning lever arm of automatic driving vehicle and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113932835B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115267838A (en) * | 2022-06-22 | 2022-11-01 | 湖北星纪时代科技有限公司 | Method, device, equipment and medium for testing positioning performance |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108225362A (en) * | 2017-12-29 | 2018-06-29 | 驭势科技（北京）有限公司 | Intelligent driving vehicle positioning method and system, computer storage media and positioning device |
| CN110501024B (en) * | 2019-04-11 | 2023-03-28 | 同济大学 | Measurement error compensation method for vehicle-mounted INS/laser radar integrated navigation system |
| GB2584463B (en) * | 2019-06-04 | 2023-06-28 | Atlantic Inertial Systems Ltd | Direction finder |
| CN111469855A (en) * | 2020-04-20 | 2020-07-31 | 北京易控智驾科技有限公司 | Vehicle motion parameter calculation method |
| CN112082547B (en) * | 2020-09-08 | 2022-05-10 | 北京邮电大学 | Method and device for optimizing integrated navigation system, electronic equipment and storage medium |
-
2021
- 2021-12-17 CN CN202111546068.6A patent/CN113932835B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN113932835A (en) | 2022-01-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111947671B (en) | Method, apparatus, computing device and computer-readable storage medium for positioning | |
| CN112113574B (en) | Method, apparatus, computing device and computer-readable storage medium for positioning | |
| CN112129321B (en) | Gyro zero offset calibration value determining method and device and computer storage medium | |
| CN112946681B (en) | Laser radar positioning method fusing combined navigation information | |
| CN112859131B (en) | Positioning method and device of unmanned equipment | |
| CN114279453B (en) | Automatic driving vehicle positioning method and device based on vehicle-road cooperation and electronic equipment | |
| CN115184976B (en) | Positioning method and device for automatic driving vehicle, electronic equipment and storage medium | |
| CN113932835B (en) | Calibration method and device for positioning lever arm of automatic driving vehicle and electronic equipment | |
| CN113984044A (en) | Vehicle pose acquisition method and device based on vehicle-mounted multi-perception fusion | |
| CN115727843A (en) | Wheel speed determination method, device and equipment for dead reckoning | |
| CN115236714A (en) | Multi-source data fusion positioning method, device and equipment and computer storage medium | |
| CN112414415A (en) | High-precision point cloud map construction method | |
| CN115390086A (en) | Fusion positioning method and device for automatic driving, electronic equipment and storage medium | |
| CN114677663A (en) | Vehicle positioning method and device, electronic equipment and computer-readable storage medium | |
| CN116222586A (en) | Fusion positioning method and device for automatic driving vehicle and electronic equipment | |
| CN115856979B (en) | Positioning method and device for automatic driving vehicle, electronic equipment and storage medium | |
| CN115112125A (en) | Positioning method and device for automatic driving vehicle, electronic equipment and storage medium | |
| CN115014395A (en) | Real-time calibration method and device for vehicle course angle for automatic driving | |
| CN115183786A (en) | Training method and device of sensor error prediction model for automatic driving | |
| CN116929407A (en) | Self-adaptive data calibration method and device | |
| CN115839718A (en) | Fusion positioning method and device based on motion constraint | |
| CN114739416A (en) | Automatic driving vehicle positioning method and device, electronic equipment and storage medium | |
| CN114370872A (en) | Vehicle attitude determination method and vehicle | |
| CN112506190A (en) | Robot positioning method, robot positioning device and robot | |
| CN111964676A (en) | Attitude heading calculation method and device, electronic equipment and computer 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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |