Vehicle positioning calibration method and system based on sensor and marker

Abstract

The invention discloses a vehicle positioning calibration method and system based on a sensor and a marker, and the method comprises the steps: setting a plurality of calibration piles in a driving region of a vehicle, setting a two-dimensional code on each calibration pile, and storing the calibration parameters of the calibration piles in an associated manner through the two-dimensional codes; when the vehicle runs into the area range of the calibration pile, actual measurement parameters of the calibration pile are collected through a vehicle-mounted sensor, and calibration parameters stored in the two-dimensional code are recognized; and comparing the actual measurement parameters with the calibration parameters, and calibrating the position and the posture of the vehicle body based on a comparison result. According to the scheme, the efficiency and accuracy of vehicle positioning calibration can be improved.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and in particular to a vehicle positioning calibration method, system, computing device and storage medium based on sensors and markers. Background Art

[0002] High-precision vehicle positioning is a key technology in the development of intelligent transportation systems. Currently, vehicle positioning mainly relies on satellite positioning systems. However, in places where satellite signals are blocked, such as underground tunnels, indoors, and mining areas, accurate positioning data cannot be output.

[0003] In the prior art, a Chinese patent document with publication number CN117109599A discloses a vehicle auxiliary positioning method based on a roadside QR code, which specifically includes: during the vehicle driving process, the roadside QR code image is collected in real time by the vehicle-mounted camera; the position of the QR code and the straight-line distance between the vehicle and the QR code are determined in real time according to the QR code image; the lateral distance between the vehicle and the road edge is determined in real time according to the straight-line distance and a calibrated database; the vehicle position is calculated in real time according to the position, lateral distance and road azimuth of the QR code. This solution only relies on the camera to capture the QR code in real time. Although it can provide continuous positioning function during the vehicle driving process, it is insufficient in terms of accuracy and environmental adaptability. Summary of the invention

[0004] In view of the above problems, the present invention provides a vehicle positioning and calibration method and system based on sensors and markers, wherein multiple calibration piles are set in the actual driving path of the vehicle and the calibration parameters of the calibration piles (including the known position and posture information of the calibration piles) are carried based on a QR code. When the vehicle drives to the calibration area, the QR code is automatically identified and the calibration piles are actually measured. The actual measurement parameters are compared with the calibration parameters, and the calibration of multiple sensors of the vehicle is completed according to the comparison results, which can improve the efficiency, accuracy and consistency of vehicle positioning and calibration.

[0005] According to a first aspect of the present invention, a vehicle positioning and calibration method based on sensors and markers is provided, comprising: setting a plurality of calibration piles in a driving area of ​​the vehicle, each calibration pile being provided with a two-dimensional code, and the two-dimensional code being associated with and storing calibration parameters of the calibration piles; when the vehicle drives into an area of ​​the calibration piles, collecting actual measurement parameters of the calibration piles through on-board sensors and identifying the calibration parameters stored in the two-dimensional code; comparing the actual measurement parameters with the calibration parameters, and calibrating the vehicle body position and posture based on the comparison results.

[0006] The above technical solution, by combining the use of ground markers and on-board sensors, uses QR codes to associate and store the known calibration parameters of the calibration piles. The vehicle can directly read the accurate calibration parameters from the QR code and compare them with the actual measurement parameters collected by multiple on-board sensors. This helps the vehicle correct any potential sensor errors and improves the accuracy and efficiency of vehicle positioning calibration.

[0007] Optionally, in the vehicle positioning and calibration method based on sensors and markers provided by the present invention, the vehicle path is planned based on obstacles in the vehicle working area to determine the planned route of the vehicle; multiple calibration piles are set along the planned route of the vehicle, each calibration pile is provided with a QR code, and the QR code is associated with and stores the posture information of the current calibration pile, the key coordinate points of the QR code on the calibration pile, and the position coordinates of the next calibration pile associated with the current calibration pile; based on the multiple calibration piles, the autonomous driving vehicle is guided to the destination.

[0008] The above technical solution uses calibration stakes and a QR code system for path planning, reducing the reliance on GPS signals, especially in areas such as mining areas where GPS signals are weak or unstable.

[0009] Optionally, in the vehicle positioning and calibration method based on sensors and markers provided by the present invention, when the vehicle drives to the first calibration pile, the position information of the current calibration pile and the position information of the next calibration pile associated with the current calibration pile are obtained by identifying the QR code; based on the position information of the current calibration pile and the position information of the next calibration pile, the vehicle is guided to the destination.

[0010] The above technical solution uses the posture information stored in the QR code and the position coordinates of the next calibration stake, so that the vehicle can automatically navigate to the next calibration stake, reducing the dependence on manual intervention and automating the calibration process.

[0011] Optionally, in the vehicle positioning and calibration method based on sensors and markers provided by the present invention, an environmental perception module is set on the calibration pile, and the environmental perception module is connected to the QR code for real-time detection of the environmental conditions of the calibration area and adjustment of the calibration parameters, and the adjusted calibration parameters are updated to the QR code.

[0012] The above technical solution enables the calibration parameters to be updated in real time and transmits new calibration information via a QR code, which can reduce the interference of environmental changes on sensor data and improve calibration accuracy.

[0013] Optionally, in the vehicle positioning and calibration method based on sensors and markers provided by the present invention, when the vehicle travels into the area where the calibration pile is located, the image of the calibration pile is collected by the on-board camera, and the position and posture data of the calibration pile is obtained by multiple on-board sensors; the image of the calibration pile and the position and posture data of the calibration pile are analyzed and fused, and the actual measurement parameters of the calibration pile are extracted, and the actual measurement parameters include the actual position and posture data of the calibration pile and the actual coordinates of the key points of the two-dimensional code; the calibration parameters corresponding to the two-dimensional code are identified by the on-board camera, and the calibration parameters include the calibration posture data of the calibration pile and the calibration coordinates of the key points of the two-dimensional code.

[0014] The above technical solution integrates image data and posture data to improve the accuracy of actual measurement parameters, making the sensor calibration process more reliable. By integrating multiple sensor data to obtain more accurate calibration information, the calibration deviation caused by single sensor error is reduced.

[0015] Optionally, in the vehicle positioning and calibration method based on sensors and markers provided by the present invention, the error between the actual measurement parameters and the calibration parameters is calculated, and the correction value of each sensor is calculated based on the error; the correction value is input into the vehicle's navigation and control system to adjust the position and posture of the vehicle body.

[0016] Optionally, in the vehicle positioning and calibration method based on sensors and markers provided by the present invention, at least two two-dimensional codes are arranged on each calibration pile, and the at least two two-dimensional codes are respectively arranged at different positions of the calibration pile.

[0017] The above technical solution, by setting multiple QR codes on a calibration stake, allows the vehicle's sensor to capture the QR code from different angles and positions, thereby improving the accuracy of spatial positioning. In the case where the sensor's line of sight is partially blocked or recognition is difficult at certain angles, more viewing angles can be provided so that at least one QR code is within a good line of sight, ensuring the continuity and reliability of calibration.

[0018] According to a second aspect of the present invention, a vehicle positioning calibration system based on sensors and markers is provided, comprising: A setting module, used for setting a plurality of calibration piles in the driving area of ​​the vehicle, wherein the calibration piles are provided with a two-dimensional code, and the two-dimensional code is associated with and stores calibration parameters of the calibration piles; The parameter acquisition module is used to collect the actual measurement parameters of the calibration pile through the vehicle-mounted sensor and identify the calibration parameters corresponding to the QR code when the vehicle drives into the calibration pile area; The calibration module is used to compare the actual measurement parameters with the calibration parameters, and calibrate the position and posture of the vehicle body based on the comparison result.

[0019] According to a third aspect of the present invention, a computing device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the vehicle positioning calibration method based on sensors and markers as in the first aspect.

[0020] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium, comprising a computer program stored therein which can be loaded by a processor and execute the vehicle positioning calibration method based on sensors and markers as in the first aspect.

[0021] According to the sensor- and marker-based vehicle positioning and calibration method and system provided by the present invention, multiple calibration piles are set in the vehicle's path planning area to guide the vehicle to the target position, thereby reducing the dependence on GPS signals, and using QR codes to provide calibration parameters such as the position and posture of the calibration piles, so that high-precision calibration can be achieved; during the driving process, the vehicle collects the actual measurement parameters of the calibration piles through multiple on-board sensors and recognizes the QR codes. The calibration parameters provided by the QR codes can simplify data management and calculation in the calibration process, thereby improving the efficiency of sensor calibration.

[0022] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A block diagram of a computing device 100 according to an embodiment of the present invention is shown; Figure 2 A schematic flow chart of a vehicle positioning calibration method 200 based on sensors and markers according to an embodiment of the present invention is shown; Figure 3 A schematic diagram of the structure of a vehicle positioning system 300 based on sensors and markers according to an embodiment of the present invention is shown; Figure 4 A schematic diagram of setting calibration piles according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0024] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0025] Figure 1 FIG. 1 shows a block diagram of a computing device 100 according to an embodiment of the present invention. Figure 1 As shown, computing device 100 may include memory 106 and processor 104. Memory bus 108 may be used for communication between processor 104 and system memory 106.

[0026] Memory 106 may include operating system 120, applications 122, and program data 124. Applications 122 may be arranged to be executed on the operating system by one or more processors 104 using program data 124. Applications 122 include program instructions for implementing various user desired functions.

[0027] When the computing device 100 starts running, the processor 104 reads and executes the program instructions of the operating system 120 from the memory 106. The application 122 runs on the operating system 120 and uses the interfaces provided by the operating system 120 and the underlying hardware to implement various functions desired by the user. When the user starts the application 122, the application 122 is loaded into the memory 106, and the processor 104 reads and executes the program instructions of the application 122 from the memory 106.

[0028] The computing device 100 also includes a storage device 132 and an output device 142 connected to a storage interface bus 134. An interface bus 140 facilitates communication from various interface devices (eg, output device 142, peripheral interface 144, and communication device 146) via the bus / interface controller 130.

[0029] The peripheral interface 144 may include a serial interface controller 154 and a parallel interface controller 156, which may be configured to facilitate communication with external devices such as input devices (e.g., keyboards, mice, pens, voice input devices, touch input devices) or other peripherals (e.g., printers, scanners, etc.) via one or more I / O ports 158. The communication device 146 may include a network controller 160, which may be arranged to facilitate communication with one or more other computing devices 162 via a network communication link via one or more communication ports 164. In the computing device 10 according to the present invention, the application 122 includes instructions for executing the sensor- and marker-based vehicle positioning calibration method 200 of the present invention.

[0030] Figure 2 FIG. 2 is a flow chart of a vehicle positioning calibration method 200 based on sensors and markers according to an embodiment of the present invention. Figure 2 As shown, the method 200 starts at step S210, where a plurality of calibration piles are set in a driving area of ​​the vehicle, each calibration pile is provided with a QR code, and the QR code is associated with and stores calibration parameters of the calibration pile.

[0031] First, the vehicle path is planned based on the obstacles in the vehicle working area to determine the vehicle's planned route. For example, a three-dimensional map of the mining area is obtained using laser radar, cameras, etc., and a three-dimensional model containing information such as obstacles and roads is established. Vehicle path planning is performed based on obstacle type, time efficiency, resource allocation, etc.

[0032] Then, multiple calibration stakes are set along the planned route of the vehicle, each of which is provided with a QR code, which stores the position information of the current calibration stake, the key coordinate points of the QR code on the calibration stake, and the position coordinates of the next calibration stake associated with the current calibration stake. In other words, the position and attitude of each calibration stake are known.

[0033] For example, according to the terrain and operation area of ​​the mining area, the distribution location of the calibration stakes can be determined according to the working route of the autonomous driving vehicle to ensure that the on-board camera, radar or other sensors of the autonomous driving vehicle can cover the calibration stake area. Place a calibration stake at each calibration point and configure a QR code for each calibration stake. The QR code of each calibration stake is associated with the unique ID of each calibration stake, location data (latitude and longitude), key coordinate points of the QR code on the calibration stake (such as the coordinates of the four corner points), the posture data of the calibration stake (such as the tilt angle and direction), and the ID and location data of the next calibration stake.

[0034] In one embodiment of the present invention, in order to improve the environmental adaptability of sensor calibration, this solution sets an environmental perception module on the calibration pile, and the environmental perception module is connected to the QR code, which is used to detect the environmental conditions of the calibration area in real time and adjust the calibration parameters, and update the adjusted calibration parameters to the QR code. For example, the environmental perception module can be a temperature sensor, a light sensor, etc., which is used to collect environmental data such as temperature and light intensity of the calibration area in real time, analyze the impact of real-time environmental data on sensor calibration, calculate and adjust calibration parameters, and encode the adjusted calibration parameters into new QR code data.

[0035] In order to provide more viewing angle options when the sensor's vision is partially blocked or recognition is difficult at certain angles, at least two QR codes are set on each calibration stake, and the at least two QR codes are set at different positions of the calibration stake. By setting multiple QR codes on a calibration stake, the vehicle's sensor can capture the QR code from different angles and positions, ensuring the continuity and reliability of calibration.

[0036] Finally, the autonomous driving vehicle can be guided to the destination based on multiple calibration stakes. Specifically, when the autonomous driving vehicle drives to the first calibration stake, it recognizes the QR code and obtains the location information of the current calibration stake and the location information of the next calibration stake associated with the current calibration stake, and performs vehicle path planning based on the location information of the current calibration stake and the location information of the next calibration stake until the autonomous driving vehicle is guided to the destination.

[0037] In step S220, when the vehicle travels into the area of ​​the calibration pile, the actual measurement parameters of the calibration pile are collected by the vehicle-mounted sensor and the calibration parameters stored in the QR code are identified.

[0038] When the vehicle drives into the area where each calibration pile is located, the image of the calibration pile is collected through the on-board camera, and the position and posture data of the vehicle and the calibration pile are obtained through the on-board radar. The image of the calibration pile and the position and posture data of the vehicle and the calibration pile are parsed and fused to extract the actual measurement parameters, which include the actual position and posture data of the calibration pile and the actual coordinates of the key points of the QR code. The calibration parameters corresponding to the QR code are identified by the on-board camera, which include the calibration posture data of the calibration pile and the calibration coordinates of the key points of the QR code.

[0039] For example, the on-board camera obtains the image of the calibration pile, the on-board radar obtains the distance and relative position data of the calibration pile, and the ultrasonic sensor or lidar is used to obtain the supplementary data of the calibration pile. The QR code is decoded based on the image processing algorithm to extract the information stored in the QR code. The position and direction of the calibration pile relative to the coordinate system of the on-board sensor are calculated by combining the on-board radar and other sensors. The external parameter calibration data of the on-board camera, radar and other sensors are fused to obtain the actual measurement parameters of the calibration pile, which include the posture data of the calibration pile and the key point coordinate data of the QR code on the calibration pile.

[0040] Finally, step S230 is executed to compare the actual measurement parameters with the calibration parameters, and the vehicle body position and posture are calibrated based on the comparison result.

[0041] The error between the actual measurement parameter and the calibration parameter is calculated, and the correction value of each sensor is calculated based on the error; the correction value is input into the navigation and control system of the vehicle to adjust the position and posture of the vehicle body.

[0042] For example, by adjusting the distortion coefficient of the on-board camera and the attitude angle of the laser radar to optimize the external parameter calibration, the adjusted sensor is recalibrated to ensure that the output of the sensor is consistent with the actual value at the new position and attitude, and the measurement accuracy is optimized. The adjusted calibration parameters are uploaded to the on-board control system through the communication interface, and the new calibration parameters are applied in the on-board control system.

[0043] Therefore, the calibration process of optimizing sensors is an iterative process involving error calculation, parameter adjustment, system update and actual environment testing. Through these steps, the accuracy and reliability of sensors in the vehicle system under different conditions can be ensured, and the overall performance of autonomous vehicle positioning can be improved.

[0044] Figure 3 FIG. 3 is a schematic diagram showing a vehicle positioning and calibration system 300 based on sensors and markers according to an embodiment of the present invention. Figure 3 As shown, the system 300 may include a setting module 310 , a parameter acquisition module 320 and a calibration module 330 .

[0045] The setting module 310 may set a plurality of calibration piles in the driving area of ​​the vehicle, and a QR code is set on the calibration pile, and the calibration parameters of the calibration pile are stored in association with the QR code.

[0046] Figure 4 FIG. 2 shows a schematic diagram of setting a calibration pile according to an embodiment of the present invention. Figure 4 As shown, multiple calibration stakes are set along the planned route of the vehicle, and each calibration stake is provided with a QR code. The distance between adjacent calibration stakes can be the same or different, and this solution does not limit this. The QR code of each calibration stake is associated with the unique ID of each calibration stake, the location data (latitude and longitude), the key coordinate points of the QR code on the calibration stake (such as the coordinates of the four corner points), the posture data of the calibration stake (such as the tilt angle and direction), and the ID and location data of the next calibration stake.

[0047] When the vehicle travels into the area of ​​the calibration pile, the parameter acquisition module 320 can collect the actual measurement parameters of the calibration pile through the vehicle-mounted sensor and identify the calibration parameters corresponding to the QR code. Specifically, when the vehicle travels into the area where each calibration pile is located, the parameter acquisition module 320 can collect the image of the calibration pile through the vehicle-mounted camera and obtain the posture data of the vehicle and the calibration pile through the vehicle-mounted radar. The image of the calibration pile and the posture data of the vehicle and the calibration pile are parsed and fused to extract the actual measurement parameters, which include the actual posture data of the calibration pile and the actual coordinates of the key points of the QR code. The calibration parameters corresponding to the QR code are identified by the vehicle-mounted camera, and the calibration parameters include the calibration posture data of the calibration pile and the calibration coordinates of the key points of the QR code.

[0048] The calibration module 330 may compare the actual measurement parameters with the calibration parameters, and calibrate the vehicle body position and posture based on the comparison result.

[0049] Specifically, the calibration module 330 can calculate the amount of adjustment required based on the results of the error analysis and modify the settings or calibration data of each sensor. For example, angle compensation can be performed on the laser radar and image distortion correction can be performed on the camera. Data can be collected again in the calibration area to verify whether the adjusted sensor meets the requirements of the calibration parameters. The adjustment and verification process is repeated until the measurement results of the sensor meet the calibration requirements.

[0050] According to the sensor- and marker-based vehicle positioning and calibration method and system provided by the present invention, multiple calibration piles are set in the vehicle's path planning area to guide the vehicle to the target position, thereby reducing the dependence on GPS signals, and using QR codes to provide calibration parameters such as the position and posture of the calibration piles, so that high-precision calibration can be achieved; during the driving process, the vehicle collects the actual measurement parameters of the calibration piles through multiple on-board sensors and recognizes the QR codes. The calibration parameters provided by the QR codes can simplify data management and calculation in the calibration process, thereby improving the efficiency of sensor calibration.

[0051] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0052] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting the following intention: that the claimed invention requires more features than the features explicitly recited in each claim. More specifically, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present invention.

[0053] Although the present invention has been described according to a limited number of embodiments, it will be apparent to those skilled in the art, with the benefit of the above description, that other embodiments may be envisioned within the scope of the invention thus described. In addition, it should be noted that the language used in this specification is selected primarily for readability and teaching purposes, rather than for explaining or defining the subject matter of the present invention. Therefore, many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the appended claims. The disclosure of the present invention is illustrative and not restrictive with respect to the scope of the present invention, and the scope of the present invention is defined by the appended claims.

Claims

1. A vehicle positioning calibration method based on sensors and markers, characterized in that: include: A plurality of calibration piles are arranged in the driving area of ​​the vehicle, each calibration pile is provided with a two-dimensional code, and the two-dimensional code is associated with and stores the calibration parameters of the calibration pile; When the vehicle drives into the calibration pile area, the vehicle-mounted sensor collects the actual measurement parameters of the calibration pile and identifies the calibration parameters stored in the QR code; The actual measured parameters are compared with the calibration parameters, and the vehicle body position and posture are calibrated based on the comparison result.

2. The vehicle positioning calibration method based on sensors and markers according to claim 1, characterized in that: The step of setting a plurality of calibration stakes in the driving area of ​​the vehicle comprises: Performing path planning for the vehicle based on obstacles in the vehicle's working area to determine the vehicle's planned route; A plurality of calibration stakes are arranged along the planned route of the vehicle, each calibration stake is provided with a QR code, and the QR code stores the position information of the current calibration stake, the key coordinate points of the QR code on the calibration stake, and the position coordinates of the next calibration stake associated with the current calibration stake; The autonomous driving vehicle is guided to travel to a destination based on the multiple calibration stakes.

3. The vehicle positioning calibration method based on sensors and markers according to claim 2, characterized in that: The step of guiding the autonomous driving vehicle to the destination based on the calibration pile comprises: When the vehicle drives to the first calibration pile, the location information of the current calibration pile and the location information of the next calibration pile associated with the current calibration pile are obtained by identifying the QR code; The vehicle is guided to the destination based on the location information of the current calibration stake and the location information of the next calibration stake.

4. The vehicle positioning calibration method based on sensors and markers according to claim 2, characterized in that: The step of setting a plurality of calibration stakes in the driving area of ​​the vehicle also includes: An environment perception module is arranged on the calibration pile, and the environment perception module is connected to the two-dimensional code, and is used for real-time detection of the environment of the calibration area and adjustment of calibration parameters, and updating the adjusted calibration parameters to the two-dimensional code.

5. The vehicle positioning calibration method based on sensors and markers according to claim 4, characterized in that: When the vehicle travels into the calibration pile area, the steps of collecting the actual measurement parameters of the calibration pile by the vehicle-mounted sensor and identifying the calibration parameters stored in the QR code include: When the vehicle drives into the area where the calibration pile is located, the image of the calibration pile is collected through the on-board camera, and the position and posture data of the calibration pile is obtained through multiple on-board sensors; The image of the calibration pile and the position and posture data of the calibration pile are analyzed and merged to extract actual measurement parameters of the calibration pile, wherein the actual measurement parameters include the actual position and posture data of the calibration pile and the actual coordinates of the key points of the two-dimensional code; The calibration parameters corresponding to the QR code are identified by the vehicle-mounted camera, and the calibration parameters include the calibration posture data of the calibration pile and the calibration coordinates of the key points of the QR code.

6. The vehicle positioning calibration method based on sensors and markers according to claim 1, characterized in that: The step of comparing the actual measurement parameters with the calibration parameters and calibrating the vehicle body position and posture based on the comparison result includes: Calculating the error between the actual measurement parameter and the calibration parameter, and calculating the correction value of each sensor based on the error; The correction value is input into the navigation and control system of the vehicle to adjust the position and attitude of the vehicle body.

7. The vehicle positioning calibration method based on sensors and markers according to claim 1, characterized in that: At least two two-dimensional codes are arranged on each calibration pile, and the at least two two-dimensional codes are arranged at different positions of the calibration pile respectively.

8. A vehicle positioning and calibration system based on sensors and markers, characterized in that: include: A setting module, used for setting a plurality of calibration piles in the driving area of ​​the vehicle, wherein the calibration piles are provided with a two-dimensional code, and the two-dimensional code is associated with and stores calibration parameters of the calibration piles; The parameter acquisition module is used to collect the actual measurement parameters of the calibration pile through the vehicle-mounted sensor and identify the calibration parameters corresponding to the QR code when the vehicle drives into the calibration pile area; The calibration module is used to compare the actual measurement parameters with the calibration parameters, and calibrate the position and posture of the vehicle body based on the comparison result.

9. A computing device comprising: at least one processor; A memory storing program instructions, wherein the program instructions are configured to be suitable for execution by the at least one processor, and the program instructions include instructions for executing the vehicle positioning calibration method based on sensors and markers as described in any one of claims 1-7.

10. A readable storage medium storing program instructions, when the program instructions are read and executed by a computing device, the computing device executes the vehicle positioning calibration method based on sensors and markers as described in any one of claims 1 to 7.

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