Vehicle-mounted sensor calibration method and system

Abstract

The invention relates to a calibration method and system for vehicle-mounted sensors. The calibration method comprises the following steps that a coordinate conversion algorithm between a first vehicle-mounted sensor and a second vehicle-mounted sensor is established in advance; in response to the detection that the first vehicle-mounted sensor is replaced, collecting first coordinate data of the first vehicle-mounted sensor; and converting the first coordinate data into second coordinate data of the second vehicle-mounted sensor based on the coordinate conversion algorithm.

Description

Technical Field

[0001] This application relates to the field of vehicle calibration, and more particularly, to a calibration method and system for on-vehicle sensors. Background Art

[0002] In the process of popularizing vehicle driving assistance systems, in order to optimize the performance of driving assistance functions, the number of sensors installed in vehicles is increasing rapidly. Traffic collisions and accidents during daily driving often cause sensor damage and require replacement and repair. Since the installation position of on-vehicle sensors is closely related to their performance, after replacing a sensor, it is often necessary to recalibrate it, and the calibration work needs to be completed through corresponding tools or sites. However, the existing calibration methods only focus on calibrating a single type of sensor itself and do not define system-level calibration for all sensors related to the driving assistance system. Summary of the Invention

[0003] In view of the above problems, the following technical solutions are provided.

[0004] The calibration method for on-vehicle sensors of this application includes the following steps: pre-establishing a coordinate transformation algorithm between a first on-vehicle sensor and a second on-vehicle sensor; in response to detecting that the first on-vehicle sensor is replaced, collecting first coordinate data of the first on-vehicle sensor; and based on the coordinate transformation algorithm, converting the first coordinate data into second coordinate data of the second on-vehicle sensor.

[0005] Optionally, the calibration method further includes: writing the second coordinate data into the second on-vehicle sensor.

[0006] Optionally, the coordinate transformation algorithm further includes: a coordinate mapping relationship between the first coordinate data and the second coordinate data.

[0007] Optionally, the replacement of the first on-vehicle sensor is triggered by at least one of the following methods: detecting that the maintenance diagnostic system enters the sensor replacement mode; identifying that the sensor hardware ID has changed; receiving a manual calibration start instruction.

[0008] Optionally, the on-vehicle sensor includes at least one of the following: camera, radar, ultrasonic sensor, and infrared sensor.

[0009] The calibration system of the vehicle-mounted sensor of the present application, the calibration system includes: a preset algorithm module: configured to establish a coordinate transformation algorithm between a first vehicle-mounted sensor and a second vehicle-mounted sensor in advance; a data acquisition module: configured to collect first coordinate data of the first vehicle-mounted sensor in response to detecting that the first vehicle-mounted sensor is replaced; and a coordinate transformation module: configured to convert the first coordinate data into second coordinate data of the second vehicle-mounted sensor based on the coordinate transformation algorithm.

[0010] Optionally, the calibration system further includes a calibration writing module, configured to write the second coordinate data into the second vehicle-mounted sensor.

[0011] Optionally, the coordinate transformation algorithm further includes: a coordinate mapping relationship between the first coordinate data and the second coordinate data.

[0012] Optionally, the replacement of the first vehicle-mounted sensor is triggered by at least one of the following: detecting that the maintenance diagnostic system enters the sensor replacement mode; recognizing that the sensor hardware ID has changed; receiving a manual calibration start instruction.

[0013] Optionally, the vehicle-mounted sensor includes at least one of the following: a camera, a radar, an ultrasonic sensor, and an infrared sensor.

[0014] The computer-readable storage medium of the present application, on which a computer program is stored, and when the computer program is executed by a processor, the above calibration method is implemented.

[0015] The computer device of the present application, including a storage module, a processor, and a computer program stored on the storage module and executable on the processor, wherein when the processor executes the computer program, the above calibration method is implemented.

[0016] The computer program product of the present application, including a computer program, and when the computer program is executed by a processor, the above calibration method is implemented.

[0017] The vehicle of the present application, the vehicle includes the above calibration system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or other aspects and advantages of the present application will become clearer and easier to understand through the following descriptions of various aspects in conjunction with the drawings, and the same or similar units in the drawings are denoted by the same reference numerals. In the drawings:

[0019] Figure 1 A schematic flowchart of a calibration method 100 according to an embodiment of the present application is shown;

[0020] Figure 2A schematic block diagram of a calibration system 200 according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0021] The description of the following specific embodiments is merely exemplary in nature and is not intended to limit the disclosed technology or the application and use of the disclosed technology. In addition, it is not intended to be bound by any express or implied theory presented in the aforementioned technical field, background technology or the following specific embodiments.

[0022] In the following detailed description of the embodiments, many specific details are set forth in order to provide a more thorough understanding of the disclosed technology. However, it is apparent to one of ordinary skill in the art that the disclosed technology can be practiced without these specific details. In other instances, well-known features are not described in detail to avoid unnecessarily complicating the description.

[0023] Terms such as “comprise” and “include” indicate that in addition to the units and steps directly and explicitly stated in the specification, the technical solution of the present application does not exclude the situation where it has other units and steps that are not directly or explicitly stated.

[0024] Hereinafter, various exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings.

[0025] Reference now Figure 1 , Figure 1 is a schematic flow chart of a calibration method 100 according to an embodiment of the present application.

[0026] like Figure 1 As shown, the calibration method 100 includes:

[0027] Step S110: pre-establish a coordinate conversion algorithm between the first vehicle-mounted sensor and the second vehicle-mounted sensor. Specifically, step S110 is used to construct a dynamic mapping relationship between multiple sensor coordinate systems. In one or more embodiments, during the vehicle assembly stage or the first calibration, the first vehicle-mounted sensor (e.g., a camera) and the second vehicle-mounted sensor (e.g., a millimeter-wave radar) are installed to a preset tooling position to ensure that the two are fixed in a known relative position. By arranging a high-precision calibration plate or a dynamic target (e.g., a chessboard, a reflective ball, etc.) in the calibration site, the raw data of the two sensors are synchronously collected. For example, the camera generates pixel coordinates by identifying the corner points of the calibration plate, and the radar obtains the three-dimensional point cloud coordinates of the calibration plate through the reflected signal. The least squares method or nonlinear optimization algorithm is used to fit the rotation matrix and translation vector between the two coordinate systems to establish a mapping relationship between the first coordinate data (camera pixel coordinate system) and the second coordinate data (radar polar coordinate system). This process can be repeated multiple times to eliminate noise interference and store the mapping parameters in the vehicle-mounted domain controller.

[0028] Next, in step S120: Responsive to detecting that the first vehicle-mounted sensor is replaced. Specifically, this step realizes the automatic detection and calibration triggering of sensor replacement, and specifically may include the following sub-processes:

[0029] 1. Repair diagnosis mode trigger: When the vehicle enters the repair mode (for example, the OBD (On-Board Diagnostics) interface is connected to the diagnostic device), the system automatically detects the sensor status. If the repair instruction contains the sensor replacement operation, the calibration process is started.

[0030] 2. Hardware ID change trigger: The sensor hardware ID is monitored in real time through the CAN (Controller Area Network) bus. If it is detected that the ID of the first vehicle-mounted sensor does not match the historical record (for example, the new sensor serial number), it is determined as a replacement event.

[0031] 3. Manual calibration instruction trigger: The user can send a manual calibration request through the vehicle-mounted central control screen or the mobile terminal to forcibly start the process.

[0032] After triggering, the system immediately collects the first coordinate data of the replaced first vehicle-mounted sensor (for example, the newly installed camera). For example, by taking an image of the calibration board with the new camera and extracting the corner coordinates, or by using the radar to scan static obstacles to obtain parameters such as distance and azimuth angle.

[0033] In step S130: The first coordinate data is converted into the second coordinate data based on the coordinate transformation algorithm. This step uses the mapping relationship pre-stored in S110 to convert the original data of the new sensor into the coordinate system of the second vehicle-mounted sensor. For example, if the replaced sensor is a camera, its pixel coordinates are converted into radar polar coordinate data through the pre-stored R and t matrices. It should be noted that in this step, the following optimizations can be considered:

[0034] Dynamic compensation: For the small offset caused by the installation error, the Kalman filter or the sliding window algorithm is introduced to smooth the conversion result.

[0035] Multi-frame verification: Continuously collect multiple frames of data (for example, 10 frames), remove the outliers and then take the average value to ensure the conversion stability.

[0036] Cross-modal verification: If the second vehicle-mounted sensor is an ultrasonic radar, the converted distance data needs to be compared with the actual ultrasonic echo signal to verify the consistency.

[0037] Next, in step S140: Write the second coordinate data into the second vehicle-mounted sensor.

[0038] This step completes the solidification and system integration of the calibration parameters. In some examples, the converted second coordinate data (e.g., calibration parameters in the radar coordinate system) is written to the non-volatile memory of the second vehicle sensor via CAN or Ethernet, and the fusion algorithm parameter table of the domain controller is updated synchronously. The following operations need to be performed during implementation:

[0039] 1. Permission verification: Ensure that the write operation is initiated by an authenticated electronic control unit to prevent illegal tampering.

[0040] 2. Redundant backup: Store copies of calibration parameters in multiple controllers to prevent single point failure.

[0041] 3. Closed-loop verification: trigger the second on-board sensor (such as radar) to execute the self-test procedure, compare the output calibrated data with the expected value, and trigger an alarm and roll back to the previous version parameters when the error exceeds the threshold (such as ±2%).

[0042] In summary, the calibration method of this application has the following advantages:

[0043] 1. Automation and real-time: Through hardware ID detection and dynamic compensation mechanism, "plug and play" can be achieved after replacement, avoiding the downtime of traditional manual calibration.

[0044] 2. Multi-sensor compatibility: It supports calibration of multi-modal sensors such as cameras, radars, and ultrasonic waves. It has strong versatility and can achieve autonomous calibration for different types of sensors. Any existing sensor of the vehicle can be used as a benchmark to complete the calibration of the new sensor. It is also suitable for most vehicles with driving assistance systems with independent controllers, and has a wide range of applications.

[0045] 3. Anti-interference capability: Multi-frame verification and redundant check are used to improve calibration robustness in complex environments.

[0046] Reference now Figure 2 , Figure 2 A schematic block diagram of a calibration system 200 according to an embodiment of the present application is shown.

[0047] like Figure 2 As shown, the calibration system 200 includes a preset algorithm module 210 , a data acquisition module 220 and a coordinate conversion module 230 .

[0048] The preset algorithm module 210 is configured to pre-establish a coordinate conversion algorithm between the first vehicle-mounted sensor and the second vehicle-mounted sensor.

[0049] The data collection module 220 is configured to collect first coordinate data of the first vehicle-mounted sensor in response to detecting that the first vehicle-mounted sensor is replaced.

[0050] The coordinate conversion module 230 is configured to convert the first coordinate data into the second coordinate data of the second vehicle-mounted sensor based on the coordinate conversion algorithm.

[0051] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the calibration method of the present application described above is implemented.

[0052] The present application also provides a computer device, including a storage module, a processor, and a computer program stored on the storage module and executable on the processor. When the processor executes the computer program, the calibration method of the present application described above is implemented.

[0053] The present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the calibration method of the present application described above is implemented.

[0054] The present application also provides a vehicle, which includes the calibration system of the present application. The vehicle referred to in the present application may represent any suitable vehicle having a drive system composed of at least a battery, a power conversion device, and a drive motor. For example, a hybrid vehicle, an electric vehicle, a plug-in hybrid electric vehicle, and the like. A hybrid vehicle is a vehicle having two or more power sources, such as a gasoline-powered and an electric vehicle.

[0055] The specific embodiments described above in the present application are only for more clearly describing the principle of the present application, in which each component is clearly shown or described to make the principle of the present application easier to understand. Without departing from the scope of the present application, those skilled in the art can easily make various modifications or changes to the present application. Therefore, it should be understood that these modifications or changes should be included within the scope of the patent protection of the present application.

Claims

1. A calibration method for in-vehicle sensors, characterized in that, The calibration method includes the following steps: Pre-establish a coordinate transformation algorithm between a first vehicle-mounted sensor and a second vehicle-mounted sensor; In response to detecting that the first vehicle-mounted sensor is replaced, collect first coordinate data of the first vehicle-mounted sensor; and Based on the coordinate transformation algorithm, convert the first coordinate data into second coordinate data of the second vehicle-mounted sensor.

2. The calibration method according to claim 1, wherein The calibration method further includes: writing the second coordinate data into the second vehicle-mounted sensor.

3. The calibration method according to claim 1, characterized in that: The coordinate transformation algorithm further includes: a coordinate mapping relationship between the first coordinate data and the second coordinate data.

4. The calibration method according to claim 1, wherein: The replacement of the first vehicle-mounted sensor is triggered by at least one of the following methods: Detecting that the maintenance diagnostic system enters the sensor replacement mode; Identifying that the sensor hardware ID has changed; Receiving a manual calibration start instruction.

5. The calibration method according to claim 1, wherein The vehicle-mounted sensor includes at least one of the following: a camera, a radar, an ultrasonic sensor, and an infrared sensor.

6. A calibration system for an in-vehicle sensor, characterized in that, The calibration system includes: A preset algorithm module: configured to pre-establish a coordinate transformation algorithm between a first vehicle-mounted sensor and a second vehicle-mounted sensor; A data acquisition module: configured to collect first coordinate data of the first vehicle-mounted sensor in response to detecting that the first vehicle-mounted sensor is replaced; and A coordinate transformation module: configured to convert the first coordinate data into second coordinate data of the second vehicle-mounted sensor based on the coordinate transformation algorithm.

7. The calibration system according to claim 6, wherein The calibration system further includes a calibration writing module configured to write the second coordinate data into the second vehicle-mounted sensor.

8. The calibration system according to claim 6, characterized in that: The coordinate transformation algorithm further includes: a coordinate mapping relationship between the first coordinate data and the second coordinate data.

9. The calibration system according to claim 6, wherein: The replacement of the first vehicle-mounted sensor is triggered by at least one of the following methods: Detecting that the maintenance diagnostic system enters the sensor replacement mode; Identifying that the sensor hardware ID has changed; Receiving a manual calibration start instruction.

10. The calibration system according to claim 6, wherein The vehicle-mounted sensor includes at least one of the following: a camera, a radar, an ultrasonic sensor, and an infrared sensor.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the calibration method according to claims 1-5.

12. A computer device, comprising a storage module, a processor, and a computer program stored on the storage module and executable on the processor, characterized in that, When the processor executes the computer program, it implements the calibration method according to claims 1-5.

13. A computer program product, including a computer program, which implements the calibration method according to claims 1-5 when executed by a processor.

14. A vehicle, characterized in that, The vehicle includes the calibration method according to claims 6-10.

Images