Calibration value calculation device, calibration value calculation system, calibration value calculation method, and program

Abstract

To provide a calibration value calculation device, a calibration value calculation system, a calibration value calculation method, and a program requiring no lane restrictions during calibration.SOLUTION: The calibration value calculation device is provided with: a simulation information acquisition unit that acquires virtual point cloud data which is virtual point cloud data measured by a virtual sensor having a local coordinate system with respect to a first coordinate of a world coordinate system having an origin on the road surface, in a simulation space that includes a virtually reproduced road surface, a virtually reproduced virtual sensor, and geospatial information around the virtual sensor; an information acquisition unit that acquires point cloud data measured by a real sensor arranged on the real road surface near a position of the virtual sensor; and a calibration value calculation unit that calculates angular and coordinate differences between the local coordinate system and the sensor coordinate system of the real sensor based on the virtual point cloud data and the point cloud data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a calibration value calculation device, a calibration value calculation system, a calibration value calculation method, and a program. [Background technology]

[0002] For example, Patent Document 1 discloses a laser sensor that irradiates a vehicle with laser light, receives the reflected light, and generates point cloud data indicating the position of the vehicle based on the received reflected light. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-121505 Summary of the Invention [Problem to be solved by the invention]

[0004] Typically, such laser sensors are calibrated by placing a reference marker on the road surface, measuring the distance between the laser sensor and the reference marker using the laser sensor, and comparing the results with those measured using other measuring instruments. However, this calibration method requires an operator to enter the road surface when placing the reference markers on the road surface, which entails lane restrictions. This meant that lane restrictions were imposed during calibration.

[0005] An object of the present disclosure is to provide a calibration value calculation device, a calibration value calculation system, a calibration value calculation method, and a program that solve the above-mentioned problems.

[0006] An object of the present disclosure is to provide a calibration value calculation device, a calibration value calculation system, a calibration value calculation method, and a program that do not involve lane restrictions during calibration. [Means for solving the problem]

[0007] The calibration value calculation device disclosed herein includes a simulation information acquisition unit that acquires virtual point cloud data, which is virtual point cloud data measured by a virtual sensor having a local coordinate system at first coordinates of a world coordinate system having an origin on the road surface, in a simulation space including a virtually reproduced road surface, a virtually reproduced virtual sensor, and geospatial information around the virtual sensor; an information acquisition unit that acquires point cloud data measured by a real sensor placed on the real road surface close to the position of the virtual sensor; and a calibration value calculation unit that calculates the angle and coordinate difference between the local coordinate system and the sensor coordinate system of the real sensor based on the virtual point cloud data and the point cloud data.

[0008] The calibration value calculation method of the present disclosure includes the steps of: acquiring virtual point cloud data, which is virtual point cloud data measured by a virtual sensor having a local coordinate system at first coordinates of a world coordinate system having an origin on a virtually reproduced road surface, in a simulation space including a virtually reproduced virtual sensor, and geospatial information around the virtual sensor; acquiring point cloud data measured by a real sensor placed on a real road surface close to the position of the virtual sensor; and calculating, based on the virtual point cloud data and the point cloud data, an angle and a coordinate difference between the local coordinate system and the sensor coordinate system of the real sensor. Includes.

[0009] The program disclosed herein is a program for causing a computer to execute the following steps: acquiring virtual point cloud data, which is virtual point cloud data measured by a virtual sensor having a local coordinate system at a first coordinate of a world coordinate system having an origin on the road surface, in a simulation space including a virtually reproduced road surface, a virtually reproduced virtual sensor, and geospatial information around the virtual sensor; acquiring point cloud data measured by a real sensor placed on the real road surface close to the position of the virtual sensor; and calculating the angle and coordinate difference between the local coordinate system and the sensor coordinate system of the real sensor based on the virtual point cloud data and the point cloud data. [Effects of the Invention]

[0010] According to the calibration value calculation device, calibration value calculation system, calibration value calculation method, and program of the present disclosure, calibration is not accompanied by lane restrictions. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a schematic block diagram showing the configuration of a calibration value calculation system according to a first embodiment. [Figure 2] FIG. 1 is a diagram I showing an example of measurement by a virtual sensor in a simulation space according to the first embodiment. [Figure 3] FIG. 1 is a diagram I showing an example of measurement by a real sensor placed on a real road surface according to the first embodiment. [Figure 4] 4 is a flowchart illustrating an example of processing by the calibration value calculation device according to the first embodiment. [Figure 5] FIG. 10 is a diagram illustrating an example of a calibration value calculation device according to another embodiment. [Figure 6] FIG. 2 is a diagram II showing an example of measurement by a virtual sensor in a simulation space according to another embodiment. [Figure 7] FIG. 2 is a diagram II showing an example of measurements by a real sensor placed on a real road surface according to another embodiment. [Figure 8]FIG. 1 is a hardware configuration diagram illustrating a configuration of a computer according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, each embodiment of the present disclosure will be described with reference to the drawings. Note that the drawings and specific configurations used in each embodiment should not be used to interpret the disclosure. The same or corresponding configurations in all drawings will be assigned the same reference numerals, and common descriptions will be omitted.

[0013] FIG. 1 is a schematic block diagram showing the configuration of a calibration value calculation system 1 according to a first embodiment. FIG. 2 is a diagram I showing an example of measurement by a virtual sensor VS in a simulation space SS according to the first embodiment. FIG. 3 is a diagram I showing an example of measurement by a real sensor 12 arranged on a real road surface RR according to the first embodiment. FIG. 4 is a flowchart showing an example of processing by a calibration value calculation device according to the first embodiment. FIG. 5 is a diagram showing an example of a calibration value calculation device 11B according to another embodiment. FIG. 6 is a diagram II showing an example of measurement by a virtual sensor VS in a simulation space SS according to another embodiment. FIG. 7 is a diagram II showing an example of measurement by a real sensor arranged on a real road surface according to another embodiment. FIG. 8 is a hardware configuration diagram showing the configuration of a computer according to the present disclosure.

[0014] The calibration value calculation device according to the present disclosure will be described below with reference to FIGS.

[0015] (Configuration of calibration value calculation system) FIG. 1 is a diagram showing the configuration of a calibration value calculation system 1 according to the first embodiment. The calibration value calculation system 1 and the calibration value calculation device 11 of the present disclosure are used to calculate the calibration value of a laser sensor. As shown in FIG. 1, the calibration value calculation system 1 includes a calibration value calculation device 11 and a real sensor 12. The real sensor 12 is a laser sensor placed on the real road surface RR close to the position of a virtual sensor VS, which will be described later. An example of a laser sensor is a LiDAR (Light Detection and Ranging).

[0016] (Configuration of calibration value calculation device) As shown in FIG. 1, the calibration value calculation device 11 includes a simulation information acquisition unit 111, an information acquisition unit 112, a calibration value calculation unit 113, a calibration unit 114, and a storage unit . The operation of each unit in the calibration value calculation device 11 described below corresponds to at least a part of the calibration value calculation method of the present disclosure.

[0017] (Simulation space) The simulation information acquisition unit 111 acquires virtual point cloud data PCD_SS, which is virtual point cloud data measured by a virtual sensor VS (to be described later), in the simulation space SS. The simulation space SS may be provided in the calibration value calculation device 11. Alternatively, it may be provided separately in a device such as a simulator. The simulation space SS includes a virtually reproduced road surface VR, a virtually reproduced virtual sensor VS, and geospatial information around the virtual sensor VS. In the simulation space SS, there exists a world coordinate system with its origin (00,00,00) on the road surface VR. The three axes of the world coordinate system are (X0, Y0, Z0). As an example, the origin is set on the road marking RM on the road surface, the Y0 axis direction is aligned with the lane direction, and the X0 axis direction is perpendicular to the lane direction. The Z0 axis direction thus determined points perpendicular to the road surface. The local coordinate system of the virtual sensor VS is at the first coordinate of the world coordinate system with its origin on the road surface. The local coordinate system has its origin (0 s , 0 s , 0 s ), and the three axes of the local coordinate system are (X s , Y s , Z s) The origin (first coordinate) of the local coordinate system is set to the irradiation position of the virtual sensor VS. The origin of the world coordinate system is preferably set on a linear road marking such as a lane marking, a stop line, or a crosswalk, among other road markings RM.

[0018] The road surface VR and geospatial information in the simulation space SS are configured as a 3D model by converting point cloud data obtained by scanning with a laser scanner into a mesh model. The laser scanner scans the surrounding environment of the real sensor 12 to be calibrated. The surrounding environment to be scanned includes the road surface RR and geospatial information around the real sensor 12. In this way, the unevenness of the real road surface and the geospatial information around the real sensor 12 (for example, "trees near the road surface") are reproduced in the simulation space SS as a 3D model. The point cloud data may be smoothed using a smoothing method such as the moving least squares method. The mesh fineness of the mesh model may also be changed as appropriate by the operator.

[0019] For example, to obtain geospatial information around the virtual sensor, the scan results from a phase-based and time-of-flight laser scanner are used.

[0020] The virtual sensor VS in the simulation space is determined by the spec value of the virtual sensor VS, the position of the local coordinate system (first coordinate) as seen from the world coordinate system, and the three axes (X s ,Y s ,Z s In other words, the virtual sensor VS does not need to exist as a three-dimensional model in the simulation space. The specification values of the virtual sensor may be the same as the specification values of the real sensor 12. Examples of the specification values include a detection range, an angular resolution, and a maximum field of view.

[0021] (Outline of the processing of the calibration value calculation device) Just as the virtual sensor VS has a local coordinate system, the real sensor 12 also has a sensor coordinate system. For example, the sensor coordinate system of the real sensor 12 has an origin (0 r , 0 r , 0 r ), and the three axes of the sensor coordinate system are (X r , Y r , Z r ) The origin of the sensor coordinate system is the irradiation position of the real sensor 12. The calibration value calculation device 11 of the present disclosure has the origin (0 s , 0 s , 0 s ) and a virtual sensor VS located in a local coordinate system with an origin (0 r , 0 r , 0 r ) and the real sensor 12 located in the sensor coordinate system having the virtual sensor VS. r , Y r , Z r ) and calculates the difference in angle between the virtual sensor VS and the real sensor 12. In other words, the calibration value calculation device 11 of the present disclosure calculates the positional deviation and angular deviation of the real sensor 12 with respect to the virtual sensor VS. This results in the calculation of the calibration value of the real sensor 12. Then, based on the positional deviation and the angular deviation, the position of the sensor coordinate system as viewed from the world coordinate system (hereinafter also referred to as "second coordinates") and the directions of the three axes (X0, Y0, Z0) are identified.

[0022] (Simulation information acquisition section) The simulation information acquisition unit 111 acquires virtual point cloud data PCD_SS, which is virtual point cloud data measured by a virtual sensor VS having a local coordinate system in a simulation space SS. As shown in Figure 2, the origin of the local coordinate system (0 s , 0 s , 0 s The virtual point cloud data PCD_SS of the virtual sensor VS measured by the laser irradiated from the origin (0 s , 0 s, 0 s ) is a collection of coordinates in a local coordinate system based on the For example, the virtual point cloud data acquired by the simulation information acquisition unit 111 may be stored in the storage unit 116 in association with the position information (first coordinates) of the virtual sensor VS in the simulation space SS.

[0023] (Information acquisition department) The information acquisition unit 112 acquires point cloud data PCD_RS measured by a real sensor 12 placed on the real road surface RR close to the position of the virtual sensor VS. As shown in Figure 3, the origin of the sensor coordinate system (0 r , 0 r , 0 r The point cloud data PCD_RS of the real sensor 12 measured by the laser irradiated from the origin (0 r , 0 r , 0 r ) is a set of coordinates in the sensor coordinate system based on the For example, the point cloud data PCD_RS acquired by the information acquisition unit 112 may be stored in the storage unit 116 in association with the position information (first coordinates) of the virtual sensor VS that was targeted when the real sensor 12 was approached.

[0024] By setting the origin of the world coordinate system on the road marking RM, the real sensor 12 is placed on the real road surface RR close to the position of the virtual sensor VS, with reference to the position of the virtual sensor VS from the road marking RM.

[0025] (Calibration value calculation section) Based on the virtual point cloud data PCD_SS, the calibration value calculation unit 113 calculates the angle and coordinate differences between the local coordinate system and the sensor coordinate system of the real sensor 12. In other words, the calibration value calculation unit 113 calculates the positional deviation and angular deviation of the real sensor 12 with respect to the virtual sensor VS. Point cloud matching is used to calculate the difference. Point cloud data PCD_RS, which has the same number of coordinates, is matched to virtual point cloud data PCD_SS. Examples of point cloud matching include the least squares method and the minimax method. The angle and coordinate differences between the local coordinate system and the sensor coordinate system of the real sensor 12 may be stored in the storage unit 116 . Furthermore, the calibration value calculation unit 113 may specify, from the calculated difference, a second coordinate system and second coordinates of the real sensor 12 in the world coordinate system. Specifically, the calibration value calculation unit 113 uses the calculated difference to specify the sensor coordinate system of the real sensor 12 and the position of the sensor coordinate system as the second coordinate system and second coordinates of the real sensor 12 in the world coordinate system.

[0026] (Calibration section) The calibration unit 114 calibrates the measurement values of the real sensor 12 as measurement values in the world coordinate system based on the calculated difference. The calibration is performed by using the calculated difference to perform a transformation process on the measurement value of the real sensor 12 using a rotation matrix or a homogeneous transformation matrix.

[0027] (Storage part) The storage unit 116 can store the virtual point cloud data acquired by the simulation information acquisition unit 111, the position information (first coordinates) of the virtual sensor in the simulation space SS, and the point cloud data acquired by the information acquisition unit 112.

[0028] (Manufacturing method) A calibration value calculation method in this embodiment will be described. The calibration value calculation method in this embodiment is carried out according to the flow shown in FIG.

[0029] First, the simulation information acquisition unit 111 of the calibration value calculation device 11 acquires virtual point cloud data PCD_SS, which is virtual point cloud data measured by a virtual sensor VS having a local coordinate system at the first coordinate of a world coordinate system having its origin on the road surface VR, in a simulation space SS including a virtually reproduced road surface VR, a virtually reproduced virtual sensor VS, and geospatial information around the virtual sensor VS (step ST11).

[0030] Next, the worker approaches the position of the virtual sensor VS and sets up the real sensor 12 (step ST12).

[0031] Next, the information acquisition unit 112 of the calibration value calculation device 11 acquires the point cloud data PCD_RS measured by the reality sensor 12 (step ST13).

[0032] Next, the calibration value calculation unit 113 of the calibration value calculation device 11 calculates the angle and coordinate differences between the local coordinate system and the sensor coordinate system of the real sensor 12 based on the virtual point cloud data PCD_SS and the point cloud data PCD_RS (step ST14).

[0033] Furthermore, the calibration value calculation unit 113 of the calibration value calculation device 11 identifies the second coordinate system and the second coordinates of the real sensor 12 in the world coordinate system (step ST15).

[0034] Next, the calibration unit 114 of the calibration value calculation device 11 calibrates the measurement value of the real sensor 12 as a measurement value in the world coordinate system based on the difference calculated by the calibration value calculation unit 113 (step ST16). Here, the calibration value calculation device 11 calibrates the measurement values of the real sensor 12 as measurement values in the world coordinate system using the angle and coordinate differences between the local coordinate system and the sensor coordinate system of the real sensor 12, which are calculated based on the virtual point cloud data PCD_SS and the point cloud data PCD_RS. (End)

[0035] (Action and effect) The calibration value calculation device 11 of this embodiment calculates the angle and coordinate differences between the local coordinate system of the virtual sensor VS and the sensor coordinate system of the real sensor 12 based on the virtual point cloud data PCD_SS measured by the virtual sensor VS in the simulation space SS and the point cloud data PCD_RS measured by the real sensor 12 placed on the road surface RR. This allows the measurement values of the real sensor 12 to be calibrated as measurement values in the world coordinate system. Therefore, the calibration value calculation device according to the present disclosure does not involve lane restrictions during calibration.

[0036] (Other embodiments) The above describes in detail the embodiments of the present disclosure with reference to the drawings, but the specific configuration is not limited to this embodiment, and design changes and the like are also included within the scope that does not deviate from the gist of the present disclosure.

[0037] The order of the steps of the present disclosure can be changed as appropriate. For example, the order of the processing steps of the calibration value calculation method (steps ST11 to ST13) may be changed.

[0038] As shown in FIG. 5, the calibration value calculation device 11B may further include an extraction unit 115 that extracts a part of the virtual point cloud data PCD_SS and the point cloud data PCD_RS in addition to the above embodiment. In the simulation space SS, the unevenness of the actual road surface and geospatial information around the actual sensor 12 are reproduced as a three-dimensional model. If part of the virtual point cloud data PCD_SS of the virtual sensor VS contains unclear measurement points or reflection noise from the measurement side due to geospatial information such as road surface unevenness or trees near the road surface, the extraction unit 115 may extract part of the virtual point cloud data PCD_SS after excluding these points. As shown in FIG. 6, the extracted virtual point cloud data PCD_SSELI is subjected to point cloud matching with the point cloud data PCD_RSELI instead of the virtual point cloud data PCD_SS. Note that the point cloud data PCD_RSELI is also point cloud data in which the coordinates corresponding to the virtual point cloud data PCD_SSELI are extracted by the extraction unit 115, as shown in FIG. 7.

[0039] 8 is a hardware configuration diagram showing the configuration of a computer 1100 according to this embodiment. The computer 1100 includes, for example, a processor 1110, a main memory 1120, a storage 1130, and an interface 1140.

[0040] Each functional unit of the calibration value calculation device 11 described above is implemented in a computer 1100. The operation of each functional unit described above is stored in the form of a program in a storage 1130. The processor 1110 reads the program from the storage 1130, loads it into the main memory 1120, and executes the above processing in accordance with the program. The processor 1110 also allocates storage areas in the main memory 1120 to be used by each functional unit described above in accordance with the program.

[0041] The program may be for realizing some of the functions to be performed by the computer 1100. For example, the program may be combined with other programs already stored in the storage 1130 or other programs implemented in other devices to perform the functions. Furthermore, the computer 1100 may include a custom LSI (Large Scale Integrated Circuit) such as a PLD (Programmable Logic Device) in addition to or instead of the above configuration. Examples of PLDs include a PAL (Programmable Array Logic), a GAL (Generic Array Logic), a CPLD (Complex Programmable Logic Device), and an FPGA (Field Programmable Gate Array). In this case, some or all of the functions to be performed by the processor 1110 may be realized by the integrated circuit.

[0042] Examples of storage 1130 include a magnetic disk, a magneto-optical disk, and a semiconductor memory. Storage 1130 may be an internal medium directly connected to the bus of computer 1100, or an external medium connected to computer 1100 via interface 1140 or a communication line. When this program is distributed to computer 1100 via a communication line, computer 1100 that receives the program may load the program into main memory 1120 and execute the above-mentioned processing. The program may also be a program for realizing part of the above-mentioned functions. Furthermore, the program may be a program that realizes the above-mentioned functions in combination with another program already stored in storage 1130, i.e., a so-called differential file (differential program).

[0043] <Additional Notes> The calibration value calculation device 11 described in each embodiment can be understood, for example, as follows.

[0044] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0045] (Appendix 1) (1) A calibration value calculation device 11 according to a first aspect includes a simulation information acquisition unit 111 that acquires virtual point cloud data PCD_SS, which is virtual point cloud data measured by a virtual sensor VS having a local coordinate system at a first coordinate of a world coordinate system having an origin (00,00,00) on the road surface VR, in a simulation space SS including a virtually reproduced road surface VR, a virtually reproduced virtual sensor VS, and geospatial information around the virtual sensor VS; an information acquisition unit 112 that acquires point cloud data PCD_RS measured by a real sensor 12 placed on a real road surface RR close to the position of the virtual sensor VS; and a calibration value calculation unit 113 that calculates the angle and coordinate difference between the local coordinate system and the sensor coordinate system of the real sensor 12 based on the virtual point cloud data PCD_SS and the point cloud data PCD_RS.

[0046] With this configuration, in the simulation space SS, based on the virtual point cloud data PCD_SS measured by the virtual sensor VS and the point cloud data PCD_RS measured by the real sensor 12 placed on the road surface RR, the angle and coordinate differences between the local coordinate system of the virtual sensor VS and the sensor coordinate system of the real sensor 12 are calculated. This makes it possible to calibrate the measurement values of the real sensor 12 as measurement values in the world coordinate system. Therefore, the calibration value calculation device according to the present disclosure does not involve lane restrictions during calibration.

[0047] (Appendix 2) (2) The calibration value calculation device 11 according to the second aspect is the calibration value calculation device according to (1), further comprising a calibration unit 114 that calibrates the measurement value of the real sensor 12 as a measurement value in the world coordinate system.

[0048] With this configuration, in the simulation space SS, based on the virtual point cloud data PCD_SS measured by the virtual sensor VS and the point cloud data PCD_RS measured by the real sensor 12 placed on the road surface RR, the angle and coordinate differences between the local coordinate system of the virtual sensor VS and the sensor coordinate system of the real sensor 12 are calculated. Thereafter, the calibration unit 114 can calibrate the measurement values of the real sensor 12 as measurement values in the world coordinate system. Therefore, the calibration value calculation device according to the present disclosure does not involve lane restrictions during calibration.

[0049] (Appendix 3) (3) A calibration value calculation device 11 according to a third aspect is the calibration value calculation device according to (1) or (2), in which the specification values of the virtual sensor VS are the same as the specification values of the real sensor 12.

[0050] According to this configuration, the accuracy of calculation of the angle and coordinate difference between the local coordinate system and the coordinate system of the real sensor 12, which is calculated based on the virtual point cloud data PCD_SS and the point cloud data PCD_RS, is improved.

[0051] (Appendix 4) (4) A calibration value calculation device 11B according to a fourth aspect is a calibration value calculation device according to any one of (1) to (3), further comprising an extraction unit that extracts a portion of the virtual point cloud data PCD_SS.

[0052] According to this configuration, by extracting a portion of the virtual point cloud data PCD_SS and the point cloud data PCD_RS, it is possible to calculate the angle and coordinate differences between the local coordinate system and the coordinate system of the real sensor 12 based on the virtual point cloud data PCD_SSELI and point cloud data PCD_RSELI in the extracted location. This reduces the amount of point cloud data that needs to be processed, reducing the load on the computer.

[0053] (Appendix 5) (5) A calibration value calculation system 1 according to a fifth aspect includes the calibration value calculation device according to any one of (1) to (4) and the real sensor 12.

[0054] With this configuration, in the simulation space SS, based on the virtual point cloud data PCD_SS measured by the virtual sensor VS and the point cloud data PCD_RS measured by the real sensor 12 placed on the road surface RR, the angle and coordinate differences between the local coordinate system of the virtual sensor VS and the sensor coordinate system of the real sensor 12 are calculated. This makes it possible to calibrate the measurement values of the real sensor 12 as measurement values in the world coordinate system. Therefore, the calibration value calculation system 1 according to the present disclosure does not involve lane restrictions during calibration.

[0055] (Appendix 6) (6) A calibration value calculation method according to a sixth aspect includes the steps of: acquiring virtual point cloud data PCD_SS, which is virtual point cloud data measured by a virtual sensor VS having a local coordinate system at a first coordinate of a world coordinate system having an origin (00,00,00) on the road surface VR, in a simulation space SS including a virtually reproduced road surface VR, a virtually reproduced virtual sensor VS, and geospatial information around the virtual sensor VS; acquiring point cloud data PCD_RS measured by a real sensor 12 placed on a real road surface RR close to the position of the virtual sensor VS; and calculating, based on the virtual point cloud data PCD_SS and the point cloud data PCD_RS, the angle and coordinate difference between the local coordinate system and the sensor coordinate system of the real sensor 12.

[0056] With this configuration, in the simulation space SS, based on the virtual point cloud data PCD_SS measured by the virtual sensor VS and the point cloud data PCD_RS measured by the real sensor 12 placed on the road surface RR, the angle and coordinate differences between the local coordinate system of the virtual sensor VS and the sensor coordinate system of the real sensor 12 are calculated. This makes it possible to calibrate the measurement values of the real sensor 12 as measurement values in the world coordinate system. Therefore, the calibration value calculation method according to the present disclosure does not involve lane restrictions during calibration.

[0057] (Appendix 7) (7) The program according to the seventh aspect causes a computer to execute the following steps: acquiring virtual point cloud data PCD_SS, which is virtual point cloud data measured by a virtual sensor VS having a local coordinate system at a first coordinate of a world coordinate system having an origin (00,00,00) on the road surface VR, on a simulation space SS including a virtually reproduced road surface VR, a virtually reproduced virtual sensor VS, and geospatial information around the virtual sensor VS; acquiring point cloud data PCD_RS measured by a real sensor 12 placed on a real road surface RR close to the position of the virtual sensor VS; and calculating the angle and coordinate difference between the local coordinate system and the sensor coordinate system of the real sensor 12 based on the virtual point cloud data PCD_SS and the point cloud data PCD_RS.

[0058] With this configuration, in the simulation space SS, based on the virtual point cloud data PCD_SS measured by the virtual sensor VS and the point cloud data PCD_RS measured by the real sensor 12 placed on the road surface RR, the angle and coordinate differences between the local coordinate system of the virtual sensor VS and the sensor coordinate system of the real sensor 12 are calculated. This makes it possible to calibrate the measurement values of the real sensor 12 as measurement values in the world coordinate system. Therefore, the program according to the present disclosure does not involve lane restrictions during calibration. [Explanation of symbols]

[0059] 1. Calibration value calculation system 11 Calibration value calculation device 111 Simulation Information Acquisition Unit 112 Information Acquisition Department 113 Calibration value calculation unit 114 Calibration section 115 Extraction part 116 Memory section PCD_RS point cloud data PCD_RSELI Extracted point cloud data PCD_SS Virtual Point Cloud Data PCD_SSELI Virtual point cloud data Phase-Based phase difference method RM road marking RR road surface VR road surface VS Virtual Sensor 12 Reality Sensor

Claims

1. a simulation information acquisition unit that acquires, in a simulation space including a virtually reproduced road surface, a virtually reproduced virtual sensor, and geospatial information around the virtual sensor, virtual point cloud data that is virtual point cloud data measured by the virtual sensor having a local coordinate system at first coordinates of a world coordinate system having an origin on the road surface; an information acquisition unit that acquires point cloud data measured by a real sensor placed on a real road surface close to the position of the virtual sensor; a calibration value calculation unit that calculates an angle and a coordinate difference between the local coordinate system and a sensor coordinate system of the real sensor based on the virtual point cloud data and the point cloud data; Equipped with Calibration value calculation device.

2. a calibration unit that calibrates the measurement value of the real sensor as a measurement value in the world coordinate system based on the difference; Further equipped The calibration value calculation device according to claim 1 .

3. The spec value of the virtual sensor is the same as the spec value of the real sensor. The calibration value calculation device according to claim 1 or 2.

4. an extraction unit that extracts the virtual point cloud data and a part of the point cloud data. The calibration value calculation device according to claim 1 or 2.

5. A calibration value calculation device according to claim 1 or 2; the reality sensor; and Equipped with Calibration value calculation system.

6. a step of acquiring virtual point cloud data, which is virtual point cloud data measured by the virtual sensor having a local coordinate system at first coordinates of a world coordinate system having an origin on the road surface, in a simulation space including a virtually reproduced road surface, a virtually reproduced virtual sensor, and geospatial information around the virtual sensor; acquiring point cloud data measured by a real sensor placed on a real road surface close to the position of the virtual sensor; calculating an angle and a coordinate difference between the local coordinate system and a sensor coordinate system of the real sensor based on the virtual point cloud data and the point cloud data; Contains Calibration value calculation method.

7. a step of acquiring virtual point cloud data, which is virtual point cloud data measured by the virtual sensor having a local coordinate system at first coordinates of a world coordinate system having an origin on the road surface, in a simulation space including a virtually reproduced road surface, a virtually reproduced virtual sensor, and geospatial information around the virtual sensor; acquiring point cloud data measured by a real sensor placed on a real road surface close to the position of the virtual sensor; calculating an angle and a coordinate difference between the local coordinate system and a sensor coordinate system of the real sensor based on the virtual point cloud data and the point cloud data; Have your computer run program.

Images