Computer-implemented method for checking and accumulating map expansions for digital maps for use in movable devices

Abstract

The invention relates to a computer-implemented method (100) for checking and approving a map extension (1) for a digital map (2) for use in a movable device (4), in particular in a vehicle or robot, the digital map (2) having at least one connection region (5), and the map extension (1) having at least one extension region (6) and an overlap region (7), wherein the overlap region (7) describes a surrounding region which is at least partially identical to a connection region (5) of the digital map. The invention also comprises a computing unit, a computer program and a machine-readable storage medium.

Description

Technical Field

[0001] This invention relates to a computer-implemented method for inspecting and approving (Freigeben) map extensions for use in digital maps on mobile devices. Furthermore, the invention includes a computing unit, a computer program product, and a machine-readable storage medium. Background Technology

[0002] Methods for inspecting and approving map extensions for digital maps for use in mobile devices are known from the prior art. Summary of the Invention

[0003] Therefore, the object of the present invention is to provide an improved computer-implemented method for inspecting and approving map extensions for use in digital maps for use in mobile devices.

[0004] This task is solved using a computer-implemented method according to the invention for inspecting and approving map extensions for use in digital maps on mobile devices. Advantageous embodiments are given below.

[0005] According to a first aspect of the invention, a method is provided for inspecting and approving map extensions for use in digital maps for computer implementations in movable devices, particularly vehicles or robots. The digital map has at least one connected region. The map extension has at least one extended region and an overlapping region, wherein the overlapping region describes a surrounding environmental area that is at least partially identical to the connected region of the digital map. The method includes the following steps:

[0006] - Map expansion is checked using connected regions and overlapping regions, wherein, for the check, geometric matching (Abgleich) and / or feature-based localization are performed between connected regions and overlapping regions, wherein, for the geometric matching and / or the feature-based localization, at least one dataset and at least one associated comparison data item (Vergleichsdatum) are used, the comparison data item having at least one pre-given tolerance value, wherein the position estimate of movable devices and / or the self-motion estimate of movable devices are used as the dataset for the overlapping regions, wherein measurements from at least one measurement trip are used as the comparison data item for the connected regions, and wherein at least one dataset is compared with the comparison data item.

[0007] - If the comparison between the dataset and the relevant comparison data items is within a pre-defined tolerance value when the map extension is checked, the map extension is approved for use in digital maps for use on mobile devices.

[0008] In this way, the technical advantage of providing an improved method for inspecting and approving map extensions for use in digital maps can be achieved. For this purpose, connected and overlapping regions are inspected. For this inspection, geometric matching and / or feature-based localization are performed, wherein the dataset used is compared with corresponding comparison data items. That is, a consistency check is performed for connected and overlapping regions. Advantageously, in this way, an improved estimate or statement regarding the quality of the map extension can be made. Furthermore, it is possible to check whether the map extension has also been integrated into the digital map with sufficient accuracy. Through this check, the map extension can be approved for use in the digital map and used in the same manner and method on mobile devices. Furthermore, it is possible to achieve the advantage of efficiently and with high accuracy integrating unmapped or only insufficiently mapped areas in the surrounding environment into existing digital maps.

[0009] In another implementation, the map extension is approved for use in digital maps to control driving functions for moving devices. In this way, for example, the technical advantage of being able to use the map extension also in map-based driving assistance systems in moving devices can be achieved.

[0010] In another implementation, the map extension is approved for use with digital maps for partially and / or fully autonomous control of driving functions, and / or for safety-related driving functions to control movable devices. In this way, for example, the technical advantage of enabling the map extension to be used for map-based, and especially fully autonomous, map-based control of movable devices can be achieved. In this way, the map-based steps required for initializing driving functions can be performed at the start of driving, for example, in a private parking lot. Thus, sensor calibration can be performed, for example, early on. Furthermore, the advantage of using highly autonomous driving functions for longer distances can be achieved.

[0011] In another implementation, map extensions and digital maps are matched using correspondence-based alignment, particularly using point correspondences, and / or tile correspondences, and / or line correspondences for the matching. This approach offers the technical advantage of performing the matching, or connection, of map extensions and digital maps with high accuracy. Furthermore, the efficiency of the method can be improved by using correspondence-based alignment.

[0012] In another implementation, an additional method step involves checking the map extension using redundant comparison information with pre-defined tolerance values. Satellite imagery and / or measurement data from sensors during the measurement journey are used as the redundant comparison information. The map extension is checked against the redundant comparison information in terms of geometric deviation, taking into account the pre-defined tolerance values. If the geometric match is within the pre-defined tolerance values, the map extension is approved. In this way, for example, the technical advantage of providing additional accuracy and security can be achieved. By comparing the map extension with the redundant comparison information, an additional check on the map extension can be provided. In other words, using this additional method step, it can be determined whether the map extension has been recorded sufficiently accurately and completely. In cases where there is a large deviation when comparing with the comparison information, the map extension can be prevented from being used in movable devices or discarded. Therefore, this method can ensure additional security for the checking of map extensions in this way.

[0013] In another implementation, measurement data in different data formats is used for comparison information, such as lidar data, and / or radar data, and / or video camera data, and / or infrared data, and / or magnetic field data, and / or ultrasonic data, wherein a measurement data type different from the measurement data type on which the map extension is based is used as redundant comparison information. In this way, for example, the technical advantage of the method being further secure and with improved accuracy can be achieved.

[0014] In another implementation, for feature-based localization, position estimates of movable devices are obtained as a dataset for overlapping regions. For connected regions, the positions of movable devices within the digital map during the measurement journey are obtained as comparison data items. In this way, for example, the technical advantage of particularly accurate examination of overlapping and connected regions can be achieved. By estimating positions within overlapping regions and comparing them with actual positions within connected regions, precise statements can be made regarding the quality and integration of map expansion.

[0015] In another implementation, for feature-based localization, self-motion estimates of movable devices are obtained as a dataset for overlapping regions, and the actual motion of movable devices during the measurement journey is obtained as a comparison data item for connected regions. In this way, for example, the technical advantage of improved assurance can be achieved using map extensions for movable devices. To this end, self-motion estimates are obtained for overlapping regions, i.e., estimations are performed based on map extensions, such as the state of the movable devices in the overlapping regions when they are to be automatically controlled by driving functions. The estimation results are then compared with one, or preferably multiple, measurement journeys in the connected regions of the digital map. This can also be referred to as "Shadow-Mode." This provides the advantage that when checking map extensions, not only is consistency checked on the geometric surrounding data, but also the accuracy of the virtual or simulated self-motion estimates.

[0016] According to a second aspect of the invention, a computing unit is provided, which is configured to implement all the steps of the method according to the first aspect.

[0017] According to a third aspect of the invention, a computer program is provided, the computer program including instructions, which, when implemented by a computer, cause the computer to perform the method according to the first aspect.

[0018] According to a fourth aspect of the invention, a machine-readable storage medium is provided on which a computer program according to the third aspect is stored. Attached Figure Description

[0019] The invention is described in more detail below with reference to the exemplary drawings and embodiments. Herein lies:

[0020] Figure 1 Based on the schematic flowchart of the method in the first aspect;

[0021] Figure 2 Simplified exemplary illustration of a digital map and a movable device;

[0022] Figure 3 A simplified, exemplary diagram of the map expansion;

[0023] Figure 4 A demonstrative examination of digital maps and map extensions using feature-based positioning;

[0024] Figure 5 Further exemplary examination of digital maps and map extensions using redundant comparison information;

[0025] Figure 6 The schematically simplified computational unit described in the second aspect;

[0026] Figure 7 A schematic, highly simplified illustration of the machine-readable storage medium according to the fourth aspect. Detailed Implementation

[0027] Figure 1 A schematic flowchart of the method 100 according to the first aspect is shown.

[0028] Method 100 is a method for inspecting and approving a computer-implemented map extension for a digital map. The map extension and the digital map are intended for use in movable devices, particularly in vehicles or robots. The map extension processed using Method 100 has at least one extended area and one overlapping area. The digital map has at least one connected area. The overlapping area of ​​the map extension and the connected area of ​​the digital map describe at least partially identical surrounding environmental areas.

[0029] The digital map can be, in particular, a highly accurate digital map. Furthermore, it is conceivable that this digital map is a so-called behavior map and can be used for map-based control of driving functions for movable devices. Similarly, it is conceivable that map extensions can be configured as highly accurate digital map extensions, and especially as behavior maps. Moreover, for example, the digital map can be used to map-based control of movable devices to partially and / or fully autonomous driving operations.

[0030] Method 100 is used to examine a map extension for a digital map and approve it for use in a mobile device. For this purpose, the following method steps 110 and 130 are performed. In an advantageous embodiment, method 100 has an additional second method step 120.

[0031] In step 110 of the first method, map expansion is checked using connected regions and overlapping regions. For this check, geometric matching and / or feature-based localization are performed between the connected and overlapping regions. For geometric matching and / or feature-based localization, at least one dataset and associated comparison data items with pre-defined tolerance values ​​are used. Here, position estimates of movable devices and / or self-motion estimates of movable devices are used as the dataset for the overlapping regions. For the comparison data items, measurements from at least one measurement trip are used for the connected regions. The at least one dataset is then compared with the comparison data items.

[0032] Advantageously, map extensions and digital maps are matched using correspondence-based alignment. Specifically, this correspondence-based alignment matching utilizes point correspondences, and / or tile correspondences, and / or line correspondences.

[0033] For feature-based localization, the estimated locations of movable devices can be obtained for overlapping regions as a dataset. Then, the locations of movable devices within the digital map during at least one measurement trip can be obtained for connected regions as comparison values.

[0034] Furthermore, it is conceivable that for feature-based localization, the self-motion estimates of movable devices can be obtained as a dataset for overlapping regions. Here, the actual motion of movable devices during at least one measurement journey is obtained as a comparison value for connected regions.

[0035] Particularly preferably, for feature-based localization, not only is the self-motion estimate of the movable device obtained for the overlapping area, but also the position estimate of the movable device is obtained, and then compared with the actual movement and position of the movable device.

[0036] In an additional optional method step 120, the map expansion is checked with the help of redundant comparison information.

[0037] Satellite imagery and / or sensor measurement data from at least one measurement run are used as redundancy comparison information. Map overlay and redundancy comparison information are checked for geometric deviations.

[0038] Advantageously, measurement data in different data formats are used, such as lidar data, and / or radar data, and / or video camera data, and / or infrared data, and / or magnetic field data, and / or ultrasonic data. Preferably, a measurement data type different from the measurement data type on which the map extension is based is used as redundant comparison information.

[0039] In other words, it can be stated that when examining map extensions using redundant comparative information in the form of sensor measurement data—for example, when the map extension is created based on video camera data—LiDAR data is used as the comparative information. As another example, it is conceivable that, for the case where the map extension is based on video camera data, magnetic field or ultrasonic data could be used as redundant comparative information.

[0040] In the third step 130, if, during the inspection of the map extension, the comparison between the dataset and the relevant comparison data items is within a pre-defined tolerance value, then the map extension is approved for use in digital maps for use on mobile devices.

[0041] In the case where an optional second method step 120 is used in method 100, map expansion is approved when the check is successfully performed in the first method step 110 and the second method step 120.

[0042] Map extensions can be approved for use in digital maps to control driving functions for moving devices. Furthermore, map extensions for digital maps can also be approved for partially and / or fully autonomous driving functions, and / or map extensions can also be approved for safety-related driving functions to control moving devices.

[0043] Therefore, Method 100 is an efficient method for inspecting and approving map extensions for digital maps. Using Method 100, highly accurate digital maps and highly accurate map extensions can be inspected, in particular. Through the inspection of map extensions and, especially, through the advantageous configuration of this method, Method 100 can provide a highly accurate and precise method for providing map extensions for digital maps for use in mobile devices.

[0044] In the following Figures 2 to 5 The diagram illustrates what such digital maps and map extensions might look like, how they can be used, and how they can be inspected and approved using method 100.

[0045] Figure 2 Digital map Figure 2 A simplified exemplary illustration of the movable device 4.

[0046] Digital Figure 2 For use in a movable device 4. The movable device 4 can be, for example, a vehicle. In particular, digitally... Figure 2 It can be used to control driving function 3 in a moving device 4. Digitally Figure 2 It can be used in particular to control driving functions during partially and / or fully autonomous driving operations.

[0047] For use in a device 4 that can move, digitally Figure 2 For example, high-resolution digital maps Figure 2 In particular, digital Figure 2 It is a behavior map used for map-based control of driving function 3. In this embodiment, digital map... Figure 2 It contains different information about the surrounding environment and / or driving behavior using manually controlled devices. Thus, exemplary, digitally. Figure 2 It has a driving lane direction 9. The driving lane direction 9 can have different types of road markings. Thus, for example, stop markings, boundary stripe markings, or center stripe markings can be stored digitally. Figure 2The driving lane direction 9 is used in the image. Furthermore, for use in movable devices 4, different behavioral data 11 are stored in a digital map. Additionally, for example, the digital map has a trajectory 10. As behavioral data 11, it may include, for example, average speed and / or stopping points of manually controlled movable devices. Trajectory 10 and behavioral data 11 may be based on so-called fleet data. Fleet data is typically anonymized and originates from manually controlled vehicles. Because fleet data is anonymized, the digital map... Figure 2 Behavioral data 11 and trajectory 10 are not available in all areas. For example, anonymized data is recorded 1 kilometer after the start of the drive and ends 1 kilometer before the end of the drive. Therefore, digital maps often lack sufficient information for private plots, parking lots, or parking garages. Without behavioral data 11 and trajectory 10, or with only a very small amount of trajectory 10 and behavioral data 11, it is almost impossible to utilize digital maps effectively. Figure 2 4. A device that can move based on a map during partially and / or fully autonomous driving operations.

[0048] Digital Figure 2 It has a connection area 5. Connection area 5 describes the digital location. Figure 2 The following areas contain only insufficient information regarding lane direction 9, trajectory 10, or behavior data 11. Furthermore, connecting area 5 extends at least partially into the digital area. Figure 2 In the following areas: In these areas, there is still sufficient behavioral data 11, trajectory 10, or lane direction 9.

[0049] Digital Figure 2 It can be stored online in a mobile device or in the cloud. For digital storage... Figure 2 The movable device 4, for example, has a control device 8, which is configured to control the driving function 3. For this purpose, the control device 8 is digitally... Figure 2 Information obtained allows for the control of driving function 3, taking into account behavioral data 11 and / or trajectory 10. Thus, for example, control device 8 can instruct driving function 3 when the movable device 4 should proceed straight, brake, follow a curve, or change lanes. Furthermore, it is conceivable that the movable device 4, or the vehicle, possesses a computing unit 20. The computing unit 20, for example, can process data from digital... Figure 2 The computing unit 20 can be set up online in device 4 or in the cloud.

[0050] In order to enable the use of such digital mapping in other areas of the surrounding environment Figure 2 Therefore, it is necessary to create map extensions and integrate them into digital maps accordingly. Figure 2This map extension is intended for use in China. It should be created with high accuracy and additionally provide a high level of safety, enabling control of moving devices 4, particularly utilizing partially and / or fully autonomous driving functions 3. The following... Figure 3 The diagram illustrates what such an expanded map might look like.

[0051] Figure 3 A simplified illustrative diagram of the height of map extension 1 is shown.

[0052] Map extension 1 has an extension area 6 and an overlapping area 7. Extension area 6 and overlapping area 7, for example, contain information about lane directions 9. Overlapping area 7 corresponds to a surrounding environment area that is at least partially identical to the connected area of ​​the digital map. Extension area 6 is located adjacent to overlapping area 7. Extension area 6 describes an area that does not exist or only partially exists in the digital map. For example, extension area 6 could be a parking lot. To map a private parking lot in extension area 6, the owner of the private land needs to request approval for mapping extension area 6. Extension area 6 and overlapping area 7 can then be recorded using sensors. Thus, to map or record map extension 1, and especially overlapping area 7 and extension 6, different sensors of movable devices can be used. Map extension is preferably a highly accurate map extension and is created, for example, using LiDAR data, and / or radar data, and / or video camera data, and / or infrared data, and / or magnetic field data, and / or ultrasonic data. Then, by means of alignment based on correspondence, map extension 1, recorded using these data, can be merged with the digital map.

[0053] For alignment based on correspondences, point correspondences and / or tile correspondences and / or line correspondences can be used in particular. For example, it is conceivable that map extensions can be geometrically connected to digital maps using the FCGF method.

[0054] To ensure that Map Extension 1 is correctly integrated into the digital map, the previously used methods can be employed. Figure 1 The method described herein offers the advantage that the inspection of the integration of map extension 1 provides high security and therefore map extension 1 can also be used for partially and / or fully automated control of movable devices. In the following... Figure 4 and Figure 5 The example demonstrates how such a check can be performed on map extension 1 used for digital maps.

[0055] Figure 4 This demonstrates the use of feature-based positioning for digital mapping. Figure 2 A demonstrative check was performed on map extension 1.

[0056] The smaller illustration shows a digital map with map expansion 1. Figure 2 Furthermore, connecting region 5 and overlapping region 7 are shown in a magnified form in a further detailed view. As previously mentioned, map extension 1 and digital map... Figure 2 Connections can be made using alignment based on correspondence between the connecting region 5 and the overlapping region 7. The connecting region 5 and the overlapping region 7 can be checked using feature-based positioning. Thus, for example, for the overlapping region 7 of map extension 1, a self-motion estimate for the movable device 4 is estimated. The self-motion estimate can be, for example, a trajectory 10. Furthermore, a position estimate for the overlapping region 7 of map extension 1 can also be estimated, for example, in the form of a positioning point 12. The estimated trajectory 10 is then compared with the actual movement of the movable device 4 during the measurement journey 16. The actual movement is additionally provided with a tolerance value. Thus, for example, the actual self-motion is provided with a tolerable deviation. Subsequently, the actual movement of the movable device 4 is compared with the estimated trajectory 10. If the actual movement of the movable device 4 and the estimated trajectory 10 are within a given tolerance value, or a tolerable deviation, map extension 1 can be approved for use in digital mapping. Figure 2 Alternatively or additionally, position estimation can also be used for the inspection. Here, the actual position of the movable device 4 within the connecting area 5 is determined, and a tolerance value is also specified for the actual position. Similar to the operation using trajectory 10, the actual position of the movable device is then compared with the position estimate, or positioning point 12, from map extension 1. If the comparison is within the pre-given tolerance value, map extension 1 can be approved for use in digital mapping. Figure 2 .

[0057] In other words, this check can also be called "shadow mode." It's called "shadow mode" because during the actual driving of the movable device 4, the previously performed estimate in the background is compared with the measured stroke 16. In this way, it checks whether the driving function of the movable device 4, which is controlled particularly automatically and / or partially automatically, will achieve the same or nearly the same behavior as a manually controlled movable device 4.

[0058] Additionally, a consistency check can be performed on the extended region 6 used for map extension 1 using redundant comparison information. The following exemplifies this using… Figure 5 Describe this.

[0059] Figure 5 This demonstrates the use of redundant comparison information 13 to pair digital locations Figure 2 Further exemplary checks were conducted with Map Extension 1.

[0060] Digital Figure 2The map extension 1 is interconnected as shown in the previously described diagram, and an extension area 6 is shown, for example, as a parking lot. Advantageously, the extension area 6 is compared with redundant comparison information 13. This additionally provides the advantage that the extension area 6 can be checked in addition to the consistency checks on overlapping and connected areas. For example, satellite images 14 or measurement data 15 in the form of sensor data can be used as redundant comparison information 13. Measurement data 15 can exist in different types of data forms, such as lidar data, and / or radar data, and / or video camera data and / or infrared data and / or magnetic field data and / or ultrasonic data. Preferably, these measurement data 15 have been generated by means of multiple measurement trips 16 of the measuring vehicle. Based on these measurement data 15, the extension area 6 is checked and compared. In this embodiment, for example, the extension area 6 has been created using lidar data. For example, measurement data 15 for comparing the extension area 6 is recorded using video camera data. Furthermore, the extension area 6 can also be matched using satellite images 14. Thus, for example, multiple satellite images 14 can be taken and compared with the extension area 6. It is also conceivable that not only satellite images 14, but also measurement data 15, can be used to check the redundancy comparison information 13 of the extended area 6.

[0061] This additional check, performed using redundant comparison information 13, allows for improved accuracy of the proposed method. If errors occur during the analysis and processing of measurement data 15 and / or satellite imagery 14 with the extended area 6, approval of the map extension 1 for digital mapping can be prevented. Figure 2 .

[0062] Therefore, the proposed method can provide digital... Figure 2 Map expansion 1 and simultaneously provides support for digital maps Figure 2 And an improved consistency check with Map Extension 1. Advantageously, Map Extension 1 is approved for use in digital mapping. Figure 2 This map can then be expanded to control movable devices, particularly vehicles or robots, during partially or fully autonomous driving operations. Accurate checks performed using this method ensure the accuracy of data used in digital mapping. Figure 2 Map extension 1 can also be approved for use in high-safety-related driving functions. Thus, this method enables map extension 1 to be used for digital mapping. Figure 2 It can also be used, in particular, on private plots, parking lots, or underground garages, for map-based control of driving functions.

[0063] Figure 6 The computing unit 20 according to the second aspect is shown.

[0064] The computing unit 20 is configured to perform all the steps of the previously described method, including all the steps in the advantageous embodiments. The computing unit 20 may in particular be a computer.

[0065] Figure 7 A machine-readable storage medium 30 according to the fourth aspect is shown.

[0066] A computer program 25 according to the third aspect is stored on a machine-readable storage medium 30. The computer program 25 includes instructions that, when implemented by a computer, cause the computer to perform the method according to the first aspect. The machine-readable storage medium 30 can, for example, be used by... Figure 6 The calculation unit 20 in the middle is read.

[0067] Although the present invention has been described with reference to specific embodiments, those skilled in the art can implement previously undisclosed or only partially disclosed embodiments without departing from the core of the invention.

Claims

1. A method (100) for inspecting and approving map extensions (1) for digital maps (2) for computer implementation in movable devices (4), particularly in vehicles or robots, wherein, The digital map (2) has at least one connecting region (5), wherein the map extension (1) has at least one extended region (6) and an overlapping region (7), wherein the overlapping region (7) describes a surrounding environment area that is at least partially the same as the connecting region (5) of the digital map (2), wherein the method (100) includes the following steps: - The map extension (1) is checked (110) using the connecting region (5) and the overlapping region (7), wherein, for the check, geometric matching and / or feature-based localization is performed between the connecting region (5) and the overlapping region (7), wherein, for the geometric matching and / or the feature-based localization, at least one dataset and at least one associated comparison data item are used, the comparison data item having at least one pre-given tolerance value, wherein the position estimate of the movable device (4) and / or the self-motion estimate of the movable device (4) are used as the dataset for the overlapping region (7), wherein measurements from at least one measurement trip (16) are used as the comparison data item for the connecting region (5), and the at least one dataset is compared with the comparison data item; - If the dataset is within the range of a pre-given tolerance value of the relevant comparison data item, then the map extension (1) is approved (130) for use in the digital map (2) for use in the movable device (4).

2. The method (100) according to claim 1, wherein, The map extension (1) is approved for use in the digital map (2) to control the driving function (3) of the movable device (4).

3. The method (100) according to claim 2, wherein, Approving the map extension (1) for the digital map (2) for partial and / or fully autonomous control of the driving function (3), and / or, wherein the map extension (1) is approved for safety-related driving functions for control of the movable device (4).

4. The method (100) according to any one of the preceding claims, wherein, The map extension (1) and the digital map (2) are matched by means of alignment based on correspondence, wherein, in particular, point correspondence, and / or tile correspondence, and / or line correspondence are used for the matching.

5. The method (100) according to any one of the preceding claims, wherein, In an additional method step (120), the map extension (1) is checked with the aid of redundant comparison information (13) having a pre-given tolerance value, wherein satellite imagery (14) and / or measurement data (15) from sensors from the measurement journey (16) are used as the redundant comparison information (13), wherein the map extension (1) and the redundant comparison information (13) are checked in terms of geometric deviation, taking into account the pre-given tolerance value, wherein the map extension (1) is approved if the geometric match is within the pre-given tolerance value.

6. The method (100) according to claim 5, wherein, The measurement data (15) is used in different data forms, such as lidar data, and / or radar data, and / or video camera data, and / or infrared data, and / or magnetic field data, and / or ultrasonic data, wherein a measurement data (15) type different from the measurement data (15) type on which the map extension (1) is based is used as redundant comparison information (13).

7. The method (100) according to any one of the preceding claims, wherein, For the feature-based positioning, the position estimate of the movable device (4) is obtained for the overlapping region (7) as a dataset, wherein the position of the movable device (4) within the digital map (2) during the measurement journey (16) is obtained for the connecting region (5) as a comparison data item.

8. The method (100) according to any one of the preceding claims, wherein, For the feature-based localization, the self-motion estimate of the movable device (4) is obtained for the overlapping region (7) as a dataset, wherein the actual motion of the movable device (4) during the measurement journey (16) is obtained for the connecting region (5) as a comparison data item.

9. A computing unit (20) configured to implement all steps of the method (100) according to any one of the preceding claims.

10. A computer program (25) comprising instructions that, when implemented by a computer, cause the computer to perform the method (100) according to any one of claims 1 to 8.

11. A machine-readable storage medium (30) on which a computer program (25) according to claim 10 is stored.

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