METHOD AND DEVICE FOR PRODUCEING AND UPDATING A LOCATION MAP

Description

[0001] The invention relates to a method for generating a localization map for determining the position of a forklift truck in a logistics facility, wherein an environmental map of a detection area of ​​the logistics facility is generated by scanning objects present in the detection area. The invention further relates to a method for updating such a localization map.

[0002] The invention also relates to a device for generating a localization map for determining the position of a forklift truck in a logistics facility, which includes a scanning device for generating an environmental map of a detection area of ​​the logistics facility, wherein the scanning device is configured to scan objects present in the detection area. Furthermore, the invention relates to a device for updating this localization map.

[0003] Localization maps are essential for the autonomous or semi-autonomous operation of industrial trucks in logistics facilities. These maps can be generated using a scanning device, such as a laser scanner. A defined area within the logistics facility is scanned, for example, the area where autonomous or semi-autonomous operation of an industrial truck is intended to take place. This defined area is often a sub-area of ​​the logistics facility. The scanned map is frequently a point cloud, which the industrial truck uses to determine its own position within the logistics facility.

[0004] Maps obtained through scanning inevitably contain inaccuracies. These can negatively impact the achievable accuracy of positions calculated based on such maps. EP 3 612 906 B1 discloses a system in which a scanned map is corrected using markers whose positions within the logistics facility are known. However, such markers, to which a precise position is assigned, must first be surveyed. This is only possible with considerable effort. A further technical approach is pursued by the system disclosed in US 2011 / 0178668 A1. The unit disclosed in this document allows manual corrections to be made to the scanned environmental map, thereby improving its quality.However, such manual correction is also time-consuming and only accurate within certain limits, since the corrected position is determined by input from a user.

[0005] Document DE102021130631 A1 relates to a method for navigating a forklift truck with sensors for detecting information in the operating area of ​​the forklift truck and a data processing device for evaluating this information and creating navigation instructions and / or control commands for navigating the forklift truck.

[0006] It is an object of the invention to provide a device and a method for generating a localization map for determining the position of a forklift truck in a logistics facility, as well as a method and a device for updating such a localization map, wherein a localization map with higher accuracy is to be provided with reduced effort.

[0007] The task is solved by a method for generating a localization map for determining the position of a forklift truck in a logistics facility, wherein the method comprises the following step: a) Generating a map of the surroundings of a detection area of ​​the logistics facility by scanning objects present in the detection area, and this procedure is further developed by the following additional steps: b) Capturing a scale map, at least of the capture area, wherein the scale map contains structurally fixed features; c) Displaying the generated environment map and the scale map on a display device; d) Capturing a correction command concerning an assignment between an object present in the environment map and a structurally fixed feature present in the scale map; e) Generating a correction matrix, in particular for objects depicted in a distorted position in the environment map, wherein, by applying the correction matrix to a scanned position of the object present in the environment map, which was assigned to the structurally fixed feature in step d), this scanned position can be transformed into a scaled position of the structurally fixed feature as contained in the scale map.f) Perform steps d) and e) at least for a first object present in the environment map and for a second object present in the environment map, g) Rectify the environment map using at least one first correction matrix generated for the first object and one second correction matrix generated for the second object, h) Output the environment map rectified in step g) as a localization map for determining the position of the industrial truck in the logistics facility.

[0008] In step c), the generated environment map and the scaled map are displayed on the display device, for example, by showing them side by side. Alternatively, the environment map and the scaled map can be displayed superimposed, i.e., as a single, overlaid map. To facilitate the input of the correction command in step d), the environment map and the scaled map are displayed simultaneously.

[0009] Step d) includes in particular selecting the object in the environment map and an associated selection of a structurally fixed feature of the logistics facility that is present in the scaled map.

[0010] In step e), a correction matrix is ​​created, particularly for objects displayed in a distorted position on the environment map. A correction matrix can also be created for objects displayed in an undistorted position on the environment map—that is, objects that are located at least approximately, and especially completely, at the scaled position shown on the to-scale map—but this is not mandatory. If a correction matrix is ​​created for such correctly displayed objects, it can contain information indicating that no change to the scanned position is required to realign it to the correct scale. For example, such a correction matrix could be a unit matrix or a correction matrix containing entries indicating that, for instance, no translation and / or rotation of the displayed object occurs.However, such a correction matrix contains, in particular, the information that the scanned position of the object shown in the correct position is not changed during the rectification of the environment map carried out in step g), i.e. the object remains at the location shown in the scanned environment map.

[0011] Step g) of rectifying the environment map includes, in particular, compressing and / or stretching the environment map in arbitrary directions. Furthermore, the rectification step can include, in particular, rotating and / or translating the environment map. A combination of these operations can also be performed, for example, a stretching operation. Furthermore, the aforementioned operations can be applied to the environment map as a whole or to sections of the environment map; this also applies to combinations of the aforementioned operations.

[0012] Furthermore, it is specifically intended that more than two correction matrices are generated in steps e) and f). The subsequent rectification of the environment map in step g) can, in particular, be carried out on the basis of all of these correction matrices.

[0013] According to a further embodiment, in step a) the environmental map of a detection area of ​​the logistics facility is generated by acquiring a plurality of individual scans, wherein at least some of these individual scans depict objects present in the detection area. Each of the individual scans is assigned a pose of the industrial truck, the individual scan being recorded at the assigned pose, and the plurality, in particular the concatenation of the poses, and furthermore, in particular the concatenation of all poses of a measurement run, forming a trajectory. In step g), the environmental map is rectified, in particular, by correcting the poses at which individual scans were recorded during the generation of the environmental map, and by combining the individual scans to form the environmental map, based on the correction matrices.

[0014] In particular, poses are corrected whose associated individual scans do not include an object that can be assigned to a structurally fixed feature. These additional poses can be corrected as part of the rectification of the environment map as follows.

[0015] The remaining poses lie on the trajectory between a pose whose single scan encompasses the first object and another pose whose single scan encompasses the second object. The first correction matrix can be determined for the first pose, and the second correction matrix can be determined for the second pose. For the remaining poses on the trajectory between the first and second poses, further correction matrices can be determined from the first and second correction matrices, for example, by interpolation. Applying these further correction matrices to the remaining poses allows for the rectification of the environment map.

[0016] In particular, the scale map contains only immobile objects, specifically objects that are permanently attached to a building of the logistics facility and are permanently integrated into the building structure, such as beams, gates, and / or walls. An object is considered permanently integrated into the building structure if it cannot be altered or removed without extensive structural modifications, or if the object is relevant to the building's statics, such as a beam, load-bearing wall, or column. However, the position(s) of racks and other permanently installed logistics objects are also shown on the scale map and may be considered immobile objects within this map.

[0017] Advantageously, such a method can generate and provide a localization map, which serves as the basis for determining the position of a forklift truck within the logistics facility and offers higher accuracy compared to conventional scanned maps. The localization map is primarily used to determine the forklift truck's position within the logistics facility. A separate navigation map can be used for the forklift truck's navigation, defining, for example, the truck's operating areas. Compared to localization maps based solely on scaled maps, the scanned map includes more detail, particularly non-stationary or moving objects, thus enabling more precise positioning of the forklift truck within the logistics facility.It is advantageous not to need to use more than one map to determine the position of the industrial truck in the logistics facility and, for example, to increase the accuracy of the position determination by comparing or matching these multiple maps.

[0018] Furthermore, the method according to aspects of the invention enables the advantageous generation of an environmental map compared to methods in which the captured environment would be completely aligned with a scaled map. This is because, firstly, the logistics facility is a highly dynamic environment that is constantly changing due to the movement and repositioning of objects, making it difficult to align all captured structures or objects with a scaled map. Secondly, this process is very computationally intensive without resulting in greater accuracy of the generated map compared to the method according to aspects of the invention. Therefore, this approach would unnecessarily delay and potentially even prevent map rectification, meaning the method could be performed directly on a forklift truck, whose computing power might not be sufficient for this purpose.

[0019] Furthermore, it is specifically intended that steps d) and e) are performed for more than two objects present in the environment map and their corresponding fixed structural features present in the scaled map, and that more than two correction matrices are generated accordingly. If more than two correction matrices exist for different objects at different locations in the environment map, their direction and magnitude can be interpolated depending on location. This interpolation can be linear or based on another suitable function. From this interpolation, a large number of correction matrices for the environment map can be calculated, for example, in a grid of a desired resolution. Subsequently, the environment map can be rectified based on this information.

[0020] The generation of the environment map in step a) is carried out, for example, with a forklift truck equipped with a suitable scanning device, such as a laser scanning device or a LI-DAR scanning device.

[0021] The structurally fixed features are, in particular, the load-bearing structures of a building within the logistics facility. These include, for example, walls or columns, especially load-bearing walls or columns, gates, passageways, or other features of the logistics facility, particularly safety-relevant features. Furthermore, these features are those for which it can be assumed that, during the construction of a building within the logistics facility, a position and dimensions consistent with the plans will be maintained. The position and dimensions of such a feature can therefore be considered to be in accordance with the plans and thus consistent with the position and dimensions shown on the scaled map.

[0022] Furthermore, the fixed features are not easily movable, as might be assumed, for example, for load-bearing elements of the logistics facility building or for gate passages. In other words, the features are located at a fixed and known location, and it can also be assumed that this location will not change during the operation of the logistics facility.

[0023] According to an advantageous embodiment, the method is further developed in that in step a) the environment map is generated by carrying out a plurality of individual scans of objects present in the detection area and combining the individual scans by registration to form the environment map, wherein the environment map is in particular a point cloud or an occupancy grid.

[0024] Additional information can be evaluated during the registration of individual scans, i.e., the appropriate merging of the individual scans. For example, the radodometry of the forklift truck used for scanning can be evaluated, or measurements from an inertial measurement unit (IMU) can be analyzed. An IMU contains, for example, accelerometers, gyroscopes, and / or magnetometers, thus providing additional information that allows the pose of the scanning vehicle to be determined. A relative pose of the scanning vehicle can also be determined from the individual scans, each scan being relative to one or more subsequent scans. In this process, structures from a first scan are identified in a second scan, thus determining the relative position of the first scan to the second scan. The aforementioned additional information can complement or support this pose determination.The result of registering the individual scans is, for example, an occupancy grid.

[0025] Inaccuracies arise during the registration of individual scans due to inaccuracies in the pose of the scanning vehicle or device, which generates the environmental map by scanning the surroundings in step a). These inaccuracies arise, for example, from error propagation during registration. Thus, a small error in the relative arrangement or orientation of a first individual scan leads to a second individual scan containing an error in its relative arrangement or orientation, as well as in every subsequent scan. These propagated errors cannot be avoided either during the registration of individual scans or through the (combined) use of odometry data, since these methods only allow position determination relative to the preceding measurement.This results in the environment map composed from the individual scans exhibiting drift or distortion, which, if such an (uncorrected) environment map were later used as the basis for position determination in the logistics facility, would lead to inaccuracies in the position determination of the industrial truck and thus in its navigation.

[0026] By selectively rectifying the scanned environmental map based on the location of fixed structural features, a scanned map with unprecedented precision and positional accuracy of the contained objects can be generated and provided. Similar accuracy can currently only be achieved through rectification using measured position markers – which, however, involves considerable effort, as the position markers must be measured manually. The advantage of the aforementioned embodiments is that the need to measure position markers within the logistics facility is eliminated.

[0027] In particular, the rectification of the environment map is achieved by appropriately correcting the poses, i.e. the position information and the direction information, of the scanning device used in step a) to generate the environment map, for example a forklift truck.

[0028] A scale map is typically a vector-based map, such as a CAD map. However, a scale map can also be in a raster-based format, for example, a PNG file or another raster-based format.

[0029] According to a further advantageous embodiment, the method is further developed in that the logistics facility, in particular a building of the logistics facility, was realized based on the scaled map. The scaled map is, for example, a CAD map, in particular a digital construction plan. In a digital construction plan, the structurally fixed features, such as gates, passageways, walls, columns, and the like, are recorded. It can be assumed that, with appropriate construction, these features will actually be located at the positions recorded in the digital construction plan, so that correcting the site map based on the location of these features is a valid and suitable approach.

[0030] According to a further embodiment, the method is further developed by including in the environment map a first class of objects that can be assigned or are assigned to structurally fixed features, and a second class of objects that cannot be assigned or are not assigned to structurally fixed features, wherein the corrected environment map, which is output as a localization map for determining the position of the industrial truck in step h), includes objects of both the first and second class.

[0031] A rectified scanned map of the environment offers greater detail as a localization map compared to a scaled map. Based on such a localization map, the forklift can calculate its position within the logistics facility using a broader data set, thus determining it more quickly and precisely.

[0032] According to a further advantageous embodiment, it is also provided that in step d) a correction command generated by a user is captured.

[0033] The correction command is generated, for example, by reading, querying, or receiving a corresponding command from a suitable user device or display device. The user device could be, for example, a touchpad on which a position can be marked, or a computer mouse with whose cursor a position is selected. A user can, for instance, identify an object in the scanned environment map and display or mark its exact position on the scaled map. For example, the edge of a column, a passageway, or a gate can be identified by the user in the scanned environment map, and its position on the scaled map can be assigned using the correction command. The difference in the positions of these two objects yields the correction matrix, which is then used as the basis for rectifying the scanned environment map.

[0034] According to a further embodiment, the method is further developed in that the correction command recorded in step d) defines a search area in the environment map displayed in step c) and / or the scaled map, wherein the object present in the environment map and the structurally fixed feature present in the scaled map are present in the search area, wherein the assignment between the object present in the environment map and the structurally fixed feature present in the scaled map is carried out by an object recognition algorithm or is carried out with the assistance of a user by an object recognition algorithm.

[0035] For example, the user can define a search window in the overlaid map, whereby the object recognition algorithm identifies similar or corresponding structures within this search window, such as the outline or partial outline of a column, a gate, or the like. Based on this mapping suggested by the object recognition algorithm, the correction matrix can then be calculated, and a further, and in particular, suitable correction algorithm can also suggest the correction matrix to the user. According to such an embodiment, the user only needs to confirm the mapping.

[0036] According to such a procedure, the rectification of the environmental map can be carried out quickly and efficiently.

[0037] According to an advantageous further development of the procedure, it is further provided that step d) is carried out during the execution of step a).

[0038] In other words, the rectification and correction of the environmental map is performed while it is being generated by the corresponding environmental scans. Such real-time processing is particularly advantageous in combination with the aforementioned object recognition algorithm and its associated features. For example, during a scan, a user can be presented with a suggested assignment, which they can then confirm directly, almost in real time. The acquisition and correction of the environmental map can thus be carried out quickly and efficiently.

[0039] The rectification of the environment map is achieved, for example, by appropriately correcting the poses of the forklift during the scanning process. Other rectification methods, such as a rectification method based on linear interpolation, or a rectification method that uses other suitable functions for interpolation between the displacement vectors, can also be employed.

[0040] The problem is further solved by a method for updating the localization map, in which a localization map is first generated according to a method based on one or more of the aforementioned embodiments. The following steps are performed to update this localization map: a1) Generating an updated environmental map of the detection area of ​​the logistics facility by scanning the objects present in the detection area and other objects not captured or captured in a different position during the generation of the environmental map, b1) Using the scaled map captured in step b), c1) Displaying a generated updated environmental map and the scaled map on the display device, d1) Using the mapping captured in step d) between the object present in the environmental map and the structurally fixed feature present in the scaled map, e1) Generating an updated correction matrix, in particular for objects depicted in a distorted position in the environmental map, wherein the updated correction matrix is ​​applied to an updated scanned position of the object present in the environmental map, which was assigned to the structurally fixed feature in step d1),this updated scanned position can be transformed into the scaled position of the structurally fixed feature, as contained in the scaled map, f1) Perform steps d1) and e1) at least for a first object present in the environment map and for a second object present in the environment map, g1) Rectify the environment map using at least one updated first correction matrix generated for the first object and one updated second correction matrix generated for the second object, h1) Output the environment map rectified in step g1) as an updated localization map for determining the position of the industrial truck in the logistics facility.

[0041] The links established during the creation of the localization map between objects present in the environment map and the fixed features in the scaled map can also be used to update the map. This speeds up the localization map update and reduces the effort required.

[0042] The task is further solved by a device for generating a localization map for determining the position of a forklift truck in a logistics facility, comprising: a) a scanning device for generating an environmental map of a detection area of ​​the logistics facility, wherein the scanning device is configured to scan objects present in the detection area, wherein this device is further developed by: b) a scanning device configured to capture a scale map of at least the scanning area, wherein the scale map contains structurally fixed features; c) a display device configured to display the generated environment map and the scale map; d) a correction command scanning device configured to capture a correction command relating to an assignment between an object present in the environment map and a structurally fixed feature present in the scale map; e) a correction matrix generation device configured to generate a correction matrix, in particular for objects depicted in a distorted position in the environment map, wherein the correction matrix is ​​applied to the scanned position of the object present in the environment map.which can be assigned or has been assigned by the correction command acquisition device to the structurally fixed feature, this scanned position can be converted into a scaled position of the structurally fixed feature as contained in the scaled map, f) wherein the correction command acquisition device and the correction matrix generation device are configured to perform the assignment and the correction matrix generation at least for a first object present in the environment map and for a second object present in the environment map, g) a rectification device configured to rectify the environment map using a first correction matrix generated for the first object and a second correction matrix generated for the second object, h) an output device configured to,to output the area map rectified by the rectification device as a localization map for determining the position of the industrial truck in the logistics facility.

[0043] The device offers the same or similar advantages as those already mentioned with regard to the method for generating the localization map, so repetition is unnecessary.

[0044] The device is further developed in particular by the fact that the scanning device is configured to generate the environment map by performing a large number of individual scans of objects present in the detection area and combining the individual scans into the environment map by registration, wherein the environment map is in particular a point cloud or an occupancy grid.

[0045] According to another embodiment, the logistics facility was implemented on the basis of the scale map.

[0046] The device is further preferably developed in that the environment map contains a first class of objects that can be assigned or are assigned to structurally fixed features, and a second class of objects that cannot be assigned or are not assigned to structurally fixed features, wherein the corrected environment map, which can be output or is output by the output device as a localization map for determining the position of the industrial truck, includes objects of both the first and second class.

[0047] The device is furthermore specifically designed so that the correction command detection device is configured to detect a correction command generated by a user.

[0048] Furthermore, it is specifically provided that the correction command detection device is configured to detect a correction command that defines a search area in the environment map and / or scale map that can be displayed or shown by the display device, wherein the object present in the environment map and the structurally fixed feature present in the scale map are present in the search area, and wherein the correction command detection device is further configured to perform the assignment between the object present in the environment map and the structurally fixed feature present in the scale map by means of an object recognition algorithm or to assist a user by means of an object recognition algorithm.

[0049] Furthermore, the device is further developed in particular by the fact that the correction command detection device is configured to detect the correction command, while the scanning device detects the environment map of the detection area of ​​the logistics device.

[0050] Furthermore, the problem is solved by a device for updating a localization map, which comprises a device according to one or more of the aforementioned embodiments with which a localization map can be generated or is generated. This device is further developed in that a1) the scanning device is configured to generate an updated environmental map of the detection area of ​​the logistics facility by scanning the objects present in the detection area and other objects not detected or detected in a different position during the generation of the environmental map, b1) the detection device is configured to use the detected scaled map, c1) the display device is configured to display an updated environmental map generated by the scanning device and the scaled map, d1) the correction command detection device is configured to use the detected mapping between the object present in the environmental map and the structurally fixed feature present in the scaled map, e1) the correction matrix generation device is configured to generate an updated correction matrix,in particular for objects depicted in a distorted position in the environment map, wherein by applying the updated correction matrix to an updated scanned position of the object present in the environment map, which was assigned to the structurally fixed feature by the correction command acquisition device, this updated scanned position can be transformed into the scaled position of the structurally fixed feature as contained in the scaled map, f1) the correction command acquisition device and the correction matrix generation device are configured to perform the assignment and the correction matrix generation at least for a first object present in the environment map and for a second object present in the environment map, g1) the rectification device is configured toh1) to rectify the environment map using at least one updated first correction matrix generated for the first object and one updated second correction matrix generated for the second object, h1) the output device is configured to output the rectified environment map as an updated localization map for determining the position of the industrial truck in the logistics facility.

[0051] According to further embodiments, a method for determining the position and / or navigating a forklift truck in a logistics device is provided, wherein this forklift truck performs a position determination based on a localization map which was generated according to a method for generating a localization map according to aspects of the invention.

[0052] Furthermore, according to another embodiment, a forklift truck is provided which includes a device for generating a localization map according to one or more of the aforementioned embodiments. According to further aspects of the invention, a logistics system is provided which includes such a forklift truck and a device for generating a localization map.

[0053] Further features of the invention will become apparent from the description of embodiments according to the invention together with the claims and the accompanying drawings.

[0054] The invention is described below, without limiting the general concept, with reference to exemplary embodiments and the drawings, whereby for all details of the invention not explained in detail in the text, explicit reference is made to the drawings. The drawings show: Fig. 1 a flowchart of a method for generating a localization map, Fig. 2 a scanned environment map of a detection area of ​​a logistics facility, Fig. 3 a scaled map representing part of the detection area of ​​the logistics facility, Figs. 4 and 5 a further flowchart of a modified method for generating a localization map, Fig. 6 a) to e) each a schematic representation of an environment in which, by way of example, two scanned objects and their associated fixed structural features of the logistics facility as well as locations where individual scans were acquired are shown, wherein the figures illustrate individual steps of the method for generating the localization map, from the acquisition of the environment map to its rectification, Fig. 7 a forklift truck with a scanning device and a device for generating a localization map.

[0055] In the drawings, identical or similar elements and / or parts are provided with the same reference numbers, so that a re-presentation is omitted.

[0056] Fig. 1 Figure 1 shows a flowchart of a procedure for generating a localization map. The localization map serves as the basis for determining the position of a forklift truck 2 in a logistics facility 4 (see Figure 2). Fig. 7 The process for generating the localization map begins in step a) with the creation of a map of the surrounding area of ​​the logistics facility. This map is generated by scanning objects within the area. Specifically, it is created by combining numerous individual scans of objects within the area. These individual scans are combined into the map, for example, by registration. In this process, the various individual scans are aligned with previously recorded features based on their captured characteristics. Odometry data and / or IMU data from the forklift truck 2 can be used to increase accuracy. The location of each measurement, i.e., the location where the individual scan was captured, can also be recorded in the map, allowing the vehicle's trajectory to be tracked.The resulting map of the surroundings is then available, for example, as a point cloud or in the form of an occupancy grid.

[0057] Fig. 2 Figure 6 shows an exemplary map of the area covered by logistics facility 4. The area covered is specifically a sub-area of ​​logistics facility 4. Various objects 8 and 26 are shown as examples, such as pallets, pallet positions, or racking systems (as in the case of object 26), or columns 1 to 3 and a fire door (as in the case of object 8). The differentiation of the objects, which are identified by different reference numbers, is explained in more detail below.

[0058] Depending on the trajectory of the vehicle that records the individual scans underlying the environment map 6, some objects 8 are only partially visible. This can be seen, for example, in columns 1 to 3, of which only the areas visible in the respective individual scans are shown in the environment map 6. The remaining areas are either facing away from the scan direction or have been obscured or shadowed by other objects that are also within the detection range.

[0059] In step b) of the Fig. 1 The described method for generating the localization map produces a scaled map 10. Fig. 3 shows an exemplary scale map 10.

[0060] The scaled map 10 shows a portion of the survey area or at least the survey area; that is, the scaled map 10 can show a larger area of ​​the logistics facility 4 than the surrounding area map 6, which was surveyed in step a). The scaled map 10 includes structurally fixed features 12. These are, for example, the columns 1 to 3, which are also labelled as such in the figure, and the fire door.

[0061] The generation of the environmental map 6 in step a) is carried out using a scanning device 14, such as the one shown in Fig. 7 The scanning device 14 can be attached to the forklift truck 2 shown. The scanning device 14 can also, contrary to the schematic representation, be arranged just above the ground, i.e., in the lower part of the forklift truck 2. Furthermore, the scanning device 14 can comprise several individual scanners, which can be attached both near the ground and at other locations on the forklift truck 2. The scan data from the individual scanners can be related to or calculated back to a common reference point, for example, a vehicle pivot point, by suitable transformations. The environmental map 6 can be composed of individual scans. After the environmental map 6 has been acquired, in particular after the individual scans have been acquired, which are stored, for example, in a suitable storage medium 16 of the forklift truck 2, the individual scans can be transferred to an external processing unit 20.For this purpose, the industrial truck 2 includes a communication unit 22, which is designed to operate a wired or wireless data connection between the industrial truck 2 and the external processing unit 20.

[0062] The external processing unit 20 comprises a display device 24, on which, according to step c) of the in Fig. 1 In the described procedure, an overlaid map is displayed. The overlaid map comprises the environmental map 6 generated in step a) superimposed on the scaled map 10 acquired in step b). In the displayed overlay, deviations between the objects 8 present in the scanned environmental map 6 and the fixed features 12 included in the scaled map 10 can be displayed and identified.

[0063] To rectify the environment map 6, in step d) of the Fig. 1 The procedure shown captures a correction command. This correction command relates to an assignment between an object 8 present in the environment map 6 and a structurally fixed feature 12 present in the scaled map 10. For example, the correction command relates to an assignment between one of the columns 1 to 3 visible in the environment map 6 and a corresponding column as shown in the scaled map 10. The same applies to the fire door.

[0064] Since the environmental map 6 is assembled from a large number of individual scans by registration, and errors inevitably occur during this process, for example due to inaccuracies in determining the pose of the industrial truck 2 capturing the individual scan, the environmental map 6 exhibits drift and / or inaccuracies. The position of object 8, for example column 1 in the environmental map 6, will differ from the position of feature 12, which is also column 1, shown in the scaled map 10.

[0065] In step e), a correction matrix is ​​therefore generated between the scanned position of object 8 present in the environment map 6 and the previously assigned, structurally fixed feature 12. This correction matrix would, for example, be the displacement vector between column 1 as it appears in the environment map 6 and column 1 as it is shown as feature 12 in the scaled map 10. Furthermore, the correction matrix can define a rotation or a combination of a displacement and a rotation.

[0066] The correction matrix generated in this way indicates the deviations of the scanned environmental map 6 from the actual conditions of the logistics facility 4, as depicted in the scale map 10. The structurally fixed features 12 shown in the scale map 10 are structural elements that are not subject to change in location during the operation of the logistics facility 4. Assuming proper construction, it can be assumed that these features 12 are indeed located at the positions shown in the scale map 10.

[0067] As a further step f) according to the in Fig. 1 The procedure shown in the flowchart, step d), namely the recording of the correction command concerning the assignment between the object 8 present in the environment map 6 and the structurally fixed feature 12 present in the scaled map 10, and the subsequent generation of the correction matrix between the positions of these two elements for at least a first and a second object, is repeated. This is indicated by the return arrow to step d) in Fig.1 As indicated, for example, for column 1, an assignment is first made between object 8 (column 1 in the environment map 6) and feature 12 (column 1 in the scaled map 10), and then the correction matrix between these two elements is determined. This step is then repeated, for example, for column 2. Naturally, this step can also be repeated for further objects 8 and their associated features 12, for example, for column 3 and / or the fire door.

[0068] The surrounding area map 6 is then used in step g) of the process described in Fig. 1 The process, depicted as a flowchart, is rectified. This rectification is performed based on a correction matrix generated for the first object, for example, column 1, and one for the second object, for example, column 2 and / or the fire door. The map is rectified, for example, by linearly stretching the map, interpolating between the correction matrices for individual objects 8 and features 12. A correction can also be performed based on a correction of the pose of the vehicle performing the scanning process in step a), for example, the forklift 2.

[0069] This rectification is necessary because the environment map 6 and the scaled map not only need to be aligned relative to each other, i.e., placed and rotated, but the environment map 6 also needs to be changed in its relative dimension. As mentioned above, this is because the relative arrangement of the individual scans is subject to inaccuracies that, for example, create an angular error. This error can lead to, for instance, two perpendicular aisles in logistics facility 4 being misaligned, as shown in the diagram. Fig. 2 and 3As shown in the surrounding area map 6, the angles between the two elements are slightly larger or smaller than 90°. To correct this, it is not sufficient to simply shift the two maps into the correct position relative to each other. Instead, at least the position and, if applicable, the orientation of a first fixed element in the surrounding area map 6 (for example, the position of the fire door) relative to a second fixed element (for example, column 1) must be corrected, i.e., rectified, according to the true and scaled relative position and, if applicable, orientation as indicated in the scaled map.

[0070] The rectified environment map 6 is output in step h) as a localization map for determining the position of the industrial truck 2 in the logistics facility 4.

[0071] For this purpose, the rectified environmental map 6 is transmitted from the external processing unit 20 to the industrial truck 2, for example via the communication unit 22 of the industrial truck 2. The localization map can then be stored, for example, in the storage medium 16 of the industrial truck 2. The processing unit 18 of the industrial truck 2 can then determine the position of the industrial truck 2 in the logistics facility 4 based on this data. The position detection can, in turn, be based on data that the scanning device 14 captures from the environment of the industrial truck 2 in the logistics facility 4. For position determination, a comparison is made, for example, with the localization map stored in the storage medium 16.

[0072] Logistics facility 4 was designed, in particular on the basis of the scale map 10, as shown. Fig. 3 shows, realized. The scale map is, for example, a building plan available in digital form. In particular, a building that includes or houses logistics facility 4 was realized based on scale map 10.

[0073] The exemplary in Fig. 2 The environment map 6 shown comprises two classes of objects. The first class of objects is designated with reference number 8, the second class with reference number 26. The objects 8 of the first class can be assigned to, or are capable of being assigned to, fixed structural features 12 in the scaled map 10. The objects 26 of the second class cannot be assigned to fixed structural features 12 and therefore cannot be assigned to any fixed structural features 12 shown in the scaled map 10. Nevertheless, the environment map 6 includes the objects 26 of the second class. Their position is also corrected in rectification step g). The objects 26 of the second class enrich the data basis of the environment map 6 compared to the scaled map 10, thus creating a broader data basis for determining the position of the industrial truck 2 in the logistics facility 4.

[0074] The correction command mentioned earlier in connection with step d) is, for example, a user-generated correction command. For instance, a user can first mark the location of column 1 (or the location of an edge of column 1) on the overlaid map, as displayed on the display device 24, in the surrounding map 6. The user then marks the corresponding fixed feature 12, which represents column 1, on the scaled map 10. Here, too, instead of column 1 as a whole, an edge of this column can be marked, which can increase the accuracy of the assignment. The correction matrix generated in step e) can be derived from these two user inputs.

[0075] If the user proceeds in this way with columns 2 and 3, or with the components of the fire door, the environment map 6, as it appears, can be displayed. Fig. 2 shows, using this information to rectify, and a high-quality environment map 6 can be provided as a localization map for the industrial truck 2.

[0076] The user can utilize an assistance function in this process by selecting a search area 28, as exemplified for column 1 with reference symbols and for the objects 8 of the first class as well as for the associated features 12 in the environment map 6 and the scaled map 10 in the Fig. 2 and 3The user defines this search area 28, for example, in the overlaid map displayed on the display device 24. Within search area 28, object 8 is located in the environment map 6, and feature 12 is located in the scaled map 10. An object recognition algorithm provided by the external processing unit 20 identifies corresponding or similar structures within search area 28. For example, the algorithm can suggest a correction matrix to the user for assigning object 8 to feature 12, such as aligning the two elements.

[0077] Such a process can be carried out in real time, for example, while the industrial truck 2 travels through a detection area of ​​the logistics facility 4 and creates the environmental map 6 using the scanning device 14. For this purpose, the industrial truck 2 includes, for example, a further display device 30. The superimposed map can be displayed on this device. During the scanning process, the operator of the industrial truck 2 can be shown suggested mappings between detected objects 8 and features 12. In such a case, the operator simply has to agree to the suggested mapping. In this way, the environmental map 6 can be both captured and rectified during the scanning process itself.

[0078] The previously described procedure for generating the localization map can be extended by updating the localization map. Accordingly, the following additional steps can be carried out: First, according to step a1), an updated environment map 6 of the detection area of ​​the logistics facility 4 is created by scanning objects 8 present in the detection area and other objects 8 that were not detected or were detected in a different position during the generation of the environment map 6.

[0079] According to procedure step b1), the scaled map 10 already recorded in step b) is used again.

[0080] According to a further process step c1), an updated overlaid map is displayed, for example on the display device 24 of the external processing unit 20 or on the further display device 30 of the industrial truck 2. This updated overlaid map comprises the updated environment map 6 generated in step a1) superimposed on the scaled map 10. If the corresponding display is made on the further display device 30 of the industrial truck 2, the processing unit 18 of the industrial truck 2 has the corresponding functionality to carry out the process.

[0081] The mapping already established in step d) between object 8 present in the environment map 6 and the structurally fixed feature 12 present in the scaled map 10 can now be reused in step d1) of the procedure for updating the localization map. In other words, no new mapping between object 8 and feature 12 needs to be performed to update the localization map.

[0082] Subsequently, in step e1), an updated correction matrix can be generated between an updated scanned position of the object 8 present in the environment map 6, which was assigned to the structurally fixed feature 12 in step d1), and the scaled position of the structurally fixed feature 12, as contained in the scaled map 10.

[0083] The steps of using d1) and generating the updated correction matrix e1) are performed again for at least two objects 8 present in the environment map 6.

[0084] According to step g1), the environment map 6 is then rectified using the updated correction matrix generated for these two objects 8.

[0085] According to step h1), the environment map 6 rectified in step g1) is output as an updated localization map for determining the position of the industrial truck 2 in the logistics facility 4.

[0086] Both the in Fig. 7 The forklift truck 2 shown, as well as the external processing unit 20, can be configured as a device for generating a localization map for determining the position of the forklift truck 2 within the logistics facility 4. If the external processing unit 20 is configured as such a device, it accesses data from the scanning device 14 of the forklift truck 2. This is not necessary if the forklift truck 2 itself is equipped with the corresponding functionality, i.e., if its processing unit 18 is configured accordingly. Individual processing steps of the procedure for generating the localization map can therefore be performed by the forklift truck 2, and other steps can be performed by the external processing unit 20.The processing steps can be divided flexibly and arbitrarily, and sub-steps or sub-tasks within the processing steps can also be distributed arbitrarily and flexibly between the two units. This does not apply to steps for which the respective unit requires corresponding hardware. For example, the acquisition of the individual scans is always performed by the unit that includes the scanning device 14, i.e., typically by the forklift 2. For example, the forklift 2 acquires the individual scans and assembles them into a distorted environmental map. The rectification and correction of this map then takes place on the external processing unit 20. An exemplary embodiment will be described below, in which the external processing unit 20 is configured as a device for generating the localization map.

[0087] As already mentioned, the scanning device 14 of the industrial truck 2 generates an environmental map 6 of a detection area of ​​the logistics facility 4 by scanning objects 8 present in the detection area using the scanning device 14. The individual scans can be transmitted to the external processing unit 20 for registration purposes.

[0088] The external processing unit 20 comprises a capture device 32, which is configured to capture the scale map 10. For example, the capture device 32 is a storage medium on which the scale map 10 is stored or an interface via which the scale map 10 is received.

[0089] The external processing unit 20 also includes the aforementioned display device 24, on which the superimposed map is displayed.

[0090] The external processing unit 20 further comprises a correction command acquisition device 34, which is configured to acquire the correction command concerning the assignment between the object 8 present in the environment map 6 and the feature 12 present in the scaled map 10. The correction command acquisition device 34 is, for example, a peripheral device such as a computer mouse.

[0091] The external processing unit 20 further comprises a correction matrix generation device 36, which is configured to generate the correction matrix between the scanned position of the object 8 present in the environment map 6 and the feature 12, as shown on the scaled map 10. The acquisition of the correction command and the calculation of the correction matrix are performed for at least two objects. A rectification device 38 then rectifies the environment map 6 based on at least the correction matrices. Finally, the rectified environment map 6 is output via an output device 40 and, for example, transferred to the industrial truck 2 for the purpose of position determination. For this purpose, the output device 40 communicates the localization map to the communication unit 22 of the industrial truck 2.The acquisition device 32, the correction command acquisition device 34, the correction matrix generation device 36, and / or the equalization device 38 of the external processing unit 20 can be implemented as functional units in the external processing unit 20 and need not be physically discrete units. For example, the units are functions or algorithms that are executed on the external processing unit 20.

[0092] Fig. 4 Another flowchart illustrates parts of a procedure for generating the localization map.

[0093] In step S1, the scanning process is started, referred to as "Start map capture".

[0094] In step S2, the industrial truck 2 travels a trajectory within the detection area, acquiring individual scans of its surroundings. These individual scans are recorded at various positions of the industrial truck 2. Each position contains information about the location and orientation of the industrial truck 2. This process is completed in step S3.

[0095] In the next step S4, the preliminary (distorted) environment map 6 is created, for example, by processing the scan data in the industrial truck 2. Data processing can also be performed in the external processing unit 20. A trajectory of the industrial truck 2 with corresponding poses (each encompassing the position and orientation) at which the individual scans were recorded is available. This trajectory is also referred to as a "pose graph." Each individual scan is assigned a node. For each node, an individual scan, for example, in the form of a laser scan, and the associated pose at which this scan was recorded are available.

[0096] The respective pose can be determined using data from vehicle odometry or based on data from an IMU (Integrated Measurement Unit) located in the industrial truck 2. Likewise, at least relative information about the pose can be obtained from matching the individual scans, as explained below. Furthermore, combinations of several or all methods of position determination are possible, for example, so-called sensor fusion.

[0097] The preliminary (distorted) environment map 6 is created by combining the individual scans to match the environment map 6 as closely as possible. This process is often referred to as "matching". How this process is carried out according to the specific implementation example is explained in the context of steps S5 and S6.

[0098] First, corresponding structures are identified, particularly in successive individual scans. All points of the two individual scans can also be aligned so that they exhibit maximum pixel-level overlap. Based on the structural or pixel-level alignment, the individual scans are then aligned, for example, by shifting and / or rotating them. Additionally, the pose of the forklift truck (2) at which each individual scan was taken can be considered for matching. The relative poses, i.e., the difference between one pose and the next, can also be derived from matching the corresponding individual scans. For example, the relative pose results from the necessary shifting and / or rotation of the successive individual scans. Both approaches can be combined.This allows for the processing of information from sources such as vehicle odometry, as well as information from the matching of individual scans. The result is the calculation of corresponding transformations that describe the relative transition between individual poses, particularly between successive poses. Based on these transformations, the individual scans are then combined to create the distorted environment map 6.

[0099] This situation is in Fig. 6a ) illustrated. A first object 8a and a second object 8b, as well as a plurality of poses 42, are shown schematically and in a simplified manner. For the sake of clarity, only some of these poses are labeled with reference symbols. The individual scans were captured at the poses 42 and simultaneously represent nodes for matching the individual scans.

[0100] In step S5, as already explained, relevant structures are extracted from the individual scans available for each node, for example, wall corners or columns. These structures can be detected manually or automatically. The relevant structures include, for example, the [missing information]. Fig. 6a ) depicted first and second objects 8a, 8b.

[0101] The transition to the following takes place: Fig. 5 The depicted part of the flowchart begins with step S6. Here, the transformations between the individual nodes or poses are determined in order to assemble the individual scans into the environment map 6. A relative transformation of the individual scans, particularly those occurring consecutively, takes place, for example, during the map recording process, similar to a so-called SLAM method (SLAM = Simultaneous Localization and Mapping). This preliminary environment map 6 includes, as explained above, corresponding errors.

[0102] When combining the individual scans, the physical distances between the individual scanners used as scanning devices 14, which may be mounted at different locations on the industrial truck 2, can also be taken into account. An intrinsic transformation of the scan data is useful when using multiple scanners in order to relate the scan data of the individual scanners to a common reference point, for example, the vehicle's pivot point. Such an intrinsic transformation is typically performed before matching the individual scans.

[0103] After capturing the individual scans and combining these individual scans to form the (distorted) environment map 6, the correction of the environment map 6 follows.

[0104] In step S7, the assignment between the objects captured in the scan data and those present, for example the first object 8a and the second object 8b, to the structurally fixed features 12 of the logistics facility 4 present in the scaled map, which is for example a CAD map, is carried out.

[0105] This illustrates Fig. 6b The first object 8a is assigned a first feature 12a, and the second object 8b is assigned a second feature 12b of logistics facility 4. This step corresponds to the recording of the correction command (step d)). By assigning structures within the scanned environment map 6 to features 12 or to structures of the layout or CAD representation of logistics facility 4, the individual transformations between the successive nodes can be changed or adjusted, thereby rectifying the environment map 6.

[0106] The subsequent correction of the environment map (corresponds to step g)) takes place in the flowchart in step S8, as part of an optimization run with adjusted poses for the individual scans.

[0107] First, however, a correction matrix is ​​generated. By applying this matrix to the scanned position of object 8, which is present in the environment map 6 and was previously assigned to the fixed feature 12 in step d), the previously scanned position can be transformed into the scaled position of the structurally fixed feature 12, as it is contained in the scaled map 10. This is shown in Fig. 6c ) indicated.

[0108] The special case of a correction vector is shown as an example of a correction matrix. Specifically, by applying a first correction vector 44a to the scanned position of the first object 8a, its position is transformed into the scaled position of the first fixed feature 12a. By applying the second correction vector 44b, the scanned second position of the second object 8b is transformed into the scaled second position of the second fixed feature 12b. The determination of the first and second correction vectors 44a, 44b, and more generally the determination of a first and second correction matrix, can be carried out, for example, as follows.

[0109] The scanned environment map 6 and the scaled map 10 are displayed side by side or superimposed on the display device 24, 30. Corresponding points of the object 8 and the structurally fixed feature 12 are marked, for example, by user input. For instance, corresponding edges or corners of a column or a gate passage are marked in both map displays. These could be the corners or edges of the first and second objects 8a, 8b, respectively, which might be a column and a gate passage. The correction vector is derived from the difference between these two markings. This process is in Fig. 6c ) illustrated.

[0110] The corresponding correction vectors 44a, 44b (or, more generally, the corresponding correction matrices) are then applied to the positions 42 at which the individual scans were determined. This illustrates Fig. 6d As an example, the first correction vector 44a is applied to a pose 42x. The second correction vector 44b is applied to a pose 42y.

[0111] A complete correction of the environment map 6 is achieved by applying correction vectors or, more generally, corresponding additional correction matrices to each of the further positions 42 located between position 42x and position 42y. These additional correction vectors (in the example shown) or, more generally, additional correction matrices can be calculated, for example, by interpolation between the first correction vector 44a and the second correction vector 44b. Other optimization methods can also be applied, such as error minimization using a covariance matrix.

[0112] Fig. 6e Figure 1 illustrates this process. Corresponding calculated additional correction matrices, or, as shown in the specific example, correction vectors (indicated by arrows), are applied to the additional poses 42 located between poses 42x and 42y. By applying these additional correction vectors, the poses 42 are transformed into corrected poses 46.

[0113] If the individual scans taken at the corresponding poses 42 are now combined on the basis of the locations and orientations of the corrected poses 46, the environment map 6 can be rectified.

[0114] In step S9, the localization map is reviewed, for example, by a user-side visual inspection. If the localization map is deemed sufficient in this step, it is output in step S10, referred to as the "corrected map". If, however, the localization map is considered insufficient in step S9, further objects 8 and their associated features 12 can be added to the analysis in a subsequent step S11, referred to as "adding relevant structures". Bezugszeichenliste

[0115] 2 Forklift 4 Logistics equipment 6 Environment map 8 Object (first class) 8a first object 8b second object 10 Scale map 12 Features 12a first feature 12b second feature 14 Scanning device 16 Storage medium 18 Processing unit 20 External processing unit 22 Communication unit 24 Display device 26 Object (second class) 28 Search area 30 Additional display device 32 Capture device 34 Correction command capture device 36 Correction matrix generation device 38 Rectification device 40 Output device 42 Pose 44a first correction vector 44b second correction vector 46 Corrected poses

Claims

1. A method for creating a localization map for determining the position of an industrial truck (2) in a logistics facility (4), having the following steps: a) creating an environment map (6) of a detection area of the logistics facility (4) by scanning objects (8) present in the detection area, wherein the method for creating a localization map is characterized by the following further steps: b) detecting a scale map (10) at least of the detection area, wherein structurally stationary features (12) of the logistics facility (4) are present in the scale map (10), c) displaying the created environment map (6) and the scale map (10) on a display device (24), d) detecting a correction command regarding an allocation between an object (8) present in the environment map (6) and a structurally stationary feature (12) present in the scale map (10), e) creating a correction matrix, in particular for objects (8) represented at a distorted position in the environment map (6), wherein by applying the correction matrix to a scanned position of the object (8) present in the environment map (6), which was allocated to the structurally stationary feature (12) in step d), said scanned position can be converted into a scale position of the structurally stationary feature (12) as it is contained in the scale map (10), f) performing the steps d) and e) at least for a first object (8) present in the environment map (6) and for a second object (8) present in the environment map (6), g) equalizing the environment map (6) with the aid of at least one first correction matrix created for the first object (8) and a second correction matrix created for the second object (8), h) outputting the environment map (6) equalized in step g) as a localization map for determining the position of the industrial truck (2) in the logistics facility (4).

2. The method according to Claim 1, in which the environment map (6) is created in step a) by performing a plurality of individual scans of objects (8) present in the detection area and by combining the individual scans by registration to form the environment map (6), wherein the environment map (6) is in particular a point cloud or an occupancy grid.

3. The method according to Claim 1 or 2, in which the logistics facility (2) was realized on the basis of the scale map (10).

4. The method according to any one of Claims 1 to 3, in which a first class of objects (8) which can be assigned or are assigned to structurally stationary features (12), and a second class of objects (8) which cannot be assigned to structurally stationary features (12) are present in the environment map (6), wherein the corrected environment map (6) which is output as a localization map for determining the position of the industrial truck (2) in step h) comprises both objects (8) of the first and the second class.

5. The method according to any one of Claims 1 to 4, in which a correction command created by a user is detected in step d).

6. The method according to any one of Claims 1 to 4, in which the correction command detected in step d) specifies a search area (28) in the environment map (6) displayed in step c) and / or the scale map (10), wherein the object (8) present in the environment map (6) and the structurally stationary feature (12) present in the scale map (10) are present in the search area (28), wherein the allocation between the object (8) present in the environment map (6) to the structurally stationary feature (12) present in the scale map (12) is performed by an object recognition algorithm or is performed by a user assisted by an object recognition algorithm.

7. The method according to any one of Claims 1 to 6, in which step d) is carried out during the performance of step a).

8. A method for updating a localization map, in which a localization map is created according to a method according to any one of Claims 1 to 7 and the following steps are performed in order to update said localization map: a1) creating an updated environment map (6) of the detection area of the logistics facility (2) by scanning the objects (8) present in the detection area and further objects (8) which are not detected or are detected at a different position during the creation of the environment map, b1) using the scale map (12) detected in step b), c1) displaying a created updated environment map (6) and the scale map (12) on the display device (24), d1) using the allocation detected in step d) between the object (8) present in the environment map (6) and the structurally stationary feature (12) present in the scale map (10), e1) creating an updated correction matrix, in particular for objects (8) represented at a distorted position in the updated environment map (6), wherein by applying the updated correction matrix to an updated scanned position of the object (8) present in the environment map (6), which was allocated to the structurally stationary feature (12) in step d1), said updated scanned position can be converted into the scale position of the structurally stationary feature (12), as it is contained in the scale map (10), f1) performing the steps d1) and e1) at least for a first object (8) present in the environment map (6) and for a second object (8) present in the environment map (6), g1) equalizing the environment map (6) with the aid of at least one updated first correction matrix created for the first object (8) and one updated second correction matrix created for the second object (8), h1) outputting the environment map (6) equalized in step g1) as an updated localization map for determining the position of the industrial truck (2) in the logistics facility (4).

9. A device for creating a localization map for determining the position of an industrial truck (2) in a logistics facility (4), having: a) a scanning device (14) for creating an environment map (6) of a detection area of the logistics facility (2), wherein the scanning device (14) is designed to scan objects (8) present in the detection area, wherein the device is further characterized by: b) a detection device (32) which is designed to detect a scale map (10) at least of the detection area, wherein structurally stationary features (12) are present in the scale map (10), c) a display device (24) which is designed to display the created environment map (6) and the scale map (10), d) a correction command detection device (34) which is designed to detect a correction command regarding an allocation between an object (8) present in the environment map (6) and a structurally stationary feature (12) present in the scale map (10), e) a correction matrix creating device (36) which is designed to create a correction matrix in particular for objects (8) represented at a distorted position in the environment map (6), wherein by applying the correction matrix to the scanned position of the object (8) present in the environment map (6), which can be assigned or was allocated by the correction command detection device (36) to the structurally stationary feature (12), said scanned position can be converted into a scale position of the structurally stationary feature (12), as it is contained in the scale map (10), f) wherein the correction command detection device (34) and the correction matrix creating device (36) are designed to perform the allocation and the correction matrix creation at least for a first object (8) present in the environment map (6) and for a second object (8) present in the environment map (6), g) an equalizing device (38) which is designed to equalize the environment map (6) with the aid of at least one first correction matrix created for the first object (8) and a second correction matrix created for the second object (8), h) an output device (40) which is designed to output the environment map (6) equalized by the equalizing device (38) as a localization map for determining the position of the industrial truck (2) in the logistics facility (4).

10. The device according to Claim 9, wherein the scanning device (14) is designed to create the environment map (6) by performing a plurality of individual scans of objects (8) present in the detection area and by combining the individual scans by registration to form the environment map (6), wherein the environment map (6) is in particular a point cloud or an occupancy grid.

11. The device according to Claim 9 or 10, wherein a first class of objects (8) which can be or are assigned to structurally stationary features (12), and a second class of objects (8) which cannot be assigned to structurally stationary features (12) are present in the environment map (6), wherein the corrected environment map (6) which can be output or is output by the output device (40) as a localization map for determining the position of the industrial truck (2) comprises both objects (8) of the first and the second class.

12. The device according to any one of Claims 9 to 11, wherein the correction command detection device (34) is designed to detect a correction command created by a user.

13. The device according to any one of Claims 9 to 11, wherein the correction command detection device (34) is designed to detect a correction command which specifies a search area in the environment map (6) which can be or is displayed by the display device (24) and / or scale map (10), wherein the object (8) present in the environment map (6) and the structurally stationary feature (12) present in the scale map (10) are present in the search area (28), wherein the correction command detection device (34) is further designed to perform the allocation between the object (8) present in the environment map (6) to the structurally stationary feature (12) present in the scale map (10) by an object recognition algorithm or to assist a user by an object recognition algorithm.

14. The device according to any one of Claims 9 to 13, wherein the correction command detection device (34) is designed to detect the correction command while the scanning device (14) detects the environment map (6) of the detection area of the logistics facility (4).

15. A device for updating a localization map, having a device according to any one of Claims 9 to 14, with which a localization map can be created or is created, wherein further: a1) the scanning device (14) is designed to create an updated environment map (6) of the detection area of the logistics facility (4) by scanning the objects (8) present in the detection area and further objects (8) which are not detected or are detected at a different position during the creation of the environment map (6), b1) the detection device (32) is designed to use the detected scale map (10), c1) the display device (54) is designed to display an updated environment map (6) created by the scanning device (14) and the scale map (10), d1) the correction command detection device (34) is designed to use the detected allocation between the object (8) present in the environment map (6) and the structurally stationary feature (12) present in the scale map (10), e1) the correction matrix creating device (36) is designed to create an updated correction matrix, in particular for objects (8) represented at a distorted position in the updated environment map (6), wherein by applying the updated correction matrix to an updated scanned position of the object (8) present in the environment map (6), which was allocated to the structurally stationary feature (12) by the correction command detection device (36), said updated scanned position can be converted into the scale position of the structurally stationary feature (12), as it is contained in the scale map (10), f1) the correction command detection device (34) and the correction matrix creating device (36) are designed to perform the allocation and the correction matrix creation at least for a first object (8) present in the environment map (6) and for a second object (8) present in the environment map (6), g1) the equalizing device (38) is designed to equalize the environment map (6) with the aid of at least one updated first correction matrix created for the first object (8) and one updated second correction matrix created for the second object (8), h1) the output device (40) is designed to output the equalized environment map (6) as an updated localization map for determining the position of the industrial truck (2) in the logistics facility (4).