Method for determining a movement path for a mobile device

Abstract

The invention relates to a method for determining a movement path for a mobile device, wherein the mobile device is asymmetrical, and the mobile device is to move along the movement path in a surrounding area, having the steps of: providing (204) a surrounding area map (206) which comprises information about free regions in the surrounding area; determining (208), on the basis of the surrounding area map, a contour path (210) or a contour coverage region for at least part of the surrounding area; determining (212) one or more coverage units (214) for at least part of the surrounding area; determining (216) the movement path (220) using a travelling salesman problem (218), which is based on the contour path or the contour coverage region, and the one or at least one of the plurality of coverage units; and providing (222) the movement path (220).

Description

[0001] Description

[0002] title

[0003] Method for determining a for a mobile device

[0004] The present invention relates to a method for determining a movement path for a mobile device, in particular an at least partially automated vehicle or robot, in particular a vacuum and / or mop robot or a lawnmower robot, a system for data processing and a computer program for carrying out the method, as well as a mobile device.

[0005] Background of the invention

[0006] Mobile devices such as at least partially automated vehicles or robots typically move in an environment, in particular an environment to be processed or a work area, such as a home, in a garden, in a factory hall or on the street, in the air or in water. One of the fundamental problems of such or other mobile devices is to orient itself, i.e. to know what the environment looks like, in particular where obstacles or other objects are, and where it is (absolutely) located. For this purpose, the mobile device can be equipped with various sensors, such as cameras, lidar sensors or inertial sensors, with the help of which the environment and the movement of the mobile device can be recorded, for example in two or three dimensions. This enables the mobile device to move locally, detect obstacles in good time and to avoid them.

[0007] Disclosure of the invention

[0008] According to the invention, a method for determining a movement path for a mobile device, a data processing system and a computer program for implementing the method, as well as a mobile device having the features of the independent patent claims are proposed. Advantageous embodiments are the subject of the dependent claims and the following description.

[0009] The invention generally relates to mobile devices that move or at least can move in an environment or there, e.g. in a work area. Examples of such mobile devices (or mobile work devices) are, for example, robots and / or drones and / or partially or (fully) automated vehicles (on land, water or in the air). Robots that can be considered include household robots such as cleaning robots (e.g. in the form of vacuum and / or mop robots), floor or street cleaning devices, construction robots or lawnmower robots, as well as other so-called service robots, as well as at least partially automated vehicles, e.g. passenger transport vehicles or goods transport vehicles (including so-called industrial trucks, e.g. in warehouses), but also aircraft such as so-called drones or watercraft.

[0010] Such a mobile device comprises, in particular, a control or regulating unit and a drive unit for moving the mobile device, so that the mobile device can be moved in the environment, in particular along a movement path. For this purpose, navigation information can be determined based on the movement path, for example, specific instructions regarding the direction in which the mobile device should travel in order to follow the movement path. These instructions can then be implemented via the control or regulating unit and the drive unit.

[0011] In addition, a mobile device can have one or more sensors that can be used to capture the environment or information in the environment. As mentioned, these can be cameras, lidar sensors, or even inertial sensors, which can be used to capture the environment and the movement of the mobile device, for example, in two or three dimensions.

[0012] For certain types of mobile devices, such as cleaning and lawnmower robots, it is desirable for them to cover the entire environment or an entire, predetermined work area or at least a specific part of it when moving. This applies in particular to a so-called end effector of the mobile device, such as a cleaning brush, a suction opening or a cutting blade. In other words, a cleaning robot should completely clean a predetermined work area (e.g. an apartment or the open areas on the floor there), and a lawnmower robot should completely mow a predetermined work area (e.g. a lawn). The mobile device should be able to find the most optimized coverage path possible, i.e. a movement path along which the mobile device moves or should move in order to process the environment.

[0013] The problem of generating a path or movement path that covers the entire area accessible to the mobile device (coverage path) is referred to as "coverage path planning" (CPP). The definition of a movement path covering an area specifically means that when the mobile device moves along the path, the entire area is covered by the mobile device's end effector (although overlaps may occur). In addition to cleaning and lawnmower robots, this can also be used in other applications or robotic applications, such as exploring areas, inspections, surveying, photographing or imaging entire environments, and the like.

[0014] This problem can be divided into online and offline cases. In the offline case, it can be assumed that the mobile device's working area is completely known, i.e., a known and fixed map (environment map) is available, and the mobile device is able to precisely follow a specific movement path (reference path). In practice, uncertainties in sensor data and actuators can lead to a certain dynamic behavior, which can be circumvented by regularly recalculating a coverage path using a suitable algorithm.

[0015] Algorithms for the offline case usually take a little longer to complete their calculations than those for the online case because they calculate a path that completely covers the entire environment. Algorithms for the online case, on the other hand, usually do not make any prior assumptions and instead focus on strategies that are only valid in the short term, evaluating and / or updating the path as the mobile device moves along it. In practice, however, both approaches require some kind of strategy because unforeseen events can occur (e.g., what should the robot do if it suddenly encounters an obstacle that is invisible to the lidar?), to which the mobile device should nevertheless be able to react appropriately and replan. The current movement path must then, for example, be changed or replanned. The present invention is particularly concerned with the offline case.

[0016] Another aspect that has been shown to complicate the determination of such a motion path is the asymmetry of the mobile device. For simplification, the determination of a motion path is often performed only for a single point, e.g., a center or center of gravity of the mobile device, especially when assuming a circular or round mobile device.

[0017] However, if the mobile device exhibits an asymmetry, such as a D-shape or even a triangular or square shape (possibly with rounded edges), determining the movement path can become more difficult. This is due, for example, to the fact that a round mobile device can simply rotate in place, which is not the case, or at least not always, for an asymmetrical mobile device, for example, near obstacles such as walls.

[0018] However, the asymmetry of the mobile device may not only affect the shape of the mobile device or its housing, but may also be present, in particular, with respect to the end effector. Such an end effector, as described above by way of example, may be arranged asymmetrically within the mobile device and may also be asymmetrical itself.

[0019] Against this background, a possibility is proposed for determining a movement path for a mobile device which has an asymmetry, wherein the mobile device is then to move along the movement path in an environment. This should in particular be understood to mean that the movement path to be determined starts from the current position of the mobile device. The invention will now be explained in particular using the example of a cleaning robot, in particular a vacuum cleaner robot, as a mobile device, although the principle can also be transferred to other types of mobile devices, in particular mobile devices which are set up to carry out processing, i.e. to carry out a work function and for this purpose in particular have an end effector. Such processing or

[0020] In addition to cleaning, work functions can include mowing lawns, measuring an area or taking pictures of the surroundings.

[0021] A map of the environment is provided; the map includes information about free areas in the environment. Free areas are understood to be areas that the mobile device, especially its end effector, can reach. An area of ​​the environment containing an object or obstacle is therefore not a free area.

[0022] The free areas of the environment map include, for example, one or more areas to be processed, i.e., areas where processing is (still) to be carried out, e.g., cleaning is still to be done. Depending on the situation, there may be one contiguous, larger area to be processed, or several separate (or even adjacent), smaller areas to be processed.

[0023] In one embodiment, a preliminary environmental map of the environment, in particular obtained using SLAM, can be provided for this purpose. The environmental map can then be determined based on the preliminary environmental map. The environmental map is then, in particular, a binary environmental map that includes information about free areas in the environment and information about restricted areas in the environment. In such a binary environmental map, it is then very easy to decide whether the movement path can lead to a specific area or not.

[0024] SLAM ("Simultaneous Localization and Mapping") is a robotics technique in which a mobile device, such as a robot, can or must simultaneously create a map of its environment and estimate its spatial position within this map. It is used to detect obstacles and thus supports autonomous navigation. SLAM offers various approaches to representing maps and positions. Conventional SLAM methods generally rely on geometric information such as nodes and edges. Nodes and edges are typically components of the SLAM graph. The nodes and edges in the SLAM graph can take on various forms; traditionally, nodes correspond, for example, to the pose (position and orientation) of the mobile device or certain environmental features at specific times, while edges represent relative measurements between the mobile device and the environmental feature.SLAM graphs are described in more detail in “Giorgio Grisetti, Rainer Kümmerle, Cyrill Stach- niss, Wolfram Burgard, A Tutorial on Graph-Based SLAM, IEEE Intelligent Transportation Systems Magazine, Vol. 2(4), pp 31 -42, 2010”.

[0025] Based on such a SLAM graph, a map of the environment (environment map or, in this case, a preliminary environment map) in which the mobile device is moving can be determined. With each new data set containing information about the environment, which is obtained from or based on a sensor on the mobile device, the map (or SLAM graph) can be expanded or updated, for example.

[0026] Based on the environment map, a contour path or contour coverage area is then determined for at least part of the environment. A contour path is understood to be a path along which the mobile device can move, and which path runs along a contour of that part of the environment, i.e., along walls or other obstacles. The contour coverage area is then the area covered by the mobile device—or, if applicable, its end effector—when the mobile device moves along the contour path.

[0027] In addition, one or more coverage units are determined for at least part of the environment. Coverage units are understood to mean, in particular, generic paths or path parts or even just points, which - as explained in more detail later - can be combined to obtain a final movement path. Using a traveling salesman problem, the movement path is then determined based on the contour path or contour coverage area and the one or at least one of the multiple coverage units, and this path is then also provided. In particular, the contour path can form a first part of the movement path, to which a further part then follows, determined by solving the traveling salesman problem from the coverage units. A traveling salesman problem can generally be determined by defining points, edges and weights for them.

[0028] In one embodiment, navigation information for the mobile device is also determined based on the movement path, which can then be used, for example, to control the mobile device to follow the movement path.

[0029] By using the contour path or contour coverage area, the movement path for asymmetric mobile devices can be determined particularly efficiently and accurately, since the asymmetry is particularly relevant for areas close to obstacles, which are covered by the contour path or contour coverage area. The remaining area can then be covered particularly easily and quickly by solving the traveling salesman problem.

[0030] In one embodiment, the mobile device has an end effector, wherein the mobile device has an asymmetry with respect to the end effector. The determination of the contour path or contour coverage area and / or the one or more coverage units is then carried out based on coordinates of the end effector, while the determination of the movement path is carried out based on coordinates of the mobile device. In this way, the contour path or contour coverage area relevant for the end effector as well as the coverage units can be specifically tailored to the requirements of the end effector, so that processing is particularly precise. A conversion for the final movement path can then be carried out, based on which the mobile device can then be controlled.

[0031] In one embodiment, a plurality of coverage units are determined, wherein at least some of the plurality of coverage units are each determined as rectilinear, in particular mutually parallel, path sections. This is also known under the term Boustrophedon coverage algorithm (C.Boustrophedon coverage algorithm"). The coverage units are also referred to as "coverage ranks". The coverage units are found here, for example, iteratively using an approach in which the best coverage unit is removed from the next search until most of the free area is covered. The problem is then formulated as a traveling salesman problem in which the nodes are grouped into disjoint sets and only one node per set is visited. Each contour coverage unit is a traveling salesman problem set with one node.Each Boustrophedon covering unit is a traveling salesman problem set with two nodes corresponding to two possible directions of movement.

[0032] In one embodiment, a plurality of coverage units are determined, wherein at least some of the plurality of coverage units are determined such that they are parallel to parts of the contour path or contour coverage area, in particular, follow the contour path. With such an algorithm, further sections can be continually added, in particular to the first (above-mentioned) contour path or contour coverage area, e.g., iteratively and / or in a spiral manner, until the free area is sufficiently covered. The problem is also formulated as a traveling salesman problem and solved in a manner similar to the Boustrophedon approach.

[0033] In one embodiment, a plurality of coverage units are determined, wherein at least some of the plurality of coverage units are determined as, in particular, uniformly distributed points (e.g., so-called landmarks). Such points or landmarks are, for example, points without orientation that are or will be distributed across the free area, e.g., using a grid. The movement path is reached when the mobile device (if it follows the movement path) has visited each of these points once. This is a common traveling salesman problem.

[0034] In one embodiment, however, each of the distributed points can also be assigned a predefined orientation for the mobile device. This can then be referred to as the so-called general traveling salesman problem. Each point corresponds in particular to a position that the end effector will visit and, for example, corresponds to several poses. Each orientation point corresponds to a general traveling salesman problem set, where each pose is a node, so that the mobile device must visit each point with an orientation once.

[0035] To use solvers for the traveling salesman problem or the general traveling salesman problem, it is convenient to formulate the problem with nodes, edges, and weights. The nodes then correspond to the coverage units. Edges can be defined between all possible pairs of nodes. The edge weights can be approximated, for example, by the Euclidean and angular distance.

[0036] A computing unit according to the invention, e.g. a control device or a control unit of a mobile device, or a server or other computer, is configured, in particular in terms of programming, to carry out a method according to the invention.

[0037] The invention also relates to a mobile device configured to receive navigation information determined as described above, or having a computing unit according to the invention. The mobile device preferably also has a drive system and a control or regulating unit for controlling according to the control information. The mobile device is preferably configured to perform processing (thus, in particular, having an end effector). In particular, the mobile device can be one as described above, for example, a cleaning robot or a robotic lawnmower.

[0038] The implementation of a method according to the invention in the form of a computer program or computer program product with program code for carrying out all method steps is also advantageous, since this entails particularly low costs, in particular if an executing control unit is also used for other tasks and is therefore already present. Finally, a machine-readable storage medium is provided with a computer program stored thereon, as described above. Suitable storage media or data carriers for providing the computer program are, in particular, magnetic, optical, and electrical memories, such as hard disks, flash memories, EEPROMs, DVDs, and others. Downloading a program via computer networks (Internet, intranet, etc.) is also possible. Such a download can be wired or cable-based or wireless (e.g., via a WLAN network, a 3G, 4G, 5G, or 6G connection, etc.).

[0039] Further advantages and embodiments of the invention will become apparent from the description and the accompanying drawings.

[0040] The invention is illustrated schematically in the drawing using an embodiment and is described below with reference to the drawing.

[0041] Short description of the drawings

[0042] Figure 1 a schematically shows a mobile device in an environment for explaining the invention.

[0043] Figure 1 b shows schematically various mobile devices with asymmetry to explain the invention.

[0044] Figure 2 shows schematically a sequence of a method in one embodiment.

[0045] Figures 3a, 3b, 3c show various cards to explain the invention in one embodiment.

[0046] Figures 4a, 4b show various cards to explain the invention in one embodiment.

[0047] Figures 5a, 5b, 5c show various cards to explain the invention in one embodiment.

[0048] Figures 6a, 6b, 6c show various cards to explain the invention in different embodiments.

[0049] Embodiment(s) of the invention Figure 1 a shows a schematic and exemplary representation of a mobile device 100 in an environment 120, in particular a work area, to explain the invention. The mobile device 100 is, for example, a cleaning robot with a control or regulating unit 102 and a drive unit 104 (with wheels) for moving the cleaning robot 100, e.g., along a movement path 130. Furthermore, the vacuum cleaner robot 100 has, for example, a sensor 106 designed as a lidar sensor with a detection range. For better illustration, the detection range has been chosen to be relatively small here; in practice, however, the detection range can also be up to 360° (e.g., but at least at least 180° or at least 270°).

[0050] Furthermore, the cleaning robot 100 has a computing unit 108, e.g., a control unit, by means of which data can be exchanged with a higher-level system 112, e.g., via an indicated radio connection. In the system 112, for example, movement paths (or general navigation information) can be determined, which are then transmitted to the system 108 in the cleaning robot 100, which the latter is then to follow. However, it can also be provided that a movement path (or general navigation information) is determined in the system 108 itself or is received there in some other way. Instead of a movement path, the system 108 can, for example, also receive control information that has been determined based on a movement path and according to which the control or regulating unit 102 can move the cleaning robot 100 via the drive unit 104 to follow a movement path. The movement path 130 is indicated here only as an example.

[0051] The cleaning robot 100 further comprises an end effector 110, designed here, for example, as a suction or cleaning opening, by means of which processing (here, cleaning) can be carried out. The end effector 110 is only indicated schematically here and will be explained in more detail with reference to Figure 1b.

[0052] The cleaning robot 100 is intended, for example, to move or navigate independently in the environment 120 and, for example, to clean a floor (e.g., vacuuming and / or wiping, or wet / damp cleaning). Furthermore, several different objects or obstacles are shown in the environment by way of example, namely a wall 140 and a cupboard 142. Figure 1b shows, by way of example, various mobile devices 100a, 100b, 100c, each of which is also a cleaning robot. These mobile devices each have an asymmetry. It should be noted that these mobile devices are shown schematically from above (top view). In addition, the mobile devices 100a, 100b, 100c each have an end effector 110a, 110b, 110c, designed here, for example, as a suction or cleaning opening.

[0053] The mobile device 100a or its housing, for example, has a D-shape. The end effector 110a is a suction or cleaning opening, which, however, is not located centrally in the mobile device, but rather offset laterally and longitudinally. The mobile device 100a thus has an asymmetry with respect to the housing and with respect to the end effector.

[0054] The mobile device 100b or its housing has, for example, a round shape, and the end effector 110b is a suction or cleaning opening that is offset in the longitudinal direction. Thus, while the mobile device 100a does not exhibit asymmetry with respect to the housing, it does exhibit asymmetry with respect to the end effector.

[0055] The mobile device 100c or its housing, for example, has a triangular shape with rounded edges. The end effector 110c is a suction or cleaning opening that is slightly offset in the longitudinal direction. The mobile device 100c thus has an asymmetry with respect to the housing and with respect to the end effector.

[0056] Figure 2 schematically illustrates a preferred embodiment of a method according to the invention. This process will be explained below with reference to the maps shown in Figures 3a, 3b, 3c, 4a, 4b, 5a, 5b, 5c, and 6a, 6b, 6c.

[0057] The method is used to determine a movement path for a mobile device that is to move along the movement path in an environment. This will be explained using a cleaning robot, such as the cleaning robot 100 described as an example with reference to Figure 1a. In a step 200, a preliminary environmental map 202 of the environment is provided. The preliminary environmental map 202 can, for example, have been obtained using SLAM, as explained above. In a step 204, based on the preliminary environmental map 202, an environmental map 206 is determined and provided. The environmental map is a binary environmental map that includes information about free areas in the environment and information about non-free areas in the environment.

[0058] Figure 3a shows an example of a preliminary environmental map 300, which was obtained, for example, within the framework of SLAM and by means of detection using lidar or the like. The preliminary environmental map 300 depicts an environment, here, for example, an apartment with several rooms.

[0059] Figure 3b then shows an environment map 302, which is a binary environment map. By way of example, a current position 304 of a cleaning robot (for example, this could be the cleaning robot 100 from Figure 1) in the environment is shown. In particular, the binary environment map only contains positions or areas that are either free or not free (i.e., there are only two different possibilities).

[0060] In the environment map 302, free areas are designated by way of example with 310, non-free areas, e.g. walls and the like, with 312. At this point it should be mentioned that the environments in Figures 3a and 3b or their maps do not correspond; rather, the maps shown only serve to illustrate the preliminary and the binary environment map.

[0061] In a step 208, a contour path 210 is then determined for at least part of the environment based on the environment map.

[0062] In Figure 3c, the environment map 302 from Figure 3b is shown again, but now a contour cleaning area 320 is also shown. The contour cleaning area 320 runs along the contours, i.e. in particular the walls or non-free areas 312 in the environment. The contour cleaning area 320 is determined in such a way that the end effector of the cleaning robot glides or moves as close as possible to the contour or wall. This area is calculated in particular based on the specific end effector and robot geometry. In this specific example, it can be seen, for example, that the cleaning robot cannot clean right up to the end of the inner corners of the room, which is why an area remains uncovered there. This restriction due to the shape of the cleaning robot / end effector also specifies the direction in which this area must be or at least should be cleaned.

[0063] For example, in the case of the cleaning robot 100a shown in Figure 1 b, it should move in such a way that the wall or the contour is to the right of the cleaning robot, since the end effector is then closer to the wall.

[0064] The contour cleaning area 320 also corresponds to a contour path or can be determined from a contour path. The contour path specifies the path along which the cleaning robot must move in order to clean the contour cleaning area 320 with the end effector. It should also be noted that instead of the contour cleaning area, one can also speak of a contour coverage area, especially when it is a mobile device other than a cleaning robot.

[0065] In step 212, one or more coverage units 214 are then determined for at least part of the environment. In step 216, using a traveling salesman problem (218) and based on the contour path or the contour cleaning area and the one or at least one of the multiple coverage units, the movement path 220 is determined and provided (step 222).

[0066] As mentioned, the cover units can vary depending on the design.

[0067] In Figure 4a, the environment map 302 from Figure 3c is shown again, also with the contour path or contour cleaning area 320, but additionally with, for example, three coverage units 400, 402, 404. The coverage units are each straight, in particular parallel, path sections. This is also known under the term Boustrophedon coverage algorithm (C. Boustrophedon coverage algorithm). The coverage units are found here, for example, iteratively with an approach until, for example, the largest part of the free area is covered; it should be noted that the free area here can include all rooms. It is understood that the coverage units can also be parallel to other walls. Also conceivable are some mutually parallel coverage units that are perpendicular to other coverage units, but which are in turn parallel to one another.

[0068] The problem is then formulated as a traveling salesman problem, the solution of which can be found to be a path of motion as shown in Figure 4b, labeled 410.

[0069] Figure 5a shows the environment map 302 from Figure 3c again, also with the contour path 320, but additionally with an exemplary coverage unit 500. Figure 5b also shows further coverage units 502, 504. The coverage units are determined such that they are parallel to parts of the contour path 320, in particular, they follow the contour path.

[0070] With such an algorithm, further sections can be continually added to the contour path or contour cleaning area 320, e.g., iteratively and / or in a spiral fashion, until the free area is sufficiently covered. The problem is also formulated as a traveling salesman problem and solved in a similar way to the Boustrophedon approach, whose solution can find a movement path as indicated by 510 in Figure 5c.

[0071] Figure 6a shows the environment map 302 from Figure 3c again, also with the contour path or contour cleaning area 320, but additionally with, for example, several coverage units 600. The coverage units are defined as, in particular, evenly distributed points (e.g., so-called landmarks). Such points or landmarks are, for example, points without orientation that are or will be distributed across the free area, e.g., using a grid.

[0072] The movement path, designated 610 in Figure 6b, is reached when the mobile device (if it follows the movement path) has visited each of these points once. This is a common traveling salesman problem.

[0073] In one embodiment, however, each of the distributed points 600 can also be assigned a predefined orientation for the mobile device. This can then be referred to as the so-called general traveling salesman problem. Each point corresponds in particular to a position that the end effector will visit and, for example, corresponds to several poses. The resulting motion path is designated 612 in Figure 6c as an example.

Claims

Claims 1 . A method for determining a movement path for a mobile device (100), in particular an at least partially automated vehicle or robot, in particular a cleaning robot or a lawnmower robot, wherein the mobile device (100) has an asymmetry, and wherein the mobile device is to move along the movement path (130) in an environment (120), comprising: Providing (204) an environment map (206, 302) comprising information about free areas (310) in the environment (120); Determining (208), based on the environment map, a contour path (210) or contour coverage area for at least a portion of the environment; Determining (212) one or more coverage units (214) for at least a portion of the environment; Determining (216), using a traveling salesman problem (218), based on the contour path or the contour coverage area, and the one or at least one of the plurality of coverage units, the movement path (220); and Providing (222) the movement path (220).

2. The method according to claim 1, wherein the mobile device (100, 100a, 100b, 100c) has an end effector (110, 110a, 110b, 110c), wherein the mobile device has an asymmetry with respect to the end effector, wherein the determination of the contour path or the contour coverage area, and / or the one or more coverage units is based on coordinates of the end effector, and wherein the determination of the movement path is based on coordinates of the mobile device.

3. The method according to claim 1 or 2, further comprising: Providing (200) a preliminary environment map (202) of the environment, in particular obtained by means of SLAM; wherein the environment map (206) is determined based on the preliminary environment map, and wherein the environment map is a binary environment map comprising the information about free areas (310) in the environment and information about non-free areas (312) in the environment.

4. Method according to one of the preceding claims, wherein a plurality of coverage units (400, 402, 404) are determined, wherein at least some of the plurality of coverage units are each determined as rectilinear, in particular mutually parallel, path sections.

5. Method according to one of the preceding claims, wherein a plurality of coverage units (500, 50, 504) are determined, wherein at least some of the plurality of coverage units are determined such that they are parallel to parts of the contour path, in particular follow the contour path.

6. Method according to one of the preceding claims, wherein a plurality of coverage units (600) are determined, wherein at least some of the plurality of coverage units are determined as, in particular, uniformly distributed points.

7. The method according to claim 6, wherein the distributed points are each assigned a predetermined orientation for the mobile device.

8. Method according to one of the preceding claims, further comprising: Determining navigation information for the mobile device based on the movement path.

9. A system (108) for data processing, comprising means for carrying out the method according to any one of the preceding claims.

10. A mobile device (100) comprising a system according to claim 9 and / or configured to receive navigation information determined according to a method according to claim 8 and configured to navigate based on the navigation information, which is preferably further configured to carry out processing, preferably with a control or regulating unit and a drive unit for moving the mobile device according to the navigation information.

11. Mobile device according to claim 10, which is designed as an at least partially automated vehicle, in particular as a passenger transport vehicle or as a goods transport vehicle, and / or as a robot, in particular as a household robot, e.g. a cleaning robot, a floor or street cleaning device or a lawnmower robot, and / or as a drone.

12. A computer program comprising instructions which, when executed by a computer, cause the program to carry out the method steps of a method according to any one of claims 1 to 8 when executed on the computer.

13. A computer-readable storage medium on which the computer program according to claim 12 is stored.

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