Method for determining a position of a predetermined object

Abstract

The invention relates to a method for determining a position of a predetermined object, more particularly of a docking station, in surroundings in which a mobile device is located, said method comprising: providing a set of points (500) in the surroundings, wherein the points are more particularly characteristic of a distance between the mobile device and objects in the surroundings; analysing the set of points with regard to a specified relationship between a plurality of points of the set of points, wherein the specified relationship is determined by an outer contour of the predetermined object; if one or one of several groups (512) of points from the set fulfils the specified relationship, determining this group of points as a subset of points; based on the subset of points, determining the position of the predetermined object.

Description

[0001] Description

[0002] title

[0003] Method for determining a position of a predetermined

[0004] The present invention relates to a method for determining a position of a predetermined object, in particular a docking station, in an environment in which a mobile device, in particular a robot, is located, as well as a system for data processing, a mobile device, an object with or for use with a system, and a computer program for carrying out the same.

[0005] Background of the invention

[0006] Mobile devices such as robots typically move within an environment, particularly within a workspace or work area, such as a home or garden. Such a mobile device is typically designed to repeatedly move to predetermined positions or objects in the environment, such as a docking station where the mobile device can be charged.

[0007] Disclosure of the invention

[0008] According to the invention, a method for determining the position of a predetermined object, as well as a data processing system, a mobile device, an object with or for use with a system, and a computer program for implementing the method are proposed, having the features of the independent patent claims. Advantageous embodiments are the subject of the subclaims and the following description. The invention generally relates to mobile devices that move or are intended to move in an environment or there, e.g., in a work area, and in particular to determining the position of predetermined objects in such an environment.

[0009] Examples of such mobile devices (or mobile work equipment) include robots and / or drones and / or partially or fully automated vehicles (on land, water, or in the air). Robots include, for example, household robots such as vacuum and / or mop robots, floor or street cleaning devices, or lawnmower robots, as well as other so-called service robots, as well as at least partially automated vehicles, such as passenger vehicles or goods transport vehicles (including industrial trucks, e.g., in warehouses), as well as aircraft such as drones or watercraft.

[0010] Such a mobile device comprises, in particular, a control and / or regulating unit and a drive unit for moving the mobile device, so that the mobile device can be moved in the environment, e.g., along a movement path or trajectory. Furthermore, a mobile device can comprise one or more sensors by means of which the environment or information in the environment can be detected.

[0011] In the following, the invention will be explained in particular using the example of a robot vacuum cleaner as a mobile device, although the principle can also be applied to other types of mobile devices.

[0012] Mobile devices, such as household and service robots, are usually equipped with a built-in power supply (energy storage, especially a battery), so that the mobile device must automatically detect and connect to an external power source in order to recharge. Such an external power source is typically provided at a so-called docking station. A docking station for mobile devices or robots, for example, has an electrical charging system with a series of contacts. The complementary contacts on the robot enable it to detect the contact point and receive an electrical charging current. Depending on the type of mobile device, a docking station can also serve other purposes. In the case of goods transport vehicles, a docking station can, for example, be used to load and / or unload goods to be transported (this can be done manually and / or automatically). Likewise, in addition, for examplethe battery can also be charged.

[0013] As mentioned, such robots are typically equipped with sensors that enable them to perceive and navigate their environment. A laser scanner, especially a 2D laser scanner (e.g., a lidar sensor), is a cost-effective sensor solution for a mobile robot. However, its limited perception capabilities make it difficult to detect the docking station using a scan or 2D scan alone.

[0014] Against this background, a method is proposed for determining a predetermined object, such as a docking station, in an environment based on a set of points in the environment, where the points are each characteristic of a distance between the mobile device and objects in the environment. A typical example of such a set of points is a so-called lidar point cloud resulting from a lidar scan.

[0015] This set of points is provided. For example, this can be done by receiving a lidar point cloud from a lidar sensor on the mobile device. This set of points is then analyzed with regard to a predetermined relationship between several points in the set of points, wherein the predetermined relationship is determined by an outer contour of the predetermined object. A preferred example of such a predetermined relationship is that points lie on a line of a certain length. This analysis is preferably carried out by determining several groups of points from the set of points, and then analyzing each of these groups with regard to the predetermined relationship. This determination of several groups can also be referred to as clustering. If a group of points from the set - or one of several groups of points from the set - fulfills the predetermined relationship, for exampleIf the points lie on a line of a certain length, or at least lie within specified tolerances on a line of a predetermined length, this group of points is defined as a subset of points. This subset then indicates, in particular, which object is involved.

[0016] If more than one of the multiple groups satisfies the specified relationship, the group with the shortest distance from the mobile device can be determined as the subset. The shortest distance can, for example, apply on average to every point in the group or to a central point in the group.

[0017] Alternatively, if more than one of the several groups fulfill the specified relationship (e.g., they lie at least within specified tolerances on a line of the predetermined length, but, for example, differ slightly in length), the group that best fulfills the specified relationship, e.g., corresponds most precisely to the specified length, can be determined as the subset.

[0018] Based on the subset of points, the position of the predetermined object is then determined; in particular, navigation information for the mobile device is also determined based on the position of the predetermined object.

[0019] In other words, an outer contour of the predetermined object is searched for in the existing set of points, e.g., the lidar point cloud, or a mapping of this outer contour through the set of points is searched for. This makes it particularly easy to design or configure such a predetermined object to be detected, such as the docking station. For example, a flat plate can be attached to the object or docking station. This plate is positioned at the height of the lidar sensor of the mobile device (or another sensor) and has a specific width in the detection direction of the sensor, e.g., parallel to a surface on which the mobile device is moving. This plate, as an outer contour of the object, then leads to a subset of points in the lidar scan (or the set of points) that lie on a line. This line then has (at least approximately) a length that corresponds to the aforementioned width of the plate.

[0020] It is thus possible to reduce the signature of the docking station to a straight line of known length (in contrast to, for example, uniquely coded structures used in other approaches such as pattern recognition in cameras).

[0021] Preferably, the predetermined relationship comprises that the plurality of points lie within a two- or three-dimensional area predetermined by the outer contour of the predetermined object, in particular lie on a line of a predetermined length. In addition to the (straight) line, other relationships are also conceivable; for example, it can be provided that the plurality of points should lie on a circular arc section or another curved line. Here, too, the length and / or the radius can be predetermined. It is particularly expedient to form a simple geometric shape on the outer contour of the predetermined object, which can then be easily found in the set of points. It is understood that this contour does not necessarily have to be specifically designed; existing contours can also be used.

[0022] In one embodiment, it is further provided that the one or at least one, preferably each, of the plurality of groups of points that satisfy the predetermined relationship are analyzed with respect to a predetermined pattern of points in the respective group. This takes place in particular after the analysis with respect to the predetermined relationship, but before determining the subset. The one or such group of analyzed groups that corresponds to the predetermined pattern is then determined as the subset. The predetermined pattern comprises a variation of intensity values ​​of the points. The variation of intensity values ​​can be determined in particular by a variation of a reflectivity of a surface of the predetermined object in the region of the contour.For example, a predetermined pattern can comprise at least two, preferably at least three, regions that alternately have intensity values ​​above an upper threshold and below a lower threshold. The thresholds refer to the intensity of the points, with the upper threshold indicating a higher intensity than the lower threshold.

[0023] A variation in reflectivity can be achieved on the object or its surface, for example, through different colors or matte and glossy areas. However, certain coatings in certain areas are also conceivable in order to increase or decrease the reflectivity. A pattern of such a variation in reflectivity then affects the intensity of the points, which accordingly exhibit a pattern of varying intensity values. If the points are recorded using LIDAR or laser ranging, for example, points corresponding to LIDAR beams reflected from a surface with lower reflectivity will have a lower intensity than those reflected from a surface with higher reflectivity. Instead of LIDAR (laser ranging) or a LIDAR sensor, a time-of-flight camera, a time-of-flight depth camera or a time-of-flight sensor in general can also be used.

[0024] In this way, a specific object such as the docking station can be identified even more precisely. For example, if several groups of points satisfy the specified relationship, i.e. lie on a line of a certain length, the desired object can be identified from these. For example, a box in the environment can provide a similar relationship between the points as the docking station. The desired object can be given the pattern of variation in reflectivity. In this context, it should be mentioned that in practice only one of several groups will satisfy the pattern, since this is explicitly specified and, in particular, can be chosen or specified very specifically. In the event that only one group of points satisfies the specified relationship, analysis can also be carried out according to the pattern. In this case, this is a verification.If only the switches were detected in the example above, this would otherwise be identified as the docking station, for example.

[0025] In this way, the area or radius within which the object is detected or its position is determined can be significantly expanded, since other objects with a similar relationship in the contour can also be detected; the additional pattern of intensity values ​​allows for a specific search for the desired object.

[0026] If no group of points can be determined from the set of points that satisfy the specified relationship, a new set of points is preferably provided that differs from the set of points, especially after moving the mobile device. The above-mentioned procedure can then be performed again.

[0027] This also applies if no group of points can be determined from the set of points that satisfy the given pattern, provided that this criterion is used.

[0028] Preferably, a position and / or orientation of the mobile device relative to the predetermined object is also determined based on the position of the predetermined object. Navigation information, and in particular also movement control variables, are then determined for the mobile device in order to move the mobile device to the predetermined object. A so-called docking maneuver can then be performed, for example, to dock the mobile device to the docking station.

[0029] The position and / or orientation of the mobile device relative to the predetermined object is determined, in particular, based on at least one property of the predetermined object and / or the environment, which property has an effect on the points. This at least one property includes, for example, a reflectivity of a surface of the predetermined object (wherein the reflectivity can be considered here, in particular, independently of the aforementioned pattern) and / or an inclination of a surface in front of the predetermined object. This further facilitates approaching the predetermined object or docking at the docking station.

[0030] Preferably, a potential, e.g., estimated, position of the predetermined object is first provided. Based on the potential position of the predetermined object, the position is then determined as explained above, and in particular the navigation information is used to move the mobile device to the predetermined object. If the predetermined object cannot be reached or has not been reached using the navigation information, a different potential position of the predetermined object can be provided. The method can then be performed again.

[0031] A data processing system according to the invention comprises means for carrying out the method according to the invention or its method steps. The system can be a computer or server, e.g. in a so-called cloud or cloud environment. From there - in the case of application for a mobile device - the position of the predetermined object can be transmitted to the mobile device (e.g. via a wireless data connection). Likewise, information about the environment, e.g. the number of points, can be transmitted from the mobile device to the system. However, it is also conceivable that such a data processing system is a computer or a control unit in such a mobile device.

[0032] The invention also relates to a mobile device configured to provide a set of points in an environment and to obtain a position of a predetermined object in the environment, which has been determined from the set of points according to a method according to the invention, and in particular to use this position for navigation. Preferably, the mobile device comprises a distance measurement or lidar sensor for detecting the set of points in the environment, more preferably a control and / or regulating unit and a drive unit for moving the mobile device. As mentioned, the data processing system can also be included in the device.

[0033] The mobile device is preferably 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 vacuum and / or mop robot, a floor or street cleaning device or a lawnmower robot, and / or as a drone.

[0034] The invention also relates to an object, in particular a docking station, with or for use with a data processing system according to the invention or a mobile device according to the invention. The object has an outer contour, based on which a relationship between several points of the set of points can be determined. For example, the object can have the aforementioned flat plate having a specific width. Furthermore, it is expedient if this outer contour or plate is at the level of the distance measurement or lidar sensor of the mobile device.

[0035] Preferably, the object further exhibits a variation in the reflectivity of a surface in the area of ​​the contour, e.g., a correspondingly predefined pattern. Possible examples include alternating different colors or alternating matte and glossy areas.

[0036] 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, as 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.).

[0037] Further advantages and embodiments of the invention will become apparent from the description and the accompanying drawings.

[0038] The invention is illustrated schematically in the drawing using an embodiment and is described below with reference to the drawing.

[0039] Short description of the drawings

[0040] Figure 1 schematically shows a mobile device and a predetermined object in an environment to explain the invention in a preferred embodiment.

[0041] Figures 2a, 2b and 2c schematically show the mobile device and the predetermined object from Figure 1 in other views.

[0042] Figure 3 shows schematically a method according to the invention in a preferred embodiment.

[0043] Figure 4 shows schematically a method according to the invention in a further preferred embodiment.

[0044] Figures 5a, 5b, 5c and 5d show schematic diagrams for explaining the invention in a preferred embodiment.

[0045] Figures 6a, 6b, and 6c show schematic diagrams to explain the invention in a preferred embodiment. Embodiment(s) of the invention

[0046] Figure 1 schematically shows a mobile device 100 and a predetermined object 130 in an environment 120 to illustrate a preferred embodiment of the invention. The mobile device 100 is, for example, a robot vacuum cleaner with a control or regulating unit 102 and a drive unit 104 (with wheels) for moving the robot vacuum cleaner 100 in the environment 120, e.g., an apartment or a room.

[0047] Furthermore, the robot vacuum cleaner 100 has, for example, a sensor 106 embodied as a 2D lidar sensor with a detection field (indicated by dashed lines). For clarity, the detection field is chosen to be relatively small; in practice, however, the field of view can also be up to 360° (e.g., but at least 180° or at least 270°). Using the 2D lidar sensor 106, distances between the mobile device 100 (or the sensor 106) and objects in the environment can be detected or determined.

[0048] Furthermore, the robot vacuum cleaner 100 has a system 108 for data processing, e.g., a control unit, by means of which data can be exchanged, e.g., via an indicated radio connection, with a higher-level data processing system 110. In the system 110 (e.g., a server; it can also stand for a so-called cloud), navigation information can be determined, for example, which is then transmitted to the system 108 in the robot vacuum cleaner 100, according to which the latter is then to be operated. However, it can also be provided that navigation information is determined in the system 108 itself or is received there in some other way. Instead of navigation information, the system 108 can, for example, also receive control information that has been determined on the basis of navigation information and according to which the control or regulating unit 102 can move the robot vacuum cleaner 100 via the drive unit 104.Furthermore, a docking station 130 is shown in the environment 120 as an example of a predetermined object. The docking station 130 has, for example, contacts 132 (e.g., electrical contacts) for charging an energy storage device of the robot vacuum cleaner 100, as well as, for example, a plate with a flat plane 134 on one side (a surface). The flat plane 132 is an example of an outer geometric contour of the object or the docking station 130.

[0049] Figures 2a and 2b show further different views of the robot vacuum cleaner 100 and in particular of the docking station 130. While Figure 1 shows a top view, Figure 2a shows a side view, in which it can be seen in particular that the plate with the flat plane 134 is at a certain height above a surface (floor) 122, on which the robot vacuum cleaner 100 moves on the one hand and the docking station stands on the other. The flat plane 134 is at the level of the 2D lidar sensor 106, the height of which above the surface 122 is designated HS. This ensures that the 2D lidar sensor can detect the flat plane 134. With a different sensor or, for example, a 3D lidar sensor, this need not be taken into account, or less attention must be paid to this.

[0050] Figure 2b shows the docking station 130 and in particular the flat plane 134 in a front view, as seen, for example, from the perspective of the robot vacuum cleaner 100 or the 2D lidar sensor. Two specific dimensions of the flat plane 134 are also shown here, namely its width B and its height H. While the height H serves, for example, to allow a certain amount of leeway for detection with the 2D lidar sensor or positioning at the height of the 2D lidar sensor (e.g., even on uneven surfaces), the width B serves to identify the flat plane 134 in a lidar scan, a so-called point cloud, as will be explained below.

[0051] Furthermore, the flat plane 134 or any other surface or contour to be detected can be white, in particular matte white, for example, i.e., painted white or coated with a white material to reduce or prevent any reflections. Figure 2c shows a docking station 130', which can fundamentally correspond to the docking station 130 shown in Figures 2a and 2b. In particular, the docking station 130' is also shown in the same view.

[0052] Unlike in Figure 2b, in Figure 2c, the flat plane 134' is understood to have a pattern that exhibits a variation in the reflectivity of the surface. For this purpose, four regions 134a, 134b, 134c, 134d are provided, each having a length L (as viewed along the width B). The flat plane 134' is thus divided into four regions 134a, 134b, 134c, 134d. These regions now exhibit alternating reflectivities, so that when lidar beams or similar are reflected thereon, a pattern with alternating intensity values ​​above an upper threshold and below a lower threshold is created.

[0053] For example, areas 134a and 134c may be bright and / or glossy, while areas 134b and 134d may be dark and / or matte. The 2D lidar perceives this surface as having four clearly distinguishable areas or regions, corresponding to the four areas in Figure 2c. Each area will include points with similar reflectance values ​​in the lidar scan.

[0054] It should be noted that this is merely an example of a pattern. Three, four, or more different reflectivities could be used, combining them in any way desired. However, care should be taken to ensure that the different reflectivities produce sufficiently different intensity values ​​in the points to be distinguishable. Furthermore, the lengths of the regions do not have to be identical; they can also be different.

[0055] Figure 3 schematically illustrates a method according to the invention in a preferred embodiment as a type of flowchart or sequence diagram. In particular, this should include a docking procedure. This will be explained using a robot vacuum cleaner as a mobile device and a docking station as a predetermined object, as shown in Figures 1a to 2c.

[0056] After a start 300, an (initial) potential position 304 (possibly also with orientation) of the docking station is first provided in a step 302. There are various ways in which potential positions or poses of the docking station can be made available to the robot vacuum cleaner. This can be, for example, the starting position from which it started, a position or pose specified by the user (e.g., in response to a message from the robot if it cannot detect the docking station at its previous position); a list of possible positions or poses collected during the robot's runtime is also conceivable (e.g., by executing the docking station detection algorithm, which can be particularly helpful when the robot is moving near walls).Another possibility is that these new positions or poses of the docking station are created by another process that can be started on demand, e.g., by exploring the drivable area while searching for signatures of the docking station.

[0057] In a step 306, the robot vacuum cleaner moves to or near the docking station; this occurs based on the potential position 304. If the robot vacuum cleaner is then near the docking station, i.e., at or near the potential position, navigation information 308 is determined in a step 310 in order to move the robot vacuum cleaner to the docking station. This occurs, on the one hand, based on the potential position 304, but on the other hand, also by determining the position of the docking station based on a 2D lidar scan (set of points). This will be explained in more detail below with reference to Figure 4. This navigation information can, for example, also include instructions on how the robot vacuum cleaner should navigate (e.g., how far it should travel and when, when it should turn, etc.). In particular, motion control variables for controlling the drive unit can also be determined.In step 310, a docking maneuver is performed, ie, the robot vacuum cleaner moves to the docking station according to the navigation information 308, or at least attempts to do so. The detection of the docking station, ie, the determination of its position, is performed continuously or repeatedly during the docking process (the control is based on this input).

[0058] In step 312, a check is then made to determine whether the docking maneuver was successful or not. If yes (Y), i.e., if the robot vacuum cleaner has successfully docked at the docking station and, for example, has established electrical contact to charge the battery, the method is terminated in step 314. This can be the case, for example, if the potential position is already very close to the actual position.

[0059] If, however, the docking maneuver was unsuccessful (N), i.e., if the docking station was not reached using the navigation information, a check is made in step 316 as to whether the docking station was even detected. If the docking station was detected, i.e., if the position of the docking station (or of any docking station at all) was determined (Y), a switch is made again to step 306 in order to drive back towards the docking station based on the potential position 304 or a new potential position derived from the position of the docking station detected in the previous step 310. A docking maneuver is attempted again, for example, with the same potential position of the docking station (it was actually detected), for example by driving back and approaching the docking station again with, for example, a slightly different approach angle or the like.

[0060] However, if no docking station was detected in step 316 (N), a new potential position of the docking station can be searched for or requested in step 318. If a new or different potential position of the docking station was found or provided in step 320 (as mentioned, for example, in step 302) (Y), the process can return to step 306. The entire process can be repeated until it is successful or until no more positions or poses remain (N); then the process ends with step 322. Figure 4 schematically shows a method according to the invention in a further preferred embodiment as a type of flow chart or sequence diagram. By way of example, this will again be explained using a vacuum cleaner robot as a mobile device and a docking station as a predetermined object, as also shown in Figures 1a to 2c.

[0061] In particular, the determination of the position of the docking station based on the set of points is now to be included here, as mentioned above with reference to Figure 3 in step 310 for determining the navigation information and in step 316 if the docking maneuver with the potential position was not successful.

[0062] For this purpose, a set of 500 points in the environment is first provided in step 400, e.g., using the 2D lidar scan. Figure 5a shows such a set of 500 points as an example of a 2D lidar scan, such as is obtained, for example, in an environment with the docking station in front of a wall by the 2D lidar sensor, similar to Figure 1.

[0063] This set 500 is then analyzed in a step 410, specifically with respect to a predetermined relationship 412 between several points in the set of points. This predetermined relationship is determined, for example, by the flat plane 134 of the docking station and requires that points lie on a straight line of a certain length (corresponding to the width B of the flat plane 134).

[0064] For this purpose, in step 414, several groups of points can be determined which, for example, have a similar relationship between several points; this can be referred to as a clustering process or clustering. In Figure 5b, the set 500 of points is shown again, but after a clustering process in which several groups 510, 512, 514, 516, 518 of points have been determined. A possible algorithm by means of which these groups (or clusters) can be determined is, for example, as follows: A cluster criterion such as a certain distance can be specified. For each point, it is then checked successively whether its distance to the previous point corresponds at most to the certain distance. If so, this point belongs to the same cluster or group. If not, a new cluster or group is formed.

[0065] Figure 5b, for example, shows that the points, starting at the bottom left, are initially very close together, then the next point is located further forward at a greater distance. A new group, group 512, begins there.

[0066] These groups can then be analyzed in step 416, specifically with regard to the specified relationship 412 between several points in the set of points. A possible algorithm by which a group (or cluster) can be analyzed to determine whether it or its points satisfy the specified relationship is, for example, as follows.

[0067] For example, a relationship criterion such as a certain length can be specified. For each two consecutive points in the group or cluster, a distance is then determined in the x- and y-direction (this applies, for example, to a 2D analysis in a Cartesian coordinate system; this is only an example here). This is denoted by Axi and Ayi in Figure 5c. A standard deviation is then determined for each of these distances, i.e., once in the x- and once in the y-direction. If their sum is smaller than the relationship criterion, it can be assumed that these points lie on a line.

[0068] In this way, in step 420, a group, here 512, can be determined that satisfies the predetermined relationship; this group 512 should then be a subset of points, ie, the selected group that is used to determine the position of the docking station.

[0069] If more than one of the multiple groups satisfy the predefined relationship, in step 422 the group that has the shortest distance to the robot vacuum cleaner or the lidar sensor is determined as the subset. The distance can be determined, for example, as the average distance of all points in the group to the robot vacuum cleaner or the lidar sensor. In the case of Figure 5b, for example, group 510 or 516 can also satisfy the predefined relationship. Here, it also depends on how exactly the predefined relationship is satisfied. Instead of the shortest distance, however, another preferred criterion can be used, based on which the multiple groups are ordered and / or one of the groups is determined as the subset. For example, a suitable algorithm can be used to determine the group. An algorithm can also be used to determine the shortest distance.

[0070] Optionally, however, if more than one of the multiple groups satisfy the predefined relationship, for example, instead of step 422, in step 424, these multiple groups of points that satisfy the predefined relationship can be analyzed with respect to a predefined pattern of points in the respective group. The predefined pattern comprises a variation in the intensity values ​​of the points, wherein the variation in the intensity values ​​is determined in particular by a variation in the reflectivity of a surface, for example, area 134' as shown in Figure 2c.

[0071] Figure 5d shows group 512 from Figure 5b again as an example. Here, this group 512 comprises 16 points, with four consecutive points forming a region or segment, here 512a, 512b, 512c, and 512d each with four points. While the points of each of these segments have the same or at least approximately the same intensity value within the segment, the intensity values ​​differ between the segments. Thus, there are four different intensity values.

[0072] Each segment has a length L, which corresponds, for example, to the length L of the four regions of the flat plane 134' according to Figure 2c. If the four regions of the flat plane 134' according to Figure 2c each have different reflectivities, thus a total of four, this could correspond to the group here in Figure 5c. However, if, as mentioned above with regard to Figure 2c, there are only two different reflectivities, the result for group 12 would be that, for example, segments 512a and 512c on the one hand and segments 512b and 512d on the other hand each have the same intensity value.

[0073] The pattern in the group depends on the pattern on the docking station or the object in general. In other words, any group of points that satisfies the specified relationship with regard to the contour can be analyzed with regard to the pattern assigned by the docking station or the object. If the specified pattern has four segments of equal length, the group of points can be divided into four equal numbers of points - or corresponding lengths, if, for example, the points are unevenly distributed. In practice, it may happen that the points cannot be divided exactly accordingly; however, an approximately exact division is sufficient, especially since in practice there will be a significantly higher number of points per group than just 16.

[0074] In particular, the individual intensity values ​​of the points can be compared with each other, i.e., a relative value is considered instead of an absolute value. Furthermore, average intensity values ​​can be determined for each segment (e.g., as the arithmetic mean of the individual intensity values ​​of the segment), which can then be compared across the segments.

[0075] If one of the multiple groups satisfies this pattern, this group can be determined as the subset.

[0076] Based on the subset of points, the position 432 of the docking station is then determined in step 430. The position 432 as the position of the docking station is then used in relation to Figure 3 in step 310 for the continuous provision of the navigation information 308, or, as mentioned in relation to Figure 3, it can then be continued from step 320 to step 306. As mentioned, the docking station can be defined, for example, by an arc of a circle with a specific radius and / or length instead of a straight line. For this purpose, Figure 6a shows a group 612 of points which are defined by an arc of a circle with radius r es t is defined. In Figure 6b a group 612' of points is shown, which are defined by a circular arc with a different radius r' es t is defined. In Figure 6c a group 612" of points with positions xi to x n which is defined by a circular arc of length L.

[0077] In such cases, the points from a cluster (group) can be fitted to a circle, e.g., using a closed least-squares method (e.g., according to https: / / lucidar.me / en / mathematics / least-squares-fitting-of-circle / , or https: / / www.emis.de / journals / BBMS / Bulletin / sup962 / gander.pdf). This determines the radius of the circle as well as the coordinates of the circle center x. c determined and the radius and / or the calculated arc length L es t (e.g.

[0078] Read=0*r e st) is compared with the expected radius of the docking station or its arc length. The cluster is accepted as a hit if the deviations for the radius and / or length between the measured and expected values ​​are below certain thresholds.

[0079] In this case, too, a pattern with variation in the intensity values ​​can be specified and the groups of points can be analyzed accordingly.

[0080] It goes without saying that such predefined patterns can also be used to distinguish between two or more different objects by specifying a different pattern for each of the desired objects. Care should be taken to ensure that different patterns are clearly distinguishable from one another in terms of the intensity values ​​of the points. This allows, for example, differentiation between different docking stations, such as one for charging the robot and one for emptying a dust container or the like.

Claims

Claims 1 . A method for determining a position of a predetermined object (130), in particular a docking station, in an environment (120) in which a mobile device (100), in particular a robot, is located, and to which the mobile device is to navigate, comprising: Providing (400) a set of points (500) in the environment, wherein the points are in particular each characteristic of a distance between the mobile device (100) and objects (130) in the environment, analyzing (410) the set of points with respect to a predetermined relationship (412) between several points of the set of points, wherein the predetermined relationship (412) is determined by an outer contour (134) of the predetermined object (130), Determining (420), if one or one of several groups (512) of points from the set satisfies the given relationship, this group of points as a subset of points, Determining (430) based on the subset of points the position of the predetermined object (130), and in particular determining navigation information (308) for the mobile device (100) based on the position (432) of the predetermined object.

2. The method of claim 1, wherein analyzing (410) the set (500) of points comprises: Determining (414) several groups (510-518) of points from the set of points, and Analyzing (416) each of the plurality of groups with respect to the given relationship.

3. The method according to claim 1 or 2, further comprising, Analyzing the one or at least one, preferably each, of the plurality of groups of points that satisfy the predetermined relationship with respect to a predetermined pattern of points of the respective group among each other, wherein the predetermined pattern comprises a variation in intensity values ​​of the points, wherein the variation in intensity values ​​is determined in particular by a variation in a reflectivity of a surface of the predetermined object (130) in the region of the contour, wherein the one or such of the analyzed groups is determined as the subset that corresponds to the predetermined pattern. Method according to claim 3, wherein the predetermined pattern comprises at least two, preferably at least three, regions that alternately have intensity values ​​above an upper threshold value and below a lower threshold value.Method according to one of the preceding claims, wherein the predetermined relationship comprises that the plurality of points lie within a two- or three-dimensional area predetermined by the outer contour (134) of the predetermined object (130), in particular lie on a line of a predetermined length (B). Method according to one of the preceding claims, wherein, if no group of points can be determined from the set of points that fulfill the predetermined relationship or, with reference back to claim 3, the predetermined pattern, a new set of points is provided that is different from the set of points, in particular after moving the mobile device (100). Method according to one of the preceding claims, further comprising:. Determining, based on the position of the predetermined object (130), a position and / or orientation of the mobile device (100) relative to the predetermined object (130), and Determining navigation information (308), and in particular movement control variables, for the mobile device (100) in order to move the mobile device (100) to the predetermined object (130).

8. The method according to claim 7, wherein the determination of the position and / or orientation of the mobile device (100) relative to the predetermined object (130) is further based on at least one property of the predetermined object (130) and / or the environment (120), which property has an effect on the points, wherein the at least one property comprises in particular a reflectivity of a surface of the predetermined object (130) and / or an inclination of a ground (122) in front of the predetermined object (120).

9. Method according to one of the preceding claims, further comprising: Providing (302) a potential position (304) of the predetermined object, wherein the determining (430) of the position of the predetermined object (130), and in particular the navigation information (308) for the mobile device (100), is further based on the potential position (304) of the predetermined object, in order to move the mobile device to the predetermined object (130).

10. The method of claim 9, wherein if the predetermined object (130) is not reachable or has not been reached with the navigation information (308), another potential position of the predetermined object is provided (320).

11. A system (108, 110) for data processing, comprising means for carrying out the method according to any one of the preceding claims.

12. A mobile device (100) configured to provide a set of points in an environment (120), wherein the mobile device (100) is further configured to provide a position of a predetermined object (130) in the environment, which is determined according to a method according to one of claims 1 to 10 from the set of points, and in particular to use it for navigation, preferably with a distance measuring or lidar sensor (106) for detecting the set of points in the environment, more preferably with a control or regulating unit (102) and a drive unit (104) for moving the mobile device (100), and more preferably with a system (108) according to claim 10, wherein the mobile device (100) is designed in particular as a robot, in particular as a household robot, e.g. a vacuum and / or mop robot, a floor or street cleaning device or a lawnmower robot, as an at least partially automated moving vehicle, in particular as a passenger transport vehicle or as a goods transport vehicle, and / or as a drone.

13. Object (130), in particular a docking station, with or for use with a system (108, 110) according to claim 11 or a mobile device (100) according to claim 12, wherein the object (130) has an outer contour (134) on the basis of which a relationship between a plurality of points of the set of points can be determined, and wherein the object (130) preferably further has a variation of a reflectivity of a surface in the region of the contour.

14. 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 10 when executed on the computer.

15. A computer-readable storage medium on which the computer program according to claim 14 is stored.

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