Method for determining position of predetermined object

Abstract

The invention relates to a method for determining the position of a predetermined object, in particular a docking station, in an environment in which a mobile device is located, said method comprising: providing a set of points (500) in the environment, said points characterizing, in particular, the distance between the mobile device and the object in the environment, respectively; the set of points is analyzed with respect to a predetermined relationship between a plurality of points in the set of points, the predetermined relationship being determined from the outer contour of the predetermined object, if one of one or more groups (512) of points from the set satisfies the predetermined relationship, the group of points is determined as a subset of points, and if the predetermined relationship is satisfied, the subset of points is determined as a subset of points. A position of the predetermined object is determined based on the subset of points.

Description

Technical Field

[0001] The invention relates to a method for determining the 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 having the system or for use with the system, and a computer program for executing the method. Background Art

[0002] Mobile devices such as robots typically move in an environment, in particular in an environment to be processed or a work area, such as a home or in a garden. Such mobile devices typically need to be moved repeatedly to predetermined locations or objects in the environment, such as to a docking station, where the mobile device can be charged, for example. Summary of the invention

[0003] According to the invention, a method for determining the position of a predetermined object having the features of the independent claims, as well as a system for data processing, a mobile device, an object having the system or for use with the system, and a computer program for carrying out the method are proposed. Advantageous embodiments are the subject matter of the dependent claims and of the following description.

[0004] The present invention generally relates to a mobile device which moves or is to move in an environment or in a working area therein and in particular to determining the position of a predetermined object in such an environment.

[0005] Examples of such mobile devices (or mobile working devices) are, for example, robots and / or drones and / or vehicles that move partially or (fully) automatically (on land, in water or in the air). Robots include, for example, household robots, such as vacuum and / or wiping robots, floor or road cleaning devices or lawn mowing robots, and also other so-called service robots, vehicles that move at least partially automatically, such as passenger vehicles or freight vehicles (also so-called land transport vehicles, for example in warehouses), as well as aircraft, such as so-called drones or ships.

[0006] Such a mobile device has in particular a control and / or regulation unit and a drive unit for moving the mobile device, so that the mobile device can be moved in the environment, for example, also along a movement path or trajectory. In addition, the mobile device can have one or more sensors, by means of which the environment or information in the environment can be detected.

[0007] In the following, the present invention will be explained in particular using a vacuum cleaner robot as an example of a mobile device, although the principle can also be transferred to other types of mobile devices.

[0008] Mobile devices, such as household and service robots, are usually equipped with built-in power supplies (energy storage devices, in particular batteries), so that the mobile device must automatically identify an external power source and connect to it in order to charge. Such an external power source is usually provided at a so-called docking station. For example, a docking station for a mobile device or robot has a charging system with a series of contacts. Complementary contacts at the robot enable the robot to identify the contact points and receive a charging current. However, depending on the type of mobile device, the docking station can also be used for other purposes. In the case of freight vehicles, the loading and / or unloading process of the goods to be transported can be carried out at the docking station (this can be done manually and / or automatically). But it is also possible to charge the battery in addition, for example.

[0009] As mentioned, such robots are usually equipped with sensors that enable the robot to perceive the environment and navigate therein. For example, laser scanning, especially 2D laser scanners (e.g., so-called lidar sensors), is a cost-effective sensor solution for mobile robots. However, its limited perception capabilities make it difficult to identify a docking station using only scanning or 2D scanning.

[0010] In this context, the following possibility is proposed: determine a predetermined object in the environment, such as a docking station, i.e., based on a set of points in the environment, wherein the points in particular respectively characterize the distance between the mobile device and the object in the environment. A typical example of such a set of points is a so-called lidar point cloud resulting from a lidar scan.

[0011] In this case, the set of points is provided. This can be the case, for example, by obtaining a lidar point cloud from a lidar sensor at a mobile device. The set of points is then analyzed with respect to a predetermined relationship between a plurality of points in the set of points, wherein the predetermined relationship is determined by the outer contour of a predetermined object. A preferred example of such a predetermined relationship is that the points lie on a line of a certain length. The analysis is preferably performed by determining a plurality of groups of points from the set of points and then analyzing each of these groups with respect to the predetermined relationship. This determination of a plurality of groups can also be referred to as clustering.

[0012] If a group of points from the set - or one of a plurality of groups of points from the set - satisfies a predefined relationship, i.e., for example, lies on a line of a certain length, or at least lies on a line of a predetermined length within a predefined tolerance, this group of points is determined to be a subset of points. This subset then indicates, in particular, which object it relates to.

[0013] If more than one group of the plurality of groups meets the predetermined relationship, the group with the smallest distance to the mobile device can preferably be determined as a subset. For example, the smallest distance can be applied to each point in the group on average or to an intermediate point in the group.

[0014] Alternatively, if more than one group of a plurality of groups satisfies a predetermined relationship (i.e., for example, is located on a line of predetermined length at least within a predetermined tolerance, but, for example, differs slightly from one another in length), then that group that best satisfies the predetermined relationship, i.e., that most accurately corresponds to a specific length, can be determined as a subset.

[0015] Based on the subset of points, the position of the predetermined object is then determined; in particular, navigation information is also determined for the mobile device, namely based on the position of the predetermined object.

[0016] In other words, the outer contour of the predetermined object is therefore searched in an existing set of points, for example a lidar point cloud, or an image of this outer contour is searched through the set of points. This allows such a predetermined object that should be recognized, such as a docking station, to be constructed or designed in a particularly simple way. For example, a flat plate can be placed at the object or the docking station, which is arranged at the height of the lidar sensor (or other sensor) of the mobile device and has a specific width in the detection direction of the sensor, that is, for example parallel to the foundation on which the mobile device moves. This plate as the outer contour of the object then leads to a subset of points that are located on a line in the lidar scan (or set of points). This line then has a length that corresponds (at least approximately) to the mentioned width of the plate.

[0017] It is thus possible to reduce the signature of the docking station to a straight line of known length (in contrast to structures such as unique codes which are used in the case of cameras in the case of other approaches such as pattern recognition).

[0018] Preferably, the predetermined relationship includes that the plurality of points are located in a two-dimensional or three-dimensional area predetermined by the outer contour of the predetermined object, in particular on a line of a predetermined length. However, in addition to (straight) lines, other relationships can also be considered; for example, it can be provided that the plurality of points should be located on an arc segment or another curve. The length and / or radius can also be predetermined here. It is particularly suitable to form a simple geometric shape at the outer contour of the predetermined object, which can then be easily found in the set of points. It goes without saying that the contour does not necessarily have to be designed specifically; an existing contour can also be used.

[0019] In one embodiment, it is further provided that one or at least one, preferably each, of a plurality of groups of points is analyzed with respect to a predetermined pattern between the points of the respective groups, which points satisfy a predetermined relationship. This is done in particular after the analysis with respect to the predetermined relationship, but before the determination of the subset. A group or such a group of the analyzed groups that corresponds to the predetermined pattern is then determined as a subset.

[0020] The predetermined pattern here comprises a change in the intensity value of the point. The change in the intensity value can be determined in particular by a change in the reflectivity of the surface of the predetermined object in the region of the contour. For example, the predetermined pattern can comprise at least two, preferably at least three regions, which alternately have intensity values ​​above an upper threshold value and below a lower threshold value. The threshold value is related to the intensity of the point, wherein the upper threshold value indicates a higher intensity than the lower threshold value.

[0021] A change in reflectivity can be achieved on an object or its surface, for example, by different colors or matte and shiny areas. However, specific coatings in specific areas are also conceivable in order to increase or reduce the reflectivity. The pattern of such a change in reflectivity then has an effect on the intensity of the points, which accordingly have a pattern of changes in intensity values. For example, if the points are detected by means of a LiDAR or laser rangefinder, the points corresponding to the LiDAR beam reflected from a surface with a lower reflectivity will have a lower intensity than such points reflected from a surface with a higher reflectivity. Instead of a LiDAR (laser rangefinder) or LiDAR sensor, a time-of-flight camera, a time-of-flight depth camera or generally a time-of-flight sensor can also be used.

[0022] In this way, specific objects such as docking stations can be identified more precisely. For example, if a plurality of groups of points meet a predetermined relationship, i.e., are located on a line of a certain length, the desired object can be identified therefrom. For example, a box in the environment can provide a relationship between points that is comparable to a docking station. That is, the desired object can be equipped with a pattern of changes in reflectivity accordingly. In this connection, it should be mentioned that in practice only one of the plurality of groups will meet this pattern, since this is clearly predetermined and, in particular, can also be selected or predetermined very specifically.

[0023] For the situation that only one group of points meets the predetermined relationship, it can also be analyzed according to the pattern. In this case, this is a verification. If only the switch is detected in the above example, this would also be recognized as a docking station, for example.

[0024] In this way, the circle or radius in which the recognition of objects or the determination of their position is carried out can be significantly expanded, since other objects having a comparable relationship in the contour can also be detected; the desired object can thus be searched for correctly by the additional pattern of intensity values.

[0025] If a group of points that satisfies the predetermined relationship cannot be determined from the set of points, a new set of points that is different from the set of points is preferably provided, in particular after moving the mobile device. The above-described actions can then be performed again.

[0026] The same applies if no group of points which satisfies the predefined pattern can be determined from the set of points, provided that this criterion is used.

[0027] Preferably, the 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 motion control parameters are then determined for the mobile device in order to move the mobile device to the predetermined object. For example, a so-called docking maneuver can then be performed for docking the mobile device to the docking station.

[0028] In particular, the determination of the position and / or orientation of the mobile device relative to the predetermined object is also carried out based on at least one characteristic of the predetermined object and / or the environment, which has an influence on the point. The at least one characteristic comprises, for example, the reflectivity of the surface of the predetermined object (wherein the reflectivity can be considered here, in particular, independently of the mentioned mode) and / or the slope of the ground in front of the predetermined object. This makes it even easier to approach the predetermined object or docking to the docking station.

[0029] Preferably, a potential, for example estimated, position of the predetermined object is first provided. Based on the potential position of the predetermined object, the position and in particular navigation information as explained above are then determined in order to move the mobile device to the predetermined object. However, if the predetermined object is now not reachable or has not been reached using the navigation information, in particular another potential position of the predetermined object can be provided. The method can then be carried out again.

[0030] The system for data processing according to the invention comprises means for carrying out the method according to the invention or its method steps. The system can be, for example, a computer or a server in a so-called cloud or cloud environment. From there - in the case of application to a mobile device - the position of the predetermined object can then be transmitted to the mobile device (for example via a wireless data connection). Likewise, information about the environment (for example a collection of points) can be transmitted to the system, for example, from the mobile device. However, it is also conceivable that such a system for data processing is a computer or a control device in such a mobile device.

[0031] The invention also relates to a mobile device which is 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 the method according to the invention, and in particular to use the position for navigation.

[0032] Preferably the mobile device has a distance measuring sensor or a lidar sensor for detecting a collection of points in the environment, further preferably a control or regulation unit and a drive unit for moving the mobile device.A system for data processing may also be included by the device as mentioned.

[0033] The mobile device is preferably constructed as a vehicle that moves at least partially automatically, in particular as a passenger vehicle or a freight vehicle and / or as a robot, in particular as a household robot, for example a vacuum and / or wiping robot, a floor or road cleaning device or a lawn mowing robot, and / or as a drone.

[0034] The invention also relates to an object, in particular a docking station, having or for use with a system according to the invention for data processing or a mobile device according to the invention. In this case, the object has an outer contour, from which the relationship of a plurality of points in a set of points to one another can be determined. The object can, for example, be the aforementioned flat plate with a certain width. It is also expedient if the outer contour or the plate is at the height of a range-finding or lidar sensor of the mobile device.

[0035] Preferably, the object also has a change in the reflectivity of the surface in the region of the contour, ie, for example, a correspondingly predetermined pattern. For example, alternating different colors or alternating glossy and matte regions are conceivable.

[0036] It is also advantageous to implement the method according to the invention in the form of a computer program or computer program product with a program code for executing all method steps, because this causes particularly low costs, especially if the execution control device is still used for other tasks and therefore originally exists. Finally, a machine-readable storage medium is provided, with a computer program as described above stored thereon. Suitable storage media or data carriers for providing computer programs are especially magnetic, optical and electrical memories, such as hard disks, flash memories, EEPROMs, DVDs, etc. It is also possible to download programs via computer networks (the Internet, intranets, etc.). Such downloading can be done wired or cabled or wirelessly (e.g., via WLAN networks, 3G, 4G, 5G or 6G connections, etc.).

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

[0038] The invention is schematically illustrated in the drawings on the basis of exemplary embodiments and is described below with reference to the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 In a preferred embodiment, a mobile device and predetermined objects in an environment are schematically shown for explaining the present invention.

[0040] Figure 2a , 2b and 2c schematically show in other views Figure 1 Mobile devices and scheduled objects in.

[0041] Figure 3 In a preferred embodiment, the method according to the invention is schematically illustrated.

[0042] Figure 4 In a further preferred embodiment, the method according to the invention is schematically illustrated.

[0043] Figure 5a , 5b , 5c and 5d schematically show diagrams in a preferred embodiment for explaining the present invention.

[0044] Figure 6a , 6b 6c schematically show diagrams in a preferred embodiment for explaining the invention. DETAILED DESCRIPTION

[0045] exist Figure 1 Schematically showing a mobile device 100 and a predetermined object 130 in an environment 120 in a preferred embodiment for explaining the present invention. The mobile device 100 is exemplarily a vacuum cleaner robot, which has a control or regulating unit 102 and a drive unit 104 (with wheels) for moving the vacuum cleaner robot 100 in the environment 120, such as an apartment or a room.

[0046] Furthermore, the vacuum cleaner robot 100 has, by way of example, a sensor 106 which is designed as a 2D lidar sensor and has a detection field (indicated in dashed lines). For better illustration, the detection field is selected to be relatively small here; in practice, however, the field of view can also be up to 360° (but for example at least 180° or at least 270°). With the aid of the 2D lidar sensor 106, the distance between the mobile device 100 (or the sensor 106) and an object in the environment can be detected or determined.

[0047] In addition, the vacuum cleaner robot 100 has a system 108 for data processing, such as a control device, by means of which data can be exchanged with a superordinate system 110 for data processing, for example via the indicated radio connection. In the system 110 (for example a server, which can also represent a so-called cloud), for example, navigation information can be determined, which can then be transmitted to the system 108 in the vacuum cleaner robot 100, according to which the vacuum cleaner robot should then be operated. However, it can also be provided that the navigation information is determined in the system 108 itself or is obtained there in another way. However, instead of navigation information, the system 108 can also, for example, obtain control information, which has been determined based on the navigation information, and the control or regulating unit 102 can move the vacuum cleaner robot 100 via the drive unit 104 based on this control information.

[0048] Furthermore, a docking station 130 is shown as an example of a predetermined object in the environment 120. The docking station 130 exemplarily has a contact 132 (e.g., an electrical contact) for charging an energy storage device of the vacuum cleaner robot 100, and exemplarily has a plate with a flat surface 134 on one side (surface). The flat surface 132 is an example of an outer geometrical contour of an object or the docking station 130.

[0049] Other different views of the vacuum cleaner robot 100 and in particular the docking station 130 are shown in Figure 2a and 2b In Figure 1 A top view can be seen in Figure 2a A side view is shown, in which in particular it can be seen that the plate with the flat surface 134 is located at a certain height above the foundation (ground) 122, on which the vacuum cleaner robot 100 moves on the one hand and the docking station is located on the other hand. The flat surface 134 is located at the height of the 2D lidar sensor 106, whose height above the foundation 122 is indicated by HS. This ensures that the 2D lidar sensor can detect the flat surface 134. In the case of other sensors or, for example, 3D lidar sensors, for example, this need not be taken into account or not too much.

[0050] exist Figure 2b 1 shows the docking station 130 and in particular the flat surface 134 in a front view, as can be seen from the perspective of the vacuum cleaner robot 100 or the 2D lidar sensor. Two specific dimensions of the flat surface 134 are now also shown here, namely its width B and its height H. The height H is used, for example, to allow a certain amount of leeway for detection with a 2D lidar sensor or for positioning the 2D lidar sensor at height (e.g. even in the case of uneven foundations), while the width B is used to identify the flat surface 134 in the lidar scan, the so-called point cloud, as will be explained below.

[0051] Furthermore, the flat surface 134 or any other surface or contour yet to be detected can be white, in particular matte white, ie, for example, painted white or covered with a white material, in order to reduce or prevent possible reflections.

[0052] exist Figure 2c FIG. 1 shows a docking station 130 ′, which may correspond more generally to a docking station 130 ′ according to Figure 2a , 2b In particular, a docking station 130' is also shown in the same view.

[0053] with Figure 2b Different in Figure 2c In the example, the flat surface 134' is understood by means of a pattern, which has a variation in the reflectivity of the surface. For this purpose, four regions 134a, 134b, 134c, 134d are provided, each of which has a length L (viewed along the width B). The flat surface 134' is thus subdivided into four regions 134a, 134b, 134c, 134d. These regions now alternately have different reflectivities, so that in the case of a laser radar beam or the like reflected therein, a pattern with alternating intensity values ​​above an upper threshold and below a lower threshold occurs.

[0054] For example, regions 134a and 134c may be bright and / or shiny, while regions 134b and 134d may be dark and / or matte. 2D LiDAR perceives these surfaces as having four clearly distinguishable regions or zones, corresponding to Figure 2c Each region will include points with similar reflectivity values ​​in the lidar scan.

[0055] It should be mentioned that this is only an example of a pattern. Likewise, for example, three or four or more different reflectivities can be used, which can be combined arbitrarily. However, it should be noted here that the different reflectivities produce sufficiently different intensity values ​​in the points to be able to distinguish them. Furthermore, the lengths of the areas do not have to be the same; the areas can also be different.

[0056] exist Figure 3 In a preferred embodiment, the method according to the invention is schematically shown as a flow chart or a flowchart. In particular, actions for docking should be included here. This should be explained by way of example with reference to a robot vacuum cleaner as a mobile device and a docking station as a predetermined object, as also described in Figure 1 As shown in a to 2c.

[0057] After the start 300, in step 302, firstly a (initial) potential position 304 of the docking station is provided (if necessary also with an orientation). There are various possibilities how the potential positions or poses of the docking station can be provided to the vacuum cleaner robot. This can be, for example, the initial position from which the vacuum cleaner robot starts, i.e. a position or pose specified by the user (e.g. as a response to a report of the robot when the robot could not recognize the docking station at its previous position); likewise, a list of possible positions or poses collected during the runtime of the robot (e.g. by executing an algorithm for identifying the docking station, which is particularly useful when the robot is driving near walls) is conceivable. Another possibility is that these new positions or poses of the docking station are created by other processes, which can be started when necessary, for example by exploring the drivable area when searching for a signature of the docking station.

[0058] In step 306, the robot vacuum cleaner moves to or near the docking station; this is done based on the potential position 304. If the vacuum cleaner robot is then located near the docking station, i.e. at or near the potential position, navigation information 308 is determined in step 310 in order to move the vacuum cleaner robot to the docking station. On the one hand, this is done based on the potential position 304, but on the other hand, it is also done by determining the position of the docking station based on a 2D lidar scan (a collection of points). Reference should be made below to Figure 4 This is explained in more detail. For example, these navigation information can also include instructions for how exactly the vacuum cleaner robot should navigate (e.g. when and how far the vacuum cleaner robot should travel, when the vacuum cleaner robot should turn, etc.). In particular, motion control parameters for controlling the drive unit can also be determined. In step 310, the docking maneuver is thus performed, i.e. the vacuum cleaner robot travels to the docking station or at least attempts this according to the navigation information 308. The detection of the docking station, i.e. the determination of its position, is especially performed continuously or repeatedly during the docking process (regulation is based on this input).

[0059] In step 312, it is then checked whether the docking maneuver was successful. If so (Y (yes)), that is, if the vacuum cleaner robot has been successfully docked at the docking station and, for example, electrical contact has been established for charging the battery, the method ends in step 314. This may be the case, for example, if the potential position is already very precisely at the actual position.

[0060] If, however, the docking maneuver was not successful (N (No)), i.e., if the docking station was not reached using the navigation information, then in step 316, it is checked whether the docking station has been identified at all. If the docking station has been identified, i.e., if the position of the docking station (or generally a docking station) has been determined (Y), then 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, the process is changed again to step 306 in order to approach the docking station again. For example, at the same potential position of the docking station (which itself has indeed been identified), the docking maneuver is attempted again, for example, by driving back and driving towards the docking station again, for example, with a slightly changed steering angle, etc.

[0061] However, if no docking station is identified in step 316 (N), a new potential location of the docking station may be searched or requested in step 318. If a new or another potential location of the docking station (as mentioned, for example, for step 302) has been found or provided in step 320 (Y), then a transition may be made to step 306 again. The entire process may be repeated until the process is successful or the position or pose is no longer redundant (N); the process then ends with step 322.

[0062] exist Figure 4 In another preferred embodiment, the method according to the invention is schematically shown as a flow chart or a flowchart. This should be explained again based on a vacuum cleaner robot as a mobile device and a docking station as a predetermined object, as also described in Figure 1 As shown in a to 2c.

[0063] In particular, this should now include determining the position of the docking station based on a set of points, as described above with reference to Figure 3 As mentioned in step 310 for determining navigation information and in step 316 if the docking maneuver using the potential position is unsuccessful.

[0064] For this purpose, a set 500 of points in the environment is first provided in step 400, for example by means of a 2D lidar scan. Figure 5a In this example, such a set 500 of points is shown as a 2D lidar scan, as for example in Figure 1 Similarly obtained from a 2D lidar sensor in an environment with a docking station in front of a wall.

[0065] Then, in step 410, the set 500 is analyzed, that is, analyzed with respect to a predetermined relationship 412 between a plurality of points in the set of points. The predetermined relationship is determined, for example, by the flat surface 134 of the docking station and requires that the points lie on a straight line of a certain length, which corresponds to the width B of the flat surface 134.

[0066] To this end, in step 414, groups of points may be determined, for example, having similar relationships between the points; this may be referred to as a clustering process or as clustering. Figure 5b In FIG. 5 , the set of points 500 is shown again, but after the clustering process, where a plurality of groups 510, 512, 514, 516, 518 of points have been determined. Possible algorithms by means of which these groups (or clusters) may be determined are, for example, as follows:

[0067] For example, a cluster criterion such as a certain distance can be pre-specified. For each point, it is then checked step by step whether its distance to the previous point corresponds at most to the certain distance. If so, the point belongs to the same cluster or the same group. If not, a new cluster or a new group is formed.

[0068] For example, according to Figure 5b It can be seen that, starting from the lower left, the points were first very close to each other, and then the next point was offset forward by a larger distance. There, a new group, i.e. group 512, begins.

[0069] These groups can then be analyzed separately in step 416, that is, with respect to the predetermined relationship 412 between a plurality of points in the set of points. Possible algorithms by means of which groups (or clusters) can be analyzed as follows, that is, whether the groups or their points satisfy the predetermined relationship, are as follows, for example.

[0070] For example, a relation criterion such as a certain length can be predefined. Then, for each of two consecutive points in a group or cluster, the distance in the x and y direction is determined (this is suitable, for example, for a 2D analysis in a Cartesian coordinate system; this is merely exemplary here). Figure 5c Δx i or Δy i . The standard deviation is then determined for each of these distances, once in the x direction and once in the y direction. If their sum is less than the relationship criterion, it can be assumed that the points lie on a line.

[0071] In this way, in step 420 , a group, here 512 , can be determined which satisfies the predetermined relationship; this group 512 should then be the subset of points, namely those selected groups used for determining the position of the docking station.

[0072] If more than one of the plurality of groups meets the predetermined relationship, the group with the shortest distance to the vacuum cleaner robot or the lidar sensor is determined as a subset in step 422. The distance can be determined, for example, as the average distance of all points in the group from the vacuum cleaner robot or the lidar sensor. Figure 5bIn the case of , for example, group 510 or 516 can also satisfy the predefined relationship. Here, it also depends on how exactly the predefined relationship is satisfied. However, instead of the minimum distance, another preference criterion can also be used, based on which the multiple groups are sorted and / or one of the groups is determined as a subset. For example, a suitable algorithm can be used, which determines the groups. An algorithm can also be used to determine the minimum distance.

[0073] Alternatively, however, for example, instead of step 422, if more than one of the plurality of groups satisfies the predetermined relationship, then in step 424, these plurality of groups of points that satisfy the predetermined relationship may be analyzed with respect to a predetermined pattern of the points of the respective groups. In this case, the predetermined pattern includes a change in the intensity values ​​of the points, wherein the change in the intensity values ​​is caused in particular by the surface, for example, as in Figure 2c The change in reflectivity of the surface 134' shown in FIG.

[0074] exist Figure 5d In this example, the Figure 5b 512 in the example. Here, the group 512 includes 16 points, of which four consecutive points each form a region or segment, here each having four points 512a, 512b, 512c, 512d. The points in each of these segments have the same or at least approximately the same intensity value within the segment, but the intensity values ​​are different between the segments. Therefore, there are four different intensity values.

[0075] Each segment has a length L, which corresponds, for example, to Figure 2c The length L of the four regions of the flat plane 134'. Figure 2c The four regions of the flat surface 134' have different reflectivities, thus four different reflectivities in total, which can correspond to Figure 5c However, as mentioned above, Figure 2c As mentioned, if there were only two different reflectivities, the result in the case of 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 had the same intensity value.

[0076] The pattern in the group is derived from the pattern on the docking station or, in general, on the object. In other words, each group of points that satisfies a predetermined relationship with respect to the contour can be analyzed with respect to the pattern assigned by the docking station or the object. If the predetermined pattern has four segments of equal length, the group of points can be subdivided into four equal numbers of points, or even corresponding lengths, if, for example, the points are present in an unevenly distributed manner. In practice, it may happen that the points cannot be divided up exactly accordingly; however, an approximately exact division is sufficient, especially in practice, not only 16, but a significantly higher number of points will be present for each group.

[0077] In this case, in particular, the individual intensity values ​​of the points can be compared with each other, i.e. relative values ​​are considered instead of absolute values. In addition, an average intensity value (eg the arithmetic mean of the individual intensity values ​​of the segment) can be determined for each segment and then compared across segments.

[0078] If then one of the plurality of groups satisfies the pattern, the group may be determined to be a subset.

[0079] Then, based on the subset of points, the location of the docking station is determined 432 in step 430. Then, in step 310, reference is made to Figure 3 Navigation information 308 is continuously provided using location 432 as the location of the docking station, or as referenced Figure 3 From step 320 , it is possible to continue again to step 306 .

[0080] As mentioned, the docking station can also be defined, for example, by an arc of a circle with a certain radius and / or a certain length rather than by a straight line. Figure 6a A group 612 of points is shown, which consists of a point having a radius r est The arc limit. Figure 6b A group 612' of points is shown, which consists of points with different radii r' est The arc limit. Figure 6c The positions x1 to x are shown in n A group of points 612″ is defined by an arc having a length L.

[0081] In such a case, the points in the cluster (group) can be fitted to a circle, for example using a closed least squares method (for example according to https: / / lucidar.me / en / mathematics / least-squares-fitting-of-circle / , or https: / / www.emis.de / journals / BBMS / Bulletin / sup962 / gander.pdf). The radius of the circle and the center x are thus determined. cThe coordinates and the radius and / or the calculated arc length L est (For example, L est =θ*r est ) is compared with the expected radius of the docking station or its arc length. If the deviation (one or more) of the radius and / or length between the measured and expected values, respectively, is below a certain threshold, the cluster is accepted as a hit.

[0082] In this case, too, a pattern with a change in the intensity values ​​can be predefined and the group of points can be analyzed accordingly as follows.

[0083] It is understood that such a predefined pattern can also be used to distinguish between two or more different objects, by predefining a different pattern for each of the desired objects; it should be noted that the different patterns in the intensity values ​​of the points are clearly distinguishable from each other. For example, it is possible to distinguish between different docking stations, such as a docking station for charging the robot and a docking station for emptying the dust container, etc.

Claims

1. A method for determining the 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, in particular, the predetermined object, the method comprising: providing (400) a set of points (500) in an environment, wherein the points in particular respectively characterize the distance between the mobile device (100) and an object (130) in the environment, analyzing (410) the set of points with respect to a predetermined relationship (412) between a plurality of points in the set of points, wherein the predetermined relationship (412) is determined by an outer contour (134) of a predetermined object (130), If one of the group or groups (512) of points from the set satisfies a predetermined relationship, then the group of points is determined (420) as a subset of points, A location of a predetermined object (130) is determined (430) based on the subset of points, and navigation information (308) for the mobile device (100) is determined based on the location (432) of the predetermined object.

2. The method of claim 1, wherein analyzing (410) the set (500) of points comprises: determining (414) a plurality of groups (510-518) of points from the set of points, and Each of the plurality of groups is analyzed (416) with respect to a predetermined relationship.

3. The method according to claim 1 or 2, further comprising analyzing one or at least one, preferably each, of a plurality of groups of points with respect to a predetermined pattern between points of the respective groups, the points satisfying a predetermined relationship, wherein the predetermined pattern comprises a change in intensity values ​​of the points, wherein the change in intensity values ​​is determined in particular by a change in reflectivity of a surface of a predetermined object (130) in the region of the contour, In this case, one of the analyzed groups or such a group is determined as a subset corresponding to a predetermined pattern. 4 . The method according to claim 3 , wherein the predetermined pattern comprises at least two, preferably at least three regions, which alternately have intensity values ​​above an upper threshold value and below a lower threshold value.

5. A method according to any of the preceding claims, wherein the predetermined relationship includes that the multiple points are located in a two-dimensional or three-dimensional area predetermined by the outer contour (134) of the predetermined object (130), in particular, on a line of a predetermined length (B).

6. A method according to any of the preceding claims, wherein if a group of points cannot be determined from a set of points, the points satisfying a predetermined relationship or referencing claim 3 satisfying a predetermined pattern, a new set of points is provided, which is different from the set of points, in particular after the mobile device (100) has moved.

7. The method according to any one of the preceding claims, further comprising: determining a position and / or orientation of the mobile device (100) relative to the predetermined object (130) based on the position of the predetermined object (130), and Navigation information (308) and in particular motion control parameters are determined for a mobile device (100) in order to move the mobile device (100) to a predetermined object (130).

8. A 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 also carried out based on at least one characteristic of the predetermined object (130) and / or the environment (120), which has an influence on the point, wherein at least one characteristic in particular includes the reflectivity of the surface of the predetermined object (130) and / or the slope of the foundation (122) in front of the predetermined object (120).

9. The method according to any one of the preceding claims, further comprising: providing (302) a potential location (304) of a predetermined object, The determination (430) of the position of the predetermined object (130) and in particular the navigation information (308) for the mobile device (100) is also carried out 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 is not reached using the navigation information (308), providing (320) another potential location of the predetermined object.

11. A system (108, 110) for data processing, comprising means for performing the method according to any 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 determine a position of a predetermined object (130) in an environment which has been determined from a set of points according to a method according to any one of claims 1 to 10, and in particular to use the position for navigation, Preferably having a distance measuring sensor or a lidar sensor (106) for detecting a set of points in the environment, further preferably having a control or regulating unit (102) and a drive unit (104) for moving the mobile device (100), and further preferably having a system (108) according to claim 10, The mobile device (100) is in particular configured as a robot, in particular as a household robot, such as a vacuum and / or wiping robot, a floor or road cleaning device or a lawn mowing robot, as a vehicle that moves at least partially automatically, in particular as a passenger vehicle or a freight vehicle and / or as a drone.

13. An object (130), in particular a docking station, having 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), based on which the relationship between multiple points in a set of points can be determined, and wherein the object (130) preferably also has a change in the reflectivity of the surface in the area of ​​the contour.

14. A computer program comprising instructions which, when executed by a computer, cause the computer to perform the method steps of the method according to any one of claims 1 to 10 when the method is performed on the computer.

15. A computer-readable storage medium having stored thereon the computer program according to claim 14.

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