Self-propelled cleaning device and method for operating self-propelled cleaning device

Abstract

The invention relates to a self-propelled cleaning device and to a method for operating a self-propelled cleaning device, in which the cleaning device autonomously navigates in the surroundings and the position thereof in the surroundings is determined by means of a navigation means, the cleaning device executing an identification method for identifying and locating an abnormal situation. In this case, the positioning of an abnormal situation is an imminent or deprived ability to determine a position along the at least one axis and / or a situation in which the cleaning device is located in or imminent into the corridor. In the identification method, a straight main line is identified in measurement data of the navigation mechanism and the measurement data is evaluated whether the measurement data contains a structure extending transversely to the main line, the extent of the structure in the measurement data orthogonal to the main line being determined and compared with a predetermined limit value, in particular. And when the measurement data does not contain the structure of which the extension size is greater than the limit value, the condition is evaluated as a positioning abnormal condition.

Description

Technical Field

[0001] The invention relates to a method for operating a self-propelled cleaning device and a self-propelled cleaning device. Background Art

[0002] Self-propelled or self-propelled cleaning appliances are known from the prior art, in particular as (partially) autonomous vacuum cleaner robots, mopping robots or vacuum-mopping robots for cleaning surfaces such as floors.

[0003] Such cleaning devices are usually equipped with a navigation mechanism so as to be able to navigate in known or unknown surrounding environments.

[0004] To navigate in the surroundings, the self-propelled cleaning device needs to determine its position in the surroundings with the aid of a navigation device.

[0005] As long as the surroundings are unknown, ie, for example, there is no detailed map information about the surroundings, a map of the surroundings must first be created with the aid of the cleaning device. However, for map creation, the precise / real position of the cleaning device is required.

[0006] Within the scope of so-called Simultaneous Localization and Mapping (SLAM), the problem to be solved is that the cleaning device autonomously surveys a new / unknown surrounding environment and simultaneously creates a map of this surrounding environment, which is then used for navigation of the cleaning device in the surrounding environment.

[0007] However, in particular due to the limited range of the sensors used, situations may arise where the position can no longer be determined using the navigation system.

[0008] For example, if the cleaning device is located in a corridor, i.e., in a long space defined by two parallel walls, and no other objects besides the parallel walls are located within the measurement or detection range of the navigation device, then the position cannot be determined. In this case, although the distance of the cleaning device from the wall can be determined, the position in the longitudinal direction of the corridor parallel to the wall cannot be determined because the measurement data obtained at different positions in the longitudinal direction of the corridor are identical.

[0009] Within the scope of the present invention, a situation in which the position along at least one axis is about to be lost or has lost the ability to determine the position along at least one axis and / or the cleaning device is located in a corridor or is about to enter a corridor is referred to as a positioning anomaly situation.

[0010] As known from the prior art, the covariance of the particle filter distribution of the measurement data is used to identify the positioning anomaly when the ability to determine the position is about to be lost or has been lost. However, this method is relatively time-consuming, and thus the positioning anomaly is not identified until a certain time delay has passed. Therefore, within the time required to identify the positioning anomaly, the cleaning equipment has continued to move to another position, particularly an unknown or undetermined position, so that the position finally determined is inconsistent with the position of the cleaning equipment when the positioning anomaly is identified. Therefore, even if another method for determining the position is changed, the position can no longer be determined or can only be determined very imprecisely. Therefore, the time delay may cause the loss of the determined position when identifying the positioning anomaly. Summary of the Invention

[0011] The object on which the present invention is based is to propose a method for operating a self-propelled cleaning device and an improved self-propelled cleaning device which are improved compared to the prior art, wherein a more accurate or less error-prone position determination of the cleaning device in an unknown or known surrounding environment is achieved or supported, and / or the probability of losing the determined position is reduced and / or a faster recognition of positioning anomalies is achieved.

[0012] The object on which the invention is based is achieved by a method according to claim 1 or a cleaning device according to claim 15. Advantageous developments are the subject matter of the dependent claims.

[0013] The present invention relates to a preferably computer-implemented method for operating a cleaning appliance. Preferably, the proposed method, in particular individual or all method steps of the proposed method, are automatically or autonomously performed by the cleaning appliance, in particular by corresponding means for data processing and control of the cleaning appliance, such as a data processing unit and / or a control unit.

[0014] A cleaning device within the meaning of the present invention is preferably a (partially) autonomous or self-propelled vacuum cleaner robot, mopping robot, or vacuum-mopping robot. Within the meaning of the present invention, a cleaning device is particularly designed to clean the cleaning surface autonomously or (partially) autonomously during the cleaning process. However, within the meaning of the present invention, a cleaning device may also be other devices for cleaning, processing, and / or caring for surfaces, in particular floors. For example, in principle, a polishing device or polishing robot, a window cleaning device or window cleaning robot, or a lawn mowing device or lawn mowing robot may also be understood as a cleaning device within the meaning of the present invention.

[0015] As already explained at the outset, the cleaning device within the meaning of the present invention is configured to autonomously navigate in the surrounding environment. For this purpose, the cleaning device within the meaning of the present invention preferably has a navigation mechanism, a data processing mechanism, and a control mechanism.

[0016] In the method according to the invention for operating a self-propelled cleaning device, the cleaning device autonomously navigates in a known or unknown surrounding environment, in particular by means of a navigation device, a data processing device, and a control device, wherein the position of the cleaning device in the surrounding environment is automatically determined by means of the navigation device.

[0017] The navigation system measures measurement data, which are present as measurement points in a coordinate system. The measurement points are each defined by two coordinates, in particular Cartesian coordinates.

[0018] The cleaning device performs a recognition method for identifying and locating abnormal phenomena.

[0019] A positioning anomaly is a situation in which the ability to determine the position along at least one axis is about to be lost or has been lost, in particular with the aid of a navigation mechanism, particularly preferably with the aid of a lidar sensor, and / or the cleaning device is located in a corridor or is about to enter a corridor.

[0020] The proposed method is characterized in that, in the identification method, a straight main line is identified in the measurement data and the measurement data is analyzed to determine whether it contains structures extending transversely to, i.e., obliquely or perpendicularly to, the main line. The extent of the structures in the measurement data perpendicular to the main line is determined and compared to, in particular, a predetermined limit value. A positioning anomaly is evaluated if the measurement data contains no structures with an extent greater than the limit value, or if the extent of all structures in the measurement data is less than or equal to the limit value. This method requires minimal computational effort and thus enables or achieves rapid identification of positioning anomalies. Furthermore, the sensitivity of the identification method can be adjusted by selecting the limit value, thereby enabling positioning anomalies to be detected, in particular, before a specific position is lost.

[0021] Preferably, the position of the main line relative to the coordinate system is determined, in particular the angle and / or slope of the main line. This allows a simple and rapid analysis of the measurement data to determine whether they contain structures extending transversely to the main line.

[0022] Preferably, a coordinate transformation, in particular a rotation, of the measured data is performed, in particular such that the main line after the coordinate transformation is parallel to the axes of the coordinate system. A coordinate transformation or rotation is a simple and fast mathematical operation that makes it easier to analyze whether the measured data contain structures extending transversely to the main line.

[0023] Preferably, the projection of the measured data onto an axis orthogonal to the main line is determined, in particular after a coordinate transformation or rotation. In particular, if the projection of the measured data after rotation is such that the main line is parallel to an axis of the coordinate system, the projection can be determined or calculated simply and quickly, and a rapid analysis of the measured data is possible as to whether it contains structures extending transversely to the main line.

[0024] The coordinate system or an axis of the coordinate system orthogonal to the main line is preferably divided into preferably equally sized segments. Furthermore, a segment is preferably marked as occupied if at least one measuring point or at least one projection of a measuring point lies within the segment. A segment is preferably marked as unoccupied if no measuring point or projection lies within the segment. This makes it possible to easily and quickly identify structures in the measurement data or to analyze them with respect to their extent.

[0025] Preferably, the number of adjacent segments marked as occupied is determined, in particular counted, thereby enabling an efficient or rapid analysis, in particular determination, of the extent of the structure perpendicularly or transversely to the main line.

[0026] Furthermore, preferably, if the number of measurement points in a segment is less than or equal to a predetermined minimum value and no measurement points are located in adjacent segments or in two adjacent segments, the segment is not marked as occupied and / or is not treated as a marked occupied segment when determining the number of adjacent marked occupied segments. This improves the accuracy and / or reliability of the identification method. In particular, erroneous analysis due to noise in the measurement data can be avoided.

[0027] Measuring points located in the same segment and / or adjacent segments preferably jointly form a structure. This allows for simple and rapid identification and / or analysis of the structure.

[0028] The number of adjacent segments marked as occupied preferably represents the extent of the structure perpendicular to the main line. Thus, the extent of the structure can be determined quickly and easily.

[0029] The limit value is preferably formed by the maximum number of adjacent segments marked as occupied. This allows for a quick and easy analysis or evaluation of the structure or its extent.

[0030] The main line is preferably determined using a line detection algorithm, in particular using a Hough transform or a RANSAC algorithm. In this way, the main line can be determined easily and quickly.

[0031] The limit value is preferably defined such that, when the position can still be determined using the navigation system, but the ability to determine the position using the navigation system is about to be lost, this is evaluated as a positioning anomaly. In other words, a positioning anomaly is detected before the determined position is lost. This effectively prevents the loss of position, or allows timely measures to be taken to prevent the loss of position.

[0032] Preferably, the navigation device has a laser distance sensor, in particular a lidar sensor, or is formed from the same. This facilitates precise positioning.

[0033] To determine the position of the cleaning device, particle filter positioning is preferably used. This facilitates precise positioning.

[0034] Preferably, when a positioning anomaly is detected using the recognition method, the cleaning device automatically switches to another method for determining the position, in particular to odometry and / or dead reckoning, thereby preventing the loss of the determined position.

[0035] Furthermore, it is preferred that, when no positioning anomalies are detected using the detection method, the cleaning device automatically switches to the method for determining the position used before the positioning anomaly was detected, in particular to particle filter positioning. This contributes to the most accurate positioning possible.

[0036] According to another aspect, which can also be implemented independently, the present invention relates to a self-propelled cleaning device having a navigation device, a data processing device, and a control device for autonomously navigating in an environment, wherein the cleaning device is designed to carry out the method described herein.

[0037] According to another aspect, which can also be realized independently, the invention relates to a self-propelled cleaning device having a device adapted such that the device carries out the method described herein.

[0038] According to another aspect, which can also be implemented independently, the present invention relates to a computer program having instructions which, when executed, cause a cleaning device described herein to carry out a method described herein.

[0039] According to another aspect which can also be implemented independently, the present invention relates to a computer-readable medium on which the aforementioned computer program is stored.

[0040] In particular, the corresponding advantages of the method are achieved by the cleaning device, the computer program and the computer-readable medium.

[0041] A corridor within the meaning of the present disclosure is, in particular, a lengthy or elongated space that is bounded by (exactly) two at least substantially parallel objects, in particular walls, or that extends in one direction to such an extent that only (exactly) two parallel objects or walls are located within the detection range of the navigation device of the cleaning appliance. A corridor is particularly present if, apart from the two parallel objects or walls, no other objects are present within the detection range of the navigation device.

[0042] A positioning anomaly within the meaning of the present disclosure is in particular a situation in which the position cannot be determined at least with the aid of a positioning method used in normal operation of the cleaning device, or there is a risk that the position can no longer be determined with the aid of a positioning method used in normal operation of the cleaning device - a positioning anomaly exists in particular when the cleaning device is located in a corridor.

[0043] A main line within the meaning of the present disclosure is, in particular, a large amount of measurement data that is at least substantially arranged along a particularly straight line. A main line is formed, in particular, by a large amount of measurement data that can be mathematically approximated by a line or straight line, or that can be determined as a line or straight line using an algorithm for identifying lines or straight lines. If the measurement data contains multiple such lines, the main line is preferably the first line determined using the algorithm and / or the longest of these lines.

[0044] A structure within the meaning of the present disclosure is, in particular, a large number of measurement data that are close to one another or lie in the same and / or adjacent sections of a coordinate system. Preferably, the distance between the measurement data forming a structure and the measurement data of the same structure is smaller than the distance between the measurement data and other measurement data. Preferably, in the present invention, the structure is not determined or identified explicitly, but only indirectly based on the position of the measurement data along an axis. The measurement data forming a structure may, however, correspond to the same real or measured object.

[0045] The aforementioned aspects, features and method steps of the invention as well as the aspects, features and method steps of the invention arising from the claims and the following description can in principle be realized independently of one another, but can also be realized in any desired combination or sequence. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Further aspects, advantages, features and characteristics of the present invention are apparent from the claims and the following description of preferred embodiments with reference to the accompanying drawings, in which:

[0047] Figure 1 shows a schematic perspective view of a cleaning device according to the proposal;

[0048] Figure 2shows a schematic top view of a cleaning device in the case where the position of the cleaning device can be determined with the aid of a navigation device;

[0049] Figure 3 A schematic top view of a cleaning device in a corridor or in an abnormal positioning situation is shown;

[0050] Figure 4 A schematic diagram showing measurement data of a navigation mechanism of a cleaning device in a coordinate system;

[0051] Figure 5 Shown Figure 4 Schematic diagram of the measurement data after rotation;

[0052] Figure 6 Shown Figure 5 Schematic diagram of the measurement data in which the coordinate system is divided into segments;

[0053] Figure 7 A schematic diagram showing further exemplary measurement data of a navigation mechanism in a coordinate system divided into sectors; and

[0054] Figure 8 The diagram shows further exemplary measurement data of a navigation device, wherein the cleaning device is located in a corridor or is in a positioning anomaly. DETAILED DESCRIPTION

[0055] In the partially non-scale, merely schematic drawings, the same reference numerals are used for identical, similar or similar parts and components, wherein corresponding or comparable properties or advantages are achieved even without a repeated description.

[0056] Figure 1 A self-propelled (mobile) cleaning device 1 according to the proposal is shown.

[0057] The cleaning device 1 is preferably designed as a vacuum robot, a mopping robot or a combined vacuuming-mopping robot, or is designed to automatically / autonomously travel over the cleaning surface during one or more cleaning processes in order to clean, in particular vacuum and / or mop, the cleaning surface.

[0058] The cleaning device 1 is designed in particular to suck or wipe the suction material or air and / or a liquid cleaning agent together with the suction material from the cleaning surface.

[0059] A cleaning process within the meaning of the present invention is preferably a process in which the cleaning surface is cleaned by means of the cleaning device 1 and / or in which the cleaning device 1 cleans, in particular vacuums and / or wipes, the cleaning surface.

[0060] Preferably, the cleaning surface is formed by the floor. However, other surfaces, such as windows or facades, may also have or form the cleaning surface.

[0061] The cleaning device 1 comprises a housing 2 , a plurality of (in the present case two) electric motor-driven wheels 3 , a navigation device 4 , a data processing device 5 and / or a control device 6 .

[0062] With the aid of the navigation device 4 , the data processing device 5 , the control device 6 and the wheels 3 , the cleaning device 1 can be automatically / autonomously oriented and further moved in the surroundings or on the cleaning surface.

[0063] The control device 6 is preferably designed to control, in particular activate and / or deactivate, the wheels 3 or the electric motor of the cleaning device 1 and / or the blower of the cleaning device 1 and / or to adapt the power, preferably at least partially automatically.

[0064] The cleaning device 1 preferably has an elongated or slit-shaped suction opening 7 on the bottom side or on the side facing the cleaning surface, through which suction material and / or cleaning agent applied to the cleaning surface can be received or sucked in.

[0065] The cleaning device 1 is preferably equipped with a blower (not shown) driven by an electric motor and a collection container (not shown) for the suctioned material.

[0066] In cleaning operation or during the cleaning process, suction material or air and / or cleaning agent together with the suction material can be sucked from the surroundings or from the cleaning surface into the cleaning device 1 , in particular into a container, by means of the blower through the suction opening 7 .

[0067] In the case of a vacuum cleaner robot, the sucked-in material is separated from the air, for example, by means of a filter (not shown), wherein the (cleaned) air can then be released back into the surroundings.

[0068] The cleaning device 1, in particular the navigation device 4, is preferably equipped with at least one sensor in order to detect the surroundings, in particular objects in the surroundings, such as obstacles, and / or in order to determine the (relative) position of the cleaning device 1 in the surroundings, in particular by measuring the distance between the cleaning device 1 and a reference point or object in the surroundings.

[0069] Preferably, the cleaning device 1 , in particular the navigation device 4 , has at least one distance sensor 8 for measuring the distance to objects in the surroundings.

[0070] The distance sensor 8 is preferably designed as a laser distance sensor, in particular a lidar sensor, a PMD sensor or a time-of-flight sensor, or a radar sensor, or as an ultrasonic sensor. Particularly preferably, the distance sensor 8 is designed as a 2D lidar sensor.

[0071] The distance sensor 8 is preferably arranged on the upper side of the cleaning device 1 or on its side facing away from the cleaning surface.

[0072] The distance sensor 8 is preferably configured to scan the surroundings of the cleaning device 1 and / or identify objects in the surroundings of the cleaning device 1, in particular objects laterally or horizontally in front of, behind or beside the cleaning device 1, or to measure the distance between the cleaning device 1 and objects in the surroundings.

[0073] The distance sensor 8 is preferably oriented at least substantially horizontally or parallel to the cleaning surface. The distance sensor 8 is particularly designed to measure distances in all horizontal directions or 360° around the cleaning device 1 or around the vertical axis V starting from the cleaning device 1 .

[0074] The distance sensor 8 very particularly preferably has a laser that rotates or can rotate 360° about the vertical axis V of the distance sensor 8. Preferably, the distance sensor 8 is designed such that the laser beam of the laser rotates 360° about the vertical axis V several times per second, for example five times.

[0075] The navigation device 4, in particular the distance sensor 8, preferably has a detection area B, within which the navigation device 4 or the distance sensor 8 can detect an object or measure the distance to the object. The detection area B can be a two-dimensional area, that is, an area extending only in a plane, or a three-dimensional area. The detection area B is preferably designed to be circular or cylindrical, as in Figure 2 and Figure 3 The detection area B is preferably concentric with the vertical axis V.

[0076] Optionally, the cleaning device 1 , in particular the navigation device 4 , can also have one or more further sensors, in particular distance sensors, in addition to the distance sensor 8 , for measuring distances to objects in the surroundings.

[0077] The cleaning device 1 can in particular have a further distance sensor 9 which is oriented in the direction of travel R or is designed to detect objects located in front of the cleaning device 1 in the direction of travel R or to measure the distance between the cleaning device 1 and an object located in front of the cleaning device 1 in the direction of travel R.

[0078] Preferably, the distance sensor 9 is arranged on the front side of the cleaning device 1, in particular in the middle and / or inside the housing 2, such as in Figure 1 The further distance sensor 9 is preferably designed as a PMD sensor or a time-of-flight sensor.

[0079] Therefore, the detection area B of the navigation device 4 is preferably a combination or superposition of the individual detection areas of the distance sensor of the navigation device 5, in particular the distance sensor 8 and the further distance sensor 9. Figure 2 and Figure 3 Different from the exemplary illustration in FIG, the detection area B can also have a shape other than a circle or a cylinder.

[0080] Furthermore, the cleaning device 1 can have an inertial sensor 10 , which is preferably designed as an inertial measurement unit (IMU for short), an acceleration sensor or a rotational speed sensor.

[0081] Inertial sensor 10 is designed in particular to measure or determine an acceleration, a speed, a force and / or a rotational speed of the movement of cleaning device 1 and / or an orientation and / or a change in direction of travel R of cleaning device 1 .

[0082] Optionally, the cleaning device 1 has an odometer sensor (not shown) in order to determine the position and / or orientation of the cleaning device 1 based on the rotation of the wheels 3 .

[0083] The data processing device 5 is preferably designed to evaluate the measurement data measured or determined by the navigation device 4 or the sensors 8 to 10 and / or transmit them as input values to the control device 6. The wheels 3 are then controlled by the control device 6. In this way, the cleaning device 1 can automatically / autonomously navigate within the surroundings or on the cleaning surface.

[0084] As already explained at the outset, for navigation, it is necessary for the cleaning device 1 to locate or determine its position in the surroundings or on the cleaning surface by means of the navigation device 4 or the sensors 8 to 10 .

[0085] For positioning or determining the position, the distance to a reference point or object, such as a wall, is measured by means of the navigation device 4 , in particular the distance sensor 8 and optionally a further distance sensor 9 , in particular in two mutually orthogonal directions.

[0086] Therefore, measurement data D are measured by means of the navigation device 4, in particular the distance sensor 8, and optionally by means of a further distance sensor 9. The measurement data D of the navigation device 4 are present, in particular, as measurement points in a coordinate system, wherein the measurement data D or measurement points each have (at least) two coordinates, in particular Cartesian coordinates. In other words, each measurement point is preferably defined by two coordinates, in particular an X value and a Y value.

[0087] The cleaning device 1 is preferably designed to carry out the method described herein for operating the cleaning device 1. The cleaning device 1 preferably has devices, in particular a data processing device 5 and / or a control device 6, which are suitable for carrying out the method described herein.

[0088] The cleaning device 1 , in particular the data processing device 5 and / or the control device 6 , preferably comprises a computer program having instructions which, when executed, cause the method described herein to be carried out.

[0089] The cleaning device 1 , in particular the data processing device 5 and / or the control device 6 , preferably has a computer-readable medium on which the aforementioned computer program is stored.

[0090] With the help of Figures 2 to 8 Explain in detail the suggested approach.

[0091] The method serves to operate the cleaning device 1 and is preferably carried out by means of the cleaning device 1 .

[0092] The cleaning device 1 , in particular the data processing device 5 , is preferably designed to carry out the method described herein or individual method steps.

[0093] Preferably, instructions or algorithms for carrying out the proposed method or for carrying out individual method steps of the proposed method are stored electronically in a (data) memory of the cleaning device 1 , in particular in the data processing device 5 .

[0094] The proposed method preferably comprises one or more method steps and / or procedures in order to improve the position determination or positioning of the cleaning device 1 , in particular in a large surrounding area, such as in a hallway or a corridor.

[0095] The method is preferably designed as a multi-stage or multi-step process. In particular, the method comprises a plurality of method steps, wherein the individual method steps can in principle be performed independently of one another and in any order, unless otherwise explained below. In particular, some of the method steps explained below are not mandatory and can also be omitted.

[0096] In the proposed method, the cleaning device 1 navigates autonomously in the surroundings and determines its position in the surroundings with the aid of a navigation device 4, in particular based on measurements performed using a distance sensor 8 and optionally a further distance sensor 9, or based on the navigation device 4 or on measurement data D of the distance sensor 8 and optionally the distance sensor 9.

[0097] Preferably, particle filter positioning is used as a method for determining the position of the cleaning device 1 .

[0098] Preferably, a recognition method for identifying positioning anomalies is performed.

[0099] Identification methods should be used to identify when the position can no longer be determined using the measurement data D of the navigation device 4 or the distance sensors 8 and 9, or when the ability to determine the position using these measurement data D is about to be lost. Identification should be performed in particular when the ability to determine the position using the methods used in normal operation for determining the position, in particular particle filter positioning, is about to be lost or has been lost.

[0100] Therefore, a positioning anomaly is in particular a situation in which the ability to determine the position along at least one axis by means of the measurement data D of the navigation device 4 is about to be lost or lost, and / or the cleaning device 1 is located in the corridor K or is about to enter the corridor K.

[0101] To explain the positioning anomaly, Figure 2 and Figure 3 Two examples of possible situations or the surroundings of the cleaning device 1 are shown.

[0102] exist Figure 2 In the example shown, the cleaning device 1 is surrounded by three walls W1, W2, W3 or the three walls W1, W2, W3 are located in the detection range B of the navigation device 4 or the distance sensor 8. In this case, there is sufficient information or measurement data to determine the position of the cleaning device 1 in its surroundings, especially because the objects, namely the walls W1, W2, W3, are located in the detection range B in three different directions from the cleaning device 1 or the navigation device 4.

[0103] exist Figure 3 , a situation is shown in which the cleaning device 1 is located in a corridor K.

[0104] A corridor is in particular an elongated space which is delimited by two at least substantially parallel walls W1, W2. Figure 2A corridor exists when the walls W1, W2 (in the corridor) are spaced apart from each other or away from the cleaning device 1 to such an extent that they are outside the detection range B of the navigation device 4 or the distance sensor 8. Thus, the cleaning device 1 is particularly located in a corridor K when only parallel walls W1, W2, in particular a maximum of or exactly two walls W1, W2, are located in the detection range B of the navigation device 4 or the distance sensor 8 and / or when no other objects are located in the detection range B except the parallel walls W1, W2.

[0105] When the cleaning device 1 is located in the corridor K, (when the distance from the walls W1, W2 is given or fixed) Figure 3 The measurement data D measured at different positions in the longitudinal direction of the corridor K are at least substantially identical or indistinguishable. As a result, the position of the cleaning device 1, Figure 3 The location along the corridor could not be determined.

[0106] Therefore, Figure 3 There is a positioning anomaly.

[0107] The method or identification method described herein serves in particular to reliably and / or quickly identify positioning anomalies.

[0108] The identification method is preferably carried out continuously and / or at regular intervals while the cleaning device 1 is in operation.

[0109] Especially with the help of Figures 4 to 8 The identification method for identifying positioning anomalies is described in more detail.

[0110] exist Figure 4 Exemplary measurement data D of the navigation device 4 , in particular of the distance sensor 8 , are shown in FIG. Figure 5 and Figure 6 The following diagrams show the Figure 4 The same measurement data D. Figure 7 and Figure 8 Other exemplary measurement data D are shown in FIG.

[0111] In the identification method, a main line H is first identified in the measurement data D. In other words, it is preferably determined or recognized whether and which of the measurement points lie at least substantially on a (particularly straight) line. This is preferably done with the aid of a line detection algorithm, in particular using a Hough transform or a RANSAC algorithm.

[0112] The main line H is in particular a straight line.

[0113] In particular, only one line or precisely one line is identified in the measurement data D as the main line H. Apart from the main line H, preferably no other lines are then identified.

[0114] In other words, the main line H is therefore preferably the first and / or only line identified in the measurement data D. After a line or main line H has been determined in the measurement data D, preferably no further lines are identified in the measurement data D.

[0115] Therefore, the method for identifying the line or main line, in particular the straight line detection algorithm, is preferably terminated or stopped as soon as a line or main line H is determined. This facilitates a fast method flow or helps to quickly identify positioning anomalies.

[0116] Accordingly, the main line H does not necessarily have to be distinguished by special properties from possible other lines in the measurement data D. The term "main line" therefore does not denote a particularly prominent line, but is only used to conceptually distinguish the line identified at the beginning of the identification method from other lines.

[0117] An advantage of the method described herein is that, when the measurement data D has multiple lines or when multiple lines can in principle be identified in the measurement data, it is unimportant for the identification method which line is identified as the main line H. This makes it possible to forgo the identification or any other further checking of other lines of the measurement data D, taking into account their possible presence, so that the identification method can be carried out very quickly.

[0118] If the main line H cannot be determined, it is preferably evaluated as a positioning anomaly.

[0119] Furthermore, it is analyzed whether the measurement data D contain structures S which extend transversely, that is to say in particular obliquely or perpendicularly, to the main line H. For this purpose, in particular the structures S are not directly determined or identified in the measurement data D, but rather only an analysis of the measurement data D is performed which allows the extension of the structures S perpendicular to the main line H to be determined.

[0120] In the sense of the present disclosure, the term "laterally" particularly means "obliquely or perpendicularly", ie "at an angle of 90° or less".

[0121] If the analysis reveals that the measurement data D do not have a structure S extending transversely to the main line H, this is evaluated as a positioning anomaly.

[0122] A “structure S extending transversely to the main line H” is, in particular, a structure that extends sufficiently wide or, in other words, enables, through the structure, a position of the cleaning device 1 parallel to the main line H. In this sense, a structure S that extends transversely to the main line to a small extent but does not enable or enable a position of the cleaning device 1 parallel to the main line H is preferably not a structure S extending transversely to the main line H.

[0123] Particularly preferably, in order to evaluate whether the measurement data D contain structures S extending transversely to the main line H, the extent L of the structures S perpendicular to the main line H is at least indirectly determined and compared with a limit value. The limit value is preferably a fixed or predetermined value, in particular a fixed or predetermined number.

[0124] In particular, a preferred method for evaluating the measurement data D for structures S extending transversely to the main line H or for determining the extent L of the structures S perpendicular to the main line H is explained in detail below.

[0125] Preferably, the position of the main line H, in particular relative to a coordinate system, is determined. For this purpose, in particular the angle of the main line H relative to one or more axes of the coordinate system and / or the slope of the main line H are determined, in particular calculated.

[0126] Preferably, a coordinate transformation of the measurement data D is performed, in particular a rotation of the measurement data D. The coordinate transformation or rotation is very particularly performed based on the previously determined position of the main line H relative to the coordinate system and / or is performed such that the main line H is parallel to the axis of the coordinate system after the coordinate transformation or rotation.

[0127] The result of coordinate transformation or rotation is especially Figure 5 In Figure 5 middle, Figure 4 The measured data D are transformed or rotated such that the main line H is parallel to the axis of the coordinate system, in the illustrated example, to the X axis.

[0128] Preferably, the measurement data D are projected onto an axis extending orthogonally to the main line H, or the projection of the measurement data D onto an axis extending orthogonally to the main line H, in particular an axis of the coordinate system, is at least indirectly determined, in particular calculated. This is preferably, but not necessarily, performed after the coordinate transformation or rotation explained above.

[0129] In accordance with Figure 5 In the example shown in Figure 4If the measured data D are rotated so that the main line H is parallel to the axes of the coordinate system, the projection of the measured data D can be determined particularly simply and quickly. In this case, the projection of the measured data D or the measuring point is directly given by one of the coordinates of the rotated measured data D or the measuring point, in this illustrated example, the Y coordinate of the measuring point. No additional calculation steps are required to determine the projection.

[0130] However, in principle, the measured data D does not necessarily need to be subjected to a coordinate transformation or rotation prior to projection, and the axes onto which the measured data D are projected do not necessarily need to be axes of the coordinate system. Rather, the projection of the measured data D can be determined without a prior coordinate transformation and on any axis, i.e., even on an axis that extends obliquely relative to the axes of the coordinate system. However, the projection of the measured data D onto an axis extending orthogonally to the main line H is always determined.

[0131] The coordinate system or its axis perpendicular to the main line H (ie the Y axis in the example shown) is preferably divided into segments A. This allows in particular a simple and / or computationally inexpensive analysis of whether the measurement data D contain structures S extending transversely to the main line H.

[0132] The sections A are preferably identical or of the same size.

[0133] The division of the segments A takes place in a direction perpendicular to the main line H. In other words, the segments A extend parallel to the main line H and / or the segments A follow one another perpendicularly to the main line H.

[0134] Figure 6 Show Figure 5 (rotated) measurement data D, wherein additionally segments A are shown. The segments A are each separated by a vertical dashed line, even in Figure 6 No reference numeral A is provided for each individual segment. The same applies to Figure 7 ,exist Figure 7 The example shows Figure 4 Different measurement data D.

[0135] Preferably, segment A is marked as occupied and / or unoccupied.

[0136] In particular, segment A is marked as occupied when a measuring point or its projection is located in segment A. Segment A is preferably marked as unoccupied when no measuring point or the projection of a measuring point is located in segment A.

[0137] exist Figures 6 to 8 In the example, the occupied segments are visualized by boxes on the Y-axis.

[0138] The marking of the segments A is preferably performed after determining the projection of the measuring point or based on the projection of the measuring point. However, this is not mandatory. In principle, it is also possible to determine which segments A are occupied or in which segments the measuring point is located directly based on the measuring point without performing the projection of the measuring point.

[0139] It is not mandatory to mark both occupied and unoccupied segments A. In principle, it is sufficient to mark either only occupied segments A or only unoccupied segments A, since in this way the corresponding unmarked segments A are automatically considered to be unoccupied or occupied.

[0140] In the sense of the present invention, a plurality of measuring points preferably form a structure S when the plurality of measuring points or their projections are located in the same and / or adjacent segments A. In other words, in the sense of the present invention, the structure S is preferably formed by measuring points which or their projections are located in the same segment and / or adjacent segments A.

[0141] The main line H thus also forms a structure S, as in particular in Figure 5 / 6. In addition, in the exemplary embodiment shown with Figure 5 and Figure 6 Different measurement data D Figure 7 In FIG, different structures S1, S2, and S3 are exemplarily identified.

[0142] The number of adjacent segments A marked as occupied is preferably determined, in particular counted. Thus, the extent L of the structure S transversely or orthogonally to the main line H in the measurement data D can be determined very quickly. For this purpose, in particular, a precise determination or detailed investigation of the structure S is not necessary.

[0143] In the sense of the present invention, the extension L of the structure S transversely or orthogonally to the main line H is preferably the number of segments A that the structure S has or that form the structure S. In other words, the number of adjacent segments A marked as occupied represents the extension L of the structure S orthogonally to the main line H.

[0144] Preferably, when the number of measurement points or projections in segment A is less than or equal to a minimum value and / or when no measurement points or projections are located in one or two adjacent segments A, segment A is not marked as occupied and / or is not processed or counted as a segment A marked as occupied when determining or counting the number of adjacent segments A marked as occupied.

[0145] The aforementioned minimum value can be 1 in particular. In other words, it is particularly preferred that segment A is not marked as occupied and / or not be treated or counted as a segment A marked as occupied when determining or counting the number of adjacent segments A marked as occupied if only one measuring point or its projection is located in segment A and / or if no measuring point or projection is located in one or two adjacent segments A. This prevents segments A from being marked or counted as occupied in segments in which the measuring points do not correspond to real objects in the surroundings of the cleaning device 1 but rather represent noise.

[0146] exist Figure 7 , measurement data D is shown by way of example, which has a section A between structure S3 and main line H, in which a single measuring point is present. According to the above explanation, this section is preferably not marked as occupied or is not processed or counted as a section A marked as occupied when determining or counting the number of adjacent sections A marked as occupied.

[0147] The number of adjacent sections A of the structure S marked as occupied, ie the extent L of the structure S, is preferably compared with a particularly predetermined limit value.

[0148] The limit value is in particular a (predetermined) number which is compared with the number of segments A forming or comprising the structure S. In other words, the limit value is preferably formed by the maximum number of adjacent segments A marked as occupied.

[0149] If the extent L or the number of adjacent sections A marked as occupied by a structure S is greater than a limit value, this means in particular that the structure S extends transversely to the main line H. If the extent L or the number of adjacent sections A marked as occupied by a structure S is less than or equal to a limit value, this means in particular that the structure S is at least substantially parallel to the main line H.

[0150] If no structure S has an extent L or a number of adjacent segments A marked as occupied that is greater than a limit value, the result of the analysis is in particular that the measurement data D contain no structures S extending transversely to the main line H.

[0151] Therefore, when the measurement data D does not contain a structure S extending transversely to the main line H, or when the extension size L of all structures S in the measurement data D is less than or equal to the limit value, or when the measurement data D does not contain a structure S whose extension size L is greater than the limit value, it is preferably evaluated as a positioning anomaly.

[0152] Apart from the determination and counting of the interpreted occupied segments and the subsequent comparison with limit values, the measurement data D is preferably not further analyzed with respect to any structures S contained in the measurement data D. In this way, the identification method can be performed quickly and with few computing steps or with low computing effort.

[0153] Figures 5 to 8 Different measurement data D are shown. Figure 5 / 6 and Figure 7 There is no positioning anomaly in . On the contrary, Figure 8 There is a positioning anomaly or the cleaning device 1 is located in the corridor K.

[0154] exist Figure 5 As can be seen in FIG. 6 , the measurement data D have a main line H as a structure S and a further structure S. The measurement data D of the further structure S are located in the directly adjacent section A, so that they together form the structure S.

[0155] Obviously, the structure S (also) extends transversely to the main line H or the structure S has a relatively large extent L perpendicular to the main line H. Therefore, in this case, the identification method or analysis (with a suitable choice of limit values) shows that the measurement data D has a structure S extending transversely to the main line H.

[0156] Therefore, in Figure 5 In / 6, there are no positioning anomalies, but rather the position of the cleaning device 1 can be (unambiguously) determined, in particular based on the structure S.

[0157] exist Figure 7 In the example, the measurement data D have, in addition to the main line H, a plurality of different structures S1, S2, S3. All measurement data D of the structure S1 lie in the same section A. In other words, the structure S1 therefore extends parallel to the X direction or the main line H. Therefore, the analysis explained above for the structure S1 shows that the structure S1 does not extend transversely to the main line H. On the contrary, the structures S2 and S3 extend over a plurality of sections A and therefore transversely to the main line H. Therefore, the analysis (with correspondingly selected limit values) generally shows that Figure 7 The measurement data D of have at least one structure S extending transversely to the main line H and therefore do not contain any positioning anomalies.

[0158] On the contrary, Figure 8 In FIG, the measurement data D have another straight line in addition to the main line H as the only structure S, whose measurement data D are all located in the same section A. The structure S or line runs parallel to the main line H and therefore does not extend transversely to the main line H. As a result, in Figure 8 There is a positioning anomaly or corridor K. Figure 8 The measurement data in particular correspond to Figure 3 The situation or surroundings of the cleaning device 1 are shown in FIG.

[0159] Especially in Figure 5 The advantage of the described only indirect determination of the structure S by determining the extent L or the number of adjacent segments A marked as occupied is shown at / 6: the human observer Figure 5 In addition to the main line H, at least two further structures S would be identified in / 6, namely a short line in the Y direction and an angle having a line in the X direction and a line in the Y direction, wherein, by perception or counting, each angle could also be understood as two structures S, namely two lines in the X and Y directions. However, such a distinction would be associated with a higher analysis and computational complexity and would not be helpful for the purposes of the present invention: only the presence of at least one structure S transverse to the main line H is important, as this is sufficient for determining the position of the cleaning device 1.

[0160] However, the identification method can also be designed differently from the above.

[0161] For example, it is possible to determine, in addition to the main line H, other straight lines in the measurement data D during the identification method and to determine and, in particular, compare the slope of the main line H with the slopes of the other lines and / or the angles of these lines relative to the axes of the coordinate system. In this way, it can also be determined whether the measurement data D contains at least one structure S extending transversely to the main line H. In other words, if the measurement data D contains another line with a slope significantly different from that of the main line H, then this other line is a structure S extending transversely to the main line H and there is no positioning anomaly. If one or more of the other determined lines has at least essentially the same slope as the main line H, i.e., is at least essentially parallel to the main line H, then the measurement data D does not contain a structure S extending transversely to the main line H, but rather a positioning anomaly, in particular a corridor K, is present.

[0162] Determining the slope of a line in the measurement data D is, in particular, at least indirectly determining the extent L of the structure S perpendicular to the main line H, since the slope at least indirectly represents a measure of the extent L or extension of the line perpendicular to the main line H. In this case, the limit value for comparison with the extent L of the structure S can be formed by the determined slope. For example, the limit value can be defined such that if no line is identified in the measurement data D whose slope differs from the slope of the main line H by more than a certain percentage or angle, for example, an angle of 1°, 3°, or 5°, this is considered a positioning anomaly.

[0163] In addition to the slope, in order to determine the extent L of the structure S or of another identified line in the measurement data D, the length of the corresponding line can also be determined or taken into account.

[0164] As already explained, the identification method is preferably carried out or repeated multiple times and / or continuously during the operation of the cleaning device 1 .

[0165] The limit value is preferably set or defined such that, when the position can still be determined by means of the navigation device 4 or the distance sensors 8, 9, but the ability to determine the position by means of the navigation device 4 or the distance sensors 8, 9 is about to be lost or is about to be lost, a positioning anomaly is detected or the determined situation is classified as a positioning anomaly by means of the detection method. For this purpose, the limit value is preferably selected accordingly.

[0166] In this way, measures can be taken in good time to prevent the determined position from being lost, for example by stopping the cleaning device 1 or selecting another method for determining the position.

[0167] This can be done by Figure 2 and Figure 3 The example of Figure 2 There are no positioning anomalies in , because not only the parallel walls W1, W2 but also the wall W3 perpendicular thereto are located in the detection area B of the distance sensor 8 or the navigation device 4. Therefore, the position of the cleaning device 1 can be well or clearly determined. Figure 3 The cleaning device 1 is located in the corridor K and there is a positioning anomaly because no object is located in the detection area B parallel to the walls W1 and W2 and the position in the direction parallel to the walls W1 and W2 cannot be determined. Figure 2 When the position shown in FIG is moved in the direction of travel R parallel to the walls W1 and W2, the portion of the wall W3 located in the detection area B becomes smaller and smaller until the wall W3 is finally completely outside the detection area B and is in the Figure 3 . In the measurement data D, the movement away from wall W3 is represented by increasingly shorter lines that extend perpendicularly to the lines corresponding to walls W1 and W2. The line corresponding to wall W1 or W2 represents the main line H in the measurement data D, and the line corresponding to wall W3 represents the structure S that extends perpendicularly to the main line H. If the limit value for the extension L of structure S in the measurement data D is now selected to be sufficiently large, the presence of a positioning anomaly can be detected by the detection method even when a portion of wall W3 is still within detection area B and its position can thus be determined. Thus, the positioning anomaly is detected before cleaning device 1 is located in corridor K.

[0168] If a positioning anomaly is detected by the detection method, the cleaning device 1 preferably automatically switches from the method used in normal operation for determining the position, or from particle filter positioning, to another method for determining the position. In particular, the switch can be to odometry and / or dead reckoning. In odometry or dead reckoning, the position is preferably determined using the previously described inertial sensor 10 and / or odometry sensor of the cleaning device 1, optionally also taking into account the measurement data D of the distance sensors 8 and 9.

[0169] If a positioning anomaly is no longer detected by the detection method, the cleaning device 1 preferably automatically switches back to the method for determining the position used before the detection of the positioning anomaly, in particular particle filter positioning.

[0170] The various aspects, features and method steps of the present invention can be implemented independently of each other, but can also be implemented in any combination or order.

[0171] Reference Signs List

[0172] 1. Cleaning equipment

[0173] 2 Shell

[0174] 3 wheels

[0175] 4 Navigation mechanism

[0176] 5 Data processing organization

[0177] 6 Control mechanism

[0178] 7 Suction opening

[0179] 8 distance sensor

[0180] 9 Additional distance sensors

[0181] 10 Inertial Sensors

[0182] Section A

[0183] B Detection area

[0184] D Measurement data

[0185] H Main Line

[0186] L extension size

[0187] K Corridor

[0188] R Direction of travel

[0189] S structure

[0190] S1-S3 structure

[0191] V vertical axis

[0192] W1-W3 wall.

Claims

1. Method for operating a self-propelled cleaning device (1), in, The cleaning device (1) autonomously navigates in the surroundings and determines its position in the surroundings by means of a navigation device (4). The measurement data (D) of the navigation device (4) are present as measurement points in a coordinate system, wherein the measurement points are respectively defined by two coordinates. The cleaning device (1) performs a recognition method for recognizing a positioning anomaly, wherein the positioning anomaly is a situation in which the ability to determine the position along at least one axis is about to be lost or has been lost and / or the cleaning device (1) is located in a corridor (K) or is about to enter the corridor (K), It is characterized by: In the identification method, a straight main line (H) Sw is identified in the measurement data (D) and the measurement data (D) is analyzed to determine whether it contains a structure (S) extending transversely to the main line (H), wherein an extension size (L) of the structure (S) in the measurement data (D) perpendicular to the main line (H) is determined and the extension size is compared with, in particular, a predetermined limit value, and when the measurement data does not contain a structure (S) whose extension size (L) is greater than the limit value, it is evaluated as a positioning anomaly.

2. The method according to claim 1, characterized in that The position of the main line (H) relative to the coordinate system is determined, in particular the angle and / or the slope of the main line (H).

3. The method according to any one of the preceding claims, characterized in that The measurement data (D) are subjected to a coordinate transformation, in particular a rotation, in particular such that after the coordinate transformation the main line (H) is parallel to an axis of the coordinate system.

4. The method according to any one of the preceding claims, characterized in that In particular, after a coordinate transformation or rotation, the projection of the measurement data (D) onto an axis orthogonal to the main line (H) is determined.

5. The method according to any one of the preceding claims, characterized in that The coordinate system or an axis of the coordinate system orthogonal to the main line (H) is divided into segments (A) of preferably equal size, wherein the segment (A) is marked as occupied when at least one measuring point or its projection is located within the segment (A), and / or wherein the segment (A) is marked as unoccupied when no measuring point or no projection of a measuring point is located within the segment (A).

6. The method according to claim 5, characterized in that The number of adjacent segments (A) marked as occupied is respectively determined, in particular counted.

7. The method according to claim 5 or 6, characterized in that When the number of measurement points in the segment (A) is less than or equal to a predetermined minimum value and no measurement point is located in one adjacent segment (A) or in two adjacent segments (A), the segment (A) is not marked as occupied and / or is not processed as a segment (A) marked as occupied when determining the number of adjacent segments (A) marked as occupied.

8. The method according to any one of claims 5 to 7, characterized in that The measuring points located in the same segment (A) and / or in adjacent segments (A) together form a structure (S), and / or the number of adjacent segments (A) marked as occupied represents the extension (L) of the structure (S) perpendicular to the main line (H), and / or the limit value is formed by the maximum number of adjacent segments (A) marked as occupied.

9. The method according to any one of the preceding claims, characterized in that The main line (H) is identified using a line detection algorithm, in particular using a Hough transform or a RANSAC algorithm.

10. The method according to any one of the preceding claims, characterized in that The limit value is defined such that if the position can still be determined with the aid of the navigation device (4), but the ability to determine the position with the aid of the navigation device (4) is about to be lost, this is evaluated as a positioning anomaly.

11. The method according to any one of the preceding claims, characterized in that The navigation device (4) comprises a distance sensor (8), in particular a laser distance sensor, particularly preferably a lidar sensor, or is formed thereof.

12. The method according to any one of the preceding claims, characterized in that In order to determine the position of the cleaning device (1), particle filter positioning is used.

13. The method according to any one of the preceding claims, characterized in that When a positioning anomaly is detected using the identification method, the cleaning device (1) automatically switches to other methods for determining the position, in particular to odometry and / or dead reckoning.

14. The method according to claim 13, characterized in that When no positioning anomalies are detected using the detection method, the cleaning device (1) automatically switches to the method for determining the position used before the detection of the positioning anomaly, in particular to particle filter positioning.

15. A self-propelled cleaning device (1), wherein: The cleaning device (1) comprises a navigation device (4), a data processing device (5) and a control device (6) in order to autonomously navigate in the surrounding environment, and is characterized in that The cleaning device (1) is designed to carry out the method according to any of the preceding claims.

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