Identification and localization of base stations of autonomous mobile robots

Abstract

A system comprising an autonomous mobile robot and a base station for the robot is described. In accordance with an example of the present invention, the robot includes a navigation module having a navigation sensor for detecting a geometric feature of an object in an environment surrounding the robot. The base station has at least one geometric feature that can be detected by means of a navigation sensor of the robot. The robot includes a robot controller coupled with the navigation module configured to identify and / or locate the base station and / or determine a docking position of the robot based on at least one geometric feature of the base station.

Description

[0001] Divisional application

[0002] This application is a divisional application of Chinese invention patent application No. 201680063343X, filed on September 2, 2016, entitled "Identification and Positioning of Base Stations for Autonomous Mobile Robots". Technical Field

[0003] This invention relates to a method for an autonomous mobile robot to identify and locate a base station. Additionally, the invention describes how to use the base station to calibrate the robot's sensors and how to improve docking operations. Background Technology

[0004] In recent years, autonomous mobile robots, especially service robots, have been increasingly used in the home, for example, for cleaning or monitoring residences. If these robots have no work to do, they are typically docked to a base station. This allows them to, for example, charge their batteries, clean their dust bags, or refill their cleaning supplies via the base station. Reliable retrieval of the base station is crucial for the robot to operate fully autonomously. Various solutions are known for this purpose. Published documents US20090281661A1 and US20140100693A contain background information on this subject.

[0005] More generally, the object of the present invention is to simplify or improve known methods for robot identification and location of robot base stations and methods for docking with base stations. Summary of the Invention

[0006] The solutions of this invention to achieve the above-mentioned objectives are the system described in claims 1 and 23, the base station described in claim 19, and the methods described in claims 21, 34, 36, 41, and 49. Various embodiments and improvements of this invention are described in the dependent claims.

[0007] This invention describes a system comprising an autonomous mobile robot and a base station for the robot. According to an example of the invention, the robot includes a navigation module with navigation sensors for detecting geometric features of objects in the robot's surrounding environment. The base station has at least one geometric feature that can be detected by means of the robot's navigation sensors. The robot includes a robot controller coupled to the navigation module, configured to identify and / or locate the base station and / or determine the robot's docking position based on at least one geometric feature of the base station.

[0008] Another example of the invention relates to a base station for a mobile robot. The base station includes a housing having at least one opening disposed therein, the housing defining at least one geometric feature detectable by the robot's sensor system due to its geometry.

[0009] Furthermore, the present invention also describes a method for an autonomous mobile robot. According to an example of the invention, the method includes detecting geometric features of objects in the robot's surrounding environment by means of a navigation module of the robot having navigation sensors. Here, at least one detected object is a geometric feature of a base station. Furthermore, the method also includes identifying and / or locating the base station based on at least one geometric feature of the base station.

[0010] According to another example of a system with an autonomous mobile robot and a base station, the robot includes a navigation module with navigation sensors for detecting geometric features of objects in the robot's surrounding environment. The base station includes at least one geometric feature detectable by means of the robot's navigation sensors. The navigation module is configured to test and / or calibrate the navigation sensors using at least one detected geometric feature of the base station.

[0011] The present invention also relates to other examples of methods for autonomous mobile robots. According to one example, a method includes detecting geometric features of objects in the robot's surrounding environment by means of a navigation module of the robot having navigation sensors, wherein at least one of the detected features is a geometric feature of a base station. The navigation sensors are calibrated and / or tested using at least one geometric feature of the base station.

[0012] Another method is used to dock an autonomous mobile robot to a base station. According to an example of the invention, the method includes determining the docking position of the robot at the base station, wherein the docking position includes the robot's position and orientation, and navigating the robot to the docking position. Thereafter, it is verified that the robot has been correctly docked to the base station. If not, the robot's position is changed and the docking is re-verified. This process of modification and verification continues until the verification is successful or the termination criteria are met.

[0013] According to another example of the invention, a method for enabling an autonomous mobile robot to automatically connect to a base station includes: detecting obstacles by means of a navigation module of the robot having navigation sensors, and verifying whether the detected obstacles obstruct the robot's approach to the base station within a defined area around the base station. If the verification indicates that the robot's approach to the base station is obstructed, interference is communicated through a user interface.

[0014] Another exemplary method for autonomous mobile robots includes: detecting geometric features of objects in the robot's surrounding environment using a navigation module equipped with navigation sensors, and navigating the robot based on at least one of the detected geometric features and an electronic map of the robot's work area. Here, the location of the robot's base station is recorded in the electronic map. Furthermore, the method includes verifying whether the detected geometric features contain geometric features associated with the base station. If so, the current location of the base station is determined based on the geometric features associated with the base station, and the location of the base station in the electronic map is updated. Alternatively, the base station can also be identified and located in other ways to update its position in the robot's map.

[0015] Another example of a method for an autonomous mobile robot includes: detecting geometric features of objects in the robot's surrounding environment using a navigation module of the robot equipped with navigation sensors; and navigating the robot based on at least one of the detected geometric features and an electronic map of the robot's work area. Here, the location of the robot's base station is recorded in the electronic map. According to the method, a first geometric feature not defined by the base station is associated with the location of the base station. This first geometric feature is tracked using a SLAM algorithm, wherein the location of the first geometric feature in the electronic map is kept up-to-date, and the location of the base station is stored as a relative position to the location of the first geometric feature. Attached Figure Description

[0016] The invention will now be described in detail with reference to the examples shown in the accompanying drawings. The drawings are not necessarily drawn to scale, and the invention is not limited to the aspects illustrated. Rather, the focus is on presenting the basic principles of the invention. In the drawings:

[0017] Figure 1 The robot shown has a base station within its work area;

[0018] Figure 2 A schematic diagram illustrating optical distance measurement using triangulation;

[0019] Figure 3 An example of a base station is shown, which has geometric features that can be detected by a robot's navigation sensors, and these geometric features are defined by openings in the front wall of the base station housing;

[0020] Figure 4 The figure illustrates how to detect the geometric features of a base station using a robot's navigation sensors and possible system measurement errors.

[0021] Figure 5 The diagram illustrates a method for docking a robot to a base station, where the robot changes its orientation until a correct docking is achieved. Detailed Implementation

[0022] Generally, mobile robots should be able to dock safely and reliably with their base stations. Known systems and methods for locating and identifying base stations and their precise locations and orientations (base station and robot) often utilize specialized sensors (e.g., guided beams) on the robot, employ complex image processing algorithms in addition to navigation algorithms, and / or make special markings at the base station or in the robot's work area. Furthermore, various interferences must be eliminated to reliably locate the base station and dock the robot with it. For example, base station displacement can affect reliable positioning. The navigation sensors used by the robot cannot be reliably tested in unknown environments such as the robot's work area. Approaching the base station (docking operation) can sometimes lead to charging contact misalignment due to ranging errors. For example, a user might place an obstacle near the base station that interferes with the docking operation, causing docking failure.

[0023] Given the aforementioned shortcomings of conventional robot base station systems and methods for identifying and locating base stations and safely docking robots to them, improvements are still needed. For example, it is desirable to be able to locate a robot's base station using navigation sensors already present in or on the robot, without the base station needing to emit signals or be specially marked. To this end, according to some embodiments described herein, the base station is identified and located based on its geometry (e.g., certain geometric features of the base station housing (external shape / form)). In other words, the base station itself has at least one geometric feature due to its external shape / form, based on which the robot can identify the base station. Making special markings on the base station housing (which has no effect on its geometry / form) or emitting (locating) signals is no longer necessary. Generally, the robot should be able to quickly and reliably find its way back to its base station after completing a task (e.g., a cleaning task). To this end, according to some embodiments described herein, the location of the base station is marked on a map and kept up-to-date by various methods. Another desirable capability of mobile robots is their ability to navigate well (capable of good and rapid self-orientation) within different robot work areas (e.g., different floors of a house). To address this, according to some embodiments described herein, placing base stations in each robot's work area enables the robots to distinguish themselves from one another. The robot associates a map of its respective work area with each base station. If a robot identifies a specific base station, it can immediately begin (self-)localization on the correct map associated with that base station.

[0024] Another desirable capability of mobile robots is reliable and more precise docking with base stations, for example, to establish a secure connection between the robot's charging contacts and the base station. To this end, according to some embodiments described herein, after reaching a pre-calculated docking position, the robot's position and orientation can be easily corrected to enable safe docking. Docking should also be possible even if interference is possible (e.g., obstruction to approaching the base station). To this end, according to some embodiments described herein, potential interference is detected and the user is notified accordingly.

[0025] Generally, it is desirable for a robot's navigation sensors to be able to verify their effectiveness within the work area and be recalibrated as needed. To this end, according to some embodiments described herein, base stations with their prior known geometric parameters are used.

[0026] Figure 1 A illustrates an autonomous mobile robot 100 and associated base stations 200 in the robot's work area. The robot has a navigation module with at least one navigation sensor 110 for self-localization and navigation through the robot's work area to autonomously perform tasks. The navigation module of robot 100 acquires information about "navigation features" in the robot's surrounding environment via the navigation sensor 110, such as the location of geometric features of objects (e.g., obstacles), information about ground cover, etc. Geometric features are, for example, faces (e.g., walls), lines (e.g., the outlines of walls, furniture, or other objects in the environment surrounding robot 100), and points (e.g., corners or edges of objects in the environment surrounding robot 100). Each navigation feature may be associated with a location (including orientation) in the room and may be stored in an electronic map of robot 100 if necessary. The navigation module operates, for example, using obstacle avoidance strategies and / or SLAM (Simultaneous Localization and Mapping) algorithms and / or utilizing one or more robot work area maps. The robot may recreate the robot work area map during operation or use a map that already exists at the start of the operation. Existing maps can be created by the robot itself in previous tasks (such as reconnaissance missions) or provided by another robot and / or personnel.

[0027] The navigation sensor 110 acquires information about the robot's surrounding environment (and therefore its work area) in one, two, or three dimensions, particularly about its geometry. The navigation sensor 110 can be, for example, a distance measurement sensor, such as an optical and / or acoustic sensor, which determines the distance between the sensor and obstacles by performing triangulation or time-of-flight measurements on emitted signals (e.g., laser beams, ultrasonic signals). Therefore, triangulation sensors, time-of-flight cameras, laser scanners, ultrasonic sensors, etc., can be used as navigation sensors. Using this navigation sensor 110, the robot 100's navigation module can determine the distances between the robot and various points, lines, and / or surfaces of objects in its surrounding environment. These determined points, lines, and / or surfaces are called "navigation features" and are stored in the robot's map (i.e., the geometry of the navigation features and their positions (including orientation) are recorded in an electronic map). The robot can later orient itself and / or avoid such detected obstacles in a collision-free manner based on these navigation features. Another typical example of a navigation sensor 110 is a camera (e.g., with a CCD or CMOS image sensor) that has a detection module that identifies the edges and corners (navigation features) of objects in the surrounding environment in an image by means of image data processing. In this way, the position of the navigation features relative to the robot in the projection plane can be determined. As the robot moves, the navigation features and the robot's position in the room, including orientation, are thus determined. This mode of operation is called visual SLAM.

[0028] Figure 1 C illustrates a simplified example of base station 200. This base station consists of a body 210 having geometric features detectable by navigation sensors as navigation characteristics. The body 210 of base station 200 can house various other components, such as those for charging the battery of robot 100 or for vacuuming up debris. Two charging contacts 220 are present at base station 200, for example. Robot 100 has corresponding contacts that must engage with the charging contacts 220 for its battery to be successfully charged. In other words, the robot must be positioned and oriented to the base station to charge its battery. If the position and orientation of body 200 are known, the robot can determine its desired position and orientation (and thus the path to travel).

[0029] According to the embodiments described herein, the geometric features (i.e., external shape / form or its various parts) of the base station 200 are automatically detected as navigation features for navigation by means of the navigation sensor 110 of the mobile robot 100. By determining and interpreting the properties of the navigation features (by the robot's navigation module), the navigation features of the base station can be identified explicitly and without significant additional cost, thereby identifying the base station, determining its position and orientation in the robot's surrounding environment, and recording it in the robot's map. For this purpose, simple criteria are used, such as (1.) the distance from certain points (e.g., angles) of a feature to other features, (2.) the length of an edge / segment / line, (3.) the size of a surface, (4.) the relative positions of features to each other, especially the angle between two edges, segments or lines or the angle defined by three specific points (angles), (5.) ratios (relative size, relative length), such as the ratio of the lengths of two lines, and (6.) error measures, such as the (square) deviation of (error) measurements of design-related ratings (a set of points, for example, can determine a straight line, which can be calculated by linear regression; and the deviation of specific points of the regression line can be used as a criterion for determining whether a point belongs to an imaginary line).

[0030] For example, at least a portion of the detected features indicates the width, depth, and / or height of a main body portion of the base station. The base station positioning standard used should be easy to calculate and reliably measurable from different locations. This is illustrated in detail below.

[0031] exist Figure 1 In the example shown in A, the navigation sensor 110 determines the distance to obstacles in the robot's surrounding environment, for example, by means of optical triangulation, which involves emitting structured light in a straight line approximately parallel to the ground (within the visible or invisible range). The principle of optical triangulation is as follows... Figure 2 As shown. The emitted structured light 111 strikes obstacle H and diffuses there. An image of the surrounding environment is captured by a camera, imaged by the light (e.g., a ray) backscattered from the obstacle. By means of triangulation, the distance d from the vertical position x of the structured light (e.g., a ray) backscattered from the image to the illuminated obstacle H can be determined at a selected point or along the entire line (in the case of horizontal light).

[0032] For effective detection, the base station 200 is geometrically designed such that it is illuminated by the light emitted by the navigation sensor 110 due to its height and protrudes significantly from the wall due to its depth. Furthermore, the surface of the base station is designed to effectively scatter the light emitted by the navigation sensor 110 (i.e., especially with surfaces that are non-absorbing or specularly reflective).

[0033] Figure 1 B is shown as an example. Figure 1Possible results of sensor measurements in scenario A. Specifically, robot 100, using its navigation module and navigation sensor 110, identifies two linear navigation features 201 and 202 originating from a measurement base station. Navigation features 201 and 202 are subsequently referred to as boundary lines or simply lines. Both lines 201 and 202 have feature lengths corresponding to the widths (in the horizontal direction) of the side (line 201) and front (line 202). Furthermore, these two lines 201 and 202 form a known angle (e.g., a right angle). Therefore, if, for example, base station 200 (e.g., in a horizontal plane at a certain height on the ground) has a rectangular cross-section with side lengths of, for example, 5 cm and 15 cm, and robot 100, using its navigation sensor 110, determines two approximately right-angled lines with lengths of approximately 5 cm (line 201) and 15 cm (line 202), respectively, it can interpret these two lines 201 and 202 as base stations. Alternatively, an aspect ratio of 5:15 = 1:3 can be used. Figure 1 As shown in Figure B, the robot cannot identify one side of the base station due to the light blocking on the front of the navigation sensor. To acquire this further geometric feature of the base station, the robot can circle around the base station until it reliably detects the second side. Therefore, in this case, the base station can be observed from at least two different locations.

[0034] In the method described above, base station 200 is identified solely based on its rectangular shape. This leads to an increased probability of false detection, as every cubic object (e.g., a box) with appropriate side lengths is identified as a base station. Furthermore, for safety reasons (risk of injury) and design considerations, the sharp corners are typically replaced with rounded edges. In principle, such rounded corners could also be detected by the aforementioned navigation sensors. However, processing circles requires more computation than processing straight lines.

[0035] Therefore, according to the embodiments described herein, the interior of the base station is also used for inspection. For this purpose, one or more openings are introduced into the main body of the base station. Through these openings, various components of the base station can be seen (e.g., for vacuuming up dirt). However, this can also be avoided, where only one or more inner walls are visible.

[0036] Figure 3 A shows an example of a base station 200, which has a rounded edge arranged in front of the base station and two openings 230. Figure 3 B shows Figure 3 A cross-sectional view of base station 200 of A, wherein the cross-section is a horizontal plane at a certain height on the ground. This certain height is the ground height at which the navigation sensor 110 measures the distance to obstacles in the robot's surrounding environment. Figure 3C illustrates an example of such a measurement when the robot stands at a certain distance (e.g., 0.5 to 1 meter) in front of the base station. A portion of the rear wall of base station 200 can be seen here, all of which lie on a straight line. Furthermore, the robot can determine the positions of four points (1,2,3,4) with minimal measurement error. In this case, the positions and sizes of the two openings 230 (windows) are chosen, for example, such that the distance between any two points in any pair of points is different (i.e., specifically, d(1,2)≠d(1,3)≠d(1,4)≠d(2,3)≠d(2,4)≠d(3,4), where d(i,j) represents the distance between point i and point j). These distances can be easily calculated and compared with stored nominal values. Furthermore, for example, the distances from points to the line formed by the rear wall can be compared. The ratio of distances can also be taken into account. Using error functions, such as the coefficient of determination in a regression model, we can test whether points 1, 2, 3, and 4 lie exactly on a line parallel to the back wall. Thus, many features can significantly reduce the probability of false positives, making this situation unlikely to occur in everyday life.

[0037] To protect the interior from contamination, a cover 250 can be installed in front of the opening 230. This cover is made of a material permeable to light emitted by the navigation sensor 110. The emitted light can be, for example, in the infrared region invisible to humans, making the cover 250 appear transparent from the robot's perspective, but colored and opaque from a human's perspective. This cover 250 not only needs to cover the opening 230 but can also be used independently to form different geometries recognizable by both the user and the robot. This allows for a design that is easily detectable. The cover 250 can be provided with an anti-reflective coating that matches the wavelength of the light emitted by the navigation sensor 110.

[0038] In the measurement of the (horizontal) plane, its distance from the ground can easily vary (e.g., due to different mounting heights of the navigation sensor 110, or because the measurement plane is not perfectly parallel to the ground, for example, because the robot is slightly tilted). In order to reliably identify the geometry of the base station in the plane, at least one selection is made from identifiable navigation features (or dimensions based thereon) in the surrounding environment measured in the expected cross-section, regardless of the actual measurement height (the distance of the plane from the ground to which the distance measurement is performed).

[0039] In some applications, robots are used in isolated robotic work areas, such as two different floors of a house. Each work area has a base station 200, which the robot 100 can clearly identify using its navigation sensors 110. If the robot 100 can already distinguish the base station 200, it will also automatically acquire information about which work area it is in without additional user intervention.

[0040] To achieve the distinguishability of base station 200, for example, a user can modify a portion of the base station's geometry (e.g., during base station startup), thus altering features recognizable by navigation sensor 110 in a predetermined manner. This modification can be accomplished, for example, by moving, removing, or adding parts of the base station. Figure 3 Base station 200 of A can be modified, for example, by changing the size (width) of one of the two openings. Therefore, point 3 can be modified, for example. Figure 3 C) can be located, specifically by adding an additional partition. For example, a sliding partition can be installed behind the bridge between the two viewing windows.

[0041] It is known that an autonomous mobile robot 100 marks its base station 200 on a map. Typically, a base station serves as the starting point of the map; that is, the base station has a fixed location on the map. However, the location of a base station can change. Detecting a base station allows for easy updating of its location on the map, based on characteristics (navigation features) that are used by default for navigation and are detectable by the navigation sensor 110. However, base stations can also be detected in other ways to update the robot's location on the base station map. Changes to the base station location can be performed by the user, for example, (1.) during robot operation, or (2.) during robot docking with a base station. Furthermore, map construction by the robot and / or its Localization in a Map (SLAM) may result in discrepancies between the robot's expected base station location and the actual location due to measurement and ranging errors. Thus, in the worst-case scenario, any (useful) information about the base station location is lost. The following examples illustrate how to address or at least mitigate such problems.

[0042] Position Updates Using SLAM Algorithms - Navigation Autonomous mobile robots typically employ SLAM (Simultaneous Localization and Mapping) algorithms, which continuously associate the robot's position with selected navigation features detected by navigation sensors. Despite measurement and ranging errors, the robot achieves robust map building. SLAM is computationally expensive, so only a few clearly visible navigation features are selected, such as considering walls, to maintain the necessary computational power within a certain range. The positions of navigation features (and the robot) tracked by the SLAM algorithm are constantly corrected; therefore, they are not located in fixed (relative) positions relative to other things not tracked by SLAM. Base station features are often too small to be taken into account by the SLAM algorithm, so their stored positions relative to walls (which are tracked by the SLAM algorithm) may be displaced. This could result in stored positions being in the wrong room or even outside the work area. For this reason, updating the base station positions is highly beneficial.

[0043] Since base stations also contain detectable geometric features (navigation features), their positions can be easily kept up-to-date using SLAM algorithms. For example, this can be achieved by selecting and tracking at least one well-detectable feature of the base station using SLAM algorithms (see...). Figure 3 This could be, for example, Figure 3 The segment formed by points 2 and 3 in C. Alternatively, features detected near the base station can also be used. This could be, for example, the segment formed by points 2 and 3. Figure 1 Line 300 in B is generated by the wall where the base station is located. In both cases, the robot records which feature among the features tracked by the SLAM algorithm determines the location of the base station. Furthermore, the robot can store the position of the base station relative to this navigation feature. If the robot wants to return to the base station, it can travel to a location near these features, thus ensuring a reliable return route is found.

[0044] Position Updates During Robot Operation - In cases where the base station is moved by the user during robot operation, advantageously, robot 100 identifies base station 200 during its movement and updates the new location on the map. As navigation sensors detect features of the base station for the navigation robot, the newly identified features are tested to see if they might be part of the base station. In this case, in the first step, easily identifiable features can be used selectively, requiring only minimal additional computation time to identify. If the feature is confirmed, other features of the base station can then be examined.

[0045] For example, Figure 3 For base station A, its length can be found to correspond to Figure 3 The distance between points 2 and 3 in C is considered as a segment (e.g., a line with a specific length and orientation). If such a segment is found, further checks can be performed to identify the back wall, whether it is at the correct distance, and whether points 1 and 4 exist and lie on a line. For example, the navigation module could detect the length of the identified segments by default to assess their relevance to navigation.

[0046] If a base station is identified at a new location, the robot has different action options. If the new location deviates only slightly from the old location (e.g., less than 1 meter), the current location of the base station is recorded and the old location is deleted. This is particularly useful when the navigation sensors simultaneously check the old location of the base station and do not identify it at that location. If a base station is detected at a location in the robot's work area far from the previous base station, this base station is likely a second base station. In this case, the location of the base station is re-recorded, and the old location is retained for later verification. When the robot is near the old location, it checks whether the base station is still there. Depending on the result, the old location is deleted, or it is recorded that two base stations are located within the robot's work area. For these two base stations, the relevant locations (along with orientation) can be stored in a map.

[0047] It's also possible that the robot is near a base station according to map information, but this goes undetected. This happens if the user changes the base station's location, even if only for a brief moment, such as when cleaning it. In the simplest case, the robot removes the base station's location from the map data. Alternatively, the robot's location on the map is marked "undetermined." If the robot later identifies a base station in another location during its operation, the "undetermined" location is removed and the new location of the base station is recorded. Otherwise, the robot returns to the "undetermined" location when it wants to approach a base station. If the base station is not found there either, a special search procedure is initiated to locate it, where the robot navigates around the work area and specifically searches for base station features (navigation features). Additionally, messages can be sent to users (e.g., via a user interface, such as an app on a tablet or mobile phone) so they can respond as needed.

[0048] The measurement accuracy of the navigation sensor 110 may decrease as the distance to the object whose distance should be measured increases. With respect to extended objects, the measurement accuracy also depends on their orientation. This is especially true when using a triangulation sensor. For example, if viewed from directly in front... Figure 3Base station 200 can determine the distance between points 2 and 3 with sufficient accuracy within a distance of approximately 2 meters. However, if the base station is viewed at a 45° angle, the distance must not exceed approximately 1 meter to reliably measure the distance between base station 200 and robot 100. Based on this, to improve the quality of base station detection, a maximum distance can be determined to verify the potential correlation between identifiable navigation features and the base station. The maximum distance used to perform the verification can also depend on the orientation of the feature (relative to the robot).

[0049] Robot Position Update at Start of Operation - When the robot is docked at a base station, for example in pause mode, the user can move the robot along with the base station. For example, if the robot uses an existing map it built during a previous operation, its new position (and the base station's position) will not match the existing navigation information. According to the embodiments described herein, the robot can perform the following steps at the start of the operation: (1.) shut down the base station and load map data relevant to the operation; (2.) determine the robot's position in the existing map data; and (3.) update the base station's position in the map data.

[0050] Self-localization of the robot can be achieved by using an algorithm that determines its position on a map by comparing data detected by navigation sensors with existing map data. To accelerate the localization algorithm, previously known base station locations can be used as a first hypothetical location for the robot. For example, if the robot fails to locate itself in step 2 above, it begins to reconstruct the map, recording the base station locations in the new map. At the end of the robot's operation, the user can be notified of the newly created map and asked whether it should replace or supplement the old map.

[0051] Navigation within Multiple Robotic Work Zones – A robot can be used in two or more isolated robotic work zones, such as multiple floors of a house. In each work zone, a base station can be placed where the robot can clearly identify it using its navigation sensors (as described above). Having identified the base station, the robot "knows" which work zone (e.g., floor) it is in. Accordingly, the robot's navigation module can load map data associated with the corresponding base station. This assumes the user has pre-positioned the robot on or near one of the base stations. Using the loaded map data, the robot can begin localization. In this case, as previously described, the robot can use the known location of the base station on the map and its relative position to that known location to accelerate localization. For example, this is accomplished by using the location of the base station (or the robot's docking position) as a hypothetical location. In an alternative form, the area where the robot is attempted to be located on the map is limited to the area surrounding the base station. For example, this area could be a square in front of (adjacent to) the base station or a circle surrounding the base station. Its side length / radius can depend on the distance between the robot and the base station.

[0052] According to another embodiment, the robot performs the following steps for localization: (1.) turning off the base station; (2.) detecting and identifying the base station; (3.) loading map data associated with the base station; (4.) locating the robot in the map based on the loaded map data; and (5.) updating the location of the base station in the map data. Step 1 is optional and depends on whether the robot initially docks with the base station.

[0053] If no map data is associated with the identified base station or localization fails in the corresponding map, a new map of the robot's work area is created. The newly created map can be announced to the user at the end of the robot's operation. The robot can then ask the user whether the new map should be associated with a base station and stored permanently. In an alternative implementation, in the event of localization failure, the robot can attempt localization using map data associated with other base stations. This latter approach is more reasonable, for example, if the user has replaced one base station with another.

[0054] For example, distance measurement sensors and navigation sensors (see, for example, according to...) Figure 2 A triangulation sensor is a highly sensitive measurement system. For example, collisions can cause sensor misalignment, leading to persistent measurement errors. This can significantly affect a navigation robot's movement through its work area. For the robot to operate reliably, it may be necessary to detect system measurement errors in the navigation sensors and compensate for them through calibration whenever possible. The base station described in the embodiments herein can be used for this purpose (calibration) because it has well-defined geometric features that can be identified by the navigation sensors.

[0055] For example, the misalignment of a navigation sensor can be determined by measuring the position, distance, length, size, and / or angle of one or more geometric features (or navigation features derived therefrom) of a base station and comparing them to corresponding ratings. These ratings can also be used to recalibrate the navigation sensor. Furthermore, the various geometric features of the base station can be designed such that at least one of the parameters of the navigation sensor to be calibrated can be directly inferred from their measurements.

[0056] To improve calibration accuracy, multiple independent measurements can be combined, thereby reducing the impact of measurement errors from a single measurement. For this purpose, multiple independent geometric features of the base station (e.g., width and depth, see...) can be measured. Figure 1 B and Figure 3 Alternative or additional locations can be used to perform the same measurements from different distances to the base station. In particular, the distance traveled by the robot between the two measurement locations (range measurement) can also be taken into account.

[0057] An example of a navigation sensor (especially a distance measurement sensor) is a triangulation sensor, which emits structured light from a light source (see reference). Figure 2 (beam 111) and using a camera (see Figure 2 Camera 112) captures images of the brightly lit surrounding environment. From the camera images and the relative position of the camera and the light source, the distance to the obstacle can be determined (see...). Figure 2 The distance d). Small changes in relative position due to displacement (e.g., about 1 μm) or rotation (e.g., about 0.01°) of the light source (and beam 111) relative to the camera 112 (e.g., due to impact) can introduce system measurement errors in distance measurements, causing the (previously calibrated) navigation sensor 110 to become inaccurate. Figure 1 Figure A shows an example of detecting the (horizontal) cross-section of base station 200 using a triangulation sensor (navigation sensor 110). Figure 3 The possible results of this measurement can be seen in section C. Various different measurement results (measurements) can be derived from these sensor data, leading to conclusions about the quality of the distance measurement. For example, it is possible to (a) determine the distance between point 1 and point 4 and compare it to the (known) actual width, (b) determine the distance from one or more features in front of the base station (such as point 1, point 2, point 3, and point 4) to the rear wall and compare it to the (known) actual depth of the base station, (c) check whether point 1, point 2, point 3, and point 4 are on a line, and / or (d) determine the angle between the rear wall and the line defined by the features in front (point 1, point 2, point 3, and point 4) (ideally, in this example, this angle should be zero, i.e., the line is parallel to the rear wall). In particular, the distance between robot 100 and base station 200 can also be determined based on, for example, the width and / or depth of base station 200. This value can be used to calibrate the distance measurement.

[0058] A particular challenge to achieving calibration accuracy using base station 200 may be its relatively small configuration (compared to large pieces of furniture). While navigation sensors spaced several meters apart can provide accurate measurements, the base station is only a few centimeters wide and deep. By installing a reflector within the base station, the internal optical path can be extended. This can improve the calibration accuracy of the navigation sensor emitting the target light. For example, in accordance with... Figure 3 In base station A, the inner side of the rear wall can be mirrored. In this case, for navigation sensor 110, the inner surface of the front wall of the housing is visible, thus allowing for a measurement path with twice the depth compared to the non-mirrorized case.

[0059] In the case of a triangulation sensor, the following sensor parameters can be calibrated: the distance (focal length) between the image sensor (e.g., CCD or CMOS sensor) and the lens; the distance from the optical axis of the light source (e.g., laser and lens); and the inclination of the measurement plane (equivalent to the inclination of the optical axis of the light source, see...). Figure 4 a), Case b); Zero point at position x on the image sensor (see Figure 2 In particular, the last two parameters (the inclination of the light source's optical axis and the zero-point position on the image sensor) can severely distort distance measurements when misaligned, especially at larger distances, leading to system measurement errors. These two parameters of the triangulation sensor can be calibrated, for example, by measuring the width of the base station (or... Figure 3 The distance between point 1 and point 4 in C) and the adjustment (calibration) parameters to make the measured values ​​match known reference values. Furthermore, the depth of the base station (e.g., the distance between point 3 and the back wall, see...) Figure 3 C) is a known parameter that can be used to calibrate the parameter.

[0060] Although the above example only considers the shape of the base station in the horizontal cross section, alternatively or additionally, navigation characteristics that depend on the distance of the (horizontal) measuring plane from the ground can also be considered.

[0061] Figure 4 A illustrates a robot 100 with a navigation sensor 110 (especially a triangulation sensor) performing a measurement of a cross-section of a base station 200. Ideally, the measurement is performed in a plane parallel to the ground at a distance h above the ground. Figure 4 Case a in A), but it can deviate from it ( Figure 4 Case b in A). Figure 4 B shows base station 200, which is connected to... Figure 3 Example A is similar, but with an opening 230' (window) formed such that the location (and / or extended range) of the navigation feature depends on the ground distance at which the sensor measurements are performed. Figure 4 (The dashed line in B). Figure 4 C represents the corner points of the base station openings 230 and 230' in case a, which serve as navigation features (measured distance from the ground h = h). a ),as well as Figure 4 D represents the corner points of the base station openings 230 and 230' in case b, which serve as navigation features (measured distance from the ground h = h). b In case b, point 2 is shifted to the left compared to case a. As a result, in case b, the distance between point 1 and point 2 is smaller than in case a, while the distance between point 2 and point 3 is larger than in case a. By measuring the base station from different distances, it is possible to determine, for example, whether the sensor measurement is parallel to the ground, or how much the measurement plane is tilted relative to the horizontal plane. Therefore, in this process, in addition to the two-dimensional cross-sectional measurement, the third dimension of the base station is used to directly determine or calibrate the sensor parameters (here, the inclination of the light source's optical axis or the inclination of the navigation sensor's measurement plane). For this, the base station needs to be significantly dependent on the geometric characteristics of the distance h from the ground (e.g., the position of point 2 or the distance between point 1 and point 2).

[0062] According to another example of the invention, the robot's navigation module calculates the docking position based on the detected geometric features (navigation features) of the base station and then guides the robot to that position. If the navigation sensor's measurement is incorrect, the docking operation will fail because the calculated docking position does not match the actual necessary position. Calculating the docking position depends on one or more parameters, which can be calibrated when the exact docking position is known. These parameters may be, for example, the position of the navigation sensor 110 on the robot 100, but may also be, for example, the displacement of the reflector of the receiving optics system of the navigation sensor 100. Calibration can be performed using a trial-and-error method. In this process, the calculated docking position is varied, and the docking operation is performed accordingly. This process is repeated, and the success rate is determined. The docking position with the highest success rate is used to calibrate the necessary parameters. Changing the position (or orientation) can be done randomly or systematically and progressively within an interval around the calculated position. Alternatively, the position can be replaced, or the parameters of interest can be changed directly, thereby determining the position of interest.

[0063] As described above, the robot 100 can also determine its docking position and orientation based on the location of the base station 200. According to... Figure 5 In the example shown in A, the navigation module can determine the robot's path from its calculated docking position and orientation and guide the robot to the docking position. However, for example, due to ranging errors, the actual ending position and orientation of robot 100 (during docking) may deviate from the planned and necessary docking position and orientation. Figure 5B shows that even small deviations can lead to errors. For example, if the charging contact 220 of the base station does not make contact with the corresponding charging contact 120 of the robot, the autonomous function of the robot 100 will be affected.

[0064] To calibrate the robot position and / or orientation after the docking operation from any small deviation from the actual necessary docking position and / or orientation, robot 100 slightly alters its position (e.g., orientation). For example, as... Figure 5 As shown in C, regardless of the imprecise docking position, charging contact can be achieved through a small rotation (see Figure C). Figure 5 D).

[0065] From the basis Figure 5 Starting from the first docking position of B, the robot rotates to the left by a predetermined angle α for the first time. Figure 5 As shown in C, this may not be successful, so a second rotation is performed in the opposite direction. For example, to cover the symmetrical area around the initial orientation, the angle of the second rotation is approximately twice the angle 2a of the first rotation, but in the opposite direction.

[0066] Whether the required docking orientation has been achieved can be determined, for example, by the effective voltage at the charging contacts or by the contact switch. For instance, if successful docking is not achieved, the robot may return to its starting orientation after completing the rotation.

[0067] To further enhance the reliability of docking operations to the base station, the base station may, for example, have one or more (flexibly mounted) noses that engage with corresponding recesses on the robot. Figure 1 In C, these are, for example, two charging contacts 220. By rotating the robot, these protruding noses can slide into corresponding notches on the robot, thereby defining a precise docking position and orientation. Interfaces for sucking up dust bags from the robot via base stations or for filling cleaning agents can perform similar functions.

[0068] To ensure a successful docking operation, a docking area in front of the base station should be free of obstructions. This area should be large enough for the robot to reliably identify the base station during its movement and to have sufficient space for a simple and direct docking operation. This area could be, for example, approximately one robot diameter to the left and right of the base station and approximately two robot diameters in front of the base station.

[0069] User interference can cause various disturbances, such as: (i) the base station being configured such that walls extend through the docking area (especially because the base station is too close to a corner); (ii) small obstacles such as chair legs or loose shoes being placed in the docking area, which can impede part of the journey; and (iii) small obstacles such as wires or clothing being placed in the docking area, which can make it difficult for the robot to move, for example, by increasing wheel slippage.

[0070] Typically, users do not intentionally create such interference, nor do they deliberately place obstacles in the robot's path to prevent it from approaching the base station and docking safely. According to the embodiments described herein, efforts are made to detect such problems as early as possible and communicate them to the user so that they can eliminate the interference. The robot, for example, has a detection module that can identify when it is calculating a path and / or traveling on a path to dock, which becomes quite difficult or impossible, for example, due to one of the aforementioned interferences. In this situation, navigation sensors can be used, for example, to detect obstacles in the docking area. For example, small, run-over obstacles in the docking area can be identified using sensors that detect ranging errors such as slippage.

[0071] To notify users of identified problems, the robot has at least one communication interface (human-machine interface, HMI). This can include a visual display or sound signals directly on the robot, especially voice output. Furthermore, it may be configured to connect to external devices, such as smartphones or tablets, via WLAN, enabling it to send information to the user. This information may include, for example, the type of interference detected.

[0072] Furthermore, the robot can assess the severity of interference and communicate it to the user (e.g., minor issues (Level I, no immediate user interaction required), relevant issues (Level II, user interaction recommended / desirable), serious issues (Level III, user interaction required)). Therefore, the user can determine the urgency of their intervention. For example, the base station might be placed too close to a wall, interfering with docking but not completely preventing it (Level I or II). In this case, the user can decide that the base station remains in place and the robot should attempt docking. On the other hand, the user might inadvertently place a chair in front of the base station, preventing direct docking (Level III). The user can quickly resolve this issue, thus ensuring the robot's functionality. Depending on the actions taken, the user can provide feedback to the robot via the communication interface. This feedback could include, for example: (i) the problem has been resolved; (ii) the problem has been ignored and docking attempted; (iii) waiting for docking and resolving the problem later. Classifying interference into three levels is, of course, merely illustrative and can be implemented in any other way.

[0073] To notify users of problems as early as possible, the robot should always perform interference detection after leaving the base station, especially when starting a new task.

[0074] Finally, it should be noted that the technical features of the devices, methods, and systems described herein according to different examples can often be combined with each other to achieve other embodiments of the invention. These combinations are generally feasible and reasonable, unless explicitly stated otherwise. It goes without saying that each method described herein is performed by a robot. In other words, the robot includes a robot controller, which is generally programmable and programmed according to the application to cause the robot to perform the relevant methods. The robot controller is not necessarily implemented as a single component of the robot. Typically, all components affecting the robot's externally identifiable behavior form part of the robot controller. Therefore, the robot controller does not need to be physically installed within the mobile robot, but can also be partially located outside the robot in a fixed (control) device, such as a computer, which is connected to the robot via a communication link.

Claims

1. A system comprising an autonomous mobile robot (100) and a base station (200) for the robot (100), in, The robot (100) includes a navigation module with a navigation sensor (110) for detecting geometric features of objects in the environment surrounding the robot (100). The base station (200) has multiple geometric features that can be detected by means of the robot's navigation sensors (110). The robot includes a robot controller coupled to the navigation module, which is configured to identify and / or locate the base station (200) and determine the docking position of the robot (100) based on the plurality of geometric features of the base station (200); The base station (200) has at least one opening (230, 230') in its housing wall, and the at least one opening defines at least one geometric feature of the plurality of geometric features of the base station; The at least one opening (230, 230') is asymmetrically arranged in the base station such that the detected geometric features are asymmetrical with respect to the vertical plane of symmetry.

2. The system according to claim 1, in, The navigation sensor is configured to non-contactly measure the distance between the navigation sensor and objects in the environment surrounding the robot (100), and The navigation module is configured to detect the geometric features of objects in the environment surrounding the robot (100) based on the measured distance.

3. The system of claim 2, wherein the navigation sensor performs distance measurement substantially in a horizontal plane having a defined distance from the ground.

4. The system according to any one of claims 1 to 3, in, The navigation module is configured to store the geometric features of detected objects in an environmental electronic map.

5. The system according to any one of claims 1 to 4, in, At least one geometric feature of the base station (200) is at least one of the following: a feature point on the housing of the base station (200); a feature line on the housing of the base station; A polygon defined by the housing of the base station (200); a surface defined by the housing of the base station (200).

6. The system according to any one of claims 1 to 5, in, The robot controller is configured to associate at least one detected geometric feature with at least one metric and compare them with a relevant reference value to identify and / or locate the base station.

7. The system according to claim 6, in, The at least one metric is at least one of the following: length, distance, angle, ratio of two lengths, ratio of two distances, and ratio of two angles.

8. The system according to claim 6, in, The at least one metric is at least one of the following: the distance between two points, the length of a line, the distance from a point to a line, the distance from a point to a surface, an angle defined by three points, an angle defined by two lines, and the ratio of the lengths of two lines.

9. The system according to any one of claims 1 to 8, in, The at least one opening (230, 230') is covered by a covering made of a material that is transmissible to the navigation sensor (110).

10. The system according to claim 9, in, The navigation sensor (110) is an optical sensor that emits light in a specific spectrum, and The covering has an anti-reflective coating adapted to the spectrum of light emitted by the optical sensor.

11. The system according to any one of claims 1 to 10, in, The at least one opening (230, 230') can be varied in size or shape by attaching or moving a partition or by removing a portion of the housing wall along a predetermined fracture location.

12. The system according to any one of claims 1 to 11, in, The base station has a geometry such that the geometric features of the base station (200) are asymmetric with respect to the vertical plane of symmetry.

13. The system according to any one of claims 1 to 12, in, At least one geometric feature of the base station (200) can be varied by adding an accessory to the housing of the base station (200), removing an accessory from the housing of the base station (200), or shifting or tilting the accessory on the housing of the base station (200).

14. The system according to any one of claims 1 to 12, in, At least one of the geometric features of the base station is different when it is detected by the navigation module at different horizontal planes at different distances from the ground.

15. The system according to any one of claims 1 to 14, wherein the navigation module has a memory for multiple electronic maps, wherein, Each map can be equipped with a specific base station (200) and indicate the robot's work area where that specific base station is located.

16. The system according to any one of claims 1 to 15, further comprising: At least one additional base station, wherein the base station (200) is located in a first robot operating area and the additional base station is located in a second robot operating area. The navigation module includes a memory for multiple electronic maps, which can be associated with one of the base stations. After identifying a specific base station, the navigation module loads a map associated with the identified base station.

17. A base station for a mobile robot, comprising: A housing having at least one opening (230, 230') arranged therein, the opening defining, by its geometry, at least one of a plurality of geometric features detectable by the sensor system of the robot (100); The at least one opening (230, 230') is asymmetrically arranged in the base station such that the detected geometric features are asymmetrical with respect to the vertical plane of symmetry.

18. The base station according to claim 17, further comprising: in, The at least one opening (230, 230') is covered by a covering made of a material that is permeable to the sensor system of the robot (100).

19. A method for an autonomous mobile robot (100), comprising: The navigation module of the robot (100) with navigation sensor (110) is used to detect the geometric features of objects in the environment surrounding the robot (100), wherein at least one of the detected objects is a geometric feature of a plurality of geometric features of the base station (200). The base station (200) is identified and / or located based on the plurality of geometric features of the base station (200); The base station (200) has at least one opening (230, 230') in its housing wall, and the at least one opening defines at least one geometric feature of the plurality of geometric features of the base station; The at least one opening (230, 230') is asymmetrically arranged in the base station such that the detected geometric features are asymmetrical with respect to the vertical plane of symmetry.

20. The method of claim 19, wherein identifying and / or locating the base station (200) comprises: Associate at least one metric value with at least one detected geometric feature. The at least one metric is compared with an associated reference value.

21. A system comprising an autonomous mobile robot (100) and a base station (200) for the robot (100), in, The robot (100) includes a navigation module with a navigation sensor (110) for detecting geometric features of objects in the environment surrounding the robot (100). The base station (200) has at least one geometric feature that can be detected by means of the robot's navigation sensor (110), and The navigation module is configured to test and / or calibrate the navigation sensor (110) using at least one geometric feature of the detected base station.

22. The system according to claim 21, in, The navigation sensor is configured to non-contactly measure the distance between the navigation sensor and objects in the environment surrounding the robot (100), and The navigation module is configured to detect the geometric features of objects in the environment surrounding the robot (100) based on the measured distance.

23. The system according to claim 22, The navigation sensor described therein performs distance measurements essentially in a plane with a defined position.

24. The system according to any one of claims 21 to 23, The navigation sensor (110) is a non-contact optical sensor such as a triangulation sensor, a time-of-flight camera, or a camera.

25. The system according to any one of claims 21 to 24, in, To test or calibrate the navigation sensor, the navigation module associates at least one detected geometric feature with at least one metric value and adjusts at least one parameter of the navigation sensor based on the metric value.

26. The system according to claim 25, in, At least one geometric feature of the base station (200) is configured such that the metric associated with it depends directly on the parameters of the navigation sensor.

27. The system according to claim 23, in, To test or calibrate the navigation sensor (110), the navigation module associates at least one geometric feature of the detected base station (200) with at least one metric and compares it with a relevant reference value. In this configuration, at least one geometric feature of the base station (200) is configured such that the metric associated therewith depends on the position of the plane on which the navigation sensor (110) performs the distance measurement.

28. The system according to any one of claims 21 to 27, in, In order to test or calibrate the navigation sensor (110), the navigation module detects at least one geometric feature of the base station (200) at least twice from different positions of the robot (100).

29. The system according to claim 28, in, The relative positions of the robot (100) at different locations are determined by means of a ranging method and are taken into account during the testing / calibration of the navigation sensors.

30. The system according to claim 22, in, The navigation sensor is an optical sensor that emits light, and In this configuration, a portion of the base station is mirrored to increase the measurement length of the navigation sensor during calibration.

31. The system according to claim 30, in, The at least one geometric feature is formed by an opening (230, 230') in the front wall of the housing of the base station (200); as well as The internal area of ​​the base station, such as the rear wall of the base station (200), is mirrored to increase the measurement length of the navigation sensor during calibration.

32. A method for an autonomous mobile robot, comprising: The navigation module of the robot (100) with navigation sensors (110) is used to detect the geometric features of objects in the environment surrounding the robot (100), wherein at least one of the detected features is a geometric feature of the base station (200). The navigation sensor (200) is tested and / or calibrated using at least one geometric feature of the detected base station (100).

33. The method of claim 32, wherein testing and / or calibrating the navigation sensor (100) comprises: Associate at least one metric value with at least one detected geometric feature. At least one parameter of the navigation sensor is adjusted based on at least one metric.

34. A method for automatically docking an autonomous mobile robot to a base station, comprising: Determine the docking position of the robot (100) at the base station (200), the docking position including the position and orientation of the robot (100); Navigate the robot (100) to the docking position; Verify whether the robot (100) has been correctly connected to the base station (200); If the robot (100) has not yet been correctly connected to the base station (200), then: change the position of the robot (100) and re-verify whether the robot (100) has been correctly connected to the base station (200) until the verification is successful or the termination criteria are met.

35. The method of claim 34, wherein changing the position of the robot (100) comprises: Starting from the docking position of the robot (100): rotate the robot (100) along the first direction to change the robot's orientation until the inspection is successful or the maximum rotation angle is reached.

36. The method according to claim 35, When the maximum rotation angle is reached: the robot (100) is reversed back to the docking position and the robot (100) is further rotated in the second direction to change the robot's orientation until the inspection is successful or the maximum rotation angle is reached.

37. The method according to any one of claims 34 to 36, wherein verifying whether the robot (100) is correctly connected to the base station (200) comprises: Check whether there is electrical contact between the charging contact (220) of the base station (200) and the corresponding charging contact (120) of the robot (100), and / or Verify whether the locking element of the robot (100) is engaged with the corresponding locking element of the base station (200), and / or Check whether the mechanical contact between the robot (100) and the base station (200) triggers the switch.

38. The method according to any one of claims 34 to 37, in, The position where the robot (100) successfully docks with the base station (200) is stored as a new docking position.

39. A method for automatically docking an autonomous mobile robot to a base station, comprising: Obstacles are detected by means of the navigation module of the robot (100) with navigation sensors (110); The test examines whether the detected obstacles within a defined area around the base station (200) prevent the robot (100) from approaching the base station (200); If the test shows that the robot (100) is obstructed from approaching the base station (200), the interference is communicated through the user interface.

40. The method of claim 39, further comprising: If the test shows that the robot (100) is obstructed from approaching the base station (200), then: the interference caused by the obstacle is evaluated according to predetermined criteria; The evaluation is conveyed through the user interface.

41. The method according to claims 39 and 40, further comprising: The ground properties within a defined area surrounding the base station (200) are evaluated according to predetermined criteria. If the ground properties do not meet the predetermined standards, the interference is communicated through the user interface.

42. A method for an autonomous mobile robot, comprising: The navigation module of the robot (100) with navigation sensors (110) is used to detect the geometric features of objects in the environment surrounding the robot (100); The robot (100) is navigated based on at least one of the detected geometric features and an electronic map of the robot's (100) work area, wherein the location of the robot's (100) base station (200) is recorded in the electronic map; The detected geometric features are examined to determine whether they include geometric features associated with the base station (200). If one of the detected geometric features is a geometric feature associated with the base station (200), then: the current location of the base station is calculated based on the geometric feature associated with the base station (200), and the location of the base station (200) in the electronic map is updated.

43. The method according to claim 42, wherein, Updating the location of the base station (200) in the electronic map includes: Determine the distance between the current location of the base station and the location of the base station (200) stored in the map; If the distance does not exceed a predetermined threshold, the current location of the base station (200) is used to overwrite the location of the base station (200) stored in the map.

44. The method according to claim 42 or 43, wherein, Updating the location of the base station (200) in the electronic map includes: The location of the base station (200) stored in the map is marked as the old location; Store the current location of the base station (200) in the map; The presence of a base station at the old location is determined based on the detected geometric features. If there is no base station at the old location, then delete it; otherwise, retain the old location as the location of another base station.

45. The method according to any one of claims 42 to 44, in, At the start of the robot's operation, the base station locations stored in the map are used as the robot's assumed location.

46. ​​The method according to any one of claims 42 to 45, in, When the location of the base station (200) is updated, the user is notified via the user interface.

47. A method for an autonomous mobile robot, comprising: The navigation module of the robot (100) with navigation sensors (110) is used to detect the geometric features of objects in the environment surrounding the robot (100); The robot (100) is navigated based on at least one of the detected geometric features and an electronic map of the robot's (100) work area, wherein the location of the robot's (100) base station (200) is recorded in the electronic map; Associating a first geometric feature, which is not defined by the base station (200), with the location of the base station (200). The first geometric feature is tracked using the SLAM algorithm, wherein the position of the first geometric feature in the electronic map is kept up-to-date, and the position of the base station is stored as a relative position to the position of the first geometric feature.

48. The method according to claim 47, wherein, The first geometric feature is defined by an object near the base station (200), such as a wall.

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