JP2021114103A - Map processing device, map processing method, and mobile robot - Google Patents

Abstract

To provide a map processing device and the others that are able to divide a task area included in a map so that an autonomously moving mobile robot can accurately estimate a self-position.SOLUTION: A map processing device 100 divides a task area corresponding to a predetermined area, included in a map 141 used by a mobile robot 200 autonomously moving in the predetermined area, into a plurality of sub-areas, comprises: an extraction unit 120 that extracts from the task area a plurality of feature points corresponding to a plurality of points respectively in the predetermined area where the mobile robot 200 can recognize a position and a division unit 130 that divides the task area into the plurality of sub-areas, based on the plurality of feature points.SELECTED DRAWING: Figure 3

Description

The present invention relates to a map processing device, a map processing method, and a mobile robot that autonomously moves using a map processed by the map processing device.

Conventionally, there are mobile robots that autonomously move in a predetermined area. This type of mobile robot calculates a movement route based on a map (map information) including a task area corresponding to a predetermined area, and autonomously moves along the calculated movement route.

For example, when a predetermined area is too wide, the mobile robot generates a plurality of sub-areas by dividing the task area included in the map corresponding to the predetermined area into several areas, and the generated sub-areas. The movement route is calculated for each. The mobile robot moves along the movement path for each sub-area. Patent Document 1 discloses a method of dividing a task area included in a map into a plurality of rectangular sub-areas.

Chinese Patent Application Publication No. 106175606

Spatial Tesselations: Concepts and Applications of Voronoi Diagrams, Second Edition

The mobile robot moves while estimating its own position in order to move along the movement path. For example, a sensor such as LIDAR (Light Detection and Ringing) is used to detect information indicating the positions of walls and objects located around the mobile robot, and the self-position is estimated using the detected information. The mobile robot estimates its own position by, for example, using a localization algorithm to compare the map with the information detected by LIDAR. The mobile robot performs tasks such as cleaning, minesweeping, or data collection while moving along the calculated movement path, for example. In a mobile robot that moves autonomously while executing such a task, it is required to move all over a predetermined area. Therefore, the mobile robot is required to be able to estimate its own position with high accuracy.

The present invention provides a map processing device or the like that can divide a task area so that a mobile robot that moves autonomously can accurately estimate its own position.

The map processing device according to one aspect of the present invention is a map processing device that divides a task area corresponding to the predetermined area into a plurality of sub-areas included in a map used by a mobile robot that autonomously moves in a predetermined area. An extraction unit that extracts a plurality of feature points corresponding to a plurality of points in the predetermined area where the mobile robot can recognize the position from the task area, and the task based on the plurality of feature points. It is provided with a division portion for dividing the area into a plurality of sub-areas.

Further, the map processing method according to one aspect of the present invention includes a map included in a map used by a mobile robot that autonomously moves in a predetermined area, and divides a task area corresponding to the predetermined area into a plurality of sub-areas. It is a processing method based on an extraction step of extracting a plurality of feature points corresponding to a plurality of points in the predetermined area where the mobile robot can recognize a position from the task area, and the plurality of feature points. A division step for dividing the task area into a plurality of sub-areas is included.

Further, the mobile robot according to one aspect of the present invention is a mobile robot that autonomously moves in a predetermined area, and is calculated by calculating the movement route for each of the map processing device described above and the plurality of sub-areas. After moving the mobile robot along the movement path of the unit and one of the plurality of sub-areas, the mobile robot is located at a position corresponding to the other sub-area of the plurality of sub-areas. The mobile robot is provided with a control unit for moving the mobile robot along a movement path in the other sub-area.

The present invention may be realized as a non-temporary recording medium such as a CD-ROM that can be read by a computer that records the above program. The present invention may also be realized as information, data or signals indicating the program. Then, those programs, information, data and signals may be distributed via a communication network such as the Internet.

According to the present invention, it is possible to provide a map processing device or the like capable of dividing a task area so that a mobile robot that moves autonomously can estimate its own position with high accuracy.

FIG. 1 is a perspective view showing the appearance of the mobile robot according to the embodiment. FIG. 2 is a bottom view showing the appearance of the mobile robot according to the embodiment. FIG. 3 is a block diagram showing a characteristic functional configuration of the mobile robot according to the embodiment. FIG. 4 is a flowchart for explaining a processing procedure of the mobile robot according to the embodiment. FIG. 5 is a diagram showing a first example of a map. FIG. 6 is a diagram showing a plurality of feature points in the map shown in FIG. FIG. 7 is a Voronoi diagram generated from the map shown in FIG. FIG. 8 is a diagram in which the map shown in FIG. 5 and the Voronoi diagram shown in FIG. 7 are superimposed. FIG. 9 is a diagram showing a plurality of sub-areas. FIG. 10 is a diagram showing a second example of the map. FIG. 11 is a diagram showing feature points in the map shown in FIG. FIG. 12 is a Voronoi diagram generated from the map shown in FIG. FIG. 13 is a diagram showing a third example of the map. FIG. 14 is a Voronoi diagram generated from the map shown in FIG. FIG. 15 is a flowchart showing details of the deletion process executed by the map processing device according to the embodiment. FIG. 16 is a diagram showing an example of a point set generated by the dividing portion. FIG. 17 is a diagram showing a fourth example of the map. FIG. 18 is a flowchart showing details of the division process executed by the map processing device according to the embodiment. FIG. 19 is a diagram showing details of division processing executed by the map processing apparatus according to the embodiment. FIG. 20 is a diagram for explaining a specific example of a map including a plurality of sub-areas generated by the map processing device according to the embodiment. FIG. 21 is a diagram for explaining a specific example of a map including a plurality of sub-areas generated by the map processing device according to the embodiment. FIG. 22 is a diagram for explaining a specific example of a map including a plurality of sub-areas generated by the map processing device according to the embodiment. FIG. 23 is a diagram for explaining a specific example of a map including a plurality of subareas generated by the map processing device according to the embodiment. FIG. 24 is a diagram for explaining a specific example of a map including a plurality of subareas generated by the map processing device according to the embodiment. FIG. 25 is a diagram for explaining a specific example of a map including a plurality of sub-areas generated by the map processing device according to the embodiment.

Hereinafter, embodiments of the map processing apparatus and the like according to the present invention will be described in detail with reference to the drawings. The numerical values, shapes, materials, components, arrangement and connection forms of the components, steps, the order of steps, etc. shown in the following embodiments are examples, and are not intended to limit the present invention.

Further, each figure is a schematic view and is not necessarily exactly illustrated. Further, in each figure, substantially the same configuration is designated by the same reference numerals, and duplicate description may be omitted or simplified.

Further, in the following embodiments, expressions using "abbreviations" such as substantially triangles are used. For example, a substantially triangle means not only that it is a perfect triangle, but also that it is substantially a triangle, that is, it also includes, for example, a triangle with rounded corners. The same applies to expressions using other "abbreviations".

Further, in the following embodiments, the case where the mobile robot moving in the predetermined region is viewed from the vertically upper side may be described as the top view, and the case where the mobile robot moving in the predetermined region is viewed from the vertically lower side may be described as the bottom view.

(Embodiment)
[Constitution]
FIG. 1 is a perspective view showing the appearance of the mobile robot 200 according to the embodiment. FIG. 2 is a bottom view showing the appearance of the mobile robot 200 according to the embodiment.

The mobile robot 200 is a mobile robot that autonomously moves (in other words, autonomously travels) in a predetermined area such as a floor while performing a predetermined task such as cleaning, minesweeping, or data collection. In the present embodiment, the mobile robot 200 is an autonomous traveling vacuum cleaner that cleans a predetermined area while autonomously traveling. The mobile robot 200 moves in a predetermined area by using a map including a task area corresponding to the predetermined area.

For example, the mobile robot 200 first runs around while capturing an image of a predetermined area (more specifically, within the predetermined area) using a camera 60 or the like, thereby performing a map including a task area corresponding to the predetermined area (more specifically, within the predetermined area). Map information) is generated.

Next, the mobile robot 200 calculates a movement route (travel route) to move (travel) when cleaning a predetermined area based on the generated map. Next, the mobile robot 200 travels in a predetermined area and cleans the calculated movement path.

The mobile robot 200 may start moving even if the map (task area) corresponding to the predetermined area is not completely generated. For example, when the mobile robot 200 recognizes only a part of a predetermined area by using the camera 60 or the like, the task area is divided into a plurality of sub-areas by dividing the feature points of the recognized part into a plurality of sub-areas as described later. A movement route may be calculated for each area, and the movement may be performed along the calculated movement route.

For example, the mobile robot 200 uses SLAM (Simultaneus Localization and Mapping) to generate a map showing a predetermined area to be cleaned and estimate the self-position of the mobile robot 200 on the generated map.

The mobile robot 200 includes, for example, a main body 10, two wheels 20, two side brushes 30, a laser rangefinder 40, a main brush 50, a camera 60, and a depth sensor 70.

The main body 10 is a housing for accommodating each component included in the mobile robot 200. In the present embodiment, the main body 10 has a substantially triangular shape when viewed from above. The shape of the main body 10 when viewed from above is not particularly limited. The top view shape of the main body 10 may be, for example, a substantially rectangular shape or a substantially circular shape. As shown in FIG. 2, the main body 10 has a suction port 11 on the bottom surface.

The two wheels 20 are wheels for running the mobile robot 200.

The side brush 30 is provided on the lower surface of the main body 10 and is a brush for cleaning a predetermined area. In this embodiment, the mobile robot 200 includes two side brushes 30. The number of side brushes 30 included in the mobile robot 200 may be one or three or more, and is not particularly limited.

The laser rangefinder 40 is a sensor for measuring the distance between the mobile robot 200 and an object, a wall surface, or the like in a predetermined area. The laser rangefinder 40 is provided, for example, on the upper part of the main body 10. The laser rangefinder 40 is, for example, a so-called lidar.

The main brush 50 is a brush that is arranged in a suction port 11 that is an opening provided on the lower surface of the main body 10 to suck dust.

The camera 60 is an imaging device that is arranged in the main body 10 and generates an image by imaging a predetermined area.

The depth sensor 70 is, for example, a sensor that detects the distance between the moving robot 200 and a subject such as an obstacle included in the image generated by the camera 60. The depth sensor is, for example, an infrared sensor.

The map processing device 100 is a processing device that divides, for example, a map generated by a mobile robot 200 by SLAM or the like into a plurality of sub-areas. Specifically, the map processing device 100 divides the task area corresponding to the predetermined area included in the map used by the mobile robot 200 that autonomously moves in the predetermined area into a plurality of sub-areas. The map processing device 100 is realized, for example, by a control program for executing such processing and a CPU (Central Processing Unit) that executes the control program.

FIG. 3 is a block diagram showing a characteristic functional configuration of the mobile robot 200 according to the embodiment.

The mobile robot 200 moves in a predetermined area based on, for example, the map 141. As shown in FIG. 3, the mobile robot 200 includes a map processing device 100, a calculation unit 210, a control unit 220, a detection unit 230, a mobile unit 240, and a cleaning unit 250.

The map processing device 100 is, for example, a processing unit that divides a map 141 showing a predetermined area to be cleaned into a plurality of sub-areas by SLAM. For example, the control unit 220 controls the moving unit 240 having the camera 60, the wheels 20, and the like to cause the mobile robot 200 to travel in a predetermined area, and generates and generates a map 141 which is data indicating the predetermined area. The created map 141 is stored in the storage unit 140 included in the map processing device 100. The map processing device 100 divides a predetermined area indicated by the map 141 into a plurality of sub-areas.

The map 141 includes, for example, information indicating a task area corresponding to a predetermined area, and a plurality of feature points corresponding to a plurality of points in a predetermined area located in the task area and recognizable by the mobile robot 200. Information indicating that, and is included.

The mobile robot 200 may not generate the map 141, but may receive the map 141 from a communication device such as a PC (Personal Computer) outside the mobile robot 200.

The map processing device 100 includes an acquisition unit 110, an extraction unit 120, a division unit 130, and a storage unit 140.

The acquisition unit 110 is a processing unit that acquires the map 141. In the present embodiment, the acquisition unit 110 acquires the map 141 stored in the storage unit 140. When the acquisition unit 110 acquires the map 141 by receiving the map 141 from a communication device such as an external PC of the mobile robot 200, the acquisition unit 110 may include a communication interface including an antenna for communication, a wireless communication circuit, and the like.

The extraction unit 120 is a processing unit that extracts a plurality of feature points included in the map 141 acquired by the acquisition unit 110. Specifically, the extraction unit 120 extracts a plurality of feature points corresponding to a plurality of points in a predetermined area where the mobile robot 200 can recognize the position from the task area. That is, the feature points are points on the map 141 corresponding to points that can be recognized (identified) by the mobile robot 200 by the detection unit 230 having the laser rangefinder 40, the camera 60, or the like. The feature point may be an object or position that can be detected by the detection unit 230, for example, a corner between a wall located in a predetermined area, an object such as a table, and a floor surface or wall as a mark. Etc. are markers attached to the above. The extraction unit 120 extracts a plurality of feature points included in the map 141.

The division unit 130 is a processing unit that divides the task area included in the map 141 into a plurality of sub-areas based on the plurality of feature points extracted by the extraction unit 120. The division unit 130 divides the task area so that each of the plurality of sub-areas includes at least one feature point, for example.

The division unit 130 divides the task area into a plurality of sub-areas so that, for example, each of the plurality of sub-areas includes at least one feature point. In the present embodiment, the division unit 130 generates a Voronoi diagram having a plurality of feature points as mother points, and uses the boundary line indicating the Voronoi boundary included in the generated Voronoi diagram to divide the map 141 into a plurality of sub-areas. To divide. That is, the division unit 130 divides the task area into a plurality of sub-areas by using the Voronoi diagram so that each of the plurality of sub-areas includes at least one feature point.

Further, for example, the dividing unit 130 deletes a part of the generated boundary line that satisfies a predetermined condition, and divides the map 141 into a plurality of sub-areas based on the remaining boundary line portion. ..

A predetermined condition for determining the portion of the boundary line to be deleted is, for example, that the distance between two or more feature points among the plurality of feature points is less than the predetermined distance. In other words, for example, when the distance between two or more feature points among the plurality of feature points is less than a predetermined distance, the division unit 130 corresponds to the boundary line generated by generating the Voronoi diagram. Delete the part generated based on two or more feature points.

The predetermined distance may be arbitrarily determined in advance.

Further, the dividing unit 130 generates, for example, a point set which is a set of feature points whose distance between the feature points is less than a predetermined distance, and among the boundary lines, two or more features included in the generated point set. Delete the part generated based on the point. Specifically, the division unit 130 is, for example, a point set to which at least two feature points belong among a plurality of feature points extracted from the task area, and at least one of the feature points belonging to the point set. , Generate a point set that is a set of feature points including feature points whose distance between feature points is less than a predetermined distance, and set two or more feature points included in the generated point set among the boundary lines of the Voronoi diagram. Delete the part generated based on it.

The division unit 130 generates a defined line that defines the range of the task area included in the map 141 and an area surrounded by the boundary line of the Voronoi diagram as a sub-area. That is, at least one of the plurality of sub-areas is, for example, a defining line that defines the range of the task area and an area surrounded by a boundary line. Alternatively, the division unit 130 may generate a region surrounded only by the boundary line as a sub-area. That is, at least one of the plurality of sub-areas is, for example, an area surrounded only by the boundary line of the Voronoi diagram.

The calculation unit 210 is a processing unit that calculates a movement route for each of a plurality of sub-areas generated by the map processing device 100 by dividing the map 141.

The control unit 220 moves the mobile robot 200 along the movement path in one of the plurality of sub-areas, and then moves the mobile robot 200 to the other sub-area among the plurality of sub-areas. , A processing unit that moves the mobile robot 200 along a movement path in another sub-area. That is, the control unit 220 moves the mobile robot 200 along the movement path calculated for each sub-area. The control unit 220 moves the mobile robot 200 by controlling, for example, the wheel 20 and the moving unit 240 including a motor for driving the wheel 20.

The detection unit 230 detects a wall located around the mobile robot 200, an object located in a predetermined area, and the like. The detection unit 230 is realized by, for example, a laser rangefinder 40, a camera 60, a depth sensor 70, and the like. The detection unit 230 detects information (feature point information) corresponding to the feature points included in the map 141 by the laser rangefinder 40, the camera 60, the depth sensor 70, and the like. Further, the detection unit 230 detects, for example, odometry information which is information indicating the direction, rotation angle, and the like of the wheel 20. The control unit 220 estimates the self-position of the mobile robot 200 using, for example, feature point information or odometry information, and the estimated self-position and the surrounding walls and objects of the mobile robot 200 detected by the detection unit 230. Based on the information indicating the position and the movement path calculated by the calculation unit 210, the movement unit 240 is controlled to move the mobile robot 200.

The moving unit 240 is a mechanism for moving the mobile robot 200. The moving unit 240 includes, for example, a wheel 20 and a motor for driving the wheel 20.

The cleaning unit 250 is a mechanism for cleaning a predetermined area. The cleaning unit 250 includes, for example, a side brush 30, a main brush 50, a motor for rotating the main brush 50, and the like. The control unit 220 controls the moving unit 240 and the cleaning unit 250 to cause the mobile robot 200 to perform cleaning while moving a predetermined area.

[Processing procedure]
Subsequently, the details of the processing procedure for the operation of the mobile robot 200 will be described.

<Overview>
FIG. 4 is a flowchart for explaining the processing procedure of the mobile robot 200 according to the embodiment.

First, the acquisition unit 110 acquires a map 141 including information indicating a task area corresponding to a predetermined area to which the mobile robot 200 moves (step S101).

FIG. 5 is a diagram showing a first example of the map 141. In FIG. 5, the task area 142 included in the map 141 is shown with hatching.

Map 141 shown in FIG. 5 includes a task area 142 and a defined line 143.

The task area 142 is a range on the map 141 corresponding to an area (predetermined area) in which the mobile robot 200 moves while executing a predetermined task. That is, the task area 142 is, for example, an area in the virtual space indicating a predetermined area in the real space.

The definition line 143 is a line indicating the range of the task area 142. The regulation line 143 is a line for a place where there is a wall or the like that the mobile robot 200 cannot pass through, such as a wall in the real space.

Next, the extraction unit 120 extracts a plurality of feature points from the task area 142 included in the map 141 (step S102). Here, extracting the feature points means extracting the coordinates of the points on the map 141 corresponding to the points (corners of objects, etc.) in a predetermined space that the mobile robot 200 detects and recognizes the position.

FIG. 6 is a diagram showing a plurality of feature points 144 in the map 141 shown in FIG. In FIG. 6, the definition line 143 of the task area 142 is shown for explanation.

For example, the extraction unit 120 extracts eight points corresponding to the corners of the task area 142 from the map 141 as feature points 144.

Next, the division unit 130 generates a Voronoi diagram based on the plurality of feature points extracted by the extraction unit 120 (step S103). Specifically, the division unit 130 generates a Voronoi diagram having a plurality of feature points extracted by the extraction unit 120 as a base point.

The Voronoi diagram is a diagram in which a plurality of points (mother points) arranged at arbitrary positions in a certain metric space are divided into regions according to which mother point the other points in the same metric space are close to. .. Specifically, the Voronoi diagram is a diagram composed of a plurality of mother points and a line (boundary line) in which positions closest to and equidistant from two or more mother points at the plurality of mother points are plotted. In other words, the Voronoi diagram is a diagram consisting of a plurality of mother points and a line generated by plotting the positions where the closest mother points are two or more. For example, when there are two mother points in a plane, the boundary line is a vertical bisector in the plane of the line segment connecting the two mother points.

As a method of calculating the Voronoi diagram, for example, there is an O (nlogn) algorithm such as a divide-and-conquer method (a method of dividing and processing) (see, for example, Non-Patent Document 1).

FIG. 7 is a diagram showing Voronoi diagram 147 generated from the map 141 shown in FIG.

Voronoi diagram 147 includes a plurality of feature points 144, each of which is a mother point, and a boundary line 145 generated based on the feature points 144. The area surrounded by the boundary line 145 is also referred to as a boronoisel 146. The boundary line is a combination of a straight line extending to infinity at both ends, a half straight line extending to infinity only at one end, and a straight line having 0, 1 or 2 vertices (ends). be.

With reference to FIG. 4 again, after step S103, the portion of the boundary line 145 satisfying a predetermined condition is deleted from the generated Voronoi diagram 147 (step S104). A specific example of deleting a part of the boundary line 145 will be described later.

Next, the division unit 130 divides the task area 142 into a plurality of sub-areas based on the portion of the boundary line 145 that remains without being deleted in step S104 and the defined line 143 of the task area 142 included in the map 141. Divide (step S105).

FIG. 8 is a diagram in which the map 141 shown in FIG. 5 and the Voronoi diagram 147 shown in FIG. 7 are superimposed. For example, as shown in FIG. 8, the map 141 and the boundary line 145 are overlapped based on the position of the feature point 144.

FIG. 9 is a diagram showing a plurality of sub-areas 148.

As shown in FIG. 9, the area partitioned by the boundary line 145 overlapping the task area 142 and the defined line 143 is the sub area 148. According to this, each of the plurality of sub-areas 148 includes the feature point 144.

Next, the calculation unit 210 calculates a movement route for each subarea generated by the division unit 130 (step S106).

Next, the control unit 220 executes the task while moving the mobile robot 200 along the movement path calculated by the calculation unit 210 for each sub-area (step S107). Specifically, the control unit 220 moves the mobile robot 200 along the movement path in one of the plurality of sub-areas, and then moves the mobile robot to the other sub-area among the plurality of sub-areas. To move the mobile robot 200 along the movement path in the other sub-area. In the present embodiment, the control unit 220 controls the moving unit 240 to move the moving robot 200 along the moving path for each sub-area, and controls the cleaning unit 250 to determine the mobile robot 200. Clean the area.

The position of the feature point may be not only the corner of the wall or the like but also a marker provided on the wall or the like.

Further, since the boundaries of the areas (task area and sub-area) are not actually drawn on the surface (specifically, in the real space), they are not generally visually recognized. However, when the moving body (robot vacuum cleaner 200) is a vacuum cleaner and the moving body cleans the entire area in sequence for each area, the boundary of the area is determined by observing the trajectory of the moving body. Can be seen.

FIG. 10 is a diagram showing a second example of the map.

The map 141a shown in FIG. 10 includes information indicating the marker portion 149 on the defined line 143. The marker unit 149 is, for example, a mark provided on a wall that can be detected by the detection unit 230 in real space, and is a striped pattern having a high light reflectance (for example, a light reflectance of 90% or more). The extraction unit 120 may also extract such a portion as a feature point.

FIG. 11 is a diagram showing feature points on the map 141a shown in FIG.

As shown in FIG. 11, the extraction unit 120 extracts not only the eight feature points 144 but also the points corresponding to the marker unit 149 as the feature points 144a as in the map 141.

FIG. 12 is a diagram showing Voronoi diagram 147a generated from the map 141a shown in FIG.

As shown in FIG. 12, the Voronoi diagram 147a is partially different from the Voronoi diagram 147 shown in FIG. 7 in the position of the boundary line 145a around the feature point 144a.

The position of the feature point may be a curved wall surface as well as a corner such as a wall surface.

FIG. 13 is a diagram showing a third example of the map.

In the map 141b shown in FIG. 13, a part of the regulation line 143a that regulates the range of the task area 142a is curved at the curved surface portion 149a. The curved surface portion 149a is, for example, a curved wall that can be detected by the detection unit 230. The extraction unit 120 also extracts such a portion as a feature point.

FIG. 14 is a diagram showing Voronoi diagram 147b generated from the map 141b shown in FIG.

As shown in FIG. 14, the Voronoi diagram 147b is partially different from the Voronoi diagram 147 shown in FIG. 7 in the position of the boundary line 145b around the feature point 144b, which is a feature point corresponding to the curved surface portion 149a.

<Delete process>
Subsequently, the details of the boundary line deletion process (step S104 shown in FIG. 4) executed by the map processing device 100 will be described.

As described above, when the boundary line of the Voronoi diagram is generated with the feature points as the base points, the boundary lines may become too large when the feature points are densely packed in a narrow range. In this case, there will be many small sub-areas. If the sub-area is extremely small, it is highly possible that the mobile robot 200 will make many turns such as a U-turn or a 90 ° turn in order to move all over the sub-area. Therefore, the time for the mobile robot 200 to execute the task is likely to increase. Therefore, for example, in an area where a plurality of feature points are densely packed, the map processing device 100 deletes a boundary line satisfying a predetermined condition in order to prevent the sub-area from becoming too small.

FIG. 15 is a flowchart showing details of the deletion process (step S104 shown in FIG. 4) executed by the map processing device 100 according to the embodiment.

First, the dividing unit 130 is connected by an arc by connecting the two feature points by an arc when the two feature points are less than a predetermined distance among the plurality of feature points extracted by the extraction unit 120. A point set, which is a set of feature points, is calculated (step S201).

FIG. 16 is a diagram showing an example of a point set generated by the dividing unit 130. In FIG. 16, eight feature points (feature point F1, feature point F2, feature point F3, feature point F4, feature point F5, feature point F6, feature point F7) among the plurality of feature points included in the task area are shown. , And the feature point F8) are illustrated.

The dividing unit 130 determines, for example, whether or not another feature point exists in a range less than a predetermined distance with respect to the feature point F1. For example, when the dividing unit 130 determines that the feature point F2 is less than a predetermined distance from the feature point F1, the feature point F1 and the feature point F2 are connected by an arc 310. On the other hand, when the dividing unit 130 determines that the feature point F4 is not less than a predetermined distance from the feature point F1, for example, the feature point F1 and the feature point F4 are not connected by an arc 310.

The dividing unit 130 also executes the above processing at other feature points (feature points F2 to feature points F8).

By doing so, the dividing unit 130 generates, for example, point sets 300 and 301 which are a set of feature points whose distance between the feature points among the feature points F1 to F8 is less than a predetermined distance. The feature point F1 and the feature point F4 in the point set 300 are not connected by the arc 310, but from the feature point F1, they are connected to the feature point F4 by the arc 310 via the feature point F2 and the feature point F3. There is. Therefore, the feature point F1 and the feature point F4 belong to the same point set 300. Further, the point set 301 is circular due to the arc 310. For example, from the feature point F1, the feature points F5 to F8 cannot be reached through any feature point and arc 310. Therefore, the feature point F1 does not belong to the same point set as the feature points F5 to F8. Further, the feature point F0 does not belong to any point set.

As described above, a point set (also referred to as a connected component) is a point cloud in which two nodes (for example, feature points) are connected to each other by a path (for example, arc 310), and other points (for example, for example). It is a point cloud that is not connected by a path to a feature point that belongs to another set of points.

The arc 310 is a line provided for explanation and is not actually generated.

With reference to FIG. 15 again, after step S201, the division unit 130 determines whether or not all of the boundary lines of the Voronoi diagram (in other words, all the straight line portions included in the boundary lines) have been analyzed (step). S202). That is, the division unit 130 determines whether or not the processes from step S203 to step S206, which will be described later, have been executed for all the portions of the boundary line. For example, the dividing unit 130 classifies the boundary line into one or more straight line portions for each straight line portion of the boundary line, and determines whether or not the analysis has been completed for each of the classified straight line portions.

When it is determined that all the boundary lines of the Voronoi diagram have been analyzed (Yes in step S202), the division unit 130 ends the process.

On the other hand, when the dividing unit 130 determines that all the boundary lines of the Voronoi diagram have not been analyzed (No in step S202), the two feature points that have not been analyzed (here, the feature point Fi and the feature point Fj). It is called), and the portion of the boundary line generated based on the two feature points is selected (step S203).

Next, the division unit 130 determines whether or not the feature point Fi and the feature point Fj belong to the same point set (step S204). In step S204, first, the dividing unit 130 extracts the feature points Fi and the feature points belonging to the same point set as the feature points Fj. Next, the division unit 130 determines whether or not there is a distance between a plurality of feature points belonging to the point set, which is less than a predetermined distance.

When the dividing unit 130 determines that the feature point Fi and the feature point Fj belong to the same point set (Yes in step S204), the dividing unit 130 deletes the boundary line generated based on the feature point Fi and the feature point Fj (Yes). Step S205), the process returns to step S202. In this way, the division unit 130 deletes the portion of the boundary line of the Voronoi diagram generated based on the feature points belonging to any of the point sets.

For example, consider the point set 300 shown in FIG.

For example, the dividing unit 130 determines whether or not it belongs to the same point set 300 as the feature point F1 and the feature point F4 (step S204). Here, the feature point F1 and the feature point F4 belong to the same point set 300 (Yes in step S204). In this case, the division unit 130 deletes the portion of the boundary line generated based on the feature point F1 and the feature point F4 among the boundary lines included in the Voronoi diagram (for example, step S205).

Further, for example, in the example of FIG. 16, the boundary line portion generated based on the feature point F1 and the feature point F6 does not belong to the same point set as the feature point F1 and the feature point F6 (in step S204). No), so it is not deleted (step S206).

With reference to FIG. 15 again, when the dividing unit 130 determines that there is no feature point that satisfies the distance between the feature points belonging to the same point set and is less than a predetermined distance (No in step S204), the feature point Fi and the feature The part of the boundary line generated based on the point Fj is retained without being deleted (step S206).

FIG. 17 is a diagram showing a fourth example of the map.

In addition, (a), (b), and (c) of FIG. 17 all show the map 141c. In the map 141c, the feature points are indicated by black circles, the defined lines are indicated by solid lines, and the boundary lines are indicated by alternate long and short dash lines. The area surrounded by the regulation line is the task area. Further, the area surrounded by the specified line and the boundary line (in other words, the area where the task area is partitioned by the boundary line) is a sub-area.

As shown in FIG. 17 (a), for example, the division unit 130 generates a boundary line based on a plurality of feature points on the map 141c. In other words, the division unit 130 generates a boundary line of the Voronoi diagram with a plurality of feature points on the map 141c as the base points of the Voronoi diagram. In the map 141c, there are places where the feature points are partially concentrated. As described above, many boundary lines are partially generated at the relevant location, and many small sub-areas exist.

Therefore, in the division unit 130, as described in step S205 of FIG. 15, when the distance between the two feature points is less than a predetermined distance (more specifically, the two feature points belong to the same point set). Case) Delete the boundary line generated based on the two feature points.

For example, the division unit 130 first generates a boundary line based on a plurality of feature points in the map 141c shown in FIG. 17A. Next, when the distance between the two feature points is less than the predetermined distance L1, the division unit 130 deletes the boundary line generated based on the two feature points. By doing so, the boundary line shown in FIG. 17 (b) is generated.

Further, for example, the division unit 130 first generates a boundary line based on a plurality of feature points in the map 141c shown in FIG. 17A. Next, when the distance between the two feature points is longer than the predetermined distance L1 and less than the predetermined distance L2, the division unit 130 deletes the boundary line generated based on the two feature points. By doing so, the boundary line shown in FIG. 17 (c) is generated.

By appropriately setting the predetermined distance in this way, a plurality of sub-areas including one or more feature points and having a desired area or more can be generated. Further, as described above, when the distance between the feature points among the plurality of feature points belonging to the point set and the distance is less than a predetermined distance, the division unit 130 includes the plurality of feature points belonging to the point set. Delete all borders generated based on any of. For example, when the dividing unit 130 deletes the boundary line depending only on a predetermined distance, a boundary line is generated in which one end of the line segment is not connected to another specified line and another boundary line and exists in the task area. there's a possibility that. Therefore, the dividing unit 130 deletes the boundary line under the above-mentioned conditions even based on the point set. According to this, the boundary line in which one end of the line segment is not connected to other regulation lines and other boundary lines and exists in the task area is also deleted. That is, according to this, line segments unnecessary for forming a subarea can be deleted.

<Split processing>
Subsequently, the details of the task area division process (step S105 shown in FIG. 4) based on the boundary line executed by the map processing device 100 will be described.

For example, as shown in FIG. 17 and the like, the division unit 130 generates a boundary line of the Voronoi diagram with a plurality of feature points as mother points. Here, the boundary line extends to the outside of the area surrounded by the regulation line. The boundary line located outside the area surrounded by the specified line is not necessary as the boundary line for dividing the task area into a plurality of sub-areas. Therefore, the division unit 130 deletes such an unnecessary boundary line. As a result, the amount of information contained in the map divided into a plurality of sub-areas can be reduced.

FIG. 18 is a flowchart showing details of the division process (step S105 shown in FIG. 4) executed by the map processing device 100 according to the embodiment. FIG. 19 is a diagram showing details of the division process executed by the map processing device 100 according to the embodiment. In FIGS. 19A to 19E, two feature points (feature points F9 and feature points F10 shown in FIG. 19A) in the region surrounded by the broken line XIX shown in FIG. 17B. The processing for the line segment S in the boundary line of the Voronoi diagram, which is generated based on the above, is shown.

First, the division unit 130 determines whether or not all the portions of the boundary line of the Voronoi diagram have been analyzed (step S301). That is, the division unit 130 determines whether or not the processes from steps S301 to S309, which will be described later, have been executed for all the portions of the boundary line. For example, the dividing unit 130 classifies the boundary line into one or more straight line portions for each straight line portion of the boundary line, and determines whether or not the analysis has been completed for each of the classified straight line portions.

When it is determined that all the parts of the boundary line of the Voronoi diagram have been analyzed (Yes in step S301), the division unit 130 is based on the part of the boundary line that remains without being deleted in steps S302 to S309 described later. The task area is divided into a plurality of sub-areas (step S310).

On the other hand, when it is determined that all the parts of the boundary line of the Voronoi diagram have not been analyzed (No in step S301), the division unit 130 extracts the part of the boundary line that has not been analyzed (step S302). Here, for example, as shown in FIG. 19A, it is assumed that the dividing portion 130 extracts the line segment S.

Next, the dividing unit 130 determines whether or not the extracted line has an end, and if the line has an end, sets the end as, for example, a point P (step S303). For example, as shown in FIG. 19B, the dividing portion 130 sets both ends of the line segment S as points P.

Next, the dividing unit 130 determines whether or not the line intersects the defined line of the task area, and if it determines that the line intersects the defined line of the task area, the intersection is set to, for example, a point P. Further set (step S304). For example, as shown in FIG. 19C, the dividing portion 130 further sets a point P at the intersection of the line segment S and the specified line.

Next, the dividing unit 130 sets P1, P2, ..., Pn (n is the number of points P) in order with respect to the set points P along a predetermined direction (step S305). The predetermined direction is, for example, the extending direction of the extracted line. For example, as shown in FIG. 19D, the dividing unit 130 sets the points P1, the points P2, and the points P3 in order with respect to the plurality of points P along a predetermined direction.

Next, the dividing unit 130 sets the intermediate point Mk at the intermediate point between the point Pk and the point Pk + 1 (k = 1 to n-1). For example, as shown in FIG. 19 (e), the dividing unit 130 sets the intermediate point M1 at the intermediate point between the points P1 and P2, and sets the intermediate point M2 at the intermediate point between the points P2 and P3. do.

Next, the division unit 130 determines whether or not the intermediate point Mk is located in the task area (step S307).

When the dividing unit 130 determines that the intermediate point Mk is located in the task area (Yes in step S307), the dividing unit 130 holds a line segment connecting the point Pk and the point Pk + 1 (step S308), and returns the process to step S301.

On the other hand, when the dividing unit 130 determines that the intermediate point Mk is not located in the task area (No in step S307), the division unit 130 deletes the line segment connecting the point Pk and the point Pk + 1 (step S309), and processes the process in step S301. return.

For example, as shown in FIG. 19 (f), the dividing portion 130 holds (remains) a line segment connecting the point P1 and the point P2 in the line segment S, and holds the point P2 and the point P3 in the line segment S. Delete the connecting line segment. According to this, the division unit 130 can delete an unnecessary boundary line that does not exist in the task area.

In step S306, the intermediate point Mk is set at the intermediate point between the point Pk and the point Pk + 1, but it may be set at an arbitrary position as long as it is on the line segment connecting the point Pk and the point Pk + 1.

<Specific example>
Subsequently, a specific example of the division of the task area will be described.

20 to 25 are diagrams for explaining a specific example of a map including a plurality of sub-areas generated by the map processing device 100 according to the embodiment. In FIGS. 20 to 25, (a) shows a map in which a map and a Voronoi diagram generated based on the map are superimposed, and (b) shows a map shown in (a) and (a). The boundary line after the deletion process shown in FIG. 15 in the Voronoi diagram shown in a) is shown, and the map shown in (a) and the boundary line after the division process shown in FIG. 18 in the boundary line shown in (b) are shown in (c). Shows a line. That is, (c) shown in FIGS. 20 to 25 is a diagram showing a map (divided map) including a plurality of sub-areas output by the map processing device 100. Further, in each figure, hatching is attached to the task area (and sub-area).

The map 400 shown in FIG. 20A includes a square task area 142a and four feature points corresponding to the four corners of the task area 142a. In this case, Voronoi diagram 410 having four feature points as mother points includes a boundary line consisting of two straight lines. Further, in this case, as shown in FIG. 20B, the boundary line is not deleted by the deletion process shown in FIG. That is, in this case, it indicates that the distance between adjacent (in other words, the closest) feature points is a predetermined distance or more. Further, in this case, as shown in FIG. 20 (c), the map (divided map) 400a including a plurality of sub-areas output by the map processing device 100 includes four sub-areas 148a.

The map 401 shown in FIG. 21 (a) includes an annular task area 142b and eight feature points corresponding to the corners of the task area 142b. In this case, Voronoi diagram 411 with eight feature points as the mother points includes a boundary line consisting of six straight lines. Further, in this case, as shown in FIG. 21B, the boundary line is not deleted by the deletion process shown in FIG. That is, in this case, it indicates that the distance between adjacent feature points is equal to or greater than a predetermined distance. Further, in this case, as shown in FIG. 21 (c), the map (divided map) 401a including a plurality of sub-areas output by the map processing device 100 includes eight sub-areas 148b.

The map 402 shown in FIG. 22A includes an L-shaped task area 142c and six feature points corresponding to the corners of the task area 142c. In this case, the Voronoi diagram 412 with the six feature points as the base points includes a boundary line consisting of ten straight lines. Further, in this case, as shown in FIG. 22B, the boundary line is not deleted by the deletion process shown in FIG. That is, in this case, it indicates that the distance between adjacent feature points is equal to or greater than a predetermined distance. Further, in this case, as shown in FIG. 22 (c), the map (divided map) 402a including a plurality of sub-areas output by the map processing device 100 includes six sub-areas 148c.

The map 403 shown in FIG. 23 (a) includes a task area 142d having an L-shaped portion cut out, and 30 feature points corresponding to the corners of the task area 142d. In this case, the Voronoi diagram 413 having 30 feature points as a mother point includes a boundary line consisting of many straight lines. Further, in this case, as shown in FIG. 23 (b), a part of the boundary line is deleted in the deletion process shown in FIG. That is, in this case, it indicates that the distance between some adjacent feature points is less than a predetermined distance. According to this, for example, the boundary line generated based on a plurality of dense feature points is deleted. Further, in this case, as shown in FIG. 23 (c), the map (divided map) 403a including a plurality of sub-areas output by the map processing device 100 includes 12 sub-areas 148d.

The map 404 shown in FIG. 24A includes a task area 142e having an L-shaped portion cut out, and 30 feature points corresponding to the corners of the task area 142e. That is, the map 404 and the map 403 are the same map. Therefore, the Voronoi diagram 414 generated based on the map 404 is the same as the Voronoi diagram 413. Further, as shown in FIG. 24 (b), a part of the boundary line is deleted in the deletion process shown in FIG. Here, in the figure shown in FIG. 24 (b), more boundary lines are deleted than in the figure shown in FIG. 23 (b). That is, in the example shown in FIG. 24, it is shown that the predetermined distance is set longer than the example shown in FIG. 23. Further, in this case, as shown in FIG. 24 (c), the map (divided map) 404a including a plurality of sub-areas output by the map processing device 100 includes three sub-areas 148e. In this way, a desired number (or desired area) of sub-areas is generated by appropriately setting a predetermined distance.

The map 405 shown in FIG. 25 (a) includes a polygonal task area 142f and 12 feature points corresponding to the corners of the task area 142f. In this case, Voronoi diagram 415 with 12 feature points as the mother points includes a boundary line consisting of many straight lines. Further, in this case, as shown in FIG. 25 (b), a part of the boundary line is deleted in the deletion process shown in FIG. That is, in this case, it indicates that the distance between some adjacent feature points is less than a predetermined distance.

In the specific example shown in FIG. 25, (i) the distance between the feature point F11 and the feature point F12 is less than a predetermined distance, and (ii) the distance between the feature point F12 and the feature point F13 is predetermined. The distance between (iii) feature point F11 and feature point F13 is greater than or equal to a predetermined distance. Further, the straight line B1 is a part of the boundary line generated based on the feature point F11 and the feature point F12. Further, the straight line B2 is a part of the boundary line generated based on the feature point F12 and the feature point F13. Further, the straight line B3 is a part of the boundary line generated based on the feature point F11 and the feature point F13.

In the specific example shown in FIG. 25, the straight line B1 and the straight line B2 are deleted based on the distance between the feature points. On the other hand, the straight line B3 is not deleted based on the distance between the feature points. However, since the feature point F11 and the feature point F13 belong to the same set of points, the straight line B3 is also deleted.

Further, in this case, as shown in FIG. 25 (c), the map (divided map) 405a including a plurality of sub-areas output by the map processing device 100 includes eight sub-areas 148f.

As described above, in any map, the map processing device 100 can generate a map including a sub-area including one or more feature points.

[Effects, etc.]
As described above, the map processing device 100 according to the embodiment divides the task area corresponding to the predetermined area into a plurality of sub-areas included in the map used by the mobile robot 200 that autonomously moves in the predetermined area. It is a map processing device that divides. The map processing device 100 includes an extraction unit 120 that extracts a plurality of feature points corresponding to a plurality of points in a predetermined area where the mobile robot 200 can recognize the position from the task area, and a task area based on the plurality of feature points. Is provided with a division unit 130 for dividing the above into a plurality of sub-areas.

The mobile robot 200 moves while estimating its own position in order to move along the calculated movement path. For example, the laser rangefinder 40 is used to detect information indicating the positions of walls and objects located around the mobile robot 200, and the self-position is estimated using the detected information. The mobile robot 200 estimates its own position by, for example, using a localization algorithm to compare the map 141 with the information detected by the laser rangefinder 40.

Here, for example, when the environment around the mobile robot 200 does not have a wall or an object having an angle for specifying a position such as a straight passage, the laser measurement is performed at the place where the mobile robot 200 is located. Since the information obtained from the sensor such as the distance meter 40 does not change, the self-position cannot be estimated. Therefore, the mobile robot 200 is provided with a dead reckoning navigation system for acquiring odometry information in order to estimate its own position even when moving along such a passage, for example. According to this, the mobile robot 200 can estimate its own position using the odometry information. However, when the mobile robot 200 estimates the self-position using the odometry information, it is estimated to be the actual position as compared with the field where the self-position is estimated using the information obtained from the sensor such as the laser rangefinder 40. The deviation from the position becomes large. That is, when the mobile robot 200 continues to estimate its own position using the odometry information, the deviation between the actual position and the estimated position continues to increase. When information is newly obtained from the laser rangefinder 40, this deviation is reduced by the mobile robot 200 estimating its own position based on the information. The mobile robot 200 performs tasks such as cleaning, minesweeping, or data collection while moving along a calculated movement path, for example. In the mobile robot 200 that moves autonomously while executing such a task, it is required to move all over a predetermined area. However, if the predetermined area is arbitrarily divided into a plurality of sub-areas, the points (features) on the map 141 corresponding to the points that can be detected by the laser rangefinder 40 or the like, in other words, the points that the mobile robot 200 can recognize the position. There is a risk that a sub-area that does not include the point) will be generated. In such a sub-area, there is a high possibility that the self-position estimated by the mobile robot 200 deviates significantly from the actual position. Therefore, the map processing device 100 divides the task area included in the map 141 into a plurality of sub-areas based on a plurality of feature points corresponding to a plurality of points in a predetermined area where the mobile robot 200 can recognize the position. do. According to this, the map processing device 100 can divide the task area so that the feature points are included in each of the plurality of sub-areas, for example. Therefore, when the mobile robot 200 moves in a predetermined space corresponding to a plurality of sub-areas, there is a point where the mobile robot 200 can recognize the position. Therefore, the mobile robot 200 can accurately estimate its own position regardless of whether it travels in any of the plurality of sub-areas. That is, according to the map processing device 100, the task area included in the map 141 can be divided so that the mobile robot 200 that moves autonomously can estimate its own position with high accuracy.

Further, for example, the division unit 130 divides the task area into a plurality of sub-areas so that each of the plurality of sub-areas includes at least one feature point.

According to this, when the mobile robot 200 moves in a predetermined space corresponding to a plurality of sub-areas, there is at least one point at which the mobile robot 200 can recognize the position. Therefore, according to the map processing device 100, for example, the task area included in the map 141 can be divided so that the mobile robot 200 that moves autonomously can estimate its own position with high accuracy.

Further, for example, the division unit 130 generates a Voronoi diagram having a plurality of feature points as a base point, and divides the task area into a plurality of sub-areas by using the boundary line indicating the Voronoi boundary included in the generated Voronoi diagram. ..

According to this, the division unit 130 can divide the task area so that at least one feature point is included in each of the plurality of sub-areas.

Further, for example, the division unit 130 is a point set to which at least two feature points among a plurality of feature points belong, and at least one of the feature points belonging to the point set has a predetermined distance between the feature points. A point set, which is a set of feature points including feature points less than a distance, is generated, and a part of the boundary line generated based on two or more feature points included in the generated point set is deleted.

When a part of the boundary line is deleted based only on a predetermined distance, there may be a straight line portion in the boundary line that is not connected to another boundary line or the specified line. Such a straight line portion is unnecessary because it is not used as a boundary line for dividing the task area into a plurality of sub-areas. Therefore, the division unit 130 generates a point set and determines whether or not to delete the boundary line based on the generated point set. According to this, when a part of the boundary line is deleted based on a predetermined distance, an unnecessary boundary line for dividing into sub-areas can be deleted as well.

Further, for example, at least one of the plurality of sub-areas is a defining line that defines the range of the task area and an area surrounded by a boundary line.

Further, for example, at least one of the plurality of sub-areas is an area surrounded only by a boundary line.

According to these, the task area can be appropriately divided into a plurality of sub-areas.

Further, the map processing method according to the embodiment is a map processing method for dividing a task area corresponding to a predetermined area into a plurality of sub-areas included in a map used by a mobile robot 200 that autonomously moves in a predetermined area. An extraction step (step S102) of extracting a plurality of feature points corresponding to a plurality of points in a predetermined area where the mobile robot 200 can recognize the position from the task area, and a task based on the plurality of feature points. A division step (step S103 to step S105) for dividing the area into a plurality of sub-areas is included.

According to this, for example, the task area can be divided so that the feature points are included in each of the plurality of subareas. Therefore, when the mobile robot 200 moves in a predetermined space corresponding to a plurality of sub-areas, there is a point where the mobile robot 200 can recognize the position. Therefore, the mobile robot 200 can accurately estimate its own position regardless of whether it travels in any of the plurality of sub-areas. That is, according to the map processing method according to the present disclosure, the task area included in the map 141 can be divided, for example, so that the autonomously moving mobile robot 200 can estimate its own position with high accuracy.

Further, the mobile robot 200 according to the embodiment is a mobile robot that autonomously moves in a predetermined area, and includes a map processing device 100, a calculation unit 210 that calculates a movement route for each of a plurality of sub-areas, and a plurality of mobile robots 200. After moving the mobile robot 200 along the movement path in one of the sub-areas of the above, the mobile robot 200 is moved to a position corresponding to the other sub-area among the plurality of sub-areas. A control unit 220 for moving the mobile robot 200 along a movement path in another sub-area is provided.

According to this, the mobile robot 200 can move in a predetermined area while accurately estimating the self-position.

The present invention may be realized as a program for causing a computer to execute the steps included in the processing procedures of the map processing device 100 and the mobile robot 200. Further, the present invention may be realized as a non-temporary recording medium such as a CD-ROM that can be read by a computer that records the above program. The present invention may also be realized as information, data or signals indicating the program. Then, those programs, information, data and signals may be distributed via a communication network such as the Internet.

(Other embodiments)
Although the map processing apparatus and the like according to the present invention have been described above based on the above-described embodiment, the present invention is not limited to the above-described embodiment.

For example, in the above embodiment, the map processing device is arranged inside the main body (housing) of the mobile robot. The map processing device may be arranged outside the mobile robot.

Further, for example, it has been explained that in the above-described embodiment, the processing units such as the extraction unit and the division unit included in the map processing device are realized by the CPU and the control program, respectively. For example, each component of the processing unit may be composed of one or a plurality of electronic circuits. The one or more electronic circuits may be general-purpose circuits or dedicated circuits, respectively. The one or more electronic circuits may include, for example, a semiconductor device, an IC (Integrated Circuit), an LSI (Large Scale Integration), or the like. The IC or LSI may be integrated on one chip or may be integrated on a plurality of chips. Although it is called an IC or LSI here, the name changes depending on the degree of integration, and it may be called a system LSI, a VLSI (Very Large Scale Integration), or a ULSI (Ultra Large Scale Integration). Further, an FPGA (Field Programmable Gate Array) programmed after manufacturing the LSI can also be used for the same purpose.

In addition, general or specific aspects of the present invention may be realized by a system, an apparatus, a method, an integrated circuit or a computer program. Alternatively, it may be realized by a computer-readable non-temporary recording medium such as an optical disk, HDD (Hard Disk Drive) or semiconductor memory in which the computer program is stored. Further, it may be realized by any combination of a system, a device, a method, an integrated circuit, a computer program and a recording medium.

In addition, it is realized by arbitrarily combining the components and functions in the embodiment and the modification obtained by applying various modifications that a person skilled in the art can think of, and within the range that does not deviate from the gist of the present invention. Also included in the present invention.

The present invention is a device that divides a map used by an autonomously moving mobile robot into a plurality of sub-areas, and a movement that calculates a movement route for each of the plurality of sub-areas and moves along the calculated movement route. Applicable to robots.

10 Main body 11 Suction port 20 Wheels 30 Side brush 40 Laser rangefinder 50 Main brush 60 Camera 70 Depth sensor 100 Map processing device 110 Acquisition unit 120 Extraction unit 130 Dividing unit 140 Storage unit 141, 141a, 141b, 141c, 400, 401, 402, 403, 404, 405 Map 142, 142a, 142b, 142c, 142d, 142e, 142f Task area 143, 143a Default line 144, 144a, 144b, F1, F2, F3, F4, F5, F6, F7, F8, F9, F10, F11, F12, F13 Feature points 145, 145a, 145b Boundary line 146 Voronoi cell 147, 147a, 147b, 410, 411, 421, 413, 414, 415 Voronoi diagram 148, 148a, 148b, 148c, 148d , 148e, 148f Subarea 149 Marker part 149a Curved part 200 Mobile robot 210 Calculation part 220 Control part 230 Detection part 240 Moving part 250 Cleaning part 300, 301 Point set 310 Arc 400a, 401a, 402a, 403a, 404a, 405a Map ( Divided map)
B1, B2, B3 straight line L1, L2 Predetermined distance M1, M2 Midpoint S line segment P, P1, P2, P3 point

Claims (8)

A map processing device that divides a task area corresponding to a predetermined area into a plurality of sub-areas, which is included in a map used by a mobile robot that autonomously moves in a predetermined area.
An extraction unit that extracts a plurality of feature points corresponding to a plurality of points in the predetermined area where the mobile robot can recognize the position from the task area.
A map processing device including a division unit that divides the task area into a plurality of sub-areas based on the plurality of feature points. The map processing device according to claim 1, wherein the division unit divides the task area into the plurality of sub-areas so that each of the plurality of sub-areas includes at least one feature point. The division unit generates a Voronoi diagram having the plurality of feature points as a base point, and divides the task area into the plurality of sub-areas by using a boundary line indicating a Voronoi boundary included in the generated Voronoi diagram. Item 2. The map processing apparatus according to item 1 or 2. The divided portion is a point set to which at least two feature points among the plurality of feature points belong, and at least one of the feature points belonging to the point set, the distance between the feature points is less than a predetermined distance. According to claim 3, a point set that is a set of feature points including feature points is generated, and a portion of the boundary line generated based on two or more feature points included in the generated point set is deleted. The map processing device described. The map processing device according to claim 3 or 4, wherein at least one of the plurality of sub-areas is a defined line defining the range of the task area and an area surrounded by the boundary line. The map processing apparatus according to any one of claims 3 to 5, wherein at least one of the plurality of sub-areas is an area surrounded only by the boundary line. A map processing method for dividing a task area corresponding to a predetermined area into a plurality of sub-areas, which is included in a map used by a mobile robot that autonomously moves in a predetermined area.
An extraction step of extracting a plurality of feature points corresponding to a plurality of points in the predetermined area where the mobile robot can recognize the position from the task area.
A map processing method including a division step of dividing the task area into a plurality of sub-areas based on the plurality of feature points. A mobile robot that autonomously moves in a predetermined area.
The map processing device according to any one of claims 1 to 6.
A calculation unit that calculates a movement route for each of the plurality of sub-areas,
After moving the mobile robot along the movement path in one of the plurality of sub-areas, the mobile robot is moved to a position corresponding to the other sub-areas in the plurality of sub-areas. A mobile robot including a control unit for moving the mobile robot along a movement path in the other sub-area.

Images