KR20180037516A - Moving robot and control method thereof - Google Patents

Abstract

The present invention relates to a moving robot, and a controlling method thereof. The moving robot according to one embodiment of the present invention comprises: a moving unit for moving a main body; an image acquiring unit acquiring an image around the main body; a storage unit for storing the image acquired by the image acquiring unit; and a control unit setting a virtual wall based on position data of a recognized marker when the marker in which a specific pattern is formed in the image acquired by the image acquiring unit is recognized. Therefore, the present invention can set the virtual wall without any additional configuration.

Description

[0001] Moving robot and control method [0002]

The present invention relates to a mobile robot and a control method thereof, and more particularly, to a mobile robot capable of recognizing a marker and setting a virtual wall and a control method thereof.

Robots have been developed for industrial use and have been part of factory automation. In recent years, medical robots, aerospace robots, and the like have been developed, and household robots that can be used in ordinary homes are being developed. Among these robots, mobile robots capable of traveling by magnetic force are called mobile robots.

A typical example of a mobile robot used in the home is a robot cleaner. The robot cleaner is a device for cleaning a corresponding area by suctioning dust or foreign matter around the robot while running a certain area by itself.

The mobile robot is capable of moving by itself, is free to move, and is equipped with a plurality of sensors for avoiding obstacles during running, and can travel without obstacles.

In general, an infrared sensor or an ultrasonic sensor is used to detect an obstacle of a mobile robot. The infrared sensor senses the presence and distance of the obstacle through the amount of reflected light or the time of reflected light reflected by the obstacle, and when the ultrasonic sensor emits an ultrasonic wave having a predetermined period and there is an ultrasonic wave reflected by the obstacle, And the distance between the obstacle and the obstacle is determined using the time difference between the moment when the obstacle is reflected and the time when the obstacle is reflected.

On the other hand, obstacle recognition and avoidance have a great influence on the cleaning performance as well as the running performance of the mobile robot, and therefore it is required to secure the reliability of the obstacle recognition capability.

In addition, there is an increasing research on methods for setting virtual walls for various purposes such as prevention of entry of a mobile robot into a specific area, prevention of departure from a specific area, and avoidance of obstacles that the sensor can not detect.

Prior Art 1 discloses a technology for providing virtual wall information on an obstacle that is additionally generated on a robot map in advance from a robot manager in order to effectively cope with an obstacle that has not been detected (JP-A-10-2014-0087486) . However, the conventional art 1 has an inconvenience that the administrator must input virtual wall information in advance.

Prior Art 2 (Laid-Open Patent Publication No. 10-2006-0129960) discloses a technique using a marker having a light emitting element to calculate the position and posture of a mobile robot in a moving area. Conventional art 2 uses the light emission interval or light emission order of a plurality of light emitting elements in the marker as identification data of the marker. Therefore, the conventional art 2 has a problem in that the cost increases because the markers must each include the light emitting element, the light emission interval, the order and the like of the light emitting elements must be accurately controlled, and the risk of false recognition may increase.

Prior Art 3 (Laid-Open Patent Publication No. 10-2012-0054669) uses a beacon, which has a problem in that a beacon emitter and a beacon sensor responding to beacon emission must be provided.

1. Published Japanese Patent Application No. 10-2014-0087486 (Published on July 9, 2014) 2. Open Patent Publication No. 10-2006-0129960 (published on December 18, 2006) 3. Published Patent Application No. 10-2012-0054669 (Published on May 30, 2012)

SUMMARY OF THE INVENTION It is an object of the present invention to provide a mobile robot and a control method thereof that can set a virtual wall and travel based on a set virtual wall without any additional configuration.

An object of the present invention is to set a virtual wall using a low-cost marker.

An object of the present invention is to provide a mobile robot and a control method thereof that can improve the stability of the mobile robot itself and the user's convenience by running based on the set virtual wall, and improve the operation efficiency and cleaning efficiency.

According to one aspect of the present invention, there is provided a mobile robot including a traveling unit for moving a main body, an image acquisition unit for acquiring images around the main body, a storage unit for storing images acquired by the image acquisition unit, And a controller configured to set a virtual wall based on the position data of the recognized marker when a marker having a specific pattern is recognized in the image acquired by the image acquisition unit, You can set the wall.

According to another aspect of the present invention, there is provided a method of controlling a mobile robot including the steps of: acquiring a moving image; recognizing a marker having a specific pattern formed on the acquired image; , And setting a virtual wall based on the positional data of the recognized marker.

According to at least one of the embodiments of the present invention, it is possible to provide a mobile robot and its control method that can set a virtual wall and travel based on a set virtual wall without any additional configuration.

Further, according to at least one of the embodiments of the present invention, a virtual wall can be set using a low-cost marker.

Further, according to at least one of the embodiments of the present invention, traveling based on the set virtual wall improves the stability of the mobile robot itself and the user's convenience, and improves the operation efficiency and the cleaning efficiency.

Meanwhile, various other effects will be directly or implicitly disclosed in the detailed description according to the embodiment of the present invention to be described later.

1 is a perspective view illustrating a mobile robot and a charging stand for charging the mobile robot according to an embodiment of the present invention.
FIG. 2 is a top view of the mobile robot shown in FIG. 1. FIG.
FIG. 3 is a front view of the mobile robot shown in FIG. 1. FIG.
Fig. 4 is a view showing a bottom portion of the mobile robot shown in Fig. 1. Fig.
FIG. 5 is a block diagram illustrating a control relationship between main components of a mobile robot according to an embodiment of the present invention. Referring to FIG.
FIG. 6 is a diagram illustrating an example of region classification and map generation according to an embodiment of the present invention.
FIGS. 7 and 8 are views referred to the description of the marker according to the embodiment of the present invention.
FIG. 9 and FIG. 10 are diagrams referred to in explaining the marker recognition of the mobile robot according to the embodiment of the present invention.
11 and 12 are views referred to the description of the marker according to the embodiment of the present invention.
13 is a flowchart illustrating a method of controlling a mobile robot according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, it is needless to say that the present invention is not limited to these embodiments and can be modified into various forms.

In the drawings, the same reference numerals are used for the same or similar parts throughout the specification.

The suffix "module" and " part "for components used in the following description are given merely for convenience of description and do not give special significance or role in themselves. Accordingly, the terms "module" and "part" may be used interchangeably.

The mobile robot 100 according to an embodiment of the present invention refers to a robot that can move by itself using wheels or the like, and may be a home helper robot and a robot cleaner. Hereinafter, a robot cleaner having a cleaning function of a mobile robot will be described with reference to the drawings, but the present invention is not limited thereto.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a perspective view illustrating a mobile robot and a charging station for charging the mobile robot according to an embodiment of the present invention. FIG. 2 is a top view of the mobile robot shown in FIG. 1, FIG. 4 is a view illustrating a bottom portion of the mobile robot shown in FIG. 1; FIG.

FIG. 5 is a block diagram illustrating a control relationship between main components of a mobile robot according to an embodiment of the present invention. Referring to FIG.

1 to 5, the mobile robot 100 includes a main body 110 and an image acquisition unit 120 for acquiring images around the main body 110. Hereinafter, in defining each part of the main body 110, a portion facing the ceiling in the running zone is defined as a top surface portion (see FIG. 2), and a portion facing the bottom in the running zone is defined as a bottom surface portion And a portion facing the running direction among the portions forming the circumference of the main body 110 between the upper surface portion and the bottom surface portion is defined as a front surface portion (see FIG. 3).

The mobile robot 100 includes a traveling unit 160 for moving the main body 110. The driving unit 160 includes at least one driving wheel 136 for moving the main body 110. The driving unit 160 includes a driving motor (not shown) connected to the driving wheels 136 to rotate the driving wheels. The driving wheels 136 may be provided on the left and right sides of the main body 110 and will be referred to as the left wheel 136 (L) and the right wheel 136 (R), respectively.

The left wheel 136 (L) and the right wheel 136 (R) may be driven by a single drive motor, but may be driven by a left wheel drive motor and a right wheel 136 (R) And a right wheel drive motor for driving the right wheel drive motor. The running direction of the main body 110 can be switched to the left or right side by making a difference in rotational speed between the left wheel 136 (L) and the right wheel 136 (R).

A suction port 110h for sucking in air may be formed on the bottom surface of the main body 110. A suction device for supplying suction force for sucking air through the suction port 110h is provided in the main body 110 And a dust container (not shown) for dust collecting with the air through the suction port 110h.

The main body 110 may include a case 111 forming a space in which various components constituting the mobile robot 100 are accommodated. An opening for inserting and removing the dust container may be formed in the case 111, and a dust container cover 112 for opening and closing the opening may be rotatably provided with respect to the case 111.

An auxiliary brush 135 having a brush having a plurality of blades extending radially and located on the front side of the bottom surface of the main body 110, May be provided. By the rotation of the brushes 134 and 135, the dusts are separated from the floor in the traveling zone, and the dusts separated from the floor are sucked through the suction port 110h and collected in the dustbin.

The battery 138 supplies not only the drive motor but also the power necessary for the overall operation of the mobile robot 100. When the battery 138 is discharged, the mobile robot 100 can return to the charging station 200 for charging. During the returning operation, the mobile robot 100 can automatically set the position of the charging station 200 Can be detected.

The charging stand 200 may include a signal transmitting unit (not shown) for transmitting a predetermined return signal. The return signal may be an ultrasound signal or an infrared signal, but is not necessarily limited thereto.

The mobile robot 100 may include a signal sensing unit (not shown) for receiving a return signal. The charging base 200 may transmit an infrared signal through a signal transmitting unit, and the signal sensing unit may include an infrared sensor that senses an infrared signal. The mobile robot 100 moves to the position of the charging base 200 according to the infrared signal transmitted from the charging base 200 and docks with the charging base 200. [ And charging is performed between the charging terminal 133 of the mobile robot 100 and the charging terminal 210 of the charging stand 200 by such docking.

The image acquisition unit 120 photographs a driving area, and may include a digital camera. A digital camera includes an image sensor (e.g., a CMOS image sensor) configured with at least one optical lens, and a plurality of photodiodes (e.g., pixels) that are formed by light passing through the optical lens, And a digital signal processor (DSP) that forms an image based on signals output from the photodiodes. The digital signal processor is capable of generating moving images composed of still frames as well as still images.

Preferably, the image acquiring unit 120 is provided on the upper surface of the main body 110 to acquire images of the ceiling in the driving area. However, the position and the photographing range of the image acquiring unit 120 must be limited thereto no. For example, the image acquisition unit 120 may be provided to acquire an image in front of the main body 110.

In this embodiment, a camera is installed in a part (ex, top part) of the mobile robot to acquire an image while driving. In addition, an image captured by the camera can be used to recognize a marker existing in the space.

In addition, the mobile robot 100 may further include an obstacle detection sensor 131 for detecting an obstacle ahead. The mobile robot 100 may further include a cliff detection sensor 132 for detecting the presence or absence of a cliff on the floor in the driving area and a lower camera sensor 139 for obtaining a bottom image.

In addition, the mobile robot 100 includes an operation unit 137 which can be turned on / off or input various commands. Various control commands necessary for the overall operation of the mobile robot 100 can be inputted through the operation unit 137. [ In addition, the mobile robot 100 can display reservation information, a battery state, an operation mode, an operation state, an error state, and the like, including an output unit (not shown).

Referring to FIG. 5, the mobile robot 100 includes a controller 140 for processing and determining various information such as a current position, and a storage unit 150 for storing various data. The mobile robot 100 may further include a communication unit 190 for transmitting and receiving data to / from an external terminal.

The external terminal is provided with an application for controlling the mobile robot 100. The mobile robot 100 displays a map of a traveling area to be cleaned by the mobile robot 100 through the execution of the application and can designate a region for cleaning a specific area on the map have. The external terminal may be, for example, a remote controller, a PDA, a laptop, a smart phone, or a tablet on which an application for setting a map is mounted.

The external terminal communicates with the mobile robot 100 to display the current position of the mobile robot together with the map, and information about a plurality of regions can be displayed. Further, the external terminal updates its position and displays it according to the traveling of the mobile robot.

The control unit 140 controls the overall operation of the mobile robot 100 by controlling the image acquisition unit 120, the operation unit 137, and the travel unit 160 constituting the mobile robot 100.

The storage unit 150 records various types of information required for controlling the mobile robot 100, and may include a volatile or nonvolatile recording medium. The storage medium stores data that can be read by a microprocessor, and includes a hard disk drive (HDD), a solid state disk (SSD), a silicon disk drive (SDD), a ROM, a RAM, a CD- Tape, floppy disk, optical data storage, and the like.

Also, the storage unit 150 may store a map of the driving area. The map may be input by an external terminal capable of exchanging information with the mobile robot 100 through wired or wireless communication, or may be generated by self-learning by the mobile robot 100.

The map can display the location of the rooms in the driving area. In addition, the current position of the mobile robot 100 can be displayed on the map, and the current position of the mobile robot 100 on the map can be updated in the course of travel. The external terminal stores the same map as the map stored in the storage unit 150.

The map for the driving area stored in the storage unit 150 may include at least one of a navigation map used for traveling during cleaning, a simultaneous localization and mapping (SLAM) map used for position recognition, A learning map used for learning cleaning, a global position map used for global position recognition, an obstacle recognition map for recording information about recognized obstacles, and the like.

Meanwhile, although the maps can be separately stored and managed in the storage unit 150 according to the usage as described above, the maps may not be clearly classified for each use. For example, a plurality of pieces of information may be stored in one map for use in at least two applications.

The control unit 140 includes a travel control module 141, a zone classification module 142, a learning module 143, and a recognition module 144.

The travel control module 141 controls the travel of the mobile robot 100, and controls the travel of the travel unit 160 according to the travel setting. In addition, the travel control module 141 can grasp the travel path of the mobile robot 100 based on the operation of the travel unit 160. [ For example, the driving control module 141 can grasp the current or past traveling speed and the traveling distance of the mobile robot 100 based on the rotational speed of the driving wheel 136, L), 136 (R)), the current or past direction change process can be grasped. Based on the travel information of the mobile robot 100, the position of the mobile robot 100 on the map can be updated.

The zone classification module 142 may divide the traveling zone into a plurality of zones according to a predetermined criterion. The travel zone can be defined as a range including all of the area on the plane where the mobile robot 100 is experiencing driving and the area on the plane on which the mobile robot 100 is traveling.

The zone division module 142 divides the traveling zone into a plurality of sub-zones, and the sub-zone may be divided based on each room (room) in the traveling zone. In addition, the zone division module 142 can divide the traveling zone into a plurality of large zones separated from each other in terms of driving capability. For example, two indoor spaces completely separated from each other by a line can be divided into two major zones, respectively. As another example, even in the same indoor space, the large area can be divided based on each layer in the driving area.

The learning module 143 may generate a map of the driving area. Also, the learning module 143 processes the image acquired through the image acquisition unit 120 at each position and recognizes the global position in association with the map.

The recognition module 144 estimates and recognizes the current position. The recognition module 144 grasps the position in cooperation with the learning module 143 by using the image information of the image acquisition unit 120 so that the current position is estimated and recognized even when the position of the mobile robot 100 suddenly changes can do.

The mobile robot 100 learns the position during continuous travel through the zone classifying module 142 and learns the map through the learning module 143 and the recognition module 144 without the zone classifying module 142 The current position can be estimated.

During traveling of the mobile robot 100, the image acquisition unit 120 acquires images around the mobile robot 100. Hereinafter, the image acquired by the image acquisition unit 120 is defined as an 'acquired image'. The acquired image includes various features such as lights, edges, corners, blobs, ridges, etc., located on the ceiling.

The learning module 143 detects features from each of the acquired images. Various methods for detecting features from an image in the field of Computer Vision (Feature Detection) are well known. Several feature detectors suitable for detecting these features are known. For example, Canny, Sobel, Harris & Stephens / Plessey, SUSAN, Shi & Tomasi, Level curve curvature, FAST, Laplacian of Gaussian, Difference of Gaussians, Determinant of Hessian, MSER, PCBR and Gray-level blobs detector.

The learning module 143 calculates a descriptor based on each minutiae point. The learning module 143 may convert the feature point into a descriptor using a Scale Invariant Feature Transform (SIFT) technique for feature detection. The descriptor may be denoted by an n-dimensional vector.

The SIFT can detect unchanging features with respect to the scale, rotation, and brightness change of the object to be photographed. Even if the same region is photographed with a different attitude of the mobile robot 100 (i.e., -invariant) can be detected. Of course, various other techniques (e.g., HOG: Histogram of Oriented Gradient, Haar feature, Fems, Local Binary Pattern (LBP), Modified Census Transform (MCT)) may be applied.

The learning module 143 classifies at least one descriptor for each acquired image into a plurality of groups according to a predetermined lower classification rule on the basis of the descriptor information obtained through the acquired image of each position, The included descriptors can be converted into lower representative descriptors, respectively.

As another example, it is also possible to classify all descriptors gathered from acquired images in a predetermined area, such as a room, into a plurality of groups according to a predetermined sub-classification rule, and write descriptors included in the same group according to the predetermined lower representative rule, . ≪ / RTI >

The learning module 143 can obtain the feature distribution of each position through this process. Each position feature distribution can be represented as a histogram or an n-dimensional vector. As another example, the learning module 143 can estimate an unknown current position based on the descriptors calculated from each feature point, without going through a predetermined lower classification rule and a predetermined lower representative rule.

In addition, when the current position of the mobile robot 100 becomes an unknown state due to a positional jump or the like, the current position can be estimated based on data such as a previously stored descriptor or a lower representative descriptor.

The mobile robot 100 acquires an acquired image through the image acquisition unit 120 at an unknown current position. Through the image, various features such as lights, edges, corners, blobs, ridges, etc., are found on the ceiling.

The recognition module 144 detects the features from the acquired image. Various methods of detecting features from an image in the field of computer vision technology and descriptions of various feature detectors suitable for detecting these features are as described above.

The recognition module 144 calculates the recognition descriptor through the recognition descriptor calculating step S31 based on each recognition minutiae. Here, the recognition minutiae and the recognition descriptor are used to describe the process performed by the recognition module 144, and distinguish it from the term describing the process performed by the learning module 143. [ However, the characteristics of the external world of the mobile robot 100 are merely defined by different terms.

The recognition module 144 may convert recognition feature points into recognition descriptors using a Scale Invariant Feature Transform (SIFT) technique for detecting the feature. The recognition descriptor may be denoted by an n-dimensional vector.

As described above, the SIFT selects characteristic points that are easily distinguishable, such as corner points, from the acquired image, and then determines the distribution characteristics of the brightness gradient of pixels belonging to a certain region around each characteristic point ) Is an image recognition technique that obtains an n-dimensional vector (vector) in which the degree of change in each direction is a numerical value for each dimension.

Based on at least one recognition descriptor information obtained through an acquired image of an unknown current position, the recognition module 144 generates position information (for example, feature distribution of each position) Into a comparable information (lower recognition feature distribution).

According to a predetermined lower comparison rule, each position feature distribution can be compared with each recognition feature distribution to calculate each similarity. The similarity degree (probability) is calculated for each position corresponding to each position, and the position where the greatest probability is calculated can be determined as the current position.

In this way, the control unit 140 can distinguish the driving zone, generate a map composed of a plurality of areas, or recognize the current position of the main body 110 based on the pre-stored map.

When the map is generated, the control unit 140 transmits the generated map to the external terminal through the communication unit 190. Also, as described above, the control unit 140 can store the map in the storage unit when the map is received from the external terminal.

In addition, when the map is updated during travel, the controller 140 transmits the updated information to the external terminal so that the map stored in the external terminal and the mobile robot 100 are the same. As the map stored in the external terminal and the mobile robot 100 are kept the same, the mobile robot 100 can clean the designated area with respect to the cleaning command from the mobile terminal, and the current position of the mobile robot So that it can be displayed.

At this time, the map is divided into a plurality of areas in the cleaning area, and includes a connection path connecting the plurality of areas, and includes information on the obstacles in the area. The division for the cleaning area is divided into a small area and a large area by the area classification module 142 as described above.

When the cleaning command is inputted, the control unit 140 determines whether or not the position on the map matches the current position of the mobile robot. The cleaning command can be input from the remote controller, the operation unit, or an external terminal.

If the current position does not coincide with the current position on the map or the current position can not be confirmed, the controller 140 recognizes the current position and restores the current position of the mobile robot 100, And to move to the designated area.

If the current position does not match the position on the map or the current position can not be confirmed, the recognition module 144 analyzes the acquired image input from the image acquisition unit 120 and estimates the current position based on the map have. In addition, the zone classification module 142 or the learning module 143 may also recognize the current location as described above.

After recognizing the position and restoring the current position of the mobile robot 100, the travel control module 141 calculates the travel route from the current position to the designated area and controls the travel unit 160 to move to the designated area.

When at least one of the plurality of areas is selected from the external terminal, the travel control module 141 sets the selected area as the designated area and calculates the travel route. The travel control module 141 performs cleaning after moving the designated area.

On the other hand, when a plurality of areas is selected as the designated area, the travel control module 141 determines whether or not the priority area is set among the plurality of areas, or whether or not the cleaning order for the selected plurality of designated areas is set, Move to perform cleaning.

When one of the plurality of designation areas is set as the priority area, the travel control module 141 moves to the priority area among the plurality of designation areas, cleans the priority area first, and moves to the remaining designation area to clean. In addition, when the cleaning order for the designated area is set, the travel control module 141 performs cleaning while sequentially moving the designated area according to the designated cleaning order.

In addition, when a new arbitrary area is set irrespective of the division of a plurality of areas on the map, the travel control module 141 moves to the set designated number of miles to perform cleaning.

The control unit 140 stores the cleaning history in the storage unit 150 when the cleaning of the designated area is completed.

The control unit 140 may transmit the operation state or the cleaning state of the mobile robot 100 to the external terminal at predetermined intervals through the communication unit 190. Accordingly, the external terminal displays the position of the mobile robot along with the map on the screen of the application being executed based on the received data, and can also output information on the cleaning state.

FIG. 6 is a diagram showing an example of area classification of the mobile robot according to the present invention and generation of the map. FIG.

6A, if the stored map does not exist, the mobile robot 100 can generate a map while traveling through the driving zone X1 through the wall follow-up.

The zone classification module 142 generates a map as shown in FIG. 6 (c) by dividing the driving zone X1 into a plurality of zones A1 'to A9', as shown in FIG. 6 (b) . The generated map is stored in the storage unit 150 and transmitted to the external terminal through the communication unit 190. The zone division module 142 divides the small area and the large area into the driving area X1 as described above, and generates a map accordingly.

The external terminal executes the application and displays the received map on the screen. At this time, the plurality of divided regions A1 to A9 are displayed differently. A plurality of areas A1 to A9 are displayed in different colors or different names are displayed on the map.

When the cleaning command is input, the mobile robot 100 determines the current position based on the stored map. If the current position coincides with the position on the map, the mobile robot 100 performs the designated cleaning. If the current position does not match, Recognize and repair the location and perform cleaning. Accordingly, the mobile robot 100 can perform cleaning by moving to a designated area after determining the current position regardless of any of the plurality of areas A1 to A9.

1 to 5, the mobile robot 100 according to an embodiment of the present invention includes a traveling unit 160 for moving the main body 110, A storage unit 150 for storing an image acquired by the image acquisition unit 120 and a control unit 140 for controlling the overall operation of the mobile robot 100 .

The controller 140 sets a virtual wall based on the position data of the recognized marker when a marker having a specific pattern formed on the image acquired by the image acquiring unit 120 is recognized .

FIGS. 7 and 8 are views referred to the description of the marker according to the embodiment of the present invention, and FIGS. 9 and 10 are views referred to the description of the marker recognition of the mobile robot according to the embodiment of the present invention.

Referring to FIG. 7, the marker 700 may include a specific pattern 710. The pattern 710 may be printed or attached to a portion of the outer surface of the marker 700.

Referring to FIG. 8, a user may attach or install one or more markers 701 and 702 at a position where a virtual wall is to be set. The virtual wall can act as a boundary line or a forbidden area in which the mobile robot should not move even if the mobile robot 100 recognizes it as an actual wall and is a passable area.

For example, markers 701 and 702 may be attached to the left and right door frames of the door 800 to prevent the mobile robot 100 from going out of the home entrance.

9A illustrates an input image acquired by the image acquisition unit 120 and FIG. 9B illustrates a case where the control unit 140 receives a marker (FIG. 9A) 701, and 702) are recognized.

The control unit 140 recognizes the markers 701 and 702 and can set an area corresponding to the position of the recognized markers 701 and 702 as a virtual wall.

When the virtual wall is set in the door 800, the mobile robot 100 recognizes that there is a wall at the corresponding position even when the door 800 is opened, So that it does not come out of the casing 800.

The control unit 140 may control the driving unit 160 to avoid or run on the wall corresponding to the virtual wall. Therefore, the mobile robot 100 can move without passing through the area corresponding to the virtual wall, but without leaving the predetermined area.

The specific pattern 710 may be a geometric pattern used to set a virtual wall, and may be a geometric pattern that is distinguished from a background such as a circle, a square, and the like.

Preferably, as shown in FIG. 7, the specific pattern 710 has an asymmetric shape, so that it can include relatively more feature points such as a corner, and the recognition rate can be further improved.

Meanwhile, the preset pattern corresponding to the virtual wall may be stored in the storage unit 150 of the mobile robot 100, and when the preset pattern is recognized, the control unit 140 may proceed to the process for setting the virtual wall .

When the marker including the specific pattern for virtual wall setting is recognized in the image acquired by the image acquisition unit 120 during driving, the controller 140 controls the position of the marker and the map stored in the storage unit 150, And a virtual wall can be set in the map based on the position of the marker.

The controller 140 may register information on the set virtual wall in a map stored in the storage unit 150 and store and manage the virtual wall in association with the map.

The control unit 140 extracts a pattern 710 of the marker 700 from the image acquired by the image obtaining unit 120. When the extracted pattern 710 is a predetermined pattern for virtual wall setting, Can be determined.

The recognition module 144 may analyze the acquired image input from the image acquisition unit 120 and estimate the current position of the mobile robot 100 based on the map. Also, the zone classification module 142 or the learning module 143 can recognize the current position as described above.

The mobile robot 100 can determine the direction and the distance in which the marker 700 is positioned with respect to the mobile robot 100 based on the size and angle of the pattern 710 to be recognized.

In addition, the mobile robot 100 can determine the position information of the marker 700 by using its current position, the direction and the distance in which the marker 700 is positioned.

Preferably, the use of two or more markers 701 and 702 is more effective in determining the position information of the markers 701 and 702 and setting the virtual walls.

The two or more markers 701 and 702 may be disposed apart from each other and may be disposed, for example, in the left and right door frames of the door 800 to be set as a virtual wall as shown in FIG.

When the patterns included in the markers 701 and 702 arranged in the left and right door frames are recognized, the size of the door 800 can be estimated. For example, the controller 140 may estimate the size of the door 800 using a known homography-based image processing technique.

The image obtained by the camera of the image obtaining unit 120 is usually a two-dimensional plane image, but the feature point can be found in the two-dimensional image and converted into three-dimensional feature points.

The feature points included in the obtained two-dimensional plane image can be converted into three-dimensional feature points by homography obtained by a known method such as a DLT (Direct Linear Transformation) algorithm.

The controller 140 may obtain positional information of two or more markers 701 and 702 spaced apart from each other. The positional information may reflect the positions of the markers 701 and 702 on the three-dimensional space in which the actual distance from the mobile robot 150 to the markers 701 and 702 is considered.

Meanwhile, when two or more markers 701 and 702 are recognized, the control unit 140 can set the virtual wall based on a virtual line connecting the recognized markers 701 and 702. [

For example, the control unit 140 may set virtual walls between the recognized markers 701 and 702, set the coordinates of the left marker 701 to the start coordinates of the virtual wall, 702 can be set as the end coordinates of the virtual wall. Accordingly, the virtual wall can be set so as to best match the intention of the user to attach the markers 701 and 702.

In addition, when one marker is recognized, the controller 140 may set the virtual wall to a predetermined area centered on the position of the recognized one marker.

For example, the controller 140 may set the coordinates of the recognized coordinates of the marker of one marker as the coordinates of the center of the virtual wall, and may set an area of the virtual wall within a predetermined distance from the coordinates of the center of the marker.

Alternatively, when one marker is recognized, the control unit 140 may set the virtual wall to a predetermined area starting from the position of the recognized one marker.

10A illustrates an input image acquired by the image acquisition unit 120 and FIG. 10B illustrates a case where a control unit 140 receives a marker (FIG. 10A) 703) is recognized.

It may be configured to set a virtual wall with only one marker 703 without using a plurality of markers according to an embodiment.

In this case, the control unit 140 sets the virtual wall around a position of the recognized one marker 703 as a center, or sets a position of the recognized one marker 703 as a starting point The virtual wall can be set to a predetermined area.

Alternatively, the recognized one marker 703 may be one of a plurality of markers.

When one marker 703 is recognized, the control unit 140 can set the virtual wall to a predetermined area starting from the position of the recognized one marker 703. FIG.

In this case, it is more preferable that the pattern included in the marker 703 is formed in an asymmetric shape. When the pattern is formed asymmetrically, since the shapes are different in the left and right or up and down directions, it can be used as the direction information.

Taking the pattern 710 illustrated in FIG. 7 as an example, the pattern 710 differs in its inner shape from the upper left corner and the remaining corners. Accordingly, the virtual wall can be set to the left side of the marker 700 corresponding to the left corner. Alternatively, a virtual wall may be set in a different direction.

Meanwhile, the image acquiring unit 120 may include at least one camera installed upward or forward. 2 shows a general example in which one camera 120 is installed facing upward.

In this case, the camera may include a lens having a wide angle of view so that a wide area around the camera can be photographed. In the case of using a wide-angle lens having a wide angle of view, the shooting distance may be shorter than the case of using a general lens depending on its performance.

Therefore, it is necessary to improve the visibility of the marker and the pattern in order to increase the recognition rate of the marker while commonly using the camera used for position recognition.

Referring to FIG. 7, the marker 700 may include a specific pattern 710 formed in a color and a white background area 720 and 730 disposed around the specific pattern.

For efficient recognition of the pattern, the pattern can be composed of a color contrasting with the background color. The entire area having a predetermined size (a * b) smaller than the size (c * d) of the external white background area 730 may be formed in a colored pattern.

More preferably, the pattern 710 can be recognized more easily by treating the inside 720 and the outside 730 of the colored pattern 710 with a white background, respectively.

Alternatively, the marker may be a solid figure having a predetermined volume.

That is, the marker may be a polygonal or circular plane figure or a three-dimensional figure having a predetermined volume. Since the marker itself has a specific shape, the recognition rate of the marker can be improved.

11 and 12 are views referred to the description of the marker according to the embodiment of the present invention. FIG. 11 illustrates markers constructed in a plan view, and FIG. 12 illustrates markers constructed in a plan view.

Referring to FIG. 11A, a pattern 1111 may be printed or attached inside the marker 1110 of a triangle.

Alternatively, a pattern 1121 may be formed inside the pentagonal marker 1120 as shown in FIG. 11 (b), or a pattern 1131 may be formed inside the circular marker 1130 as shown in FIG. 11 (c) .

Or an elliptical marker or the square marker illustrated in Fig. 7 may be used.

12 (a) illustrates a pattern 1211 formed on at least one surface of a marker 1210 formed in a cubic shape of a rectangular parallelepiped. FIG. 12 (b) illustrates a marker 1220 And a pattern 1221 formed on the outer surface of the substrate 1210. [

As in the case of the markers illustrated in FIGS. 11 and 12, the marker may have a specific shape and the mobile robot may recognize the shape of the marker itself, thereby increasing the recognition rate.

13 is a flowchart illustrating a method of controlling a mobile robot according to an embodiment of the present invention.

Referring to FIG. 13, first, the mobile robot 100 moves according to an instruction or a setting and performs cleaning (S1310). During movement, the image acquisition unit 120 acquires an image around the main body 110 (S1320).

The image obtaining unit 120 may perform image processing such as brightness adjustment, noise removal, and color correction of the obtained image.

In operation S1330, the controller 140 may recognize a marker having a predetermined pattern for virtual wall setting in the acquired image.

Based on the recognized marker, the control unit 140 can calculate the positional information of the marker based on the size and shape of the marker and the pattern, the distance between the markers, and the distance between the marker and the mobile robot 100.

According to the recognition of the marker and / pattern, the controller 140 may set an area corresponding to the recognized position of the marker as a virtual wall (S1340).

The controller 140 may set a virtual wall based on the position data of the recognized marker. According to an embodiment, when two or more markers are recognized, the controller 140 sets the virtual wall based on a virtual line connecting the recognized markers, or when one marker is recognized, The virtual wall can be set to a predetermined area centered on the position of the recognized one marker.

In addition, the controller 140 may register the set virtual wall information in a map stored in the storage unit 150 (S1350).

Thereafter, the control unit 140 may control to avoid a wall corresponding to the virtual wall or to run along a wall following the wall (S1360).

The present invention relates to a method for setting a virtual wall for identifying a region of a mobile robot using a marker.

In the present invention, by setting a virtual wall at low cost by using a marker, it is possible to set a virtual wall such as an area where a mobile robot should not enter such as a room where a newborn baby sleeps, an area where the mobile robot should not go, You can divide the area.

Accordingly, there is an advantage in that the mobile robot can prevent entry and exit of dangerous areas with many dangerous substances and reduce the restraint situation, and the mobile robot itself such as the newborn room can prevent the mobile robot from accessing the harmful space.

In addition, the recognized virtual wall can be maintained as a virtual wall as long as the map is maintained even if the marker is removed. That is, it is possible to create a virtual wall at a plurality of places in a home with a small number of the same markers, without having to include a separate marker.

Therefore, according to at least one of the embodiments of the present invention, it is possible to provide a mobile robot and its control method which can set a virtual wall and travel based on a set virtual wall without adding any additional configuration.

Further, according to at least one of the embodiments of the present invention, a virtual wall can be set using a low-cost marker.

Further, according to at least one of the embodiments of the present invention, traveling based on the set virtual wall improves the stability of the mobile robot itself and the user's convenience, and improves the operation efficiency and the cleaning efficiency.

The mobile robot according to the present invention is not limited to the configuration and method of the embodiments described above, but the embodiments may be modified such that all or some of the embodiments are selectively combined .

Meanwhile, the control method of the mobile robot according to the embodiment of the present invention can be implemented as a code that can be read by a processor on a recording medium readable by the processor. The processor-readable recording medium includes all kinds of recording apparatuses in which data that can be read by the processor is stored. Examples of the recording medium that can be read by the processor include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like, and may also be implemented in the form of a carrier wave such as transmission over the Internet . In addition, the processor-readable recording medium may be distributed over network-connected computer systems so that code readable by the processor in a distributed fashion can be stored and executed.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, It should be understood that various modifications may be made by those skilled in the art without departing from the spirit and scope of the present invention.

100: mobile robot 110: main body
120: Image acquisition unit 140:
141: travel control module 142: zone division module
143: learning module 144: recognition module
150: storage unit 160:
50: External terminal

Claims (14)

A traveling part for moving the main body;
An image acquiring unit acquiring an image around the main body;
A storage unit for storing an image acquired by the image acquisition unit; And
And a controller configured to set a virtual wall based on the position data of the recognized marker when a marker having a specific pattern is recognized in the image acquired by the image acquisition unit. The method according to claim 1,
Wherein,
And registers information on the set virtual wall in a map stored in the storage unit. The method according to claim 1,
Wherein,
And controls the traveling section so as to avoid or run on a wall following in the area corresponding to the virtual wall. The method according to claim 1,
Wherein,
And when the two or more markers are recognized, sets the virtual wall based on a virtual line connecting the recognized markers. The method according to claim 1,
Wherein,
And when the one marker is recognized, sets the virtual wall to a predetermined area centered on the position of the recognized one marker. The method according to claim 1,
Wherein the marker includes a specific pattern formed in a color and a white background area arranged around the specific pattern. The method according to claim 1,
Wherein the marker is a polygonal or circular plane figure or a three-dimensional figure having a predetermined volume. Acquiring a moving image;
Recognizing a marker in which a specific pattern is formed in the acquired image; And
And setting a virtual wall based on positional data of the recognized marker. 9. The method of claim 8,
And storing information on the set virtual wall in a map. ≪ Desc / Clms Page number 20 > 9. The method of claim 8,
Further comprising the steps of: avoiding or traveling following a virtual wall in an area corresponding to the virtual wall. 9. The method of claim 8,
Wherein the virtual wall setting step comprises:
Wherein the virtual wall is set based on a virtual line connecting the recognized markers when two or more markers are recognized. 9. The method of claim 8,
Wherein the virtual wall setting step comprises:
And when the one marker is recognized, sets the virtual wall to a predetermined area centered on the position of the recognized one marker. 9. The method of claim 8,
Wherein the marker includes the specific pattern formed in color and a white background area arranged around the specific pattern. 9. The method of claim 8,
Wherein the marker is a polygonal or circular plane figure or a three-dimensional figure having a predetermined volume.

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