KR20180089234A - Cleaner - Google Patents

Abstract

According to one embodiment of the present invention, provided is a cleaner, which comprises: a cleaner main body; a suction nozzle sucking dust of a bottom surface; and a suction hose transferring the dust delivered from the suction nozzle to the cleaner main body. Moreover, the cleaner main body can comprise: a driving operation unit moving the cleaner main body; a depth sensor obtaining image information of an object around the cleaner main body; and a processor extracting both foot sole areas of a user based on the obtained image information, obtaining a movement route of the user based on the extracted both foot sole areas, and controlling the driving operation unit to enable the cleaner main body to be driven along the obtained movement route of the user.

Description

Cleaner {CLEANER}

The present invention relates to a vacuum cleaner, and more particularly, to a vacuum cleaner capable of automatically following a person.

Generally, a vacuum cleaner sucks dust-containing air using a suction force generated by a suction motor mounted inside the main body, and then filters dust inside the main body.

Such a vacuum cleaner is divided into a manual vacuum cleaner and an automatic vacuum cleaner. The manual vacuum cleaner is a vacuum cleaner for the user to carry out cleaning by moving the vacuum cleaner, and the vacuum cleaner is a vacuum cleaner that performs cleaning while traveling on its own.

The manual cleaner can be distinguished by a canister type in which the suction nozzle is provided separately from the cleaner main body and connected by an extension pipe, and an upright type in which the suction nozzle is coupled to the main body.

Such a conventional manual vacuum cleaner must be pulled by the user, which places a strain on the wrist or the back.

Further, when the user forcibly pulls the cleaner main body connected to the suction hose through the handle, the suction hose is detached from the cleaner main body.

To solve these problems, technologies were developed that automatically follow the person in the vacuum cleaner.

Conventionally, an ultrasonic sensor is used to recognize only the distance and direction between the main body of the cleaner and the user, and the user is followed.

However, in this case, since the cleaner main body moves along the shortest path to the follow-up point, there is a risk that the cleaner main body collides with the user, the suction hose becomes twisted, or collides with the obstacle.

An object of the present invention is to provide a vacuum cleaner capable of keeping track of a user's movement path, following a user along a movement path, and following a user while maintaining a certain distance.

The present invention aims at providing a vacuum cleaner which can more precisely grasp a moving path of a user.

An object of the present invention is to provide a vacuum cleaner capable of distinguishing an obstacle from a user located on the front of the cleaner body and grasping a motion trajectory of the user.

An object of the present invention is to provide a cleaner capable of avoiding an obstacle while following a user along a movement path of a user.

An object of the present invention is to provide a vacuum cleaner capable of adjusting a follow-up speed of a cleaner main body according to a moving speed of a user.

The vacuum cleaner according to the embodiment of the present invention can acquire the movement route of the user by using the image information obtained from the depth sensor and can drive the cleaner main body by the obtained movement route when the distance to the user is more than a certain distance .

The cleaner according to the embodiment of the present invention can grasp the position of the user by using the relative position between the left foot area and the right foot area included in the plantar pair area.

The depth sensor of the vacuum cleaner according to the embodiment of the present invention is mounted on the upper surface of the upper part of the main body of the vacuum cleaner and can irradiate the light source downward.

The cleaner according to the embodiment of the present invention can detect the obstacle on the movement path of the user, avoid the detected obstacle, and then return the cleaner main body to the movement path again.

The cleaner according to the embodiment of the present invention can control the motor of the traveling driving unit to adjust the traveling speed of the cleaner body according to the moving speed of the user.

Further scope of applicability of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and specific examples, such as the preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art.

According to the embodiment of the present invention, the distance between the users can be stably maintained in the cleaner main body, the user can be prevented from colliding with the cleaner main body, and the suction hose can be prevented from being twisted.

According to the embodiment of the present invention, the position of the user is accurately grasped, and the cleaner main body can follow the user stably.

According to the embodiment of the present invention, since the depth sensor provided at the upper part of the front surface is provided, it is possible to clearly distinguish between the person and the obstacle, and the position of the person can be accurately grasped.

According to the embodiment of the present invention, the collision of the obstacle can be prevented while the cleaner main body follows the movement route of the user.

According to the embodiment of the present invention, the cleaner main body follows the user in accordance with the moving speed of the user, so that collision with the user can be prevented in advance.

FIG. 1A is a block diagram illustrating a configuration of a vacuum cleaner according to an embodiment of the present invention.
1B is a view illustrating a canister-type cleaner according to an embodiment of the present invention.
1C and 1D are diagrams illustrating a robot type cleaner according to an embodiment of the present invention.
1E and 1F are views for explaining the structure of a depth sensor and the principle of acquiring image information according to an embodiment of the present invention.
2 is a flowchart illustrating an operation method of a vacuum cleaner according to an embodiment of the present invention.
3 is a flowchart illustrating a process of extracting a human candidate region based on image information obtained according to an embodiment of the present invention.
4 is a diagram for explaining an example of separating a foreground region and a background region based on image information obtained according to an embodiment of the present invention.
Figure 5 illustrates an example of a three-dimensional human model stored in memory in accordance with one embodiment of the present invention.
6 is a flowchart illustrating an example of obtaining a moving point of a cleaner from a person area obtained according to an embodiment of the present invention.
Fig. 7 is a diagram for explaining an example of judging whether a pair of legs is the same person based on the distance between leg regions according to an embodiment of the present invention. Fig.
FIGS. 8 and 9 are views illustrating a process of projecting a projected foot area by projecting a pair of legs selected as a subject to be monitored by a cleaner on a floor plane according to an embodiment of the present invention.
10 is a view for explaining an example of acquiring a movement path of a user based on the relative positions of plantar regions according to an embodiment of the present invention.
11 is a view for explaining a method of measuring a distance between a user and a cleaner main body according to an embodiment of the present invention.
FIG. 12 is a view for explaining an embodiment in which the cleaner main body travels according to the movement path of the user. FIG. 13 shows an example of returning to the movement path after avoiding an obstacle when an obstacle is detected on the movement path of the user Fig.
14 is a view for explaining how an actual user and a cleaner main body of a canister type cleaner follow a user's movement path 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, wherein like reference numerals are used to designate identical or similar elements, and redundant description thereof will be omitted. The suffix "module" and " part "for the components used in the following description are given or mixed in consideration of ease of specification, and do not have their own meaning or role.

FIG. 1A is a block diagram illustrating a configuration of a vacuum cleaner according to an embodiment of the present invention.

The vacuum cleaner 100 shown in FIG. 1A can be applied to both a vacuum cleaner of a canister type including a suction hose, and a vacuum cleaner of a robot type that does not include a suction hose. This will be described later.

1A, a vacuum cleaner 100 according to an embodiment of the present invention includes an image information obtaining unit 110, an obstacle detecting unit 130, a memory 150, a travel driving unit 170, and a processor 190 .

The image information obtaining unit 110 may obtain image information, which is information on the image around the cleaner 100.

The image information obtaining unit 110 may include at least one of a depth sensor 111 and an RGB sensor 113.

The depth sensor 111 can sense that the light emitted from the light emitting unit (not shown) is reflected by the object and returns. The depth sensor 111 can measure the distance from the object based on the time difference between the time when the returned light is detected and the amount of returned light.

The depth sensor 111 can obtain two-dimensional image information or three-dimensional image information about the cleaner 100 based on the distance between the measured objects.

The RGB sensor 113 can acquire color image information about an object around the cleaner 100. The color image information may be a captured image of an object. The RGB sensor 113 may be called an RGB camera.

 The image information obtaining unit 110 will be described later in detail.

The obstacle sensing unit 130 may sense obstacles disposed around the cleaner 200.

The obstacle sensing unit 130 may include an ultrasonic sensor, an infrared sensor, a laser sensor, and / or a vision camera. The obstacle detection unit 210 may include a camera for photographing a cleaning area irradiated with a laser by a laser sensor and acquiring an image.

The processor 190 extracts the laser light pattern from the image obtained through the camera and generates a map of the obstacle situation and the cleaning area in the cleaning area based on the change of the position, shape, and posture of the pattern in the image .

In FIG. 1A, the obstacle sensing unit 130 and the image information acquiring unit 110 are described as separate components. However, the present invention is not limited thereto. That is, the obstacle detecting unit 130 may be included in the configuration of the image information obtaining unit 110 or may not be included in the configuration of the cleaner 100. In this case, the image information obtaining unit 110 replaces the obstacle detection.

The memory 150 may store a plurality of human models including a leg shape. The plurality of person models may be a two-dimensional or three-dimensional person model.

The driving drive unit 170 can move the cleaner 100 in a specific direction or by a certain distance. The travel driving part 170 may include a left wheel driving part 171 for driving the left wheel of the cleaner 100 and a right wheel driving part 173 for driving the right wheel.

The left wheel driving portion 171 may include a motor for driving the left wheel, and the right wheel driving portion 173 may include a motor for driving the right wheel.

In FIG. 1A, the travel driving unit 170 includes the left wheel driving unit 171 and the right wheel driving unit 173, but the present invention is not limited thereto. In the case of one wheel, only one driving unit may be provided have.

The processor 190 may control overall operation of the vacuum cleaner 100.

The processor 190 may extract one or more person candidate regions based on the image information obtained by the image information obtaining unit 110. [

The processor 190 can extract a human region from among the extracted one or more human candidate regions, and determine the position and posture of a person based on the extracted human region.

The processor 190 can select a movement point at which the vacuum cleaner 100 will automatically move based on the determined position and posture of the person.

The processor 190 may control the travel driving unit 170 to move the vacuum cleaner 100 to a predetermined moving point.

Accordingly, the cleaner 100 can follow a person at a position separated by a certain distance from the person.

The processor 190 can independently control the operation of the left wheel drive section 171 and the right wheel drive section 173. [ Thus, the vacuum cleaner 100 is advanced, retracted, or turned.

The cleaner 100 according to the embodiment of FIG. 1A can be applied to a cleaner of a canister type or a robot type.

1B is a view illustrating a canister-type cleaner according to an embodiment of the present invention.

The canister type cleaner 100-1 may include a cleaner body 10 and a suction device 20. [

The cleaner main body 10 may include all the components of the cleaner 100 described with reference to FIG.

The cleaner main body 10 may further include a dust separator (not shown) for separating the air and dust from the suction device 20 and a dust container 101 for storing dust separated from the dust separator .

The dust container 101 can be detachably mounted on the cleaner body 10. [ The dust separator may be manufactured as a separate article from the dust container 101, or may form one module with the dust container 101.

The suction device 20 is connected to the cleaner main body 10 and can guide air containing dust to the cleaner main body 10. [

The suction device 20 may include suction nozzles 21 for sucking dust on the floor and air and connecting portions 22, 23 and 24 for connecting the suction nozzles 21 to the cleaner main body 10 .

The connecting portions 22, 23 and 24 are provided with an extension pipe 24 connected to the suction nozzle 21, a handle 22 connected to the extension pipe 24 and a suction hose 22 connecting the handle 22 to the cleaner body 10 23).

The cleaner main body 10 may include an image information obtaining unit 110. The image information obtaining unit 110 may be disposed on the upper surface of the upper end of the cleaner main body 10.

The cleaner main body 10 may have a constant height. The constant height can range from 15 cm to 30 cm, but this is only an example.

When the depth sensor 111 is disposed on the upper surface of the upper end of the cleaner body 10, the light source can be irradiated downward, so that information on the image below the knee of the person lying on the floor surface can be accurately extracted.

Next, a robot type vacuum cleaner will be described.

1C and 1D are diagrams illustrating a robot type cleaner according to an embodiment of the present invention.

1C and 1D, the robot type vacuum cleaner 100-2 may include a cleaner main body 50, a left wheel 61a, a right wheel 61b, and a suction portion 70. [

The cleaner main body 50 may include all the components of the cleaner 100 described with reference to FIG.

Particularly, the image information obtaining unit 110 including the depth sensor 111 may be provided on the front upper surface of the robot type vacuum cleaner 100-2. Of course, an RGB sensor 113 may also be provided.

The left wheel 61a and the right wheel 61b can make the cleaner main body 50 run. As the left wheel 61a and the right wheel 61b are rotated by the travel driving unit 170, foreign substances such as dust and trash can be sucked through the suction unit 70. [

The suction unit 70 is provided in the cleaner main body 50 to suck dust on the floor surface.

The suction unit 70 may further include a filter (not shown) for collecting foreign substances in the sucked air stream and a foreign matter receiver (not shown) in which foreign substances collected by the filter are accumulated.

1E and 1F are views for explaining the structure of a depth sensor and the principle of acquiring image information according to an embodiment of the present invention.

1E and 1F, it is assumed that the depth sensor is a TOF (Time Of Flight) type depth sensor, but this is merely an example.

The depth sensor 111 of the TOF type can measure the reflected time by irradiating light and measure the distance to the object.

The depth sensor 111 of the TOF type can measure the distance to an object using the amount of reflected light.

The depth sensor 111 of the TOF type can output image information including the depth image 93 to the real object 91, as shown in Fig. 1E, using the TOF method.

Fig. 1F shows an example of a TOF type depth sensor.

The TOF-type depth sensor 111 may include a plurality of cells 95 for sensing light emitted from a light emitting unit and light emitted from the light emitting unit, as shown in FIG. 1F.

The light emitting portion can irradiate light to the outside at a predetermined time interval. The predetermined time may indicate the blinking interval of the light emitting portion.

Each of the plurality of cells 95 may include a first receiver 95a and a second receiver 95b.

The first receiver 95a can be activated while irradiating light in the light emitting portion, and can receive reflected light returning from the activated state.

The second receiver 95b can be activated while not emitting light in the light emitting portion, and can receive the reflected and returning light in the activated state.

When the first receiver 95a and the second receiver 95b are activated with a time difference from each other, a difference occurs in the amount of light accumulated in each receiver depending on the distance from the object.

By comparing the difference in the amount of light, the distance to the object can be measured.

The depth sensor 111 of the TOF type can convert the actual object 91 into the depth image 93 shown in Fig. 1E according to the measured distance, and output it.

Can be used to extract a human candidate region using the converted depth image (93).

2 is a flowchart illustrating an operation method of a vacuum cleaner according to an embodiment of the present invention.

Hereinafter, an operation method of the vacuum cleaner according to the embodiment of FIG. 2 will be described in connection with the embodiment of FIG.

The image information obtaining unit 110 of the cleaner 100 obtains image information that is information about the image located around the cleaner 100 (S201).

In one embodiment, the image information obtaining unit 110 may include at least one of the depth sensor 111 and the RGB sensor 113.

The depth sensor 111 can sense the reflected light when the light irradiated on a pixel-by-pixel basis is reflected, and obtain the distance data between the depth sensor and the object.

The processor 190 may obtain three-dimensional image information based on the distance data obtained by the depth sensor 111. [ The 3D image information can be used later to extract a human candidate region.

According to another embodiment of the present invention, in order to acquire image information, an RGB sensor 113 may additionally be used. The RGB sensor 113 can acquire color image information about an object around the cleaner 100.

The RGB sensor 113 can be used when the depth sensor 111 fails to extract a human candidate region through the acquired image information. In other words, the RGB sensor 113 can serve as a complement to the depth sensor 113.

That is, when the human candidate region can not be extracted through the image information acquired by the depth sensor 111, the processor 190 may extract the human candidate region using the color image information acquired by the RGB sensor 113 have.

The case where the depth sensor 111 can not extract the human candidate region may be a case where an external light source including sunlight is directly irradiated to the light emitting portion of the depth sensor 111. [

As another example, when the depth sensor 111 can not extract a human candidate region, the distance between the object and the depth sensor 111 is very close, the reflectivity of the object is high, and a light saturation phenomenon occurs .

The human candidate region can be extracted through the RGB sensor 113 regardless of the external environment change in which the depth sensor 111 is not available.

Conversely, when the human candidate region can not be extracted through the color image information acquired by the RGB sensor 113, the processor 190 may extract the human candidate region based on the distance data acquired by the depth sensor 111 have.

The case where the human candidate region can not be extracted through the color image information acquired by the RGB sensor 113 means that the surrounding illumination is less than the predetermined illumination as in the case where the light is not lit so that the human candidate region can be extracted It may be absent.

When both the depth sensor 111 and the RGB sensor 113 are used for acquiring image information, any one of the sensors can complement the other sensor, so that the detection capability of the human candidate region can be improved.

The processor 190 of the cleaner 100 extracts one or more human candidate regions based on the acquired image information (S203).

The processor 190 can extract the human candidate region by separating the background region from the foreground region based on the acquired image information.

In yet another embodiment, the processor 190 may remove the bottom planar region from the isolated foreground region and extract the human candidate region.

In another embodiment, when the acquired image information includes RGB information, the processor 190 may extract a human candidate region using a Histogram of Oriented Gradient (HOG) based human recognition algorithm.

The RGB information may be a color image acquired by the RGB sensor 113. [

The HOG-based human recognition algorithm is an algorithm technique for acquiring a histogram of the direction of edge pixels among a plurality of cells in which a color image is divided and recognizing a human region included in the color image. Here, the edge pixel is a pixel whose slope size is equal to or larger than a certain size.

The processor 190 can extract at least two candidate candidate regions using the acquired image information.

Step S203 will be described with reference to the following drawings.

3 is a flowchart illustrating a process of extracting a human candidate region based on image information obtained according to an embodiment of the present invention.

Particularly, FIG. 3 is a diagram embodying step S203 of FIG.

Referring to FIG. 3, the processor 190 determines whether RGB information is included in the acquired image information (S301).

If RGB information is not included in the obtained image information, the processor 190 separates the background area from the foreground area based on the acquired image information (S303).

In this case, the processor 190 can extract the human candidate region using only the depth sensor. That is, when RGB information is not included in the image information, the image information may be depth information sensed by the depth sensor.

The depth information may include distance data indicating the distance between the depth sensor and the surrounding objects.

Step S303 will be described with reference to FIG.

4 is a diagram for explaining an example of separating a foreground region and a background region based on image information obtained according to an embodiment of the present invention.

Referring to FIG. 4, an actual image 400 positioned on the front surface of the cleaner 100 is shown.

The depth sensor of the image information acquiring unit 110 may acquire image information corresponding to the real image 400.

The preprocessing unit (not shown) included in the processor 190 preprocesses the acquired image information to acquire the foreground region 410 corresponding to the entire real image 400. [ In this process, the preprocessor can remove the noise from the image information and acquire the foreground region 410 from which noise has been removed.

The foreground region 410 may include a background region 411 that does not include the object regions 413 and 415. The preprocessor may separate the background area 411 not including the object areas 413 and 415 from the foreground area 410.

3 will be described again.

The processor 190 extracts, as a human candidate region, a region in which a background region has been removed and a bottom plane region of the foreground region is removed (S305).

In one embodiment, the processor 190 may extract regions of motion within the foreground region with the background region in a separate state into a human candidate region.

Referring to FIG. 4, the processor 190 may extract object regions 413 and 415 in which motion exists in the foreground region 410 where the background region 411 is separated.

When each of the object areas 413 and 415 is moved based on the first image information obtained at the first time point and the second image information obtained at the second time point, ) Can be extracted as human candidate regions. Here, the second time point may be later than the first time point.

If any one of the object areas 413 and 415 is located at the same position at the first view point and the second view point, the processor 190 may not extract the corresponding area as a human candidate area.

In another embodiment, if the background region is defined as a bottom plane region, the processor 190 may separate the bottom plane region within the foreground region and remove the separated bottom plane region.

The processor 190 may remove the bottom planar region and then extract, in the remaining region, the region in which the motion is present, into the human candidate region.

If the acquired image information includes RGB information, the processor 190 performs a HOG-based human recognition algorithm (S307), and extracts a human candidate region according to the execution result (S309).

The processor 190 may perform the HOG-based human recognition algorithm using the RGB information obtained through the RGB sensor.

As described above, the HOG-based human recognition algorithm obtains a histogram of the direction of edge pixels among a plurality of cells obtained by dividing an image region corresponding to RGB information, and performs an algorithm for recognizing a human region included in the target region Technique.

According to steps S301 to S307, the processor 190 may extract a minimum of two or more candidate regions. As the two or more candidate regions are extracted, the human region can be extracted more accurately.

Fig. 2 will be described again.

The processor 190 determines whether there is a human candidate region among the extracted one or more candidate regions (S205), and acquires a human region according to the determination result (S207).

In one embodiment, the processor 190 may convert the extracted person candidate region into three-dimensional coordinates to obtain a three-dimensional human candidate region.

The processor 190 may match the three-dimensional human model and the three-dimensional human candidate region stored in the memory 150 to determine whether the three-dimensional human candidate region is a human region.

The three-dimensional human model may be a model including a human leg shape.

The memory 150 may store three-dimensional human models corresponding to various leg shapes.

The processor 190 may determine that the person candidate region is a human region when the three-dimensional human candidate region matches the three-dimensional human model as a result of the matching.

The three-dimensional human model will be described with reference to Fig.

On the other hand, if there is an area that is not judged as a person among the extracted one or more person candidate areas, the processor 190 regards the person candidate area as an obstacle area and controls the driving part to avoid the obstacle area (S206) .

As a result of the matching, if the three-dimensional human candidate region is not matched with the three-dimensional human model, the processor 190 can determine the corresponding human candidate region as an obstacle rather than a human region.

If the candidate candidate region is determined to be an obstacle, the processor 190 may control the traveling of the cleaner 100 to avoid an obstacle.

Figure 5 illustrates an example of a three-dimensional human model stored in memory in accordance with one embodiment of the present invention.

The memory 150 of the cleaner 100 may store a plurality of three-dimensional human models 510, 530, and 550. Each dimensional human model may have a shape that includes a pair of legs corresponding to the back of a person.

The processor 190 may compare each of the extracted three-dimensional human models 510, 530, and 550 stored in the memory 150 with the extracted human candidate region.

The processor 190 may determine the extracted human candidate region as a human region when the matching rate between the extracted human candidate region and the previously stored three-dimensional human model is equal to or greater than a predetermined matching rate.

The processor 190 can recognize the human candidate region as an obstacle region when it is determined that the human candidate region is not a human region.

Fig. 2 will be described again.

The processor 190 obtains the movement path of the acquired human area (209), and stores the obtained movement path in the memory 150 (S211).

In one embodiment, the processor 190 may extract one or more pairs of legs from the acquired human region.

The processor 190 may select one of the pair of extracted leg pairs as an object to which the cleaner main body should follow.

The processor 190 can obtain the position of the selected follow subject (the user corresponding to the selected leg pair) in real time.

The processor 190 may obtain the user's travel route based on the location of the user obtained in real time.

The obtained travel route of the user may be a travel route on which the cleaner main body should travel.

Hereinafter, a process of selecting a tracking target from a human region and acquiring a movement route of the selected tracking target will be described.

FIG. 6 is a flowchart illustrating a process of selecting a tracking target from a human region obtained according to an embodiment of the present invention and obtaining a movement route of the selected tracking target.

Referring to FIG. 6, the processor 190 extracts one or more pairs of legs from the acquired human region (S601).

In one embodiment, the acquired human region may include the entire region of a person, and may include only a portion of a person's region including a leg region.

The processor 190 determines whether the distance between the leg regions included in each extracted pair of legs is within a predetermined distance (S603).

If the distance between the leg regions included in the pair of legs is within a certain distance, the processor 190 can recognize that the pair of legs is a pair of legs of the same person.

If the distance between the leg regions included in the pair of legs exceeds a certain distance, it is recognized that the pair of legs is not a leg pair of the same person (S604).

Here, the predetermined distance may be 80 cm, but this is only an example.

Fig. 7 is a diagram for explaining an example of judging whether a pair of legs is the same person based on the distance between leg regions according to an embodiment of the present invention. Fig.

Referring to FIG. 7, leg pairs 710, 720 extracted from one human region are shown.

The first pair of legs 710 may include a first leg region 711 and a second leg region 713.

The second pair of legs 720 may include a third leg region 721 and a fourth leg region 732.

The processor 190 determines whether the first distance d1 between the first leg region 711 and the second leg region 713 is within a certain distance. The distance may be 80 cm.

The processor 190 may determine that the first leg pair 710 is a leg pair of the same person when the first distance d1 is within 80 cm.

Meanwhile, the processor 190 determines whether the second distance d2 between the third leg region 721 and the fourth leg region 723 is within a certain distance.

The processor 190 may recognize that the second leg pair 720 is not a leg pair of the same person if the second distance d2 exceeds a certain distance. The processor 190 may remove the second pair of legs 720 that are recognized as not the same person's leg pair.

According to this process, the subject to be followed by the cleaner 100 can be clarified.

6 will be described again.

The processor 190 extracts a pair of legs whose distance between the leg regions is within a predetermined distance, and determines whether there are two or more pairs of extracted legs (S605).

If there are two or more extracted leg pairs, the processor 190 selects a pair of legs located closest to the depth sensor 111 included in the image information obtaining unit 110 as a follow subject (S607).

In one embodiment, the processor 190 may obtain distance data between each of the extracted leg pairs and the depth sensor 111.

The processor 190 can obtain the distance between each pair of legs and the depth sensor 111 using the distance data included in the depth information of the object through the depth sensor 111 in step S201 of FIG.

The processor 190 can select a pair of legs located at a distance closest to the depth sensor 111 among the distances between each pair of legs and the depth sensor 111 to be followed by the vacuum cleaner 100. [

The processor 190 projects the selected pair of legs to the floor plane (S609).

FIGS. 8 and 9 are views illustrating a process of projecting a projected foot area by projecting a pair of legs selected as a subject to be monitored by a cleaner on a floor plane according to an embodiment of the present invention.

FIG. 8 is a view for explaining a sole region obtained at a first time point, and FIG. 9 is a view for explaining a sole region obtained at a second time point at a predetermined time point at a first time point.

The processor 190 may project the first pair of legs 810 selected as the object of tracking to the bottom plane 830. [ Accordingly, the first sole pair region 850 can be obtained. The first sole pair region 850 may be used later by the cleaner 100 to obtain the user's path of travel for follow-up.

Likewise, when the person to be monitored of the cleaner 100 moves, the processor 190 may project the second pair of legs 910 selected as the subject to be watched on the floor plane 930. Accordingly, a second sole pair region 950 can be obtained.

The second sole pair region 950 may be used later by the cleaner 100 to obtain the user's path of travel for follow-up.

6 will be described again.

The processor 190 obtains the position of the user in real time using the sole pair region corresponding to the pair of legs obtained by projection (S611).

In one embodiment, the processor 190 may obtain the position of the user in real time using the relative position between the plantar regions that make up the plantar pair region.

The relative position between the plantar regions may be the center point of the line segment between the center of the left foot region and the center of the right foot region.

The processor 190 acquires the movement path of the user using the acquired position of the user (S613).

The processor 190 can acquire the movement path of the user at predetermined time intervals using the position of the user obtained in real time. The time interval may be one second, but this is only an example.

Hereinafter, an example of acquiring the movement route of the user based on the location of the user will be described.

10 is a view for explaining an example of acquiring a movement path of a user based on the relative positions of plantar regions according to an embodiment of the present invention.

10 illustrates a process in which a user draws a curved trajectory and acquires a movement path of the user when the user draws a curved trajectory.

In FIG. 10, the constitution of the suction nozzle 21 and the suction hose 23 is omitted for convenience of explanation.

Referring to Fig. 10, a sole pair region 1000 is shown.

The sole pair region 1000 may be an area obtained by projecting a pair of legs selected as a subject to be tracked.

The sole pair region 1000 may include a left foot region 1010 and a right foot region 1030.

The processor 190 may obtain the center point 1050 of the line segment between the center point 1011 of the left foot area 1010 and the center point 1031 of the right foot area 1030. [

The processor 190 may recognize the center point 1050 of the line segment as the position of the user.

The processor 190 can acquire the center point 1011 of the left foot area 1010 and the center point 1050 of the line segment between the center point 1031 of the right foot area 1030 in real time.

In one embodiment, when the user draws a straight line trajectory, and moves, the center point 1050 can also draw a straight line trajectory.

In another embodiment, as shown in FIG. 10, when the user draws a curved trajectory, the center point 1050 can also draw a curved trajectory.

The processor 190 can obtain the curved trajectory 1070 of the center point 1050 obtained in real time by the movement path of the user to which the cleaner main body 10 should follow.

According to this process, the movement trajectory of the user can be extracted more accurately, and the cleaner main body 10 can accurately follow the target to be followed.

Fig. 2 will be described again.

The processor 190 determines whether the distance between the cleaner main body 10 and the user is equal to or greater than a predetermined distance, based on the acquired travel path of the user (S213).

In one embodiment, the distance between the cleaner body 10 and the user may be the distance between the depth sensor 111 provided in the cleaner body 10 and the center point 1050 of the line segment described in FIG.

This will be described with reference to FIG.

11 is a view for explaining a method of measuring a distance between a user and a cleaner main body according to an embodiment of the present invention.

For the explanation of FIG. 11, a part of the contents of FIG. 10 is borrowed.

11, the center point 1050 of the line segment between the center 1011 of the left foot area 1010 and the center 1031 of the right foot area 1030 can be determined as the current position of the user.

The distance between the user and the cleaner main body 10 may be the distance between the center point 1050 of the line segment and the depth sensor 111 provided in the cleaner main body 10. [

The processor 190 may determine whether the cleaner body 10 follows the user based on the distance between the depth sensor 111 and the center point 1050 of the line segment.

The reason why the distance between the cleaner main body 10 and the user is greater than a predetermined distance is that the cleaner main body 10 keeps a certain distance from the user and follows the user.

Fig. 2 will be described again.

The processor 190 controls the travel driving unit 170 to travel along the travel route on which the cleaner main body 10 is stored when the distance between the cleaner main body 10 and the user is equal to or greater than a certain distance (S215).

The processor 190 may control the travel driving unit 170 so that the cleaner main body 10 travels along the movement trajectory in which the user has moved in the past rather than the current position of the user.

The processor 190 may control the travel driving unit 170 such that the cleaner main body 10 is located at a distance of a certain distance or more from the user's position.

Accordingly, the user may not be disturbed by the cleaner body 10 due to the cleaning operation.

In one embodiment, the processor 190 may adjust the number of revolutions of the motor included in the travel driving unit 170 based on the moving speed of the user.

For example, the processor 190 may increase the number of revolutions of the motor included in the travel driving unit 170 when the moving speed of the user increases.

When the user performs the cleaning while moving quickly, the cleaner main body 10 can travel on the movement path at a relatively slow speed. In this case, the user has to draw the suction hose to draw the cleaner main body 10 inconveniently. In order to solve the inconvenience of the user, the processor 190 may increase the number of revolutions of the motor included in the travel driving unit 170 so as to rapidly travel the moving route.

The moving speed of the user can be increased as the positional variation of the user is larger than the predetermined time.

The amount of change in the position of the user may indicate the moving distance of the center point 1050 located between the left foot area 1010 and the right foot area 1030 illustrated in FIG.

The moving distance of the center point 1050 may correspond to the moving distance of the user.

The processor 190 may calculate the moving speed of the user by measuring the moving distance of the user with respect to a predetermined time.

The processor 190 may adjust the rotation speed of the motor included in the travel driving unit 170 according to the calculated movement speed of the user.

The processor 190 determines whether an obstacle is detected during traveling the cleaner main body along the movement path (S217).

In one embodiment, the processor 190 may use the depth sensor 111 to detect that it is present on a pathway obstacle. This is replaced with the contents described in step S206.

In another embodiment, the processor 190 can detect an obstacle using the obstacle sensing unit 130 described in FIG.

When an obstacle is detected, the processor 190 controls the driving driving unit 170 to return to the moving path of the user after avoiding the obstacle (S219).

Steps S215 to S219 will be described with reference to Figs. 12 and 13. Fig.

FIG. 12 is a view for explaining an embodiment in which the cleaner main body travels according to the movement path of the user. FIG. 13 shows an example of returning to the movement path after avoiding an obstacle when an obstacle is detected on the movement path of the user Fig.

12 and 13, the constitution of the suction nozzle 21 and the suction hose 23 is omitted for convenience of explanation.

12, the processor 190 controls the travel driving unit 170 so that the cleaner main body 10 travels along the travel route 1070 using the user's travel route 1070 stored in the memory 150 can do.

Accordingly, the cleaner main body 10 can be moved according to the movement trajectory of the past user, rather than moving directly to the current position of the user.

Referring to FIG. 13, an obstacle 1300 may exist on the movement path 1070.

When the processor 190 detects that the obstacle 1300 is present on the movement route 1070, the processor 190 moves the cleaner main body 10 in accordance with the temporary movement route 1310 for avoiding the obstacle 1300, (170).

After the obstacle is avoided, the processor 190 may control the travel driving section 1070 to return to the original travel route 1070. [

Accordingly, the cleaner main body 10 can be prevented from colliding with the obstacle even when traveling along the movement route of the user.

On the other hand, if the distance between the main body of the cleaner and the user is less than a predetermined distance, the processor 190 performs step S211. That is, in this case, the processor 190 may not run the cleaner main body until the distance between the cleaner main body and the user becomes a certain distance.

This is because, if the cleaner main body 10 comes too close to the user, it may cause a collision with the user.

As the distance between the user and the cleaner main body 10 maintains a certain distance, the user is not disturbed by the cleaner main body 10 during cleaning.

14 is a view for explaining how an actual user and a cleaner main body of a canister type cleaner follow a user's movement path according to an embodiment of the present invention.

Referring to FIG. 14, the user grips the handle 22 of the canister type cleaner, draws a curved trajectory, and cleans the cleaning area.

The cleaner body 10 of the canister type cleaner follows the user along the curved path 1400 of the user stored in the memory 150.

Conventionally, when the user moves along the curved path 1400, the cleaner main body 10 has selected the following point 1410 as a follow-up position, which is not a curved path 1400 but a distance from the user.

In this case, the cleaner main body 10 is directly moved to the follow-up point 1410 along the shortest straight path 1420, causing the cleaner main body 10 to collide with the user or the suction hose 23 to be twisted.

Further, when the cleaner main body 10 is moved along the straight path 1420, there is a problem that the cleaner main body 10 may collide with an obstacle existing on the straight path 1420. [

According to the embodiment of the present invention, since the cleaner main body 10 is moved along the curved trajectory 1400, which is the movement trajectory of the user, rather than the shortest straight path 1420, The problem of twisting can also be prevented.

The present invention described above can be embodied as computer-readable codes on a medium on which a program is recorded. The computer readable medium includes all kinds of recording devices in which data that can be read by a computer system is stored. Examples of the computer readable medium include a hard disk drive (HDD), a solid state disk (SSD), a silicon disk drive (SDD), a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, .

The foregoing detailed description should not be construed in all aspects as limiting and should be considered illustrative. The scope of the present invention should be determined by rational interpretation of the appended claims, and all changes within the scope of equivalents of the present invention are included in the scope of the present invention.

Claims (15)

In the vacuum cleaner,
A cleaner main body;
A suction nozzle for sucking dust on the floor surface;
And a suction hose for transmitting the dust transferred from the suction nozzle to the cleaner main body,
The cleaner main body
A traveling drive unit for traveling the cleaner main body,
A depth sensor for acquiring image information about an object around the cleaner main body;
Extracts the user's sole pair region based on the acquired image information,
Acquiring a movement route of the user based on the extracted sole pair region,
And a processor for controlling the travel driving unit to travel the cleaner main body along the travel path of the user when the distance between the user and the depth sensor is equal to or greater than a predetermined distance
vacuum cleaner. The method according to claim 1,
The processor
The position of the user is obtained in real time using the relative position between the left foot area and the right foot area included in the plantar pair area,
And acquires the movement route of the user using the position of the user obtained in real time
vacuum cleaner. 3. The method of claim 2,
The processor
The center of the line segment between the center of the left foot area and the center of the right foot area is obtained as the position of the user
vacuum cleaner. The method according to claim 1,
The depth sensor
The vacuum cleaner body is disposed on the upper surface of the upper end of the cleaner main body, and irradiates the light source toward the lower side to acquire the image information
vacuum cleaner. The method according to claim 1,
The processor
Wherein when the obstacle present on the moving path of the user is detected, the cleaner main body controls the traveling driving unit to avoid the obstacle,
After the obstacle is avoided, the traveling driving unit is controlled to return to the traveling route
vacuum cleaner. The method according to claim 1,
The processor
Extracting one or more person candidate regions based on the obtained image information,
Extracting a region including a leg shape among the one or more candidate regions as a human region,
Projecting the pair of legs of the extracted human region onto the floor surface, extracting the plantar-pair region
vacuum cleaner. The method of claim 3,
The processor
Measuring a moving speed of the user based on the position of the user,
The controller controls the rotational speed of the motor included in the traveling driving unit according to the measured traveling speed of the user during traveling of the cleaner main body
vacuum cleaner. The method according to claim 1,
The cleaner main body
Further comprising a memory for storing the movement path of the user
vacuum cleaner. In the vacuum cleaner,
A suction unit for sucking dust on the bottom surface;
A traveling driving unit for traveling the cleaner;
A depth sensor for acquiring image information about an object around the cleaner;
Extracting a region of the sole pair of the user based on the acquired image information, acquiring a movement route of the user based on the extracted region of the sole pair, and acquiring, when the distance between the user and the depth sensor is a certain distance or more, And controlling the traveling driving unit to travel the cleaner along a traveling path of the user
vacuum cleaner. 10. The method of claim 9,
The processor
The position of the user is obtained in real time using the relative position between the left foot area and the right foot area included in the plantar pair area,
And acquires the movement route of the user using the position of the user obtained in real time
vacuum cleaner. 11. The method of claim 10,
The processor
The center of the line segment between the center of the left foot area and the center of the right foot area is obtained as the position of the user
vacuum cleaner. 10. The method of claim 9,
The depth sensor
The vacuum cleaner body is disposed on the upper surface of the upper end of the cleaner main body, and irradiates the light source toward the lower side to acquire the image information
vacuum cleaner. 10. The method of claim 9,
The processor
Wherein when the obstacle present on the moving path of the user is detected, the cleaner main body controls the traveling driving unit to avoid the obstacle,
After the obstacle is avoided, the traveling driving unit is controlled to return to the traveling route
vacuum cleaner. 10. The method of claim 9,
The processor
Extracting one or more person candidate regions based on the obtained image information,
Extracting a region including a leg shape among the one or more candidate regions as a human region,
Projecting the pair of legs of the extracted human region onto the floor surface, extracting the plantar-pair region
vacuum cleaner. 12. The method of claim 11,
The processor
Measuring a moving speed of the user based on the position of the user,
The controller controls the rotational speed of the motor included in the traveling driving unit according to the measured traveling speed of the user during traveling of the cleaner main body
vacuum cleaner.

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