JP2020087240A - Control system for cleaner, autonomous travel type cleaner, cleaning system, and control method for cleaner - Google Patents

Abstract

To provide a control system for a cleaner, which is able to control travel of a cleaner through a simple configuration.SOLUTION: A control system for a cleaner 100 comprises: an imaging unit 12 mounted in the cleaner 100 and that captures an image of a periphery of the cleaner 100; an edge extraction unit 34 that extracts an edge shown in the image; an object detection unit 35 that extracts an area surrounded by the extracted edge and detects an object on the basis of the extracted area; and a travel control unit 37 that controls travel of the cleaner on the basis of a position of the detected object.SELECTED DRAWING: Figure 6

Description

The present invention relates to a vacuum cleaner control system, an autonomous traveling vacuum cleaner, a cleaning system, and a vacuum cleaner control method.

BACKGROUND ART It has been attempted to detect a person or an object in a room and operate a home electric appliance or the like according to the detected result.

As an example of such a technique, Patent Literature 1 describes an air conditioning system that changes the blowing angle according to the position of a human body or an obstacle. Patent Document 2 describes a vacuum cleaner that generates a distance image using a stereo camera and detects an obstacle based on the distance image.

JP 2012-102924 A JP, 2017-131556, A

However, with the conventional technique, it is difficult to control the automatic traveling of the vacuum cleaner with a simple configuration. For example, US Pat. No. 6,096,836 uses range images and thus requires multiple cameras or additional devices for range measurement. Note that Patent Document 1 does not relate to a vacuum cleaner.

The present invention has been made to solve such a problem, and has a control system for a vacuum cleaner capable of controlling the travel of the vacuum cleaner with a relatively simple configuration, an autonomous traveling vacuum cleaner, a cleaning system, and a vacuum cleaner. It aims at providing the control method of.

The control system of the vacuum cleaner according to the present invention is
An image pickup unit mounted on the vacuum cleaner and configured to pick up an image of the vicinity of the vacuum cleaner,
An edge extractor for extracting edges represented in the image,
An object detection unit that extracts a region surrounded by the extracted edges, and detects an object based on the extracted region,
Based on the detected position of the object, a traveling control unit that controls traveling of the cleaner,
Have.
According to a particular aspect, the image capturing unit captures the image based on near infrared rays.
According to a particular aspect,
A near-infrared light source unit that is mounted on the vacuum cleaner and emits near-infrared rays,
Further comprising a light source control unit for controlling the operation of the near infrared light source unit,
The light source control unit adjusts the orientation, height, or output of the near infrared light source unit.
According to a particular aspect, the light source control unit turns on and off the output of the near-infrared light source unit in accordance with the interval at which the image is captured.
According to a particular aspect, an object type determination unit for determining the type of object is further provided,
The object type determination unit,
Based on the detected shape of the object, find the height of the center of gravity of the object,
Comparing the height of the center of gravity and the first height obtained by multiplying the height in the image of the object by a first predetermined ratio,
When the height of the center of gravity is less than the first height, it is determined that the object is an object to which the cleaner should head,
If the height of the center of gravity exceeds the first height, the object is determined to be an object that the vacuum cleaner should avoid.
According to a particular aspect, the object detector is
Calculating the brightness complexity of the extracted region,
Based on whether or not the calculated brightness complexity is included in a predetermined range, it is determined whether or not the area represents an object.
According to a particular aspect, the object detector is
Calculate the circularity of the extracted region,
Based on whether or not the calculated circularity falls within a predetermined range, it is determined whether or not the area represents an object.
According to a particular aspect, the object detector is
Calculate the area of the extracted region,
Based on whether or not the calculated area is included in a predetermined range, it is determined whether or not the area represents an object.
An autonomous traveling type vacuum cleaner according to the present invention is an autonomous traveling type vacuum cleaner equipped with the above control system.
A cleaning system according to the present invention includes the control system described above and a cleaner that sucks dust.
The control method of the vacuum cleaner according to the present invention is
Capturing an image of the area around the vacuum cleaner,
Extracting the edges represented in the image,
Extracting a region surrounded by the extracted edge, and detecting an object based on the extracted region,
Controlling the travel of the vacuum cleaner based on the detected position of the object;
Have.

According to the vacuum cleaner control system, the autonomous traveling vacuum cleaner, the cleaning system, and the vacuum cleaner control method according to the present invention, the travel of the vacuum cleaner can be controlled with a relatively simple configuration.

It is a figure which shows the external appearance structure containing the vacuum cleaner which concerns on Example 1. It is explanatory drawing which shows the example of the external appearance of the remote control of FIG. 1 in more detail. It is a figure which shows the example of a structure of the sensor part of the vacuum cleaner which concerns on Example 1. FIG. 6 is an explanatory diagram showing an example of wavelength distribution when an image is taken through the visible light cut filter of the first embodiment. It is explanatory drawing which shows the example of a structure of the control part of the vacuum cleaner of Example 1. 5 is a flowchart showing an outline of an example of control processing by the control unit of the first embodiment. 7 is a flowchart illustrating the process of step S1 of FIG. 6 in more detail. 8 is a flowchart illustrating the process of step S16 of FIG. 7 in more detail. 7 is a flowchart illustrating the process of step S6 of FIG. 6 in more detail. 9 is a flowchart illustrating the content of object type determination processing according to the second embodiment. FIG. 9 is a diagram illustrating an object type determination process in the third embodiment. It is a figure which shows the example of a structure of the mobile terminal used in the modification of Examples 1-3.

Embodiments of the present invention will be described below with reference to the accompanying drawings.
Example 1.
This embodiment relates to an autonomous traveling type vacuum cleaner. The autonomous traveling type cleaner means, for example, a cleaner capable of performing a cleaning operation while traveling autonomously, and is generally called a “robot cleaner” or the like. This cleaner detects an object (cable or the like) existing in a space for cleaning, and controls traveling based on the detected position of the object. An example of a specific configuration will be described below with reference to the drawings.

FIG. 1 is a diagram showing an external configuration including a cleaner 100 according to the present embodiment. The vacuum cleaner 100 is a device that automatically cleans by incorporating a control system that controls its own operation, and is configured using, for example, traveling control technology. In the present embodiment, the vacuum cleaner 100 constitutes a cleaning system by itself, and executes the method according to the present embodiment (particularly, the vacuum cleaner control method). The vacuum cleaner 100 is used together with the remote controller 200 (remote controller).

The space in which the cleaner 100 cleans is arbitrary, but may be indoors or outdoors, for example. Inside the room (inside the room) or in the corridor may be cleaned indoors, and outdoors, a space occupying a certain volume may be cleaned. Although the present embodiment assumes an operation when cleaning the room, the same operation or a similar operation can be applied when cleaning other spaces.

The vacuum cleaner 100 and the remote controller 200 are configured to be able to communicate with each other. The communication is performed wirelessly using infrared rays, for example, but other radio waves or communication lines may be used. Remote controller 200 can be used as a terminal for a user of vacuum cleaner 100 to remotely operate vacuum cleaner 100. Vacuum cleaner 100 has a receiving unit for receiving a signal transmitted from the outside. In the present embodiment, the receiver is configured as the remote controller receiver 11 for receiving a signal from the remote controller 200.

Further, the vacuum cleaner 100 is equipped with an imaging unit 12 that captures an image around the vacuum cleaner 100 and a near-infrared light source unit 13 that radiates near-infrared rays. The imaging unit 12 can be configured using, for example, a known light receiving element, and the near infrared light source unit 13 can be configured using, for example, a near infrared LED. The vacuum cleaner 100 has a sensor unit 10 including a plurality of types of sensors for acquiring information used for control and display. In the present embodiment, the sensor unit 10 includes the above-described image pickup unit 12 and near-infrared light source. Including part 13. Further, in the present embodiment, the sensor unit 10 further includes the remote control receiving unit 11, but the remote control receiving unit 11 may be configured independently of the sensor unit 10. Further, the light transmission member 14 may be provided outside the sensor unit 10 (on the front face of the sensor unit 10 in the example of FIG. 1).

The cleaner 100 has a front panel 40 attached so as to cover the front surface of the cleaner 100. The “front surface” refers to a predetermined portion of the side surface of the cleaner 100 on the traveling direction side, for example. In the present embodiment, the sensor unit 10 is arranged on the front panel 40 together with the remote control receiving unit 11, the image capturing unit 12, and the near infrared light source unit 13 included in the sensor unit 10.

The imaging unit 12 acquires an image represented by electromagnetic waves. In particular, in this embodiment, the imaging unit 12 has a function of acquiring a visible light image represented by visible light and a function of acquiring a near infrared image represented by near infrared. When the near-infrared light source unit 13 irradiates the space with near-infrared light, the reflected light that reaches the imaging unit 12 is imaged by the imaging unit 12.

The positional relationship between the imaging unit 12 and the near-infrared light source unit 13 can be arbitrarily designed, but in the present embodiment, the imaging unit 12 and the near-infrared light source unit 13 are arranged so as to be adjacent to or close to each other in the sensor unit 10. It By installing in this way, the difference between the detection range or the detection angle of the imaging unit 12 and the irradiation range or the irradiation angle of the near infrared light source unit 13 can be reduced.

Further, the vacuum cleaner 100 has a monitor 20. Arrangement of the monitor 20 can be designed arbitrarily, but for example, it is arranged at a position where it can be easily visually recognized from the outside while the vacuum cleaner 100 is in operation. In the present embodiment, the monitor 20 is arranged on the upper surface of the vacuum cleaner 100, and particularly in the vicinity of the image pickup unit 12.

An example of the operation of the monitor 20 will be described. In the example of FIG. 1, an image showing the appearance of the vacuum cleaner 100 is displayed on the monitor 20. Further, when an object is detected by the process using the imaging unit 12 or the like (a specific example of the detection process will be described later), the cleaner 100 displays the information on the detected object on the monitor 20. For example, an appropriate image or figure is displayed at an appropriate position according to the positional relationship between the vacuum cleaner 100 and the object and the type, shape, etc. of the object. In this way, the user can visually recognize that the vacuum cleaner 100 can detect the object. Note that such an object may be displayed not only on the monitor 20 of the vacuum cleaner 100 but also on the remote controller 200. In that case, the remote controller 200 may also be provided with a monitor similar to the monitor 20.

In addition, in the present embodiment, the vacuum cleaner 100 has the remote control receiving unit 11, the imaging unit 12, the near infrared light source unit 13, the light transmitting member 14, and the monitor 20, but as a modification, at least the imaging unit 12 among them. The remote control receiver 11, the near infrared light source 13, the light transmitting member 14, and the monitor 20 can be omitted.

The cleaner 100 has a control system that controls the operation of the cleaner 100. The control system implements the methods described herein (particularly the vacuum cleaner control method). The control system of the vacuum cleaner 100 has a control unit 30. The control unit 30 is communicatively connected to the sensor unit 10, and in particular, is communicatively connected to the remote controller receiving unit 11, the imaging unit 12, and the near infrared light source unit 13. Control unit 30 controls the traveling of cleaner 100 based on the information received from sensor unit 10. The control unit 30 has a configuration as a known computer, and has a calculation unit and a storage unit (details will be described later with reference to FIG. 5 and the like). The arithmetic means is, for example, a processor, and the storage means is, for example, a semiconductor memory.

FIG. 2 is an explanatory diagram showing an example of the external appearance of the remote controller 200 of FIG. 1 in more detail.
Remote control 200 is used, for example, for remotely transmitting to vacuum cleaner 100 an instruction for causing cleaner 100 to clean the space. The user of the vacuum cleaner 100 can operate the remote controller 200 to cause the vacuum cleaner 100 to perform cleaning when he wants to clean the space.

Remote controller 200 transmits a wireless signal (for example, an infrared signal) that remote controller receiver 11 of vacuum cleaner 100 can receive. The wireless signal includes various instructions such as a driving request, a cleaning mode change, a driving mode change, and a stop request. The vacuum cleaner 100 can operate based on these instructions, and can clean the room, for example. It should be noted that remote controller 200 may have not only the wireless signal including the above-described instruction but also any other function.

The remote controller 200 has an input function unit for receiving an instruction from the user. In the example of FIG. 2, the input function unit includes seven buttons including the button 201. The button 201 is an automatic driving button. When button 201 is operated by the user (for example, pressed), remote controller 200 transmits a signal indicating that button 201 has been operated to cleaner 100, and control unit 30 of cleaner 100 causes sensor unit 10 to operate. This signal is received via and the automatic cleaning is started. More specifically, the process of FIG. 6 (described later) may be started.

By the button 201, the user can execute the cleaning of the room with one operation, and does not need to perform a plurality of operations for instructing detailed driving contents. The remote controller 200 of the present embodiment has buttons for presetting so that detection of an object such as a cable or dust is not started even if the button 201 is operated, or a travel control based on the detection result thereof. It may have a button for presetting not to be executed.

It should be noted that the position of the button 201 or the like may be installed anywhere on the remote controller 200, and when the remote controller 200 is provided with an openable/closable lid, it may be installed in a space covered by the lid.

FIG. 3 is a diagram showing an example of the configuration of the sensor unit 10 of the vacuum cleaner 100 of this embodiment. The sensor unit 10 includes a plurality of sensors included in the cleaner 100. The sensor unit 10 includes, for example, the near infrared light source unit 13 and the image pickup unit 12 as described above. Moreover, as shown in FIG. 3, it may include a timepiece or other components. Although not shown in FIG. 3, the remote controller receiver 11 may be included.

The image capturing unit 12 can capture an image of an electromagnetic wave having a specific wavelength or a wavelength range. Further, the image capturing unit 12 may be capable of capturing an image with electromagnetic waves having a plurality of wavelengths or wavelength ranges. The vacuum cleaner 100 may have a filter that blocks or attenuates electromagnetic waves of a specific wavelength or wavelength range that enter the imaging unit 12, and such a filter may be switchable. In this embodiment, the vacuum cleaner 100 has a visible light cut filter. This visible light cut filter has a low transmittance of visible light and ultraviolet rays and a high transmittance of near infrared rays, that is, it can be called a near infrared ray transmitting filter.

For example, when the imaging unit 12 acquires a near infrared image, the control unit 30 of the vacuum cleaner 100 sets a visible light cut filter on the imaging unit 12 and causes the imaging unit 12 to acquire a near infrared image. In this case, the image capturing unit 12 can capture an image by using a wavelength range near near infrared rays (for example, a specific wavelength band including 850 nm). Further, if necessary, before the image capturing by the image capturing unit 12, the control unit 30 turns on the near infrared light source unit 13, that is, irradiates the near infrared ray, and the near infrared image acquired by the image capturing unit 12 is reflected by the reflected light. Can be made clearer.

FIG. 4 is an explanatory diagram showing an example of the wavelength distribution when an image is taken through the visible light cut filter of this embodiment. FIG. 4 shows an example of a wavelength distribution of reflected light that is emitted from the near-infrared light source unit 13, is reflected around the cleaner 100, and reaches the imaging unit 12 via the visible light cut filter. In this way, the image capturing unit 12 can capture an image based on near infrared rays.

The imaging unit 12 of the present embodiment can clearly acquire the shape of an object such as a cable by acquiring an image of the vicinity of the vacuum cleaner 100 using near infrared rays. As a result, the control unit 30 can detect an object to be avoided or an object to be headed for and control traveling (a specific detection and control method will be described later).

FIG. 5: is explanatory drawing which shows the example of a structure of the control part 30 of the vacuum cleaner 100 of a present Example.
The control unit 30 receives the instruction transmitted from the remote controller 200 via the remote controller receiving unit 11. In addition, the control unit 30 acquires the detection results of other sensors included in the sensor unit 10. Then, based on the received instruction and the acquired detection result, control unit 30 controls traveling of cleaner 100.

The calculation means of the control unit 30 can operate as a functional unit, and in particular, the imaging control unit 31, the person detection unit 32, the wall detection unit 33, the edge extraction unit 34, the object detection unit 35, the object type determination unit 36, Also, it can operate as the traveling control unit 37. Here, the edge extraction unit 34 and the object detection unit 35 constitute an object recognition unit. Further, the storage unit of the control unit 30 has a storage unit 38.

These functional units may be implemented by using software (for example, a program), or may be implemented by using hardware (for example, an integrated circuit). Further, these functional units may be implemented by one program or one integrated circuit. Further, each of these functional units may be implemented by using a plurality of programs or a plurality of integrated circuits, or may be implemented by a combination of different programs or integrated devices for each processing to be executed.

The imaging control unit 31 has a function of controlling the operation of the near-infrared light source unit 13, that is, a function as a light source control unit. For example, the direction (angle), height, or output (for example, current load) of the near infrared light source unit 13 is adjusted. By doing so, it becomes possible to acquire an image in a more appropriate angle range, height range, or brightness.

Further, the imaging control unit 31 turns on and off the output of the near infrared light source unit 13 in accordance with the interval at which the near infrared light source unit 13 captures an image. For example, the near-infrared light source unit 13 is turned on immediately before the imaging operation by the imaging unit 12 is started (a predetermined time before, for example, 10 milliseconds before), and immediately after the imaging operation by the imaging unit 12 is finished (for a predetermined time only). After that, for example, after 10 milliseconds), the light is turned off. As described above, by limiting the irradiation timing to before and after the imaging timing by the imaging unit 12, the life of the near infrared light source unit 13 can be extended and power consumption can be reduced as compared with the case where the irradiation is continued steadily. can do.

The person detection unit 32 detects the position of a person in the room based on the image acquired by the image pickup unit 12. The wall detection unit 33 detects the position of the wall in the room based on the image acquired by the imaging unit 12.

The object recognition unit (edge extraction unit 34 and object detection unit 35) recognizes the object represented in the image acquired by the imaging unit 12. More specifically, the edge extraction unit 34 extracts the edge represented in the image, and the object detection unit 35 detects the object based on the extracted edge. As the image, for example, a near-infrared image captured by the image capturing unit 12 via a visible light cut filter can be used. In that case, for example, an object (cable or the like) arranged in the passage of the air flow and blocking the air flow is used. Can be recognized.

For the recognized (detected) object, the object type determination unit 36 is an object that the cleaner 100 should avoid and travel (object that should be avoided), or an object that the cleaner 100 should travel (go toward). Should be an object). The object to be avoided means, for example, an object that may block the traveling of the cleaner 100 or may hinder the traveling of the cleaner 100, and includes, for example, a cable. The object to be headed means, for example, an object to be sucked by the vacuum cleaner 100, and includes, for example, a dust piece.

The travel control unit 37 controls the travel of the cleaner 100 based on the position of the object recognized by the object recognition unit. This traveling control may be performed based on the determination result of the object type determination unit 36. For example, the traveling of the cleaner 100 can be controlled so as to move toward the dust pieces while avoiding the cable. As specific control contents, for example, the cleaner 100 may be moved forward, rotated right, rotated left, moved backward, and the like, and these may be combined and executed.

The storage unit 38 is configured by using a storage device that holds data representing an image captured by the image capturing unit 12 and the like. The storage unit 38 may include a volatile memory that retains data during power-on, and may include an auxiliary storage device that is a non-transitory storage medium. Each functional unit of the control unit 30 can store information necessary for processing and information related to the processing result in the storage unit 38.

Although the specific operation of the human detection unit 32 can be appropriately designed, an example will be described below. The human detection unit 32 detects the presence or absence of a person and the position of the person in the image based on the visible light image captured by the imaging unit 12 based on visible light. In addition, the person detection unit 32 sets the direction of the person with the cleaner 100 as a reference, the distance between the cleaner 100 and the person, and the cleaner 100 based on the detected position of the person in the image. Calculate the distance between a wall and a person.

In addition to the image acquired by the imaging unit 12, the human detection unit 32 uses the measurement result of at least one of an infrared sensor, a near infrared sensor, a thermography, a pyroelectric sensor, an ultrasonic sensor, and a noise sensor. Then, the presence or absence and the position of a person may be detected.

For example, the human detection unit 32 detects a circle having a size within a predetermined range as the human head from the image captured by the imaging unit 12, and specifies the detected position of the human head as the human position. Good. In addition, the person detection unit 32 holds in advance a person's face pattern including eyes, nose, and mouth, detects the person's face pattern, and detects the position of the area corresponding to the detected person's face pattern. You may specify as a position.

Further, the human detection unit 32 holds in advance the correspondence between the size of the person's head and the distance between the cleaner 100 and the person, and performs cleaning based on the correspondence and the detected size of the person's head. The distance between the machine 100 and a person may be calculated.

Furthermore, the person detecting unit 32 of the present embodiment may also detect the position of a person's feet. For example, the person detection unit 32 may directly detect the lower end of the moving target as the foot of the person by using the plurality of images captured by the image capturing unit 12. Further, the person detection unit 32 may detect the position of the person's head and estimate the position of the person's feet having a predetermined positional relationship with the position of the person's head.

Although the specific operation of the wall detection unit 33 can be appropriately designed, an example will be described below. The wall detection unit 33 extracts edges in the image based on the captured image, and further extracts a plurality of edges thicker and longer than a predetermined reference from the extracted edges. Then, the wall detection unit 33 detects the indoor corner by extending the straight line formed by each of the extracted thick and long edges to generate an intersection and using the center of gravity of the intersection as the vanishing point. Then, the wall detection unit 33 identifies the detected corner as a tangent line between walls, a tangent line between walls and a ceiling, or a tangent line between a wall and a floor, and determines the position of the wall, ceiling, and floor surface in the room. To detect.

The wall detection unit 33 may hold the position of the person detected by the person detection unit 32 in the past, and complement the corner detection result based on the accumulated data of the position of the person. This is based on the rule of thumb that indoor walls are more likely to be outside the space occupied by cumulative human position data and less likely to be inside the space occupied by cumulative human position data. .. The wall detection unit 33 may exclude the detection result from the indoor wall candidates when the indoor wall candidate is detected at a position inside the space occupied by the accumulated data of the human positions.

The object recognition unit (edge extraction unit 34 and object detection unit 35) recognizes an object based on the captured image. Objects include, for example, tables, kotatsu, chairs, sofas, bookshelves, cupboards, chests of drawers, fittings (walls, floors, ceilings, doors, windows, beams, rails, etc.), cables, garbage, tableware (chopsticks, etc.). .. Moreover, the object includes a large figurine, a potted pot, and the like.

In the present embodiment, the object type determination unit 36 determines the type of object for each recognized (detected) object.

FIG. 6 is a flowchart showing an outline of a control processing example by the control unit 30 of the present embodiment. This process is started, for example, in response to a predetermined instruction transmitted from remote controller 200. In the processing of FIG. 6, first, the object recognition unit recognizes an object placed in the space to be cleaned (step S1, details will be described later with reference to FIG. 7 and the like).

Next, the object type determination unit 36 determines the type of object (step S2). The definition of the type of the object and the determination process can be appropriately designed by those skilled in the art, but an example is shown below. The types of objects include objects to be avoided and objects to be headed for. Definitions of other types (charging device etc.) may be included. An example of an object to avoid is a cable that may block the travel of the cleaner 100, and an example of an object to head is a small piece of dust to inhale.

The determination process can be performed using, for example, the parameters calculated at the time of object recognition. For example, if the circularity, area, and brightness complexity (each of which will be described later with reference to FIG. 8) have been calculated for each object in step S1, the determination may be performed using these. As a more specific example, the object type determination unit 36, for a certain object, if the circularity is larger than a predetermined threshold, the area is smaller than a predetermined threshold, and the brightness complexity is smaller than a predetermined threshold, The object is determined to be the object to be headed. Also, if not (ie, circularity is less than or equal to a predetermined threshold, area is greater than or equal to a predetermined threshold, or luminance complexity is greater than or equal to a predetermined threshold), the object should be avoided. Determined as an object.

Next, the person detection unit 32 detects a person (step S3). The detection of a person can be performed based on, for example, an image captured by the image capturing unit 12, but instead of the image capturing unit 12 (or in addition to the image capturing unit 12), a pyroelectric infrared sensor or the like is used to detect the person. The position may be grasped. The person detection unit 32 acquires the presence or absence of a person, the position of the person in the image, the direction in which the person is based on the cleaner 100, the distance between the person and the cleaner 100, and the distance between the wall and the person. The person detection unit 32 may store the acquired information in the storage unit 38.

Next, the wall detection unit 33 detects a corner in the room (step S4) and detects opening/closing of the partition (step S5).

Based on the processing results in steps S3 to 5 (for example, based on the detection result of the position of the person and the position of the corner), control unit 30 determines the size (for example, shape and size) of the room.

Next, the traveling control unit 37 controls traveling of the cleaner 100 based on the processing results of S1 to S5 (step S6, details will be described later with reference to FIG. 9 and the like). For example, traveling control unit 37 determines a traveling method based on the processing results of S1 to S5, and causes cleaner 100 to travel according to the determined traveling method. The traveling may include movements such as forward movement, right rotation, left rotation, and backward movement.

FIG. 7 is a flowchart illustrating the process of step S1 of FIG. 6 in more detail. In the process of FIG. 7, the imaging control unit 31 first switches on the visible light cut filter (step S11). For example, the visible light cut filter is moved to the front of the imaging unit 12. Next, the image capturing unit 12 captures a plurality of images by repeating the loop processing of steps S12 to S17.

In the loop processing, first, the image pickup unit 12 changes the image pickup direction (step S12). The imaging direction is changed by, for example, moving or rotating or rotating the camera. By this process of changing the image capturing direction, it is possible to capture images in a plurality of directions or a wider range with one image capturing device. The imaging directions can be, for example, three directions of a left direction, a center direction, and a right direction.

Next, the imaging control unit 31 turns on the near-infrared light source unit 13, thereby irradiating the room with near-infrared light (near-infrared irradiation ON) (step S13). Next, the imaging unit 12 captures an image of the area around the vacuum cleaner 100 (step S14). Next, the imaging control unit 31 turns off the near-infrared light source unit 13, thereby stopping the irradiation of near-infrared rays (near-infrared ray irradiation OFF) (step S15).

Next, the object recognition unit (the edge extraction unit 34 and the object detection unit 35) recognizes the object based on the image acquired by the imaging unit 12 (step S16, details will be described later using FIG. 8 and the like). .. As a result, it is determined whether or not there is an object in the room. Note that the process of step S2 of FIG. 6 (determination of the type of object) may be executed after the end of step S1 as shown in FIG. 6, or during the execution of step S1 (for example, after step S16 and step S17). Before).

Next, the imaging control unit 31 determines whether or not the imaging in the designated plural directions is completed (step S17), and when the imaging in the designated plural directions is not completed (S17: No). , The process returns to step S12. On the other hand, when the imaging in the designated plural directions is completed (S17: Yes), the imaging control unit 31 switches the visible light cut filter off (step S18). For example, the visible light cut filter is removed from the front of the imaging unit 12. Then, the imaging control unit 31 ends the process of FIG. 7.

A person skilled in the art can appropriately change the execution timing of each process of FIGS. 6 and 7. For example, the processes of steps S1 and S2 may be executed independently of steps S3 to S6, in which case the steps are performed in response to operation of button 201 of remote controller 200 or another specific button. You may comprise so that the process of S1 and S2 may be performed. Further, the processes of steps S1 and S2 may be configured to be executed at predetermined time intervals.

FIG. 8 is a flowchart for explaining the process of step S16 of FIG. 7 in more detail. In the process of FIG. 8, the edge extraction unit 34 first acquires an image (step S21). The image is, for example, a visible light image or a near infrared image, but may be one of these. A person skilled in the art can appropriately determine which of these is used for the subsequent processing according to various conditions. For example, the color or pattern of an object appears in a visible light image, and thus the edge of the object may not be accurately detected, but the near infrared image reduces such a problem.

Next, the edge extraction unit 34 executes a smoothing process on the image (step S22). Specifically, the edge extraction unit 34 converts the brightness of a pixel whose brightness is largely different from that of many surrounding pixels into the same brightness as the surrounding pixels. This removes noise from the image. Note that step S22 may be omitted. Next, the edge extraction unit 34 extracts edges in the image (step S23). A specific process for extracting an edge in an image can be appropriately designed by those skilled in the art based on a known technique.

Next, the object detection unit 35 detects an object in the image based on the extracted edge. Although specific processing for detecting an object can be appropriately designed by those skilled in the art based on a known technique, an example will be described after step S24 in FIG. 8 and will be described below.

The object detection unit 35 divides the image into a plurality of areas (step S24). For example, for one continuous edge forming a closed figure, a region surrounded by the edge is extracted and separated from a region outside the edge. Next, the object detection unit 35 detects the object based on the extracted area by executing the processing of steps S26 to S33 described below for each of the divided areas. For example, it is determined whether or not the processing of steps S26 to S33 has already been executed for all areas (step S25), and if it has already been executed for all areas, the processing of FIG. 8 ends.

Note that, as will be apparent from the following, the process of FIG. 8 can be executed if an area can be extracted from one image, and an additional device for distance measurement and complicated processes such as depth calculation using a stereo image. Since these are unnecessary, it can be realized with a relatively simple configuration (however, processing using a stereo image or the like is not excluded from the scope of the present invention).

If there is an unprocessed area, the object detection unit 35 calculates the circularity of the area (step S26). Here, the circularity is a value representing “circularity” of a certain area, and is defined by the following formula:
Circularity = 4πS/(L ² )
Here, π is the pi, S is the area of the region, and L is the perimeter of the region (for example, the length of the edge). It can be said that the larger the circularity is, the closer the area is to a circle. When the circularity is 1, the area is a perfect circle.

Next, the object detection unit 35 determines whether or not the calculated circularity is within a predetermined range suitable as the circularity of the object (step S27). The value representing the predetermined range or the boundary thereof may be stored in the storage unit 38 in advance. If the circularity is not within the predetermined range, the object detection unit 35 returns the process to step S25. In this case, it can be said that it is determined that the region is unlikely to represent an object.

When the circularity is included in the predetermined range, it can be said that the area is determined to have a high possibility of representing an object. In this case, the object detection unit 35 calculates the area of the region (step S28). The area calculated here is, for example, the area in the image.

Next, the object detection unit 35 determines whether or not the calculated area is included in a predetermined range suitable as the area of the object (step S29). The value representing the predetermined range or the boundary thereof may be stored in the storage unit 38 in advance. If the area is not included in the predetermined range, the object detection unit 35 returns the process to step S25. In this case, it can be said that it is determined that the region is unlikely to represent an object.

When the area is included in the predetermined range, it can be said that the area is determined to have a high possibility of representing an object. In this case, the object detection unit 35 calculates the brightness complexity of the area (step S30). The luminance complexity is, for example, the degree of variation in the luminance of each pixel included in the area, and can be defined as, for example, the variance of the luminance of each pixel.

Next, the object detection unit 35 determines whether or not the calculated luminance complexity is included in a predetermined range suitable as the luminance complexity of the object (step S31). The value representing the predetermined range or the boundary thereof may be stored in the storage unit 38 in advance. Objects such as cables have lower brightness complexity than humans and higher brightness complexity than floors, so by setting an appropriate range, such objects can be recognized properly. be able to. When the brightness complexity is not included in the predetermined range, the object detection unit 35 returns the process to step S25. In this case, it can be said that it is determined that the region is unlikely to represent an object.

When the brightness complexity is included in the predetermined range, it can be said that the area is determined to have a high possibility of representing an object. In this case, the object detection unit 35 determines that the area represents an object (step S32). In this way, the object represented in the image is recognized.

As described above, in the example of FIG. 8, the object detection unit 35 determines whether or not each region represents an object based on the circularity, the area, and the brightness complexity. By making the determination based on the three features in this manner, a more accurate determination can be made. As a modification, the object detection unit 35 may make the determination based on only one or two of the circularity, the area, and the brightness complexity. Even if the determination is based on only one or two, relatively accurate object detection can be performed by a relatively simple determination process. Furthermore, the object detection unit 35 may make this determination using any index other than the circularity, the area, and the brightness complexity.

Next, the object detection unit 35 calculates the position, distance, and the like of the area determined to represent the object (step S33). For example, a position (for example, represented by two-dimensional coordinates) in the image is obtained for the region, and based on the obtained position, a position where the object is arranged in the actual space (for example, three-dimensional with the cleaner 100 as a reference). (Represented by the coordinates). The position of the object in the real space can be represented by the positional relationship between the cleaner 100 and the object. The positional relationship is expressed using, for example, the direction of the object viewed from the cleaner 100 and the distance between the object and the cleaner 100. The object detection unit 35 may also calculate the distance between the wall and the object.

In addition, the object detection unit 35 stores the presence or absence of an object, the position of each object in the image, and the positional relationship between the cleaner 100 and each object in the storage unit 38 based on the result of the process of FIG. 8. Good. Further, the object detection unit 35 may store the distance between the wall and each object in the storage unit 38.

In this way, the positional relationship with the cleaner 100 is specified for all the recognized objects. The control unit 30 controls the operation (for example, running operation) of the cleaner 100 based on this positional relationship. The specific control contents at this time can be appropriately designed by those skilled in the art, but one example is shown below.

FIG. 9 is a flowchart for explaining the process of step S6 of FIG. 6 in more detail. Note that this example is processing when only one object is recognized. In the process of FIG. 9, the traveling control unit 37 first refers to the determination result of step S2 to determine whether or not the object is an object to be avoided (step S51). If it is an object to be avoided, it is determined whether the object is in front of the cleaner 100 (step S52). If the object to be avoided is on the front, the traveling control unit 37 configures the traveling route so as to avoid the object, and causes the cleaner 100 to travel accordingly (step S53). The travel route can be configured by combining forward travel, right rotation, left rotation, and reverse travel, for example. A person skilled in the art can appropriately design how to construct a traveling route that avoids a certain object. For example, by first rotating the cleaner 100 right or left until the object comes out of the front, the direction of the vacuum cleaner 100 is changed, and then the traveling route is advanced. can do. After step S53, the traveling control unit 37 may end the process, or may return the process to step S52 and repeatedly perform the determination until the object to be avoided comes out of the front.

When the object is not the object to be avoided in step S51, the traveling control unit 37 further refers to the determination result of step S2 and determines whether or not the object is the object to head (step S54). If the object is the one to be headed, it is determined whether the object is in front of the cleaner 100 (step S55). When the object to be headed is on the front, the traveling control unit 37 configures a traveling path toward the object, and causes the cleaner 100 to travel accordingly (step S56). The travel route can be configured by combining forward travel, right rotation, left rotation, and reverse travel, for example. Although a person skilled in the art can appropriately design a method of forming a traveling route toward a certain object, for example, the traveling route can be a route that advances forward as it is. After step S56, the traveling control unit 37 may end the process, or may return the process to step S55 and repeatedly perform the determination so that the object to be headed is maintained in front.

When it is determined in step S52 that the object to be avoided is not in front, the traveling control unit 37 ends the process. Also, when it is determined in step S54 that the object is not the one to head for, the traveling control unit 37 ends the process. Further, when it is determined in step S55 that the object to be headed is not in the front, the traveling control unit 37 ends the process in the example of FIG. 9, but as a modification, the traveling route is configured to face the object. However, the cleaner 100 may be run accordingly.

Note that FIG. 9 is an example of the processing when only one object is recognized, but when a plurality of objects are recognized (when a plurality of objects to be avoided are recognized, when a plurality of objects to be headed are recognized, A person skilled in the art can appropriately design the processing such as (when the object to be avoided and the object to be headed are recognized at the same time) based on the above description with reference to FIG. 9 and known techniques.

With such control, the cleaner 100 can travel without being blocked by an object existing in the space to be cleaned based on the shape of the object, while being positive toward the dust existing in the space to be cleaned. It can be moved to and cleaned to improve the cleaning performance of the space to be cleaned.

Further, as compared with the technique described in Patent Document 1, the technique of Patent Document 1 detects the presence and position of an obstacle, but does not cause the device to run based on the result, and Nor is it based on the individual characteristics of obstacles such as cables. The vacuum cleaner 100 according to the first embodiment can provide a better solution to a problem in which a cable or the like arranged on the floor interferes with traveling and a need to firmly suck dust in the entire room. ..

Further, as compared with the technique described in Patent Document 2, the image capturing unit 12 of the vacuum cleaner 100 according to the first embodiment of the present invention does not need to include a stereo camera, a distance measuring device, or the like, and a single camera is also used in the present invention. Since the effect of can be obtained, it is possible to recognize an object with a relatively simple configuration.

Example 2.
The second embodiment is a partial modification of the content of the object type determination process (step S2 in FIG. 6) of the first embodiment. The difference from the first embodiment will be described below.

FIG. 10 is a flowchart illustrating the contents of the object type determination process (referred to as step S2') in the second embodiment. In the determination process according to the second embodiment, the object type determination unit 36 first obtains the height of the center of gravity of the object based on the recognized shape of the object (step S101). The height of the center of gravity is, for example, the height of the center of gravity in the image. The height of the center of gravity in the image can be calculated by any method, and may be calculated, for example, as the average of the heights (for example, Y coordinate values) of the pixels forming the region representing the object.

Next, the object type determination unit 36 calculates the height of the object in the image (step S102). The height of the object can be calculated by any method, and may be calculated, for example, as the height position of the pixel at the highest position in the object.

Next, the object type determination unit 36 calculates the reference barycentric height (first height) of the object based on the height of the object (step S103). The reference center-of-gravity height can be calculated by any method, and may be calculated, for example, as a value obtained by multiplying the height of the object by a predetermined ratio (first predetermined ratio). Alternatively, it is possible to use any method of determining the height of the center of gravity serving as a reference according to the shape of the object.

Next, the object type determination unit 36 compares the height of the center of gravity obtained in step S101 with the reference height of the center of gravity obtained in step S103 (step S104). When the height of the center of gravity is less than the reference height of the center of gravity, the object type determination unit 36 determines that the object is an object to which the object should be directed (step S105). On the other hand, if the height of the center of gravity exceeds the height of the reference center of gravity, the object type determination unit 36 determines that the object is an object to be avoided (step S106). Branches when they are equal can be designed arbitrarily.

According to such a determination method, the type of the object can be determined relatively accurately by a relatively simple determination method.

Although the height in the image is used as the “height” in the second embodiment described above, the height in the real space may be used as a modified example. The height in the real space may be represented as a difference from the height of the vacuum cleaner 100 (or its reference portion), for example. Those skilled in the art can appropriately design the conversion rule and the method of obtaining the position of the center of gravity in that case, but an example is shown below. For example, the object type determination unit 36 holds in advance the correspondence relationship between the height in the image captured by the image capturing unit 12 and the height in the real space. The object type determination unit 36 may obtain the height of the object indicated by the area based on the height of the lower end of the area in the image and the correspondence. In this way, the height of the object installed on the floor or the object falling on the floor can be appropriately determined.

Example 3.
The third embodiment is a partial modification of the content of the object type determination process (step S2 in FIG. 6) of the first embodiment. The difference from the first embodiment will be described below.
FIG. 11 is a diagram illustrating the object type determination process according to the third embodiment. The difference from the first embodiment will be described below.

In the third embodiment, the object type determination unit 36 holds the result of the object type determination process executed in the past in the storage unit 38. In the example of FIG. 11, the results of the past 10 times are retained. Although the result of the determination process may be represented in any format, in the example of FIG. 11, the image is divided into a plurality of regions, and a value representing the size of the area occupied by the object to be avoided is calculated in each region. Has been done.

Each area is, for example, a rectangular cell and is divided into the same shape having a predetermined number of pixels in each of the vertical and horizontal directions. In addition, the size of the occupied area is represented by, for example, five levels of 1 to 5, and when the pixel corresponding to the object among the pixels in the region is less than 20%, it is 1, 20% or more and less than 40%. Is 2, 40% or more and less than 60%, 3, 60% or more and less than 80%, 4 or 80% or more, and so on.

In the example of FIG. 11, the matrix 50 including a plurality of cells is generated by dividing the image into a plurality of cells. The matrix 50 is a matrix of images captured by the image capturing unit 12, and is generated by dividing the image into vertical 5 cells×horizontal 10 cells.

The object type determination unit 36 takes a majority vote of past results of the value indicating the size of the occupied area for each region. For example, if “2” is 7 times and “1” is 3 times out of 10 results for a certain area, the size of the area occupied by the object in that area to be avoided is “2” as a result of the majority vote. ..

Then, the object type determination unit 36 determines the presence or absence of the object to be avoided for each area based on the result of the majority decision, and thereby determines the position of the object to be avoided. For example, for an area in which the size of the area occupied by the object to be avoided is "2" or less, it is determined that there is no object to be avoided, and a size of the area occupied by the object to be avoided is "3" or more. Determines that there is an object to be avoided. A person skilled in the art is aware of the correspondence and conversion rule between the position or coordinates (for example, two-dimensional coordinates) of a region in an image and the position or coordinates (for example, three-dimensional coordinates) of a portion that the region represents in the real space. It can be appropriately designed based on the above.

As a modification of the third embodiment, the presence/absence of an object may be determined not for each region but for each column of the region. The row of regions is composed of, for example, all regions vertically aligned in the image (for example, regions having the same X coordinate). In each column of the region, the size of the area occupied by the objects to be avoided in the regions included in the column is summed up, and there is an object to be avoided in the column whose total value is equal to or greater than a predetermined value (eg, “7”). It is possible to determine that there is no object that should be avoided for the columns whose total value is less than the predetermined value. For example, in the example of majority vote in FIG. 11, it is determined that an object exists in the second to fourth region columns from the left and the second and third region columns from the right.

As another modification of the third embodiment, a value representing the type of the object existing in the area is recorded instead of or in addition to the value representing the size of the occupied area of the object to be avoided for each area. May be. For example, for each area, the value is recorded as "0" when there is no object, "1" when there is an object to be avoided, "2" when there is an object to be headed, etc. May be done.

As a modified example of the third embodiment, an arbitrary determination rule may be added. For example, when it is determined that there is an object to be headed even after the cleaner 100 has passed through the area once or more in the area where it was previously determined that there is an object to head, an object in that area is present. May be determined not to exist. By doing so, it is possible to automatically correct the inappropriate determination.

In this way, by determining the presence/absence of an object not in units of pixels but in units of regions, the storage capacity requirement can be relaxed. Alternatively, many past processing results can be held with a limited storage capacity.

The following modifications can be made in the first to third embodiments described above.
In the first to third embodiments, an external device that can communicate with the vacuum cleaner 100 may be added. The external device may be a mobile terminal configured separately from the remote controller 200. The mobile terminal may be, for example, a smartphone or a tablet terminal.

FIG. 12 shows an example of the configuration of a mobile terminal used in such a modification. This mobile terminal has a function of displaying a feedback screen based on the information transmitted from the vacuum cleaner 100. FIG. 12 shows an example of the feedback screen 300 when the vacuum cleaner 100 detects an object to be headed.

On the feedback screen 300, the floor plan of the room and the detection result of the object to be headed are displayed in one screen. The position of the object to be headed is indicated as "dust" on the floor plan in the example of FIG. Further, the feedback screen 300 shows the position of the vacuum cleaner 100 on the floor plan. The position of the vacuum cleaner 100 is shown as "vacuum cleaner" in the example of FIG. Further, on the feedback screen 300, a level gauge 301 showing the degree of cleaning progress on an object (dust etc.) to be headed is displayed. The level gauge 301 indicates the amount of the object to be headed, for example, the maximum value is 100, and the value of the level gauge rises as the amount of the object to head increases. Accordingly, the user of the vacuum cleaner 100 can grasp the progress of cleaning at a glance. Further, the travel data of the vacuum cleaner may be used for displaying the feedback screen 300, and for example, the determined travel route may be displayed by being superimposed on the floor plan.

The vacuum cleaner 100 of Examples 1 to 3 is an autonomous traveling type vacuum cleaner, that is, a vacuum cleaner capable of autonomous cleaning. A person skilled in the art can appropriately interpret the meaning of "the cleaning can be performed autonomously". For example, it is possible to operate from the start to the end of a predetermined cleaning operation unit without receiving an external control input. Means that. With such a configuration, it is not necessary to arrange a complicated control system outside the vacuum cleaner, and the overall configuration is simplified. Note that operations other than cleaning (charging, setting changes, etc.) may require external control input.

The vacuum cleaner 100 according to the first to third embodiments is configured as a cleaning system including a control system and a vacuum cleaner by itself, but the control system (or a part thereof) and the vacuum cleaner may be separately provided. . In particular, the cleaner may be configured to communicate with an external control system and receive commands from the control system to perform cleaning. For example, the image captured by the vacuum cleaner may be transmitted to a server on the Internet, the server may recognize the object, and the result may be transmitted to the vacuum cleaner. In particular, at least a part of the imaging control unit 31, the human detection unit 32, the wall detection unit 33, the edge extraction unit 34, the object detection unit 35, the object type determination unit 36, the traveling control unit 37, and the storage unit 38 is a vacuum cleaner. Can be provided outside of the. In such a configuration, the vacuum cleaner includes at least the imaging unit 12 and the near-infrared light source unit 13 (if present), and has a function of communicating with the control system and a function of traveling based on an instruction from the control system. , And has a function of sucking dust. With such a configuration, the configuration of the vacuum cleaner can be made simpler.

The remote controller 200 may be omitted. In that case, the input function part (button etc.) of the remote control 200 may be provided in the vacuum cleaner.

In the first to third embodiments, the object recognition unit includes the edge extraction unit 34 and the object detection unit 35. In this way, the object can be properly recognized, but the structure of the object recognition unit is not limited to this.

In the first to third embodiments, the type of the detected object is determined, but the type determination can be omitted (in that case, the object type determination unit 36 is unnecessary). For example, if it is configured to detect only the objects to be avoided, it is possible to cause the detected objects to run regardless of their types. Further, when it is not necessary to detect an object to be avoided, if only the object to be headed is detected, all the detected objects can be made to travel regardless of the type.

Steps S3 to S5 in the first to third embodiments can be arbitrarily omitted. When either of them is omitted, the traveling control unit 37 controls the traveling of the cleaner 100 without using the detection result in the omitted step.

In the first to third embodiments, the traveling route of the cleaner 100 is determined based on only the recognized object, but as a modified example, the traveling route may be determined with reference to other factors. For example, the position of a corner, partition, person (or person's foot), etc. in a room may be referred to.

In Examples 1 to 3, the area of the region representing the object in the image is used as the area of the object (step S28 and the like), but as a modification, the projected area of the object corresponding to the region in the real space is used. You may use. In that case, the object detection unit 35 may execute appropriate processing for calculating the distance from the cleaner 100 to the object in order to calculate the projected area of the region in the real space.

An example of this processing is shown below. The object detection unit 35 holds in advance the correspondence relationship between the height of the object indicated by a certain area, the area of the area in the image, and the projected area of the object in the real space. The projected area of the object in the real space may be obtained based on the distance between the object and another reference structure (for example, a wall).

Note that the object detection unit 35 indicates, for each area determined to be an area representing an object, the position of the area, the direction viewed from the cleaner 100, the height of the object represented by the area, and the area. The distance between the object and the vacuum cleaner 100 may be stored in the storage unit 38.

In Examples 1 to 3, the imaging control unit 31 turns on and off the output of the near infrared light source unit 13 according to the interval at which the imaging unit 12 captures an image. The timing can be designed arbitrarily. In addition, as a modification, the control content of the imaging control unit 31 can be arbitrarily designed. For example, the near infrared light source unit 13 may always be on. Further, the imaging unit 12 may rotate in the vertical direction instead of or in addition to the rotation in the horizontal direction to perform imaging in each direction. Further, when the image capturing unit 12 has a camera capable of capturing a wide range, the image capturing unit 12 may not rotate and may capture a wide angle range in a single direction (in that case, in the process of FIG. Loop structure is unnecessary).

In Examples 1 to 3, the near-infrared light source unit 13 emits near-infrared light having a wavelength peak around 850 nm. The image of the reflected light of the near-infrared light is whiter (brighter or stronger in intensity) as the direction of the reflected light matches the direction of the image capturing unit 12, and darker (darker or brighter) in the direction away from the image capturing unit 12. Becomes weaker).

Generally, wood, cloth, metal, paper and the like have a rough surface, and near infrared rays are diffusely reflected on the surface. The object recognition unit detects that the reflecting object exists in the reflecting direction by the imaging unit 12 imaging the near-infrared reflected in the direction of the imaging unit 12 among the diffused and reflected near-infrared rays. You can

Therefore, by using an image obtained by capturing the reflected light of near infrared rays, the object recognition unit makes a determination in consideration of the difference between the material of the object generally existing in the room and the material of the floor, wall, or other object. Can be made. Then, an image that can clearly identify the shape of an object such as an object from a background such as a wall or a floor can be acquired, and an image that clearly reflects the shape of a three-dimensional object can be acquired.

When the image capturing unit 12 captures near-infrared rays in the vicinity of 850 nm as described above, it is difficult for the image to capture the color and pattern of the captured object, and only the shape of the object is likely to be captured. This is because the reflected light of near infrared rays changes depending on the material and angle of the object, and the reflected light does not change depending on colors and patterns. Therefore, there is a possibility that the shape of the object can be recognized more accurately.

When the near-infrared light source unit 13 irradiates the near-infrared light source having a peak around 850 nm, the irradiation spectrum can be configured to include a part of visible light. With this configuration, when the near-infrared light source unit 13 is turned on, when a person in the room looks at the cleaner 100, the near-infrared light source unit 13 appears to be turned on in red. Therefore, when the near-infrared light source unit 13 is installed, a display unit for displaying whether or not the near-infrared light is being turned on is unnecessary, and thus cost can be reduced. In addition, since no color appears in the near infrared image, the amount of information required to represent the image is reduced. Further, since the color does not appear, noise in the image is reduced, and accuracy in detecting an object is improved.

In addition, in Examples 1 to 3, it is possible to accurately grasp the three-dimensional shape of the object by using the reflected light by turning on the near infrared light source unit 13, but when such an advantage is not particularly useful. Alternatively, the near infrared light source unit 13 may be omitted.

In Examples 1 to 3, the image capturing unit 12 can capture images using visible light and near infrared rays. As a modified example, only one of these may be used, or instead of these or in addition to these, imaging may be performed using another wavelength.

The vacuum cleaner 100 of the first to third embodiments is a device mainly for cleaning, but as a modified example, it may have other functions such as an air cleaning function and a watching function.

The scope of the present invention is not limited to the above-described embodiments and modified examples, and includes various other modified examples. For example, the above-described embodiments and modified examples have been described in detail in order to explain the present invention in an easy-to-understand manner, and the present invention is not limited to those having all the configurations described.

Further, it is possible to replace a part of the configuration of a certain embodiment or a modified example with a part of the configuration of another example or a modified example. It is also possible to add a part of the configuration of the example or the modified example. Further, it is possible to add, delete or replace a part of the configuration of each embodiment or the modification with a part of the configuration of the other embodiment or the modification.

Further, each of the above-described configurations, functions, processing units, processing procedures, and the like may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Further, each of the above-described configurations, functions, and the like may be realized by software by a processor interpreting and executing a program that realizes each function. Information such as a program, a table, or a file that realizes each function can be placed in a recording device such as a memory, a hard disk or an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card or a DVD.

Further, the configuration of the control line or the information line can be designed arbitrarily.

10 sensor section (11 remote control receiving section, 12 imaging section, 13 near infrared light source section, 14 light transmitting member), 20 monitor, 30 control section (31 imaging control section, 32 person detecting section, 33 wall detecting section, 34 edge extraction Section, 35 object detection section, 36 object type determination section, 37 running control section, 38 storage section), 40 front panel, 50 matrix, 100 vacuum cleaner, 200 remote controller, 201 button, 300 feedback screen, 301 level gauge.

Claims (11)

A control system for a vacuum cleaner,
An image pickup unit mounted on the vacuum cleaner and configured to pick up an image of the vicinity of the vacuum cleaner,
An edge extractor for extracting edges represented in the image,
An object detection unit that extracts a region surrounded by the extracted edges, and detects an object based on the extracted region,
Based on the detected position of the object, a traveling control unit that controls traveling of the cleaner,
A control system. The control system according to claim 1, wherein
The control system, wherein the imaging unit captures the image based on near infrared rays. The control system according to claim 1 or 2, wherein
A near-infrared light source unit that is mounted on the vacuum cleaner and emits near-infrared rays,
Further comprising a light source control unit for controlling the operation of the near infrared light source unit,
The light source control unit adjusts the orientation, height or output of the near infrared light source unit,
Control system. The control system according to claim 3, wherein the light source control unit turns on and off the output of the near-infrared light source unit in accordance with an interval at which the image is captured. The control system according to any one of claims 1 to 4,
It further has an object type determination unit for determining the type of object,
The object type determination unit,
Based on the detected shape of the object, find the height of the center of gravity of the object,
Comparing the height of the center of gravity and the first height obtained by multiplying the height in the image of the object by a first predetermined ratio,
When the height of the center of gravity is less than the first height, it is determined that the object is an object to which the cleaner should head,
If the height of the center of gravity exceeds the first height, the object is determined to be an object that the cleaner should avoid.
Control system. The control system according to claim 1, wherein
The object detection unit,
Calculating the brightness complexity of the extracted region,
Based on whether or not the calculated brightness complexity is included in a predetermined range, it is determined whether or not the region represents an object,
Control system. The control system according to claim 1 or 6, wherein
The object detection unit,
Calculate the circularity of the extracted region,
Based on whether or not the calculated circularity is included in a predetermined range, it is determined whether or not the region represents an object,
Control system. The control system according to any one of claims 1 to 7,
The object detection unit,
Calculate the area of the extracted region,
Based on whether or not the calculated area is included in a predetermined range, it is determined whether or not the region represents an object,
Control system. An autonomous traveling vacuum cleaner equipped with the control system according to claim 1. A control system according to any one of claims 1 to 8,
A vacuum cleaner that sucks in trash,
A cleaning system. A method of controlling a vacuum cleaner,
Capturing an image of the area around the vacuum cleaner,
Extracting the edges represented in the image,
Extracting a region surrounded by the extracted edge, and detecting an object based on the extracted region,
Controlling the travel of the vacuum cleaner based on the detected position of the object;
And a control method.

Images