KR101526117B1 - Cleaning robot control method and apparatus based on autonomous learning - Google Patents

Cleaning robot control method and apparatus based on autonomous learning Download PDF

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Publication number
KR101526117B1
KR101526117B1 KR1020140053594A KR20140053594A KR101526117B1 KR 101526117 B1 KR101526117 B1 KR 101526117B1 KR 1020140053594 A KR1020140053594 A KR 1020140053594A KR 20140053594 A KR20140053594 A KR 20140053594A KR 101526117 B1 KR101526117 B1 KR 101526117B1
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South Korea
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cleaning
cleaning robot
set time
mode
target material
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KR1020140053594A
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Korean (ko)
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윤진효
양정호
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재단법인대구경북과학기술원
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    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L9/00—Details or accessories of suction cleaners, e.g. mechanical means for controlling the suction or for effecting pulsating action; Storing devices specially adapted to suction cleaners or parts thereof; Carrying-vehicles specially adapted for suction cleaners
    • A47L9/28—Installation of the electric equipment, e.g. adaptation or attachment to the suction cleaner; Controlling suction cleaners by electric means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions

Abstract

The present invention relates to a method of controlling a cleaning robot based on autonomous learning and an apparatus thereof. The method of controlling a cleaning robot based on autonomous learning comprises: a step of, in an N^th cleaning process, driving a cleaning robot having a camera mounted thereon on a normal condition of a reference speed or a reference suction strength during a first set time period; a step of, when the first set time period passes in the N^th cleaning process, applying a condition of a learning mode allowing variation in phases of gradually reducing speed or increasing strength in comparison with a normal mode, and driving the cleaning robot during a second set time period; a step of, based on a photographed image of the camera obtained per variation time point during the second set time period in the N^th cleaning process, extracting a critical speed or a critical suction strength in which an arbitrary target substance which remains during the previous first set time period starts to be removed, and obtaining a correction mode having the extracted information; a step of driving the cleaning robot in the normal mode condition during the first set time period in a (N+1)^th cleaning process, and when the arbitrary substance and the same type of target substance are detected by the camera, performing conversion into the correction mode obtained in the N^th cleaning process, and driving the cleaning mode. The method of controlling the cleaning robot based on autonomous learning and apparatus thereof allows the cleaning robot to autonomously learn a movement speed or a suction strength which is most suitable for the target substance; thereby improving cleaning efficiency and optimizing driving of the cleaning robot.

Description

[0002] Cleaning robot control methods and apparatus based on autonomous learning [

The present invention relates to a cleaning robot control method based on autonomous learning and an apparatus therefor, and more particularly, to a cleaning robot control method and apparatus for autonomous learning based cleaning which can improve cleaning efficiency.

Robots have been developed for industrial use and have been used as part of factory automation or in collecting or collecting information on behalf of humans in extreme environments that humans can not tolerate. These robotics fields have been developed in recent years for use in the state of the art space development industry, and recently human-friendly home robots have been developed.

Human-friendly home robots are representative of cleaning robots. The cleaning robot radiates infrared rays or ultrasonic waves while cleaning along the set travel route, receives infrared rays or ultrasonic waves reflected from the obstacle and discriminates the existence of the obstacle, and when the obstacle is detected, the traveling direction is switched to avoid the obstacle do.

Conventionally, the focus is mainly on the movement of the cleaning robot, and a method of avoiding an obstacle or a method of smoothly switching a direction at a corner is the core. However, there have not been developed various techniques for controlling the cleaning robot to drive the robot at an optimum moving speed or suction strength according to a given environment or material.

The technology that is the background of the present invention is disclosed in Korean Patent Publication No. 2009-0017312 (published on Mar. 18, 2009).

An object of the present invention is to provide an autonomous learning-based cleaning robot control method and apparatus that can improve cleaning efficiency by allowing a cleaning robot itself to learn optimal motion speed or suction intensity suitable for a target material.

The present invention provides a method of cleaning a robot, comprising: driving a cleaning robot equipped with a camera in an Nth order cleaning process for a first set time under a normal mode condition having a reference speed or a reference suction intensity; A step of applying a learning mode to the cleaning robot in a stepwise manner to a gradually decreasing speed or increasing intensity than the normal mode condition and driving the cleaning robot for a second set time; Extracts a critical velocity or a critical suction intensity at which an arbitrary target material that has not been removed at a previous first set time starts to be removed based on the sensed image of the camera obtained at the variable time at the second set time, , And acquiring a correction mode having an N + And performing driving by switching to the correction mode acquired in the N-th order cleaning process when the target material of the same type as that of the arbitrary target material is detected from the camera, A robot control method is provided.

Here, the cleaning robot is driven during a reference operation time including the first and second operation hours during the cleaning of the corresponding order, and the first operation time is greater than the second operation time within the reference operation time Can be high.

In addition, the self-learning-based cleaning robot control method may further include a step of, when the first set time elapses in the N + 1th order cleaning process, Mode cleaning to the cleaning robot and driving the cleaning robot for the second predetermined time period based on the sensed image of the camera obtained every time the second set time of the N + The step of extracting the critical velocity or the critical suction intensity at which the arbitrary target material that has not yet been removed from the first set time of the N + 1-th cleaning process starts to be removed and updating the correction mode, and in the N + The target robot is driven under the condition of the normal mode for the first set time period, If the detection may further comprise the step of driving by switching to the calibration mode to update during the (N + 1) primary cleaning process.

The cleaning robot further includes a speed sensor and a suction strength sensor. The cleaning robot may store the sensed image of the camera, the speed sensing value of the speed sensor, and the sensed value of the intensity of the suction strength in accordance with time, have.

The acquiring of the correction mode may acquire the correction mode corresponding to the type of the target material by acquiring the critical velocity or the critical inhalation intensity for each type of the target material.

According to another aspect of the present invention, there is provided a cleaning apparatus for a cleaning robot, comprising: a normal mode driving unit for driving a cleaning robot equipped with a camera in an Nth order cleaning process for a first set time under a normal mode condition having a reference speed or a reference suction intensity; A learning mode driving unit for applying a learning mode to the cleaning robot for a second set time when the set time elapses, wherein the learning mode is changed stepwise to a gradually decreasing speed or increasing intensity, A critical velocity or critical suction intensity at which an arbitrary target material that has not been removed at a previous first set time is started to be removed is extracted based on the captured image of the camera obtained every time the variable is set at the second set time of the N- A correction mode obtaining unit for obtaining a correction mode having the extracted information, And a controller for controlling the robot to move to the correction mode acquired during the Nth-order cleaning when the target material of the same type as the target material is detected by the camera, And a mode controller for driving the robot controller.

Here, the cleaning robot may further include a speed sensor and a suction strength sensor, and the autonomous learning-based cleaning robot control device may further include a speed sensing value of the speed sensor, a speed sensing value of the speed sensor, And a data storage unit for storing the values in association with each other in accordance with a time flow.

According to the cleaning robot control method and apparatus of the autonomous learning based on the present invention, it is possible to improve the cleaning efficiency and optimize the driving by allowing the cleaning robot to learn the movement speed or the suction strength most suitable for the target material, .

1 is a configuration diagram of a cleaning robot control apparatus according to an embodiment of the present invention.
Fig. 2 is a flowchart of a cleaning robot control method based on autonomous learning using Fig. 1. Fig.
3 is a conceptual diagram corresponding to Fig.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention.

The present invention relates to a cleaning robot control method and apparatus for autonomous learning based on self-learning, in which a cleaning robot adjusts to a target space and learns an optimum speed and a suction intensity by itself, thereby achieving cleaning time, energy consumed, Thereby maximizing cleaning efficiency.

In the case of this embodiment, a camera is provided at a part (ex, front, rear, bottom) of the cleaning robot, and the captured image can be continuously acquired at the time of cleaning. Several cameras may be installed for each part of the camera for photographing efficiency. The image captured by the camera can be used to identify the type of material such as dust, hair, or floor that is present in the space, whether it is cleaned, or when to clean.

In addition to the camera, the cleaning robot is equipped with a speed sensor and a suction strength sensor. Each of these sensors can observe the moving speed and the suction strength of the cleaning robot in real time.

The moving speed or the suction strength of the cleaning robot suitable for cleaning a specific material can be extracted by using the information of the imaging image, the moving speed, and the suction intensity obtained through the camera, the speed sensor, and the suction strength sensor. In addition, when the specific material is observed with a camera at the time of the next cleaning, the driving mode of the cleaning robot can be switched and controlled so as to be driven under the conditions of the optimum moving speed or suction strength established at the time of the previous cleaning.

In the following embodiment, the cleaning robot is driven during the reference operation time including the first and second operation hours in the cleaning process of the corresponding order, and the proportion of the first operation time within the reference operation time is the second operation Time. That is, the reference operation time given to the cleaning robot is divided into two steps, that is, a first operation time and a second operation time for each cleaning process of every order. When the reference operation time is set to 100%, the first operation time is 80% And the second operation time is 20%.

Here, it operates in a normal mode (reference speed, reference suction strength condition) during the initial first operation time, and operates in a learning mode in which the speed and suction strength are changed stepwise from the reference value during the remaining second operation time. In this learning mode, the velocity is varied at a slower rate than the reference velocity during that time, and the suction intensity is changed to a higher intensity than the reference suction intensity.

Observing the image captured in such a variable process, it is possible to confirm that a certain material that has not been removed at the first operation time is removed at a specific point in time. If the conditions of the speed and suction intensity of the robot used at the specific time point are detected, the condition can be immediately applied at the time of discovery of the material during the cleaning process of the next order, It is possible to drive the cleaning robot.

Hereinafter, a method for controlling a cleaning robot based on an autonomous learning according to an embodiment of the present invention will be described in detail.

1 is a configuration diagram of a cleaning robot control apparatus according to an embodiment of the present invention. FIG. 2 is a flowchart of a cleaning robot control method based on autonomous learning using FIG. 1, and FIG. 3 is a conceptual diagram corresponding to FIG. The cleaning robot control apparatus 100 according to an embodiment of the present invention includes a normal mode driving unit 110, a learning mode driving unit 120, a correction mode obtaining unit 130, a mode control unit 140, and a data storage unit 150 .

The cleaning robot control apparatus 100 according to the present embodiment operates in cooperation with the camera 10, the speed sensor 20 and the suction strength sensor 30 and detects the image captured by the camera 10 and the speed sensor 20, And the intensity sensing value of the suction strength sensor 30 are stored in the data storage unit 150 in accordance with the passage of time. The cleaning robot control apparatus 100 may be built in or enclosed in a cleaning robot, or may be wirelessly connected to a cleaning robot to wirelessly adjust the cleaning robot at a remote place.

First, the normal mode driving unit 110 drives the cleaning robot for a first set time under a normal mode condition having a reference speed or a reference suction intensity in an Nth order cleaning process (S210).

For example, assuming that a given reference driving time is 30 minutes, the cleaning robot is driven in the normal mode for 24 minutes corresponding to 80% of the time. Here, the reference speed or reference suction strength may correspond to a normal speed or a normal suction strength used on average for the cleaning robot.

Next, when the first set time elapses in the Nth order cleaning process, the learning mode driving unit 120 sets the condition of the learning mode for gradually changing the speed to a gradually decreasing speed or increasing intensity than the normal mode condition, And drives it for a second set time period (S220).

For example, during the remaining 6 minutes corresponding to 20% of the given 30 minutes, the cleaning robot is driven in the learning mode. That is, the traveling speed of the cleaning robot is gradually lowered or the suction strength is gradually increased for 6 minutes.

The reason for applying such a gradual change in speed or intensity is that, assuming that the material has not been removed in the normal mode of operation, the material may not be removed because the reference speed is high or the suction strength is low This is because there is a possibility that it could not be done. Of course, in the variable process of this learning mode, the camera 10 will continuously acquire the captured image. Of course, the camera 10 can continuously acquire the captured image even in the previous normal mode of operation.

On the other hand, on the basis of the captured image of the camera 10 obtained at the time of the change in the second set time of the N-th order cleaning process, the correction mode obtaining unit 130 obtains the correction target A critical velocity or a critical suction intensity at which the substance starts to be removed is extracted, and a correction mode having the extracted information is obtained (S230).

That is, there may occur a case where a substance which has not been removed in the normal mode operation has been removed at the time of the operation of the learning mode, and it may be detected through the image captured by the camera 10, The speed or the suction strength can be extracted as the critical speed or critical suction strength.

This critical velocity corresponds to the highest rate at which the target material (ex, hair) is removed, and the critical suction strength corresponds to the minimum suction strength at which the target material is to be removed. If the cleaning rate is too low, the cleaning efficiency is lowered. Therefore, the maximum speed necessary for removing the target material is used as the critical speed. If the suction strength is too high, the energy consumption is increased. .

Here, in step S230, at the time of acquiring the correction mode, the critical velocity or the critical suction strength may be obtained for each type of the target material to obtain a correction mode corresponding to the type of the target material. That is, the correction board contains optimum conditions for each type of target material. This is because the optimum speed or suction strength for removing the substance may be different depending on the kind of the substance. The kind of the material can be easily recognized by applying a known image recognition method to the captured image of the camera.

As described above, the information acquired in the learning mode in steps S220 to S230 can be immediately reflected and used when the target is found at the time of cleaning the next order. Here, the next N + 1th order cleaning process is also divided into a first driving time period in which a normal mode is driven and a second driving time period in which the driving mode is driven in a learning mode. When a target material is detected during driving in a normal mode, The normal mode can be switched to the correction mode and driven. Of course, in the other cases, it is driven in the normal mode.

That is, the mode control unit 140 adaptively switches the cleaning mode corresponding to the discovery of the target material in the next N + 1-th cleaning process. In other words, the mode control unit 140 drives the cleaning robot in a normal mode condition for a first set time in the following N + 1-th cleaning process, where a target material of the same kind as an arbitrary target material found in the existing order is removed from the camera If it is detected, the control unit 20 switches to the correction mode acquired in the N-th order cleaning process and drives it (S240).

That is, during the first set time in the (N + 1) -th cleaning process, driving in the normal mode and driving in the correction mode can be used in combination. That is, in the normal mode driving process, when the learned cleaning target or floor appears, it is switched to the learned speed and suction force.

Thereafter, when the first set time elapses in the N + 1th-order cleaning process, the learning mode driver 120 sets the learning mode for gradually changing the speed to a gradually decreasing speed or increasing intensity, To the cleaning robot again for a second set time (S250).

As described above, the reason why the learning is newly performed in the cleaning process of the next order is that the performance of the robot cleaning deteriorates or changes with time, and a new learning process is required when a new target material occurs.

Accordingly, the correction mode acquisition unit 130 determines, based on the sensed image of the camera obtained at each time of the variable at the second set time of the (N + 1) th order cleaning process, that is, The critical velocity or the critical suction intensity at which the arbitrary target material that has not yet been removed from the first set time of the + 1 < th > order cleaning process starts to be removed is renewed and the correction mode is updated (S260).

Here, the update is a concept including modification, addition, and the like of information. That is, the condition may be updated for each target material, and for some targets, the same condition as the existing condition may be unnecessary. Further, for the newly recognized arbitrary target material, the optimum condition corresponding thereto can be extracted and added to the correction mode.

As described above, the information acquired in the learning mode in steps S250 to S260 can be immediately reflected and used when the target is found in the next N + 2-order cleaning. Therefore, it has a principle that the most recent information is reflected based on the order of cleaning currently.

That is, the mode controller 140 drives the cleaning robot in a normal mode condition for a first set time during the N + 2nd order cleaning of the next order, When the target material is detected from the camera, the N + 1th cleaning process is switched to the updated correction mode and driven (S270). Of course, the correction mode selectively drives the conditions suitable for the target material among the various target materials.

According to the embodiment of the present invention as described above, the cleaning robot is driven at a normal speed and a normal suction power at the time of cleaning the next order. In the course of the cleaning, It is possible to instantaneously switch to the learned speed and suction intensity in the suction force condition and to exhibit higher cleaning efficiency.

Of course, in the embodiment of the present invention, the target material is not limited to hair, dust, wet material and the like, and may correspond to a concept covering the bottom including these materials. In other words, when an existing floor and other floor (ex, carpet) where dust removal is smoothly appearing, optimum movement speed and suction force at that moment are memorized together with the object to be cleaned and floor, so that it can be utilized in the future. Also, even if the learning content of the cleaning robot is extinguished during the use of the repeated cleaning robot, the latest content replaces the old one, so that it is possible to drive the robot in a condition suitable for the state of the robot

According to the method and apparatus for controlling the cleaning robot based on the autonomous learning according to the present invention, the cleaning robot can learn the movement speed or the suction strength most suitable for the target material, thereby gradually improving the cleaning efficiency, There is an advantage to be able to do.

While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

10: camera 20: speed sensor
30: Suction intensity sensor 100: Cleaning robot control device
110: normal mode driving unit 120: learning mode driving unit
130: correction mode acquisition unit 140: mode control unit
150: Data storage unit

Claims (10)

Driving the cleaning robot equipped with the camera for a first set time under a condition of a normal mode having a reference speed or a reference suction intensity in an Nth order cleaning process;
Wherein when the first set time elapses during the Nth-order cleaning, a condition of a learning mode for gradually changing the speed to a gradually decreasing speed or increasing intensity than the normal mode is applied to the cleaning robot, Driving;
A threshold speed or a critical suction intensity at which an arbitrary target material which has not been removed at a previous first set time is started to be removed based on the sensed image of the camera obtained at the time of the variable at the second set time of the N- Extracting and obtaining a correction mode having the extracted information; And
The cleaning robot is driven in the normal mode for the first set time during the (N + 1) -th cleaning process, and when the target material of the same type as that of the arbitrary target material is detected from the camera, And switching to the correction mode to drive the robot. The method according to claim 1,
Wherein the cleaning robot is driven during a reference operation time including the first and second operation hours in a cleaning process of a corresponding order,
Wherein the first operation time is higher than the second operation time within the reference operation time. The method according to claim 1,
Wherein when the first set time elapses in the N + 1th step of cleaning, a condition of a learning mode for gradually changing the speed of the robot to a gradually decreasing speed or increasing intensity is applied to the cleaning robot again, Driving for a set time;
[0050] Based on the sensed image of the camera obtained at the variable time in the second set time of the (N + 1) -th cleaning process, any target material that has not been removed at the first set time of the (N + Extracting the critical velocity or the critical suction intensity again and updating the correction mode; And
The cleaning robot is driven in the normal mode for the first predetermined time during the (N + 2) -th cleaning process, and when the target material of the same type as that of the arbitrary target material is detected from the camera, And a step of switching to an updated correction mode at the time of starting the cleaning robot and driving the cleaning robot. The method according to claim 1,
The cleaning robot further includes a speed sensor and a suction strength sensor,
Wherein the sensed image of the camera, the velocity sensing value of the velocity sensor, and the intensity sensing value of the suction intensity are stored in association with each other in accordance with time. The method according to claim 1,
Wherein the acquiring of the correction mode comprises:
And obtaining a correction mode corresponding to the type of the target material by obtaining the critical velocity or the critical suction intensity for each type of the target material. A normal mode driving unit for driving the cleaning robot equipped with the camera in the Nth order cleaning process for a first set time under a normal mode condition having a reference speed or a reference suction intensity;
Wherein when the first set time elapses during the Nth-order cleaning, a condition of a learning mode for gradually changing the speed to a gradually decreasing speed or increasing intensity than the normal mode is applied to the cleaning robot, A learning mode driving unit for driving the driving unit;
A threshold speed or a critical suction intensity at which an arbitrary target material which has not been removed at a previous first set time is started to be removed based on the sensed image of the camera obtained at the time of the variable at the second set time of the N- A correction mode obtaining unit for obtaining a correction mode having the extracted information extracted; And
The cleaning robot is driven in the normal mode for the first set time during the (N + 1) -th cleaning process, and when the target material of the same type as that of the arbitrary target material is detected from the camera, And a mode controller for switching to one of the correction modes and driving the robot. The method of claim 6,
Wherein the cleaning robot is driven during a reference operation time including the first and second operation hours in a cleaning process of a corresponding order,
Wherein the first operation time is higher than the second operation time within the reference operation time. The method of claim 6,
Wherein the learning mode driver comprises:
Wherein when the first set time elapses in the N + 1th step of cleaning, a condition of a learning mode for gradually changing the speed of the robot to a gradually decreasing speed or increasing intensity is applied to the cleaning robot again, 2 set time,
Wherein the correction mode obtaining unit
[0050] Based on the sensed image of the camera obtained at the variable time in the second set time of the (N + 1) -th cleaning process, any target material that has not been removed at the first set time of the (N + The critical velocity or the critical suction strength again to update the correction mode,
The mode control unit includes:
The cleaning robot is driven in the normal mode for the first predetermined time during the (N + 2) -th cleaning process, and when the target material of the same type as that of the arbitrary target material is detected from the camera, The robot is moved to the updated correction mode and driven. The method of claim 6,
The cleaning robot further includes a speed sensor and a suction strength sensor,
Further comprising a data storage unit for storing the sensed image of the camera, the velocity sensing value of the velocity sensor, and the intensity sensing value of the suction intensity in association with each other over time. The method of claim 6,
Wherein the correction mode obtaining unit
And acquires the critical velocity or the critical suction intensity for each type of the target material to obtain a correction mode corresponding to the type of the target material.
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CN106335067A (en) * 2016-10-13 2017-01-18 青岛塔波尔机器人技术有限公司 Sweeping and mopping integrated cleaning robot and uniform wet-mopping control method thereof
WO2021008439A1 (en) * 2019-07-12 2021-01-21 北京石头世纪科技股份有限公司 Automatic cleaning device control method and apparatus, device and medium
US11471016B2 (en) 2018-05-11 2022-10-18 Samsung Electronics Co., Ltd. Method and apparatus for executing cleaning operation
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