Robot and control method therefor

Abstract

A robot is disclosed. One or more processors: when a liquid contaminant is identified through at least one sensor, identify a cleaning area including the liquid contaminant; when the identified cleaning area is identified as a drivable area on the basis of a spatial map corresponding to a space, acquire sensing data through the at least one sensor while traveling the cleaning area; and when the cleaning area is identified as a cleanable area on the basis of the acquired sensing data, identify a cleaning path within the cleanable area, and allow the robot to clean along the cleaning path.

Description

Robot and control method thereof

[0001] The present disclosure relates to a robot and a method for controlling the same.

[0002] Recently, as technology for cleaning robots has advanced, cleaning robots that include both dry cleaning and wet cleaning functions are being developed and distributed.

[0003] A cleaning robot is an electronic device designed to automatically perform cleaning while moving through an indoor space. Generally, since cleaning robots perform wet cleaning after dry cleaning, the components for wet cleaning are located at the rear of the cleaning robot.

[0004] In this case, for a cleaning robot that cleans liquid contaminants, user satisfaction with the wet cleaning function was not high because the robot mechanism was contaminated by the liquid contaminants.

[0005] A robot according to one or more embodiments of the present disclosure comprises a driving unit, at least one sensor, a memory for storing instructions, and one or more processors including processing circuitry.

[0006] According to one or more embodiments, the one or more processors, when the robot identifies a liquid contaminant through the at least one sensor, identify a cleaning area containing the liquid contaminant, and when the identified cleaning area is identified as a drivable area based on a space map corresponding to the space, drive through the cleaning area and acquire sensing data through the at least one sensor, and when the cleaning area is identified as a cleanable area based on the acquired sensing data, identify a cleaning path within the cleanable area and cause the robot to clean along the cleaning path.

[0007] According to one or more embodiments, when the instructions are executed individually or collectively by the one or more processors, the robot identifies a search area including the cleaning area when the cleaning area is identified as a drivable area, drives the search area, and acquires the sensing data through the at least one sensor.

[0008] According to one or more embodiments, a contaminated area containing the liquid contaminant is identified, and a cleaning area including a first margin area within a preset distance from the contaminated area is identified.

[0009] According to one or more embodiments, the location of the cleaning area in the space map is identified based on sensing data sensed through the at least one sensor, and the cleaning area is identified as the drivable area based on the location of the cleaning area and obstacle information corresponding to the cleaning area identified from the space map.

[0010] According to one or more embodiments, if the cleaning area in the space map is identified as not being a drivable area, an obstacle area including the obstacle is identified based on the obstacle information, and based on the location of the cleaning area in the space map and the obstacle area, an area excluding the obstacle area from the cleaning area is re-identified as the cleaning area, and the obstacle area is an area including a second margin area within a preset distance from the obstacle.

[0011] According to one or more embodiments, the search area including a third margin area within a preset distance from the cleaning area is identified, the boundary of the search area is traversed and sensing data corresponding to the interior of the cleaning area is acquired through the at least one sensor, and based on the acquired sensing data, the cleaning area is identified as the cleaningable area.

[0012] According to one or more embodiments, when the cleaning area is identified as the cleanable area, a first cleaning path is identified based on a preset driving pattern, and the cleaning area is driven in reverse based on the identified first cleaning path to clean the liquid contaminant.

[0013] According to one or more embodiments, when an obstacle is identified in the cleaning area based on sensing data acquired through the at least one sensor, a second cleaning path is identified based on obstacle information corresponding to the obstacle and the preset driving pattern, and the driving unit is controlled to drive in reverse in the cleaning area according to the identified second cleaning path.

[0014] According to one or more embodiments, while driving backward in the cleaning area along the first cleaning path, if the liquid contaminant is re-identified on the previously driven cleaning path based on sensing data acquired through at least one sensor, the driving unit is controlled to drive along the first cleaning path again.

[0015] According to one or more embodiments, the search area is driven forward to identify whether the cleaning area is the cleaningable area, and if the cleaning area is identified as the cleaningable area, the driving unit is controlled to drive the cleaning area backward.

[0016] According to one or more embodiments, the robot further comprises a mopping pad; the at least one sensor is positioned at least one of the front and side of the robot to sense the front of the robot, and the mopping pad is positioned at the rear of the robot.

[0017] A control method for a robot according to one or more embodiments of the present disclosure includes, when a liquid contaminant is identified, identifying a cleaning area containing said liquid contaminant; when the identified cleaning area is identified as a drivable area based on a space map corresponding to said space, driving in said cleaning area and acquiring sensing data; when the cleaning area is identified as a cleanable area based on said acquired sensing data, identifying a cleaning path within said cleaning area; and the robot cleaning along said cleaning path.

[0018] A non-transient computer-readable storage medium storing computer instructions that cause a robot to perform an operation when executed by a processor of a robot according to one or more embodiments of the present disclosure, wherein the operation includes: an operation of identifying a cleaning area containing a liquid contaminant when a liquid contaminant is identified; an operation of driving the cleaning area and acquiring sensing data when the identified cleaning area is identified as a drivable area based on a space map corresponding to the space; an operation of identifying a cleaning path within the cleaning area when the cleaning area is identified as a cleanable area based on the acquired sensing data; and an operation of the robot cleaning along the cleaning path.

[0019] FIG. 1 is a drawing for explaining the operation of a robot according to one or more embodiments.

[0020] FIG. 2 is a block diagram illustrating the configuration of a robot according to one or more embodiments.

[0021] FIG. 3 is a drawing for explaining the arrangement of components of a robot according to one or more embodiments.

[0022] FIG. 4 is a diagram illustrating the process of identifying a cleaning area of ​​a robot according to one or more embodiments.

[0023] FIG. 5 is a diagram illustrating the process of identifying a drivable area of ​​a robot according to one or more embodiments.

[0024] FIG. 6 is a diagram illustrating the process of re-identifying a cleaning area of ​​a robot according to one or more embodiments.

[0025] FIG. 7 is a diagram illustrating a secondary identification process of a drivable area of ​​a robot according to one or more embodiments.

[0026] FIG. 8 is a diagram illustrating the process of identifying a first cleaning path of a robot according to one or more embodiments.

[0027] FIG. 9 is a diagram illustrating the process of identifying a second cleaning path of a robot according to one or more embodiments.

[0028] FIG. 10 is a diagram illustrating the cleaning path re-travel process of a robot according to one or more embodiments.

[0029] FIG. 11 is a drawing for explaining the overall operation of a robot according to one or more embodiments.

[0030] FIG. 12 is a drawing for explaining the operation of a robot according to one or more embodiments.

[0031] The terms used in the various embodiments of this Disclosure have been selected to be as widely used and general as possible, taking into account their functions within this Disclosure; however, these terms may vary depending on the intent of those skilled in the art, case law, the emergence of new technologies, etc. Additionally, in specific cases, terms have been selected at the applicant's discretion, and in such cases, their meanings will be described in detail in the relevant description section of this Disclosure. Therefore, terms used in this Disclosure should be defined not merely by their names, but based on their meanings and the overall content of this Disclosure.

[0032] In the present disclosure, expressions such as “have,” “may have,” “include,” or “may include” indicate the presence of such features (e.g., numerical values, functions, actions, or components such as parts) and do not exclude the presence of additional features.

[0033] The expression "at least one of A or / and B" should be understood as representing either "A" or "B" or "A and B".

[0034] Expressions such as "first," "second," "first," or "second" used in this disclosure may modify various components regardless of order and / or importance, and are used only to distinguish one component from another and do not limit said components.

[0035] Where it is stated that a component (e.g., Component 1) is "(operatively or communicatively) coupled with / to" or "connected to" another component (e.g., Component 2), it should be understood that the component may be directly connected to the other component or connected through the other component (e.g., Component 3).

[0036] The singular expression includes the plural expression unless the context clearly indicates otherwise. In this disclosure, terms such as “comprising” or “consisting of” are intended to specify the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0037] In the present disclosure, a "module" or "part" performs at least one function or operation and may be implemented in hardware or software, or a combination of hardware and software. Additionally, a plurality of "modules" or a plurality of "parts" may be integrated into at least one module and implemented by at least one processor (not shown), except for a "module" or "part" that needs to be implemented in specific hardware.

[0038] In the present disclosure, the term "user" may refer to a person using a robot or a device used by that person.

[0039] An embodiment of the present disclosure will be described in more detail below with reference to the attached drawings.

[0040] FIG. 1 is a drawing for explaining the operation of a robot according to one or more embodiments.

[0041] According to one embodiment, the robot (100) can set a cleaning path and clean the liquid contaminant when liquid contaminant is identified while driving through a space. Here, the robot (100) may be a device that drives itself and performs cleaning using a drive motor and wheels, etc.

[0042] According to one embodiment, the robot (100) can sense the location within the space, the characteristics of the floor surface, the shape of the space, and the location and shape of objects (such as home appliances or furniture) within the space by using various sensors such as a LiDAR sensor, an infrared sensor, an image sensor, and an ultrasonic sensor. Although FIG. 1 illustrates the case where the robot (100) operates in a general home environment, the robot (100) can be used in various environments such as an office, inside a building, a factory, or a government office.

[0043] According to one embodiment, the robot (100) can identify liquid contaminants located on the floor surface based on sensing data sensed through at least one sensor. Liquid contaminants may include contaminants such as water, beverages, sauces, and pet urine. When liquid contaminants are identified, the robot (100) can set a cleaning area containing the liquid contaminants.

[0044] Referring to FIG. 1, a robot (100) can identify liquid contaminants (20) through sensors placed on the robot (100) while driving through a space within a home. When liquid contaminants (20) are identified, the robot (100) can set a cleaning area (30) containing the liquid contaminants (20). The robot (100) can identify a cleaning path within the set cleaning area and clean the liquid contaminants (20) along the identified cleaning path.

[0045] According to one example, when a liquid contaminant is identified, the robot (100) can move forward to clean the liquid contaminant. Generally, at least one sensor for sensing the front of the robot (100) and a configuration for dry cleaning may be placed on the front of the robot (100), and a configuration for wet cleaning may be placed on the rear of the robot (100). In this case, when the robot (100) moves forward to clean the liquid contaminant, a problem may occur in which the wheel and the configuration for dry cleaning located on the front are contaminated by the liquid contaminant.

[0046] Hereinafter, various embodiments in which a robot (100) drives backward to clean liquid contaminants will be described with reference to the drawings.

[0047] FIG. 2 is a block diagram illustrating the configuration of a robot according to one or more embodiments.

[0048] According to FIG. 2, the robot (100) includes a driving unit (110), at least one sensor (120), a memory (130), and one or more processors (140). However, it is not limited thereto, and the robot (100) may be implemented with some components excluded or with other components included.

[0049] The driving unit (110) is configured to move the main body of the robot (100). The driving unit (110) may include a plurality of wheels, a driving motor for rotating each of the plurality of wheels, a gear, a shaft, etc. The plurality of wheels are provided on the lower side or side of the main body of the robot (100) to support the main body of the robot (100) from the floor surface. When the driving motor operates and the driving force is transmitted to the plurality of wheels so that each wheel rotates, the robot (100) can be moved by the frictional force between the floor surface and the wheels. In addition, the driving unit (110) may change the rotational speed of at least one of the plurality of wheels or adjust the alignment direction of the wheels differently when changing direction. Depending on the type of robot (100), the weight of the loaded item, and the characteristics of the space where the robot (100) is located (e.g., roughness of the floor surface, frictional force, etc.), an endless track or the like may be used instead of wheels.

[0050] At least one sensor (120) is configured to detect the surrounding environment of the robot (100) and identify liquid contaminants. The at least one sensor (120) may include at least one of a Lidar sensor, a depth camera, an Inertial Measurement Unit (IMU) sensor, a Time of Flight (ToF) sensor, a vision sensor, a light sensor, an RGB sensor, an image sensor, an infrared sensor, an ultrasonic sensor, a gyroscope sensor, an accelerometer sensor, and a proximity sensor.

[0051] A LiDAR sensor can project light (e.g., laser, near-infrared light, visible light, ultraviolet light, etc.) in a 360-degree direction and detect light reflected by various surrounding objects (e.g., walls, furniture, home appliances, etc.) to output sensing information for obtaining information about the distance to surrounding objects. A depth camera is a sensor that projects a laser or infrared light onto an external object and receives the returning light with a stereo camera to measure the distance to the external object in three dimensions and sense depth data. An IMU sensor is a sensor for detecting the movement of a robot and may include at least one of a geomagnetic sensor, an accelerometer, and a gyroscope. A ToF sensor can measure the distance to an external object by using the time (time of flight) for the reflected signal to be received after outputting a signal such as a laser.

[0052] The memory (130) can store at least one instruction, data, program, etc. required for the operation of the robot (100). For example, the memory (130) can store a cleaning path identified within a cleaning area.

[0053] Depending on the purpose of data storage, the memory (130) may be implemented in the form of a memory embedded in the robot (100) or in the form of a memory that is detachable from the robot (100). For example, data for driving the robot (100) may be stored in a memory embedded in the robot (100), and data for the expansion function of the robot (100) may be stored in a memory that is detachable from the robot (100).

[0054] The memory embedded in the robot (100) may be implemented as at least one of volatile memory (e.g., DRAM (dynamic RAM), SRAM (static RAM), or SDRAM (synchronous dynamic RAM), non-volatile memory (e.g., OTPROM (one time programmable ROM), PROM (programmable ROM), EPROM (erasable and programmable ROM), EEPROM (electrically erasable and programmable ROM), mask ROM, flash ROM, flash memory (e.g., NAND flash or NOR flash), hard drive, or solid state drive (SSD).

[0055] The memory (130) may be implemented as a single memory that stores data generated in various operations according to the present disclosure, but is not limited thereto, and the memory (130) may be implemented to include a plurality of memories that each store different types of data or each store data generated in different stages.

[0056] One or more processors (140) control the overall operation of the robot (100). Specifically, one or more processors (140) may be connected to each component of the robot (100) to control the overall operation of the robot (100). For example, one or more processors (140) may be electrically connected to the memory (130) to control the overall operation of the robot (100). One or more processors (140) may include processing circuits and may be composed of one or more processors.

[0057] One or more processors (140) can perform the operation of a robot (100) according to various embodiments by executing one or more instructions stored in memory (130).

[0058] One or more processors (140) may include one or more of a CPU (Central Processing Unit), GPU (Graphics Processing Unit), APU (Accelerated Processing Unit), MIC (Many Integrated Core), DSP (Digital Signal Processor), NPU (Neural Processing Unit), hardware accelerator, or machine learning accelerator. One or more processors (140) may control one or any combination of other components of the robot and may perform operations or data processing related to communication. One or more processors (140) may execute one or more programs or instructions stored in memory. For example, one or more processors may perform a method according to one or more embodiments of the present disclosure by executing one or more instructions stored in memory.

[0059] When a method according to one or more embodiments of the present disclosure includes a plurality of operations, the plurality of operations may be performed by a single processor or by a plurality of processors. For example, when a first operation, a second operation, and a third operation are performed by a method according to one or more embodiments, the first operation, the second operation, and the third operation may all be performed by a first processor, or the first operation and the second operation may be performed by a first processor (e.g., a general-purpose processor) and the third operation may be performed by a second processor (e.g., an artificial intelligence dedicated processor).

[0060] One or more processors (140) may be implemented as a single-core processor including one core, or as one or more multicore processors including multiple cores (e.g., homogeneous multicore or heterogeneous multicore). When one or more processors (140) are implemented as multicore processors, each of the multiple cores included in the multicore processor may include internal processor memory such as cache memory or on-chip memory, and a common cache shared by multiple cores may be included in the multicore processor. Additionally, each of the multiple cores included in the multicore processor (or some of the multiple cores) may independently read and execute program instructions for implementing a method according to one or more embodiments of the present disclosure, or all (or some) of the multiple cores may be linked together to read and execute program instructions for implementing a method according to one or more embodiments of the present disclosure.

[0061] When a method according to one or more embodiments of the present disclosure includes a plurality of operations, the plurality of operations may be performed by one of the plurality of cores included in a multi-core processor, or may be performed by a plurality of cores. For example, when a first operation, a second operation, and a third operation are performed by a method according to one or more embodiments, the first operation, the second operation, and the third operation may all be performed by a first core included in a multi-core processor, or the first operation and the second operation may be performed by a first core included in a multi-core processor and the third operation may be performed by a second core included in a multi-core processor.

[0062] In the embodiments of the present disclosure, a processor may refer to a system-on-chip (SoC) in which one or more processors and other electronic components are integrated, a single-core processor, a multi-core processor, or a core included in a single-core processor or a multi-core processor, wherein the core may be implemented as a CPU, GPU, APU, MIC, DSP, NPU, hardware accelerator, or machine learning accelerator, but the embodiments of the present disclosure are not limited thereto. For convenience of explanation, one or more processors (140) will be referred to as processors (140) below.

[0063] According to one embodiment, the processor (140) can identify a cleaning area containing liquid contaminants when liquid contaminants are identified through at least one sensor (120). The cleaning area may be an area containing liquid contaminants and for the robot (100) to clean.

[0064] According to one embodiment, the processor (140) may, based on a space map corresponding to the space, drive through the cleaning area and acquire sensing data through at least one sensor (120) when the identified cleaning area is identified as a drivable area. Here, the sensing data may include data corresponding to the inside of the cleaning area.

[0065] The drivable area may be an area where the robot (100) can travel safely while traversing the space. For example, the drivable area may be an area where the robot (100) can travel safely because there are no obstacles, pillars, stairs, high ledges, or walls in the identified cleaning area. For example, the drivable area may be an area where there is no possibility of the robot (100) falling. The drivable area is not limited thereto and may be referred to as a safe area, a searchable area, or a driving-allowed area, but in this disclosure, it will be collectively referred to as a drivable area.

[0066]

[0067] According to one embodiment, if the processor (140) identifies a cleaning area as a cleanable area based on acquired sensing data, it can identify a cleaning path within the cleaning area.

[0068] The cleaning path may be a planned path that allows the robot (100) to efficiently drive and perform cleaning tasks within the cleaning area. For example, the cleaning path may be a spiral path that cleans from the outermost area to the central area.

[0069] According to one embodiment, the processor (140) can control the driving unit (110) to drive along a cleaning path and clean liquid contaminants.

[0070] FIG. 3 is a drawing for explaining the arrangement of components of a robot according to one or more embodiments.

[0071] According to one embodiment, the robot (100) may have at least one sensor, a dust suction port, and a rotating brush on the front of the robot (100), and a mopping pad on the rear of the robot (100).

[0072] According to one example, the robot (100) may move forward, and a dust suction port and a rotating brush for cleaning dust and foreign matter on the floor surface may be positioned on the front of the robot (100). That is, the robot (100) may have a dust suction port and a rotating brush positioned on the front for dry cleaning.

[0073] According to one example, at least one sensor (120) may be placed at at least one location on the front and side of the robot to sense the front of the robot (100).

[0074] According to one example, a mop pad may be placed on the rear of the robot (100) for wet cleaning after dry cleaning. The mop pad is configured to clean the floor surface by absorbing liquid contaminants. The mop pad may be placed on the rear of the robot (100) in contact with the bottom surface of the robot (100).

[0075] FIG. 3 illustrates the upper and lower surfaces of a robot (100). Referring to FIG. 3, at least one sensor (120), a suction port (320), and a rotating brush (330) may be disposed on the front of the robot (100). A mop pad (310) may be disposed on the rear of the robot (100).

[0076] According to one embodiment, when the robot (100) moves forward to clean liquid contaminants, the suction port (320) and the rotating brush (330) placed on the front of the robot (100) may be contaminated by the liquid contaminants. In this case, the robot (100) may move backward to clean the liquid contaminants using a mop pad placed on the rear of the robot (100). However, when the robot (100) moves backward to clean liquid contaminants, there may be difficulty in sensing obstacles in the direction the robot (100) is moving because at least one sensor (120) is placed on the front or side of the robot (100).

[0077] FIG. 4 is a diagram illustrating the process of identifying a cleaning area of ​​a robot according to one or more embodiments.

[0078] According to one embodiment, the robot (100) can identify a contaminated area containing liquid contaminants and a cleaning area including a first margin area within a preset distance from the contaminated area.

[0079] According to one example, the robot (100) can identify liquid contaminants located on the floor surface through at least one of a light sensor and an RGB sensor.

[0080] For example, a robot (100) can identify liquid contaminants by emitting light onto a floor surface through a light sensor and analyzing the wavelength of light reflected when it encounters liquid contaminants. In the case of a normal floor surface, the wavelength and intensity of the reflected light are constant, but the wavelength and intensity of the light reflected when it encounters liquid contaminants may be irregular.

[0081] For example, a robot (100) can detect liquid contaminants located on a floor surface by comparing the color of the floor surface and the color of the liquid contaminants through an RGB sensor. The robot (100) can identify the color of the liquid contaminants and the boundary with the floor surface through an RGB sensor, and can identify the liquid contaminants based on the color difference.

[0082] Referring to FIG. 4, when liquid contaminants are identified through at least one sensor (120), the robot (100) can identify a contaminated area (410) in the form of a curve or straight line containing liquid contaminants. The robot (100) can identify a cleaning area (420) including a first margin area (450) within a preset distance of 5 cm from the contaminated area.

[0083] According to one example, the robot (100) is not limited to the cleaning area (420) illustrated in FIG. 4 and can identify the cleaning area in various ways. For example, the robot (100) can identify a rectangular cleaning area (430) spaced apart from the outermost boundary of the contaminated area (410) by a predetermined distance. For example, the robot (100) can identify a polygonal cleaning area including a margin area within a predetermined distance from the contaminated area (410).

[0084] For convenience of explanation, the cleaning area (420 to 440) below will be described as a rectangular cleaning area (430).

[0085] FIG. 5 is a diagram illustrating the process of identifying a drivable area of ​​a robot according to one or more embodiments.

[0086] According to one embodiment, the robot (100) can identify the location of a cleaning area in a space map based on sensing data sensed through at least one sensor (120).

[0087] The robot (100) can acquire a spatial map while driving through the space where the robot (100) is located. The robot (100) may also receive a spatial map of the space where the robot (100) is located from a user or a server. The spatial map may include location information regarding pillars, walls, stairs, spatial structures, and obstacles in the space where the robot (100) is located.

[0088] According to one embodiment, the robot (100) can primarily identify whether the cleaning area is a drivable area based on the location of the cleaning area and obstacle information corresponding to the cleaning area identified from the space map.

[0089] Obstacle information may include information regarding the location, size, shape, type, and distance from the cleaning area of ​​the obstacle. For example, obstacle information may include information regarding the location, size, shape, and type of obstacle located within a range pre-set as the cleaning area.

[0090] Referring to FIG. 5, the robot (100) can identify the location of the cleaning area (430) in the space map (510) by sensing the shape of the space around the cleaning area (430), the location of objects (such as home appliances or furniture) inside the space, and the location of pillars and walls through at least one sensor (120).

[0091] The robot (100) can identify whether the cleaning area (430) is a drivable area based on the location of the cleaning area (430) in the space map (510) and the location of obstacles (520, 530) around the cleaning area (430). The robot (100) can identify the cleaning area (430) as a drivable area by the obstacles (520, 530) around the cleaning area (430) in the space map (510) being located at a distance greater than a certain distance from the cleaning area (430).

[0092] FIG. 6 is a diagram illustrating the process of re-identifying a cleaning area of ​​a robot according to one or more embodiments.

[0093] According to one embodiment, if the robot (100) identifies that the cleaning area (430) in the space map (510) is not a drivable area, it can identify an obstacle area (611, 621) containing obstacles based on obstacle information.

[0094] The obstacle area (611, 621) may be an area including a second margin area (612, 622) within a predetermined distance from the obstacle (610, 620). The obstacle area (611, 621) may be an area including a safety distance area to prevent the robot (100) from colliding with the obstacle. The obstacle area (611, 621) is not limited thereto and may be referred to as an avoidance area, a safety area, or a protection area, but in this disclosure, it will be collectively referred to as an obstacle area.

[0095] According to one embodiment, the robot (100) can re-identify the area excluding the obstacle area (611, 621) from the cleaning area (510) as the cleaning area based on the location of the cleaning area and the obstacle area (611, 621) in the space map.

[0096] Referring to FIG. 6, the robot (100) can identify the location of obstacles (610, 620) in a spatial map (510). If the location of the identified obstacles (610, 620) is included in a cleaning area (510), the robot (100) can identify obstacle areas (611, 621) corresponding to each of the obstacles (610, 620).

[0097] The obstacle area (611, 621) may be an area including a second margin area (612, 622) within a preset distance (e.g., 10 cm) from the obstacle (610, 620). Based on the identified obstacle area (611, 612), the robot (100) may re-identify the area excluding the obstacle area (611, 612) from the cleaning area (510) as the cleaning area (630).

[0098] FIG. 7 is a diagram illustrating a secondary identification process of a drivable area of ​​a robot according to one or more embodiments.

[0099] According to one embodiment, the robot (100) can identify a search area including a third margin area within a preset distance from a cleaning area.

[0100] According to one embodiment, the robot (100) can drive along the boundary of the search area and acquire sensing data corresponding to the inside of the cleaning area through at least one sensor (120).

[0101] The search area may be an area where the robot (100) drives directly to identify whether the cleaning area is a drivable area. That is, the robot (100) may set a search area surrounding the cleaning area and drive directly along the boundary of the search area to identify whether the cleaning area is a drivable area. The search area is not limited thereto and may be referred to as a verification area or a pre-inspection area, but in this disclosure, it will be collectively referred to as a search area.

[0102] According to one embodiment, the robot (100) can secondarily identify whether the cleaning area is a drivable area based on acquired sensing data. For example, the robot (100) can drive along the boundary of the search area and identify whether there are obstacles, pillars, walls, or moving objects inside the cleaning area through at least one sensor (120).

[0103] For example, the robot (100) can drive forward in the search area to secondarily identify whether the cleaning area is a drivable area.

[0104] Referring to FIG. 7, the robot (100) can identify a search area (710) including a third margin area (720) within a preset distance (e.g., 5 cm) from a cleaning area (430). The robot (100) can identify the boundary of the identified search area (710) and drive along the boundary of the search area (710).

[0105] According to one example, the robot (100) can obtain sensing data by driving along the boundary of the search area (710) and sensing (730) the inside of the cleaning area (430) through at least one sensor (120). The robot (100) can identify whether there is an obstacle inside the cleaning area (430) through a LiDAR sensor or a depth camera among at least one sensor (120).

[0106] According to one example, the robot (100) can drive along the boundary of the search area (710) and if no obstacle is detected inside the cleaning area (430), the cleaning area (430) can be identified as a drivable area.

[0107] FIG. 8 is a diagram illustrating the process of identifying a first cleaning path of a robot according to one or more embodiments.

[0108] According to one embodiment, when the robot (100) identifies a cleaning area as a cleanable area, it can identify a first cleaning path based on a preset driving pattern.

[0109] The pre-set driving pattern may be a driving pattern that includes the shortest cleaning path to clean the cleaning area (430) most efficiently. For example, the pre-set driving pattern may be a spiral driving pattern that cleans from the edge end point of the cleaning area toward the center, or a zigzag driving pattern that cleans from the vertex end point of the cleaning area toward the diagonal vertex end point.

[0110] According to one embodiment, the robot (100) can clean liquid contaminants by driving backward in a cleaning area based on an identified first cleaning path. The robot (100) can clean liquid contaminants by driving backward through a mop pad (310) placed on the rear of the robot (100).

[0111] Referring to FIG. 8, when the robot (100) identifies a cleaning area as a cleanable area, it may set a cleaning path of a zigzag driving pattern (810) within the cleaning area (430). The robot (100) may also set a cleaning path of a spiral driving pattern (820) different from the zigzag driving pattern (810) within the cleaning area (430). However, this is merely an example, and the cleaning path may also be set based on user settings or pre-set driving patterns.

[0112] According to one example, the robot (100) can clean the cleaning area (430) by driving backward based on the identified first cleaning path (810, 820).

[0113] FIG. 9 is a diagram illustrating the process of identifying a second cleaning path of a robot according to one or more embodiments.

[0114] According to one embodiment, when an obstacle is identified in a cleaning area based on sensing data acquired through at least one sensor (120), the robot (100) can identify a second cleaning path based on obstacle information corresponding to the obstacle and a preset driving pattern.

[0115] According to one example, while the robot (100) is driving along the boundary of the search area (710), if an obstacle is identified within the cleaning area, the robot (100) can identify an obstacle area corresponding to the identified obstacle. The robot (100) can set a second cleaning path in the area excluding the identified obstacle area.

[0116] According to one embodiment, the robot (100) can drive backward along the identified second cleaning path by controlling the driving unit (110).

[0117] Referring to FIG. 9, while the robot (100) is driving along the boundary of the search area (710), it can identify obstacles (910, 920) inside the cleaning area (430). The robot (100) can identify obstacle areas (911, 921) corresponding to each of the identified obstacles (910, 920). The robot (100) can identify a second cleaning path (930) based on the obstacle areas (911, 921) and a preset driving pattern (e.g., a zigzag driving pattern).

[0118] The second cleaning path (930) may be a cleaning path excluding the obstacle area (911, 921) from the first cleaning path (810, 820). The second cleaning path (930) is not limited to this and may be set based on a different driving pattern.

[0119] According to one example, the robot (100) can clean the cleaning area (430) by driving backward based on the second cleaning path (930).

[0120] FIG. 10 is a diagram illustrating the cleaning path re-travel process of a robot according to one or more embodiments.

[0121] According to one embodiment, while the robot (100) is driving backward along a cleaning area along a first cleaning path (810), if liquid contaminants are re-identified on the previously driven cleaning path based on sensing data obtained through at least one sensor (120), the driving unit (110) can be controlled to drive along the first cleaning path (810) again.

[0122] According to one example, while the robot (100) is driving backward along a first cleaning path (810), it can identify whether there is contaminant on the previously driven cleaning path through at least one sensor (120) positioned at the front of the robot (100). If liquid contaminant is re-identified on the previously driven cleaning path, the robot (100) can drive back along the first cleaning path to clean the identified liquid contaminant.

[0123] For example, if liquid contaminants are re-identified on a previously traveled cleaning path, the robot (100) can control the driving unit (110) to perform cleaning again at the starting point of the first cleaning path (810) after performing all cleaning along the first cleaning path (810) and reaching the end point of the first cleaning path (810).

[0124] Referring to FIG. 10, the robot (100) can clean liquid contaminants by driving backward along a first cleaning path (810) to a cleaning area. While driving backward, the robot (100) can sense (1010) the cleaning area that has already been driven through through at least one sensor (120) placed on the front of the robot (100).

[0125] If liquid contaminants are re-identified on a previously traveled cleaning path, the robot (100) can re-travel the first cleaning path (810) to clean the re-identified liquid contaminants.

[0126] According to one embodiment, the robot (100) may identify whether the cleaning area identified based on a spatial map is a drivable area, and may secondarily identify whether the cleaning area is a drivable area based on a search area. In this case, if the cleaning area identified through the spatial map or at least one sensor (120) is not a drivable area, the robot (100) may provide a user notification or warning. For example, the robot (100) may provide a warning notification through a speaker placed on the robot. For example, the robot (100) may provide a user notification in the form of a pop-up through a user terminal device communicating with the robot (100). At this time, since the cleaning area is not a drivable area, the robot (100) may provide a user notification for direct cleaning or resetting the cleaning area.

[0127] FIG. 11 is a drawing for explaining the overall operation of a robot according to one or more embodiments.

[0128] Referring to FIG. 11, in operation 1110, the robot (100) can travel through the space and clean the floor surface.

[0129] In operation 1120, the robot (100) can identify liquid contaminants through at least one sensor (120) while traveling through space.

[0130] In operation 1130, the robot (100) can set a cleaning area containing the identified liquid contaminant.

[0131] In operation 1140, the robot (100) can identify whether the identified cleaning area is a drivable area based on a space map corresponding to the space.

[0132] In operation 1150, if the robot (100) identifies the cleaning area as a drivable area, it can set a search area including the cleaning area.

[0133] In operation 1160, if the cleaning area is not a drivable area, the robot (100) may provide a user notification to reset the cleaning area or clean it directly.

[0134] In operation 1170, the robot (100) can drive through the search area to secondarily identify whether the cleaning area is a drivable area.

[0135] In operation 1180, if the robot (100) identifies the cleaning area as a cleanable area, it can set a cleaning path within the cleaning area.

[0136] In operation 1190, the robot (100) can wet clean the cleaning area based on a set cleaning path.

[0137] FIG. 12 is a drawing for explaining the operation of a robot according to one or more embodiments.

[0138] Referring to FIG. 12, in operation 1210, the robot (100) can identify a cleaning area containing liquid contaminants when liquid contaminants are identified through at least one sensor (120) while the robot (100) is traveling through space.

[0139] In operation 1220, the robot (100) can identify a search area including a cleaning area if the cleaning area identified based on a space map corresponding to the space is identified as a drivable area.

[0140] In operation 1230, the robot (100) can drive through the search area and acquire sensing data through at least one sensor (120).

[0141] In operation 1240, if the robot (100) identifies the cleaning area as a cleanable area based on the acquired sensing data, it can identify a cleaning path within the cleaning area.

[0142] In operation 1250, the robot (100) can clean by driving backward along the identified cleaning path.

[0143] Since specific methods for identifying cleaning areas and search areas, and for identifying whether a cleaning area is a drivable area or a cleanable area, have been explained through the aforementioned embodiments, a detailed explanation thereof will be omitted.

[0144] The control method described in FIG. 12 can be performed by a robot (100) having the configuration of FIG. 2 described above, but is not necessarily limited thereto and can be performed by a robot having various configurations.

[0145] The various embodiments described above may be implemented as individual embodiments, or at least one embodiment may be combined with one another, either wholly or partially, to be implemented together in a single device.

[0146] According to the various embodiments described above, the robot (100) can set a cleaning area containing liquid contaminants and set a cleaning path within the cleaning area and perform wet cleaning by driving backward along the cleaning path.

[0147] Meanwhile, the various embodiments described above may be applied to a product as embodiments alone, but at least some of their contents may be combined with other embodiments of the present disclosure to be implemented together.

[0148] The various embodiments described above may be implemented as software containing instructions stored on a machine-readable storage medium (e.g., a computer). The machine may include an electronic device (e.g., a robot (100)) according to the disclosed embodiments, which is a device capable of calling instructions stored from the storage medium and operating according to the called instructions. When instructions are executed by a processor, the processor may perform a function corresponding to the instructions directly or by using other components under the control of the processor. Instructions may include code generated or executed by a compiler or an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory computer-readable storage medium. Here, "non-transitory" means only that the storage medium does not contain a signal and is tangible, and does not distinguish whether data is stored semi-permanently or temporarily in the storage medium.

[0149] In addition, according to one embodiment of the present disclosure, the method according to the various embodiments described above may be provided by being included in a computer program product.

[0150] Specifically, a non-transient readable storage medium or computer program product may be provided that stores computer commands to perform the following actions: identifying a cleaning area containing liquid contaminants when liquid contaminants are identified; driving through the cleaning area and acquiring sensing data when the identified cleaning area is identified as a drivable area based on a space map corresponding to the space; identifying a cleaning path within the cleaning area when the cleaning area is identified as a cleanable area based on the acquired sensing data; and cleaning along the identified cleaning path.

[0151] Computer program products may be distributed in the form of device-readable storage media (e.g., compact disc read-only memory (CD-ROM)) or online through an application store (e.g., Play Store™). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0152] In addition, computer instructions or programs for performing the control method of a robot according to the various embodiments described above may be stored on a non-transitory computer-readable medium. When computer instructions stored on such a non-transitory computer-readable medium are executed by the processor of a specific device, they cause the specific device to perform processing operations according to the various embodiments described above. A non-transitory computer-readable medium refers to a medium that stores data semi-permanently and is readable by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specific examples of a non-transitory computer-readable medium may include CDs, DVDs, hard disks, Blu-ray discs, USBs, memory cards, ROMs, etc.

[0153] Although preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above. It is understood that various modifications can be made by those skilled in the art without departing from the essence of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical spirit or perspective of the present disclosure.

Claims

1. In robots, Driving part; At least one sensor; Memory for storing instructions; and One or more processors including processing circuitry; and The above one or more processors, When a liquid contaminant is identified through the above-mentioned at least one sensor, a cleaning area containing the liquid contaminant is identified, and If the identified cleaning area is identified as a drivable area based on a space map corresponding to the space above, While driving over the cleaning area, sensing data is acquired through at least one sensor, and Based on the above-mentioned acquired sensing data, if the cleaning area is identified as a cleanable area, a cleaning path is identified within the cleaning area, and A robot that cleans along the cleaning path.

2. In Paragraph 1, The above one or more processors, If the above cleaning area is identified as a drivable area, a search area including the above cleaning area is identified, and A robot that travels through the above-mentioned search area and acquires the above-mentioned sensing data through the above-mentioned at least one sensor.

3. In Paragraph 1, The above one or more processors, Identify a contaminated area containing the above liquid contaminant, and A robot that identifies the cleaning area including a first margin area within a preset distance from the contaminated area.

4. In Paragraph 1, The above one or more processors, Identify the location of the cleaning area in the space map based on sensing data sensed through the at least one sensor, and A robot that identifies whether the cleaning area is the drivable area based on the location of the cleaning area and obstacle information corresponding to the cleaning area identified from the space map.

5. In Paragraph 4, The above one or more processors If the cleaning area in the above space map is identified as not being a drivable area, an obstacle area including the obstacle is identified based on the obstacle information, and Based on the location of the cleaning area and the obstacle area in the above spatial map, the area excluding the obstacle area from the cleaning area is re-identified as the cleaning area, and The above obstacle area is, A robot, comprising a second margin area within a pre-set distance from the aforementioned obstacle.

6. In Paragraph 2, The above one or more processors, Identifying the search area including a third margin area within a preset distance from the cleaning area, and Driving along the boundary of the search area, and acquiring sensing data corresponding to the interior of the cleaning area through at least one sensor, A robot that identifies whether the cleaning area is a cleanable area based on the above-mentioned acquired sensing data.

7. In Paragraph 1, The above one or more processors, When the above cleaning area is identified as the above-mentioned cleanable area, a first cleaning path is identified based on a preset driving pattern, and A robot that cleans the liquid contaminant by driving backward in the cleaning area based on the first cleaning path identified above.

8. In Paragraph 7, The above one or more processors, When an obstacle is identified in the cleaning area based on sensing data acquired through at least one sensor, a second cleaning path is identified based on obstacle information corresponding to the obstacle and the preset driving pattern, and A robot that controls the driving unit to drive backward in the cleaning area according to the identified second cleaning path.

9. In Paragraph 7, The above one or more processors, A robot that, while driving backward along the first cleaning path, controls the driving unit to drive the first cleaning path again if the liquid contaminant is re-identified on the previously driven cleaning path based on sensing data obtained through at least one sensor.

10. In Paragraph 2, The above one or more processors, The above search area is driven forward to identify whether the cleaning area is the cleaningable area, and A robot that controls the driving unit to drive backward over the cleaning area when the cleaning area is identified as the cleaningable area.

11. In Paragraph 1, The above robot is, It further includes a mopping pad, The above at least one sensor is positioned at least one of the front and side of the robot to sense the front portion of the robot, and The above mop pad is positioned on the rear of the robot.

12. In a method for controlling a robot, When a liquid contaminant is identified, an action of identifying a cleaning area containing the liquid contaminant; If the identified cleaning area is identified as a drivable area based on a space map corresponding to the space above, the operation of driving through the cleaning area and acquiring sensing data; If the cleaning area is identified as a cleanable area based on the above-mentioned acquired sensing data, the operation of identifying a cleaning path within the cleaning area; and A control method comprising the action of the robot cleaning along the cleaning path.

13. In Paragraph 11, The operation of acquiring the above sensing data is, If the above cleaning area is identified as a drivable area, the operation of identifying a search area including the cleaning area; and A robot further comprising the operation of driving in the above-mentioned search area and acquiring the above-mentioned sensing data.

14. In Paragraph 12, The operation of identifying the above cleaning area is, An operation to identify a contaminated area containing the above liquid contaminant; and A control method further comprising: an operation of identifying the cleaning area including a first margin area within a preset distance from the contaminated area.

15. A non-transient computer-readable storage medium storing computer instructions that cause said robot to perform an operation when executed by a processor of said robot, wherein said operation is, When a liquid contaminant is identified, an action of identifying a cleaning area containing the liquid contaminant; If the identified cleaning area is identified as a drivable area based on a space map corresponding to the space above, the operation of driving through the cleaning area and acquiring sensing data; If the cleaning area is identified as the cleaningable area based on the above-mentioned acquired sensing data, the operation of identifying a cleaning path within the cleaning area; and A non-transient computer-readable storage medium comprising: an action in which the robot cleans along the cleaning path.

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