Robot cleaner and detecting method thereof

Abstract

This robot cleaner comprises: an IR light source; an IR receiving unit; a driving unit; and one or more processors for controlling the driving unit so that the robot cleaner moves in a space, outputs IR light by using the IR light source while the robot cleaner moves in the space, and performs an operation of detecting liquid on the floor around the cleaner on the basis of the IR light reflected by an object and received by the IR receiving unit. The one or more processors perform an operation of detecting liquid in a first mode, change the mode of the robot cleaner to a second mode when liquid is detected, and perform an operation of detecting the liquid in the second mode. In the first mode, the operation of detecting the liquid is performed on the basis of a specific period, and in the second mode, the period of the operation of detecting the liquid is changed on the basis of the distance between the robot cleaner and the liquid.

Description

Robot vacuum cleaner and its detection method

[0001] The present disclosure relates to a robot vacuum cleaner that explores a space and a liquid detection method thereof.

[0002] Robots perform simple, repetitive tasks, and can also sense their surroundings in real time using cameras and other means, collect information, and navigate autonomously. Robots are used in a wide range of fields. Robot vacuum cleaners are used in homes.

[0003] A robot vacuum cleaner can move around a space (e.g., an indoor space) and clean the space by sucking up foreign substances, etc.

[0004] Liquids, such as water, milk, or pet urine, may be present on the floor within the space. If the robot vacuum fails to accurately detect the location of the liquid, contamination may spread to the surrounding area, and the liquid may damage the robot vacuum.

[0005] A robot cleaner including an IR light source, an IR receiver, a driving unit, and one or more processors, and a method for detecting liquid performed by the robot cleaner are provided.

[0006] According to one aspect of the present disclosure, a robot cleaner includes an IR light source, an IR receiver, a driving unit, and at least one processor operatively connected to the IR light source, the IR receiver, and the driving unit, and configured to control the driving unit so that the robot cleaner moves through a space, output IR light using the IR light source while the robot cleaner moves through the space, and detect liquid on a floor around the robot cleaner based on IR light reflected by an object and received by the IR receiver. The at least one processor performs an operation of detecting the liquid in a first mode, and when the liquid is detected, changes the mode of the robot cleaner to a second mode, and performs an operation of detecting the liquid in the second mode. In the first mode, the operation of detecting the liquid is performed based on a specific cycle, and in the second mode, the cycle of the operation of detecting the liquid is changed based on a distance between the robot cleaner and the liquid.

[0007] The one or more processors may output the IR light to the front of the robot cleaner using the IR light source, capture the front of the robot cleaner using the IR receiver, obtain an IR image using the received IR light, and identify whether there is liquid on the floor in front of the robot cleaner based on the IR image.

[0008] The one or more processors may identify a distance between the robot cleaner and the liquid based on the received IR light when the mode of the robot cleaner is changed to the second mode, identify a cycle of an operation of detecting the liquid in the second mode based on the distance between the robot cleaner and the liquid, and perform an operation of detecting the liquid based on the identified cycle. The cycle of the second mode may become shorter as the distance between the robot cleaner and the liquid decreases.

[0009] The cycle in which the robot cleaner performs the operation of detecting the liquid in the second mode may be shorter than the cycle in which the robot cleaner performs the operation of detecting the liquid in the first mode.

[0010] The one or more processors may perform an operation of cleaning the liquid when the robot cleaner performs a cleaning operation for the liquid, and detecting the liquid based on a cycle set in the second mode when cleaning for the liquid is completed.

[0011] The one or more processors may change the mode of the robot cleaner to the first mode and perform an operation of detecting the liquid in the first mode when the robot cleaner moves a preset distance after completing cleaning of the liquid.

[0012] The one or more processors may be configured to maintain a cycle set in the second mode while the robot cleaner changes its driving direction when the robot cleaner performs an avoidance drive for the liquid, and when the robot cleaner changes its driving direction and moves away from the liquid, change the mode of the robot cleaner to the first mode and perform an operation of detecting the liquid in the first mode.

[0013] The one or more processors may change the driving direction of the robot cleaner, which was moving away from the liquid, and move toward the liquid, and change the mode of the robot cleaner to the second mode based on the distance between the robot cleaner and the liquid, and perform an operation of detecting the liquid in the second mode.

[0014] The one or more processors may identify a distance between the robot cleaner and the liquid when the robot cleaner moves toward the liquid along a path that is a distance from the path along which the robot cleaner moves in a direction away from the liquid, and if the identified distance is a preset distance, change the mode of the robot cleaner to the second mode.

[0015] A method for detecting a liquid by a robot cleaner according to one aspect of the present disclosure includes: allowing the robot cleaner to move through a space; and outputting IR light using an IR light source while the robot cleaner moves through the space; and performing an operation of detecting a liquid on a floor around the robot cleaner based on the IR light reflected by an object and received by an IR receiver. The step of performing the operation of detecting the liquid includes: performing an operation of detecting the liquid in a first mode; and, when the liquid is detected, changing the mode of the robot cleaner to a second mode and performing an operation of detecting the liquid in the second mode. In the first mode, the operation of detecting the liquid is performed based on a specific cycle, and in the second mode, the cycle of the operation of detecting the liquid is changed based on a distance between the robot cleaner and the liquid.

[0016] The step of performing the operation of detecting the liquid may include a step of outputting the IR light toward the front of the robot cleaner using the IR light source, a step of photographing the front of the robot cleaner using the IR receiving unit and obtaining an IR image using the received IR light, and a step of identifying whether there is liquid on the floor in front of the robot cleaner based on the IR image.

[0017] The step of performing the operation of detecting the liquid may include the step of identifying a distance between the robot cleaner and the liquid based on the received IR light when the mode of the robot cleaner is changed to the second mode, the step of identifying a cycle of the operation of detecting the liquid in the second mode based on the distance between the robot cleaner and the liquid, and the step of performing the operation of detecting the liquid based on the identified cycle. The cycle of the second mode may become shorter as the distance between the robot cleaner and the liquid decreases.

[0018] The cycle in which the robot cleaner performs the operation of detecting the liquid in the second mode may be shorter than the cycle in which the robot cleaner performs the operation of detecting the liquid in the first mode.

[0019] The step of performing the operation of detecting the liquid may include a step of performing an operation of detecting the liquid based on a cycle set in the second mode when the robot cleaner performs a cleaning operation for the liquid, and when the cleaning for the liquid is completed.

[0020] The step of performing the operation of detecting the liquid may include the step of changing the mode of the robot cleaner to the first mode and performing the operation of detecting the liquid in the first mode when the robot cleaner moves a preset distance after completing cleaning for the liquid.

[0021] A non-transitory computer-readable medium storing computer instructions that, when executed by one or more processors of a robot cleaner according to an embodiment of the present disclosure, cause the robot cleaner to perform an operation, the operation including: causing the robot cleaner to move through a space; outputting IR light using an IR light source while the robot cleaner moves through the space; and detecting liquid on a floor around the robot cleaner based on IR light reflected by an object and received by an IR receiver. The step of performing the operation of detecting the liquid includes: detecting the liquid in a first mode; and, when the liquid is detected, changing the mode of the robot cleaner to a second mode and detecting the liquid in the second mode. In the first mode, the operation of detecting the liquid is performed based on a specific cycle, and in the second mode, the cycle of the operation of detecting the liquid is changed based on a distance between the robot cleaner and the liquid.

[0022] The above and other aspects, features and advantages of specific embodiments of the present disclosure will become more apparent from the following description taken in conjunction with the accompanying drawings.

[0023] FIG. 1 is a drawing schematically illustrating a robot vacuum cleaner according to an embodiment of the present disclosure.

[0024] FIG. 2 is a block diagram of a robot vacuum cleaner according to an embodiment of the present disclosure.

[0025] FIGS. 3A and 3B are drawings illustrating a sensor according to an embodiment of the present disclosure.

[0026] FIG. 4 is a flowchart of a liquid detection method of a robot according to an embodiment of the present disclosure.

[0027] FIG. 5 is a drawing for explaining a method of detecting a liquid using an IR image according to an embodiment of the present disclosure.

[0028] FIGS. 6A, 6B, 6C, and 6D are drawings illustrating an example of an operation of a robot cleaner detecting liquid according to an embodiment of the present disclosure.

[0029] FIG. 7 is a flowchart of a liquid detection method of a robot cleaner when the robot cleaner performs a cleaning operation on liquid according to an embodiment of the present disclosure.

[0030] FIGS. 8A and 8B are drawings for explaining an example of an operation of a robot cleaner detecting liquid according to an embodiment of the present disclosure.

[0031] FIG. 9 is a flowchart of a liquid detection method of a robot cleaner when the robot cleaner performs liquid avoidance driving according to an embodiment of the present disclosure.

[0032] FIG. 10a, FIG. 10b, FIG. 10c, and FIG. 10d are drawings for explaining an example of an operation of a robot cleaner detecting liquid according to an embodiment of the present disclosure.

[0033] FIG. 11 is a drawing for explaining a depth sensor and an IR light source according to an embodiment of the present disclosure.

[0034] FIG. 12 is a drawing for explaining an example of an operation of a robot cleaner identifying a ratio corresponding to an area according to an embodiment of the present disclosure.

[0035] FIG. 13 is a drawing for explaining an example of a method in which a robot cleaner performs an operation based on a ratio corresponding to an area according to an embodiment of the present disclosure.

[0036] FIG. 14 is a diagram illustrating an example of a method for a user to set a ratio corresponding to an area according to an embodiment of the present disclosure.

[0037] FIG. 15 is a drawing for explaining an example of a method for a robot cleaner to perform an operation of adjusting a ratio according to a distance from a liquid according to an embodiment of the present disclosure.

[0038] FIGS. 16A and 16B are drawings for explaining an example of a method for a robot cleaner to drive an IR camera according to the direction of liquid according to an embodiment of the present disclosure.

[0039] FIG. 17 is a block diagram of a robot vacuum cleaner according to an embodiment of the present disclosure.

[0040] FIG. 18 is a flowchart of a liquid detection method of a robot vacuum cleaner according to an embodiment of the present disclosure.

[0041] The terminology used in this disclosure is provided solely to describe specific embodiments and is not intended to limit the scope of other embodiments. Unless the context clearly dictates otherwise, singular forms may include plural references. Terms and words used in this disclosure, including technical or scientific terms, have the same meaning as commonly understood by those of ordinary skill in the art. Terms commonly defined in dictionaries may be interpreted as having the same or similar meaning in the context of the relevant field. Unless otherwise defined, terms should not be construed in an idealized or overly formal sense. Even if a term is defined in this disclosure, such term should not be construed to exclude embodiments of the disclosure depending on the context.

[0042] The phrase "at least one" used with a list of items can mean that different combinations of one or more of the listed items are available, and can also mean that only one of the listed items is required. For example, "at least one of A, B, and C" can include A, B, C, A and B, A and C, B and C, A, B, and C, and variations thereof. As a further example, "at least one of a, b, or c" can mean a only, b only, c only, both a and b, both a and c, both b and c, all a, b, and c, and variations thereof.

[0043] The terms "include" and "comprise" and their derivatives mean including without limitation. The term "or" is an inclusive term meaning "and / or." The phrase "associated with" and its derivatives includes include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, have a relationship to or with, or similar meaning.

[0044] As used herein, a "unit" or "module" refers to a hardware component such as a processor or circuit and / or a software component executed by a hardware component such as a processor. A "unit" or "module" may be implemented as a program stored on an addressable storage medium and executed by a processor. For example, a "unit" or "module" may be implemented as components such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and parameters.

[0045] The various elements and areas in the drawings are schematically drawn. Therefore, the technical aspects of the present invention are not limited by the relative sizes or spacing depicted in the attached drawings.

[0046] The present disclosure will be described below with reference to the attached drawings.

[0047] FIG. 1 is a drawing schematically illustrating a robot vacuum cleaner according to an embodiment of the present disclosure.

[0048] Referring to FIG. 1, a robot vacuum cleaner (100) can move through space and perform cleaning operations. In the present disclosure, the term "space" may refer to or correspond to an area, room, or physically separated area of ​​a building (e.g., a home, office, hotel, factory, store, grocery store, or restaurant).

[0049] The movement of the robot cleaner (100) may include the robot cleaner (100) exploring its surroundings, detecting its location and surrounding objects, and using the detected information to move within the space on its own. Movement may be replaced with expressions such as driving, for example.

[0050] The object may include various types of obstacles existing in the indoor space where the robot cleaner (100) is located, such as walls, furniture, home appliances, etc. In an embodiment, the object may include liquid (1) on the floor of the space.

[0051] The cleaning action may include the robot cleaner (100) moving through space and sucking up foreign substances such as dust on the floor. In addition, the cleaning action may include the robot cleaner (100) moving through space and cleaning the floor using a mop, etc.

[0052] In one embodiment, the robot cleaner (100) can detect liquid (1) on the floor around the robot cleaner (100), and specific operations will be described in more detail through the drawings and descriptions thereof described below.

[0053] FIG. 2 is a block diagram of a robot vacuum cleaner according to an embodiment of the present disclosure.

[0054] Referring to FIG. 2, the robot cleaner (100) may include a sensor (110), a driving unit (120), and a main module (130). The configuration of the robot cleaner (100) illustrated in FIG. 2 is merely an example, and it is to be understood that some configurations may be added depending on the example.

[0055] The sensor (110) is a configuration for sensing information about the surrounding environment of the robot cleaner (100). One or more processors (133) can obtain information based on the sensing values ​​of the sensor (110). For example, one or more processors (133) can detect liquid (1) on the floor around the robot cleaner (100) using the sensor (110).

[0056] The sensor (110) may include an IR (infrared ray) light source (111) and an IR receiver (112).

[0057] The IR light source (111) can output IR light. For example, the IR light source (111) can include an IR LED or a laser for outputting IR light. The IR light source (111) can output IR light toward the front of the robot cleaner (100). Output can be replaced with expressions such as emission, irradiation, etc., and IR light can be replaced with expressions such as IR, IR signal, etc.

[0058] The IR receiver (112) can receive IR light. For example, the IR receiver (112) can include an IR camera for receiving light in the infrared band. According to an example, the IR receiver (112) can include one or more IR cameras. The IR light output by the IR light source (111) can be reflected by an object. The IR receiver (112) can receive the IR light reflected by the object and generate an IR image using the received IR light.

[0059] FIGS. 3A and 3B are drawings illustrating a sensor according to an embodiment of the present disclosure.

[0060] Referring to FIG. 3a, the IR light source (111) may be placed on the front of the body (10) of the robot cleaner (100). At this time, the IR light source (111) being placed on the front of the body (10) may include being placed on the robot cleaner (100) so that the IR light source (111) can output IR light to the front of the robot cleaner (100). Accordingly, the IR light source (111) may be installed on the front of the body (10) or installed inside the front of the body (10) to output IR light to the front of the robot cleaner (100).

[0061] In an embodiment, the IR receiver (112) may be disposed on the front of the body (10) of the robot cleaner (100). At this time, the IR receiver (112) being disposed on the front of the body (10) may include being disposed on the robot cleaner (100) so that the IR receiver (112) can receive IR light entering the robot cleaner (100) from the front of the robot cleaner (100). Accordingly, the IR receiver (112) may be installed on the front of the body (10) or installed inside the front of the body (10) so as to receive IR light entering from the front of the robot cleaner (100).

[0062] At this time, the IR light source (111) may be located below the IR receiver (112). That is, the IR light source (111) may be placed at a lower height than the IR receiver (112) in the robot cleaner (100). For example, the IR light source (111) may be placed at a height of 0.5 cm to 3 cm from the floor when the robot cleaner (100) is placed on the floor. However, the present disclosure is not limited thereto, and the IR light source (111) may be placed at various heights in the lower area of ​​the front, taking into consideration the size of the robot cleaner (100), etc. In an embodiment, the IR light source (111) may have a field of view such that the IR light output from the IR light source (111) spreads narrowly in the vertical direction and widely in the horizontal direction. For example, the horizontal field of view of the IR light source (111) may be ±60°, and the vertical field of view may be ±20°. However, the present disclosure is not limited thereto, and the IR light source (111) may have various angles of view.

[0063] For example, referring to FIG. 3B, IR light output from an IR light source (111) is reflected by liquid (1) on the floor in front of the robot cleaner (100), and the reflected IR light can be received by the IR receiver (112). One or more processors (133) can output IR light using the IR light source (111), and when the IR light is reflected by an object and received by the IR receiver (112), an operation of detecting liquid on the floor around the robot cleaner (100) can be performed based on the received IR light.

[0064] The driving unit (120) can control the movement of the robot cleaner (100) under the control of one or more processors (133). For example, the driving unit (120) can move the robot cleaner (100), stop the moving robot cleaner (100), and control the moving speed and / or moving direction of the robot cleaner (100).

[0065] For example, the robot cleaner (100) may be moved by the rotation of one or more wheels provided on the robot cleaner (100). The driving unit (120) may include a device that generates power to rotate the wheels. For example, the driving unit (120) may be implemented as a gasoline engine, a diesel engine, an LPG (liquefied petroleum gas) engine, or an electric motor, depending on the fuel (or energy source) used.

[0066] The main module (130) is implemented in hardware and may include a communication interface (131), memory (132), one or more processors (133), and a control unit (134).

[0067] The communication interface (131) can perform data communication with electronic devices under the control of one or more processors (133). At this time, the electronic devices may include servers, home appliances, mobile devices (e.g., smartphones, tablet PCs, wearable devices, etc.).

[0068] For example, the communication interface (131) may include a communication circuit that can perform data communication between the robot cleaner (100) and the electronic device using at least one of data communication methods including wired LAN, wireless LAN, Wi-Fi, Bluetooth, ZigBee, Wi-Fi Direct (WFD), infrared Data Association (IrDA), Bluetooth Low Energy (BLE), Near Field Communication (NFC), Wireless Broadband Internet (Wibro), World Interoperability for Microwave Access (WiMAX), Shared Wireless Access Protocol (SWAP), Wireless Gigabit Alliances (WiGig), and RF communication.

[0069] Memory (132) may store instructions, data structures, and program codes. Operations performed by one or more processors (133) may be implemented by executing instructions or codes of a program stored in memory (132).

[0070] The memory (132) may include a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (e.g., SD or XD memory, etc.), and may include a non-volatile memory including at least one of a ROM (Read-Only Memory), an EEPROM (Electrically Erasable Programmable Read-Only Memory), a PROM (Programmable Read-Only Memory), a magnetic memory, a magnetic disk, and an optical disk, and a volatile memory such as a RAM (Random Access Memory) or an SRAM (Static Random Access Memory).

[0071] The memory (132) can store one or more instructions and / or programs that cause the robot cleaner (100) to perform an operation of detecting liquid on the floor.

[0072] One or more processors (133) can control the overall operations of the robot cleaner (100). For example, one or more processors (133) can control the overall operations of the robot cleaner (100) to detect liquid on the floor by executing one or more instructions of a program stored in the memory (132).

[0073] For example, one or more processors (133) can detect whether there is liquid on the floor around the robot cleaner (100), and when liquid is detected, perform various operations to operate according to the detection of liquid, and transmit a signal regarding the operation result to the control unit (134).

[0074] The control unit (134) can control components of the robot cleaner (100). The control unit (134) can control components of the robot cleaner (100) (e.g., IR light source (111) and driving unit (120)) based on signals provided from one or more processors (133). For example, the control unit (134) can generate a control signal using signals provided from one or more processors (133) and provide the control signal to components of the robot cleaner (100). Accordingly, the components of the robot cleaner (100) can perform operations corresponding to the calculation results of one or more processors (133). The control unit (134) can be implemented with one or more ICs (e.g., controller ICs).

[0075] The one or more processors (133) may include one or more of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an Accelerated Processing Unit (APU), a Many Integrated Core (MIC), a Digital Signal Processor (DSP), a Neural Processing Unit (NPU), a hardware accelerator, or a machine learning accelerator. The one or more processors (133) may control one or any combination of other components of the robot cleaner (100) and may perform operations or data processing related to communication. The one or more processors (133) may execute one or more programs or instructions stored in the memory (132). For example, the one or more processors (133) may perform a method according to an embodiment of the present disclosure by executing one or more instructions stored in the memory (132).

[0076] When a method according to an embodiment of the present disclosure includes multiple operations, the multiple operations may be performed by one processor or by multiple processors. For example, when a first operation, a second operation, and a third operation are performed by a method according to an embodiment, the first operation, the second operation, and the third operation may all be performed by the first processor, or the first operation and the second operation may be performed by the first processor (e.g., a general-purpose processor) and the third operation may be performed by the second processor (e.g., an artificial intelligence-specific processor).

[0077] One or more processors (133) may be implemented as a single core processor including one core, or may be implemented as one or more multicore processors including multiple cores (e.g., homogeneous multicores or heterogeneous multicores). When one or more processors (133) are implemented as a multicore processor, each of the multiple cores included in the multicore processor may include an internal processor memory, such as a cache memory or an on-chip memory, and a common cache shared by the multiple cores may be included in the multicore processor. In addition, each of the multiple cores (or some of the multiple cores) included in the multicore processor may independently read and execute a program instruction for implementing a method according to an embodiment of the present disclosure, or all (or some) of the multiple cores may be linked to read and execute a program instruction for implementing a method according to an embodiment of the present disclosure.

[0078] When a method according to an embodiment of the present disclosure includes a plurality of operations, the plurality of operations may be performed by one core among the plurality of cores included in a multi-core processor, or may be performed by the plurality of cores. For example, when a first operation, a second operation, and a third operation are performed by a method according to an embodiment, the first operation, the second operation, and the third operation may all be performed by a first core included in the multi-core processor, or the first operation and the second operation may be performed by a first core included in the multi-core processor, and the third operation may be performed by a second core included in the multi-core processor.

[0079] In embodiments of the present disclosure, a processor may mean a system on a 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, a GPU, an APU, a MIC, a DSP, an NPU, a hardware accelerator, or a machine learning accelerator, but embodiments of the present disclosure are not limited thereto.

[0080] Hereinafter, one or more processors (133) are referred to as processors (133).

[0081] The processor (133) can control the driving unit (120) to allow the robot cleaner (100) to move through space. In an embodiment, the processor (133) can perform an operation of detecting liquid while the robot cleaner (100) moves through space.

[0082] The operation of detecting liquid may include an operation of identifying whether there is liquid on the floor in front of the robot cleaner (100). For example, the processor (133) may output IR light to the front of the robot cleaner (100) using the IR light source (111), capture the front of the robot cleaner (100) using the IR receiver (112), obtain an IR image using the IR light received by the IR receiver (112), and identify whether there is liquid on the floor in front of the robot cleaner (100) based on the IR image.

[0083] In one embodiment, the robot cleaner (100) can change the cycle of the liquid detection operation when liquid is detected.

[0084] FIG. 4 is a flowchart of a liquid detection method of a robot according to an embodiment of the present disclosure.

[0085] In operation S410, the processor (133) can perform an operation of detecting liquid in the first mode while the robot cleaner (100) moves through space.

[0086] Mode 1 is a mode in which liquid detection is performed based on a specific cycle. For example, Mode 1 may be replaced with expressions such as Normal Mode, Liquid Detection Mode, etc.

[0087] For example, when a user input for starting cleaning is received, the robot cleaner (100) may start cleaning a space and move around the space to perform cleaning. At this time, the robot cleaner (100) may perform an operation to detect liquid in the first mode.

[0088] When the robot cleaner (100) is in the first mode, the processor (133) can perform an operation to detect liquid based on a specific cycle. The specific cycle may be a fixed value. The cycle at which the robot cleaner (100) performs the operation to detect liquid in the first mode may be preset during the manufacturing stage of the robot cleaner (100).

[0089] For example, the period set in the first mode may be T0 (ms). The processor (133) may output IR light using the IR light source (111) at time t and perform a photographing operation using the IR receiver (112) to obtain an IR image. In addition, the processor (133) may identify whether there is liquid on the floor using the IR image. In an embodiment, the processor (133) may output IR light using the IR light source (111) at time t+T0 and perform a photographing operation using the IR receiver (112) to obtain an IR image. In addition, the processor (133) may identify whether there is liquid on the floor using the IR image.

[0090] The processor (133) can input an IR image into an artificial intelligence model to identify whether there is liquid on the floor. The artificial intelligence model can be stored in the memory (132). The artificial intelligence model can include a neural network model trained to recognize liquid in an IR image. The artificial intelligence model can output a probability value that an object detected in the IR image input to the artificial intelligence model can be inferred to be liquid. For example, the artificial intelligence model can include a neural network model configured with parameters trained by applying IR images acquired by photographing a floor with liquid that emits IR light as input data and applying the liquid included in the IR image as an output value.

[0091] For example, IR light may be emitted onto a floor containing liquid, and the floor containing liquid may be captured using an IR camera. In this case, the amount of IR light reflected by the side surfaces of the liquid and received by the IR camera may be greater than the amount of IR light reflected by the liquid-free portion of the floor and received by the IR camera. Therefore, in the IR image captured by the IR camera, the area corresponding to the side surfaces of the liquid may be brighter than the area corresponding to the bottom. In addition, since the upper surface of the liquid absorbs a little more IR light in a certain band, the area corresponding to the upper surface of the liquid may be slightly darker than the area corresponding to the bottom in the IR image captured by the IR camera.

[0092] The processor (133) inputs the IR image captured by the IR receiver (112) into an artificial intelligence model to identify whether there is liquid on the floor.

[0093] For example, the processor (133) can input an IR image into an artificial intelligence model, obtain a probability value from the artificial intelligence model, and compare the probability value with a preset value to identify whether liquid is present in the IR image. In addition, if liquid is detected in the IR image, the processor (133) can identify that there is liquid on the floor in front of the robot cleaner (100).

[0094] In an embodiment, the artificial intelligence model can output information about the location of an area containing liquid in an IR image.

[0095] The location of the area where the liquid is present may include the location of the bounding box for the liquid in the IR image. The bounding box for the liquid may mean a rectangular box that includes the area where the liquid is detected in the IR image. For example, as shown in FIG. 5, the processor (133) may capture the front of the robot cleaner (100) using the IR receiver (112) to obtain an IR image (510). If there is liquid on the floor in front of the robot cleaner (100), the liquid may be included in the IR image (510). At this time, the coordinates of the upper left pixel of the IR image (510) are (0, 0), and the coordinates of the lower right pixel are (x width , y height ), the position of the bounding box (520) can be expressed by the x,y coordinate values ​​of the pixel (521) corresponding to the upper left vertex of the bounding box (520) and the x,y coordinate values ​​of the pixel (522) corresponding to the lower right vertex of the bounding box (520).

[0096] In steps S420-Y and S430, if liquid is detected while the processor (133) is performing the liquid detection operation in the first mode, the mode of the robot cleaner (100) can be changed to the second mode. The second mode is a mode in which the cycle of the liquid detection operation is changed according to the distance between the robot cleaner (100) and the liquid. For example, the second mode can be replaced with expressions such as high-speed mode, high-speed liquid detection mode, etc.

[0097] In operation S440, when the mode of the robot cleaner (100) is changed to the second mode, the processor (133) can identify the distance between the robot cleaner (100) and the liquid based on the received IR light.

[0098] For example, the processor (133) can identify the distance between the robot cleaner (100) and the liquid using the IR image in which the liquid is detected.

[0099] When the robot cleaner (100) photographs a floor with liquid, if the distance between the robot cleaner (100) and the liquid is far, the liquid may be located in an upper region in the IR image, and if the distance between the robot cleaner (100) and the liquid is close, the liquid may be located in a lower region in the IR image. Considering this, the memory (132) may store information about the distance between the robot cleaner (100) and the liquid according to the position of the liquid in the IR image. For example, the memory (132) may store information about the distance corresponding to each of a plurality of y-coordinate values ​​corresponding to the positions of a plurality of liquids.

[0100] In this case, the processor (133) can identify a distance corresponding to the y-coordinate value of a pixel corresponding to the lower right corner of a bounding box for the liquid among a plurality of distances corresponding to a plurality of y-coordinate values ​​stored in the memory (132). Then, the processor (133) can identify the identified distance as the distance between the robot cleaner (100) and the liquid. For example, the processor (133) can determine that the robot cleaner (100) is located at the identified distance from the liquid.

[0101] In addition, the processor (133) can identify the location of the liquid based on the location of the robot cleaner (100) and the distance between the robot cleaner (100) and the liquid, and store information about the identified location in the memory (132). For example, the location of the robot cleaner (100) and the location of the liquid can be expressed as coordinate values.

[0102] In operation S450, the processor (133) can identify the cycle of the operation of detecting the liquid in the second mode based on the distance between the robot cleaner (100) and the liquid. The cycle of the second mode may have a smaller value as the distance between the robot cleaner (100) and the liquid becomes closer. In an embodiment, the cycle of the operation of detecting the liquid by the robot cleaner (100) in the second mode may be shorter than the cycle of the operation of detecting the liquid by the robot cleaner (100) in the first mode.

[0103] For example, the memory (132) may store information about a cycle value corresponding to the distance between the robot cleaner (100) and the liquid.

[0104] According to an example, the memory (132) may store a cycle value corresponding to each of a plurality of distance ranges for each distance range between the robot cleaner (100) and the liquid. In this case, the plurality of cycle values ​​corresponding to the plurality of distance ranges may be stored in the memory (132) in the form of a lookup table. For example, the memory (132) may store a cycle value (T1 (ms)) corresponding to a distance range in which the distance between the robot cleaner (100) and the liquid is less than d1 and greater than d2, a cycle value (T2 (ms)) corresponding to a distance range in which the distance between the robot cleaner (100) and the liquid is less than d2 and greater than d3, ..., a cycle value (T2 (ms)) corresponding to a distance range in which the distance between the robot cleaner (100) and the liquid is d n-1 smaller than d n The period value corresponding to the ideal distance range (T n-1 (ms)) can be stored. n is a natural number greater than 1, and d n <d n-1 <... <d2<d1이다.

[0105] In this case, multiple cycle values ​​corresponding to multiple distance ranges can be set so that the cycle value decreases as the robot cleaner (100) gets closer to the liquid. For example, T1>T2>...>T n-1In an embodiment, the largest period value among the plurality of period values ​​corresponding to the plurality of distance ranges may be smaller than the period value of the first mode. For example, if the period value set in the first mode is T0, then T1 <T0이다.

[0106] The processor (133) can identify the distance between the robot cleaner (100) and the liquid based on the IR image in which the liquid is detected. In addition, the processor (133) can identify a distance range to which the identified distance belongs among a plurality of distance ranges, and set a cycle value corresponding to the identified distance range as a cycle for performing an operation to detect the liquid in the second mode.

[0107] In operation S460, the processor (133) may perform an operation of detecting liquid based on the identified cycle.

[0108] For example, the processor (133) determines that the distance (d) between the robot cleaner (100) identified based on the IR image and the liquid falls within a distance range that is less than d1 and greater than d2 among multiple distance ranges (i.e., d2≤d <d1), 액체를 감지하는 동작의 주기가 T1(ms)인 것으로 식별할 수 있다. 그리고, 프로세서(133)는 t 시점에 IR 광원(111)을 이용하여 IR 광을 출력하고 IR 수신부(112)를 이용하여 촬영을 수행하여, IR 이미지를 획득할 수 있다. 그리고, 프로세서(133)는 IR 이미지를 이용하여 바닥에 액체가 있는지를 식별할 수 있다. 실시 예에서, 프로세서(133)는 t+T1시점에 IR 광원(111)을 이용하여 IR 광을 출력하고 IR 수신부(112)를 이용하여 촬영을 수행하여, IR 이미지를 획득할 수 있다. 그리고, 프로세서(133)는 IR 이미지를 이용하여 바닥에 액체가 있는지를 식별할 수 있다.

[0109] In operation S470, the processor (133) can identify whether the robot cleaner (100) is in proximity to liquid.

[0110] For example, if the distance between the robot cleaner (100) and the liquid is less than or equal to a preset value, the processor (133) can identify that the robot cleaner (100) is close to the liquid, and if the distance between the robot cleaner (100) and the liquid is greater than the preset value, the processor (133) can identify that the robot cleaner (100) is not close to the liquid.

[0111] The liquid detected by the robot cleaner (100) is located in front of the robot cleaner (100), and the robot cleaner (100) is moving forward. Therefore, the robot cleaner (100) can gradually get closer to the liquid. In addition, the robot cleaner (100) can perform an operation of detecting the liquid while moving in the direction of the liquid. In this case, the processor (133) can identify the distance between the robot cleaner (100) and the liquid using the IR image acquired while performing the operation of detecting the liquid, and can identify whether the robot cleaner (100) is close to the liquid based on the identified distance.

[0112] In operation S470-N, if the processor (133) identifies that the robot cleaner (100) is not in proximity to the liquid, it may perform operations S450 and S460.

[0113] For example, the processor (133) can identify a cycle for performing an operation for detecting liquid in the second mode based on the distance between the robot cleaner (100) and the liquid, and perform an operation for detecting liquid based on the identified cycle.

[0114] As the robot cleaner (100) moves closer to the liquid, the distance range to which the robot cleaner (100) and the liquid belong may change. Accordingly, the processor (133) may repeatedly identify the distance range to which the robot cleaner (100) and the liquid belong while the robot cleaner (100) moves, and perform an operation to detect the liquid based on the identified cycle.

[0115] In this case, since the cycle of the robot cleaner (100) detecting the liquid is set to a smaller value as the robot cleaner (100) gets closer to the liquid, the robot cleaner (100) can perform the liquid detection operation more times within a certain period of time as it gets closer to the liquid. Accordingly, the robot cleaner (100) can detect the liquid more accurately. In addition, since there is a high possibility that there is another liquid near the area where the liquid is detected, the liquid detection efficiency of the robot cleaner (100) can be increased.

[0116] In operation S470-Y, if the processor (130) identifies that the robot cleaner (100) is close to liquid, it may perform the operation illustrated in FIG. 7 (“A”) or FIG. 9 (“A”).

[0117] FIGS. 6A, 6B, 6C, and 6D are drawings illustrating an example of an operation of a robot cleaner detecting liquid according to an embodiment of the present disclosure.

[0118] Referring to FIG. 6a, the robot cleaner (100) may perform an operation of detecting liquid while moving forward in the first mode. At this time, the period during which the robot cleaner (100) performs the operation of detecting liquid in the first mode may be T0 (ms). That is, the robot cleaner (100) may move within a space and identify whether there is liquid on the floor in front of the robot cleaner (100) every T0 (ms).

[0119] As shown in Fig. 6b, when the robot cleaner (100) detects liquid (1), the robot cleaner (100) can change the mode of the robot cleaner (100) to the second mode. Then, the robot cleaner (100) can identify a cycle in which the robot cleaner (100) performs an operation to detect liquid in the second mode based on the distance between the robot cleaner (100) and the liquid, and can move while performing an operation to detect liquid based on the identified cycle.

[0120] For example, referring to FIGS. 6b, 6c, and 6d, the cycle in which the robot cleaner (100) performs the operation of detecting liquid until the robot cleaner (100) approaches the liquid is T1, T2,..., T n-1 can be sequentially changed. At this time, T1>T2>...>T n-1 That is, as the robot cleaner (100) gets closer to the liquid, it can perform the operation of detecting the liquid in increasingly shorter cycles.

[0121] When the robot cleaner (100) approaches a liquid, it can perform cleaning operation on the liquid or perform avoidance operation on the liquid.

[0122] Liquid cleaning may involve the robot cleaner (100) moving after cleaning liquid on the floor using a cleaning device. Additionally, avoidance driving may involve the robot cleaner (100) changing its driving direction to avoid liquid and moving along a different path.

[0123] Whether the robot cleaner (100) will perform cleaning or avoidance driving for liquid can be determined by various methods.

[0124] For example, the driving type of the robot cleaner (100) may be preset. For example, the robot cleaner may perform dry cleaning and / or wet cleaning. Dry cleaning may involve sucking up foreign substances on the floor, and wet cleaning may involve wiping the floor using a mop or the like.

[0125] For example, if the robot cleaner (100) performs a dry cleaning function and cannot perform a wet cleaning function, the robot cleaner (100) may be set to perform an avoidance drive for liquid.

[0126] In an embodiment, when the robot cleaner (100) can perform a dry cleaning function and a wet cleaning function, the robot cleaner (100) can perform a cleaning operation or an avoidance operation for liquids depending on the cleaning mode of the robot cleaner (100). For example, when the cleaning mode is a dry cleaning mode, the robot cleaner (100) can perform an avoidance operation for liquids. In an embodiment, when the cleaning mode is a wet cleaning mode, the robot cleaner (100) can perform a cleaning operation for liquids. At this time, the dry cleaning mode is a mode in which the robot cleaner (100) performs dry cleaning. In addition, the wet cleaning mode is a mode in which the robot cleaner (100) performs wet cleaning, or a mode in which the robot cleaner (100) performs dry cleaning or a combination of dry and wet cleaning.

[0127] Additionally, when the robot cleaner (100) is capable of performing a wet cleaning function, the robot cleaner (100) can perform a cleaning operation or an avoidance operation for the liquid depending on the type of liquid and / or the type of mop provided in the cleaning device. The type of liquid can be distinguished depending on whether the liquid is water or not.

[0128] For example, if the type of the mop is a roller type, the robot cleaner (100) can perform cleaning operation on a liquid regardless of the type of the liquid. The roller type may refer to a type in which the mop rotates based on a horizontal axis (e.g., an axis parallel to the floor). In an embodiment, if the type of the mop is a panning type and the liquid is water, the robot cleaner (100) can perform cleaning operation on a liquid, and if the type of the mop is a panning type and the liquid is a liquid other than water, the robot cleaner (100) can perform avoidance operation on a liquid. The panning type may refer to a type in which the mop rotates based on a vertical axis (e.g., an axis perpendicular to the floor).

[0129] In one embodiment, when the robot cleaner (100) approaches a liquid, it can perform an operation of cleaning or avoiding the liquid and performing an operation of detecting the liquid, and the specific operations thereof will be described below.

[0130] FIG. 7 is a flowchart of a liquid detection method of a robot cleaner when the robot cleaner performs a cleaning operation on liquid according to an embodiment of the present disclosure. FIG. 7 illustrates an operation (operation S470-Y of FIG. 4) performed by the robot cleaner (100) when the robot cleaner (100) identifies that liquid is nearby.

[0131] In operation S710, when the robot cleaner (100) performs a cleaning operation on a liquid, the processor (133) may control the robot cleaner (100) to clean the liquid. For example, the processor (133) may control the driving unit (120) to move the robot cleaner (100) to an area containing liquid based on the distance between the robot cleaner (100) and the liquid, and may perform cleaning on the area using a mop or the like. At this time, the cleaning operation may include an operation in which the robot cleaner (100) passes by while cleaning the area containing liquid using a mop or the like, or an operation in which the robot cleaner (100) moves to an area containing liquid and then moves and cleans the area containing liquid and its surrounding area using a mop or the like.

[0132] In operation S720, the processor (133) may perform an operation to detect liquid based on the currently set cycle in the second mode when cleaning for the liquid is completed. For example, when cleaning for an area containing liquid is completed, the robot cleaner (100) may move in the same direction in which it moved before approaching the liquid. That is, when liquid is detected on the path, the robot cleaner (100) may perform cleaning for the area containing liquid and move along the path.

[0133] In this case, the processor (133) may perform an operation to detect liquid based on the currently set cycle in the second mode. At this time, the currently set cycle in the second mode may be a cycle in which the robot cleaner (100) performs an operation to detect liquid when the robot cleaner (100) approaches the liquid.

[0134] For example, referring to FIG. 6b, FIG. 6c, and FIG. 6d, the robot cleaner (100) performs a liquid detection operation in a cycle of T1, T2, ..., T until it approaches the liquid in the second mode. n-1 can be sequentially changed. At this time, when the robot cleaner (100) is identified as being close to the liquid, the value of the cycle set in the second mode is T n-1 Therefore, after the robot cleaner (100) performs cleaning on the area in the liquid, T n-1 It performs a liquid detection action every (ms) and can move.

[0135] In operation S730, the processor (133) can identify whether the robot cleaner (100) has moved a preset distance.

[0136] For example, the processor (133) can identify the distance the robot cleaner (100) has moved using the number of rotations of the wheels, etc., and can identify whether the robot cleaner (100) has moved a preset distance from an area where liquid was present based on the identified distance.

[0137] In operations S730-Y, S750, and S760, when the robot cleaner (100) moves a preset distance after completing cleaning for the liquid, the processor (133) can change the mode of the robot cleaner (100) to the first mode and perform an operation of detecting the liquid in the first mode.

[0138] For example, the processor (133) may be configured to T when the robot cleaner (100) completes cleaning of the liquid. n-1(ms) can perform an action to detect liquid. At this time, the robot cleaner (100) moves a preset distance from the area where the liquid was while T n-1 (ms) can be used to perform an operation to detect liquid. In addition, when the robot cleaner (100) moves a preset distance from an area where liquid was present, the processor (133) can change the mode of the robot cleaner (100) to the first mode and perform an operation to detect liquid every T0 (ms). At this time, T0 can be a cycle set in the first mode.

[0139] If liquid is detected again before the robot cleaner (100) moves a preset distance, the robot cleaner (100) performs cleaning on the liquid and can move. At this time, the robot cleaner (100) performs the operation of detecting liquid again in the second mode before moving the preset distance, and when the robot cleaner (100) moves the preset distance, the mode can be changed to the first mode.

[0140] In an embodiment, the robot cleaner (100) may perform a cleaning operation on liquid. In this case, there is a high possibility that another liquid may be present near the area where the liquid was detected. Therefore, the robot cleaner (100) may perform a liquid detection operation by maintaining a set cycle in the second mode while moving a certain distance after cleaning the liquid, and then perform a liquid detection operation in the first mode again after moving the certain distance. Accordingly, the liquid detection efficiency of the robot cleaner (100) may be increased.

[0141] FIGS. 8A and 8B are drawings for explaining an example of an operation of a robot cleaner detecting liquid according to an embodiment of the present disclosure.

[0142] Referring to Fig. 8a, the robot cleaner (100) can approach the liquid (1). At this time, the cycle in which the robot cleaner (100) performs the operation of detecting the liquid is T n-1 It could be (ms).

[0143] The robot cleaner (100) performs cleaning on the liquid (1) and in the second mode T n-1 (ms) and can move while performing a motion to detect liquid. And, as shown in Fig. 8b, the robot cleaner (100) moves a preset distance (e.g., d) from the area where the liquid (1) was. th ) moves, the mode of the robot cleaner (100) is changed to the first mode, and the robot cleaner can move while performing an operation of detecting liquid at a cycle of T0 (ms) in the first mode.

[0144] FIG. 9 is a flowchart of a liquid detection method of a robot cleaner when the robot cleaner performs liquid avoidance maneuvering according to an embodiment of the present disclosure. FIG. 9 illustrates an operation (operation S470-Y of FIG. 4) performed by the robot cleaner (100) when the robot cleaner (100) is identified as being close to liquid.

[0145] In operation S910, when the robot cleaner (100) performs avoidance driving for liquid, the processor (133) can control the driving unit (120) to change the driving direction of the robot cleaner (100). For example, the processor (133) can control the driving unit (120) to change the direction of the robot cleaner (100) to the left or right, and to move the robot cleaner (100) to a position a certain distance away from the current position. In addition, the processor (133) can control the driving unit (120) to change the direction of the robot cleaner (100) to the left or right. Accordingly, the front of the robot cleaner (100) can be in the opposite direction to the direction in which the liquid is detected.

[0146] In operation S920, the processor (133) may perform an operation of detecting liquid using the currently set cycle in the second mode while the driving direction of the robot cleaner (100) is changed. At this time, the currently set cycle in the second mode may be a cycle in which the robot cleaner (100) performs an operation of detecting liquid when the robot cleaner (100) approaches the liquid.

[0147] For example, referring to FIG. 6b, FIG. 6c, and FIG. 6d, the robot cleaner (100) performs a liquid detection operation in a cycle of T1, T2, ..., T until it approaches the liquid in the second mode. n-1 can be sequentially changed. At this time, when the robot cleaner (100) is identified as being close to the liquid, the value of the cycle set in the second mode is T n-1 Therefore, the robot cleaner (100) changes the driving direction while T n-1 It can perform a liquid detection operation every (ms).

[0148] In operation S930, when the robot cleaner (100) changes its driving direction and moves away from the liquid, the processor (133) can change the mode of the robot cleaner (100) to the first mode and perform an operation of detecting the liquid in the first mode.

[0149] For example, when the driving direction of the robot cleaner (100) changes, the processor (133) can control the driving unit (120) to move the robot cleaner (100) away from the liquid. Accordingly, the robot cleaner (100) can move away from the liquid along a path that is a certain distance from the path along which the liquid was detected. In this way, the robot cleaner (100) can move in a zigzag pattern.

[0150] In this case, the processor (133) can change the mode of the robot cleaner (100) to the first mode and perform an operation of detecting liquid in the first mode.

[0151] For example, the robot vacuum cleaner (100) changes the driving direction while T n-1 (ms) can be performed to detect liquid. Then, when the robot cleaner (100) moves away from the liquid after the change in driving direction is completed, the mode of the robot cleaner (100) can be changed to the first mode and the operation to detect liquid can be performed every T0 (ms). At this time, T0 can be a cycle set in the first mode.

[0152] In operation S940, the processor (133) can identify the distance between the robot cleaner (100) and the liquid when the robot cleaner (100) moves in the direction where the liquid is.

[0153] For example, if an obstacle is detected in front of the robot cleaner (100) while the robot cleaner is moving away from the liquid, the robot cleaner (100) may change its driving direction again and move toward the liquid along a path that is a certain distance from the path along which the robot cleaner (100) moved away from the liquid. In other words, the robot cleaner (100) may move in a zigzag pattern to move toward the liquid. In this case, the robot cleaner (100) may move while performing an operation to detect the liquid in the first mode.

[0154] The processor (133) can identify the distance between the robot cleaner (100) and the liquid while the robot cleaner (100) moves in the direction of the liquid. For example, the processor (133) can identify the distance between the robot cleaner (100) and the liquid based on the position of the robot cleaner (100) and the position of the liquid stored in the memory (132).

[0155] In operations S950-Y, S960, and S970, if the distance between the robot cleaner (100) and the liquid is a preset distance, the processor (133) can change the mode of the robot cleaner (100) to the second mode. Then, the processor (133) can perform an operation of detecting the liquid in the second mode.

[0156] For example, the robot cleaner (100) may perform an operation to detect liquid every T0 (ms) in the first mode and move in the direction where the liquid is present. At this time, T0 may be a cycle set in the first mode. Then, if the distance between the robot cleaner (100) and the liquid is a preset distance, the robot cleaner (100) may change the mode of the robot cleaner (100) to the second mode and move while performing an operation to detect liquid in the second mode. For example, the processor (133) may identify a distance range to which the distance between the robot cleaner (100) and the liquid belongs among the plurality of distance ranges based on information about a plurality of cycle values ​​corresponding to a plurality of distance ranges stored in the memory (132). Then, the processor (133) may set a cycle value corresponding to the identified distance range as the cycle of the operation to detect liquid in the second mode and perform an operation to detect liquid based on the set cycle. Accordingly, the robot cleaner (100) can perform an operation to detect liquid at increasingly shorter cycles as it gets closer to an area containing liquid.

[0157] When the driving direction of the robot cleaner (100) moving away from the liquid is changed and the robot cleaner (100) moves toward the liquid, the processor (133) can change the mode of the robot cleaner (100) to the second mode based on the distance between the robot cleaner (100) and the liquid, and perform an operation of detecting the liquid in the second mode.

[0158] The processor (133) may perform liquid avoidance maneuvering again when liquid is detected while the robot cleaner (100) is moving toward the liquid. In addition, the processor (133) may change the mode of the robot cleaner (100) to the first mode when liquid is not detected while the robot cleaner (100) is moving toward the liquid. For example, the processor (133) may change the mode of the robot cleaner (100) to the first mode when the robot cleaner (100) moves away from the liquid by a preset distance.

[0159] In an embodiment, the robot cleaner (100) may perform liquid avoidance maneuvers. In this case, there is a high probability that another liquid may be present near the area where the liquid is detected. Therefore, after avoiding the liquid, the robot cleaner (100) may move back toward the liquid, change the mode of the robot cleaner (100) to a second mode based on the distance between the robot cleaner (100) and the liquid, and perform an operation to detect the liquid in the second mode. Accordingly, the liquid detection efficiency of the robot cleaner (100) may be increased.

[0160] FIG. 10a, FIG. 10b, FIG. 10c, and FIG. 10d are drawings for explaining an example of an operation of a robot cleaner detecting liquid according to an embodiment of the present disclosure.

[0161] Referring to Fig. 10a, the robot cleaner (100) operates in the second mode. n-1The robot cleaner (100) may move while performing an operation of detecting liquid at a cycle of (ms) and may approach the liquid (1). In this case, the robot cleaner (100) may change its driving direction to avoid the liquid (1). The robot cleaner (100) may move in a direction away from the liquid (1) along a path (12) that is a certain distance from the path (11) along which the robot cleaner (100) moved. At this time, the robot cleaner (100) may change the mode of the robot cleaner (100) to the first mode, and may move while performing an operation of detecting liquid at a cycle of T0 (ms) in the first mode.

[0162] Referring to FIGS. 10b and 10c, the robot cleaner (100) moving away from the liquid (1) may change its driving direction and move toward the liquid (1) along the path (13) when an obstacle is detected in front. At this time, the path (13) may be a path that is a certain distance away from the path (12) along which the robot cleaner (100) moved away from the liquid (1). In addition, when the distance from the liquid is identified as a preset distance while the robot cleaner (100) moves along the path (13), the mode of the robot cleaner (100) may be changed to the second mode, and the robot cleaner (100) may move while performing an operation to detect the liquid in the second mode. At this time, the cycle in which the robot cleaner (100) performs an operation to detect the liquid depending on the distance between the robot cleaner (100) and the liquid is T1, T2,..., T n-1 can be changed sequentially.

[0163] And, as shown in Fig. 10d, the robot cleaner (100) is positioned at a preset distance (e.g., d) from the area where the liquid (1) is present. th ) moves, the mode of the robot cleaner (100) is changed to the first mode, and the robot cleaner can move while performing an operation of detecting liquid at a cycle of T0 (ms) in the first mode.

[0164] In the present disclosure, the IR receiver (112) may be an IR receiver that constitutes a depth sensor. The depth sensor may obtain depth information about an object around the robot cleaner (100). For example, the depth sensor may output IR light in front of the robot cleaner (100), and when the output IR light is reflected by an object and received, the depth information about the object may be obtained using the received IR light. The depth information may include information about the distance between the robot cleaner (100) and the object. The depth sensor may be implemented in various ways, such as a stereo method, a TOF (Time of Flight) method, etc.

[0165] For example, referring to FIG. 11, the depth sensor (113) may include an IR light source (114) and an IR receiver (112).

[0166] Hereinafter, the IR light source (114) for obtaining depth information is described as the first IR light source (114), and the IR light source (111) for detecting liquid is described as the second IR light source (111).

[0167] The first IR light source (114) can output IR light. For example, the first IR light source (114) can include an IR LED or laser for outputting IR light. The first IR light source (114) can output IR light toward the front of the robot cleaner (100).

[0168] The robot cleaner (100) outputs IR light using the first IR light source (114), and when the output IR light is reflected by an external object and received by the IR receiver (112), depth information about the object can be obtained using the received IR light. In addition, the robot cleaner (100) can detect the object using the depth information.

[0169] In an embodiment, the robot cleaner (100) outputs IR light using a second IR light source (111), and when the output IR light is reflected by an external object and received by an IR receiver (112), the robot cleaner can detect liquid on the floor using the received IR light.

[0170] The depth sensor (113) may be placed in the upper area (11) of the front of the body of the robot cleaner (100), and the second IR light source (111) may be placed in the lower area (12) of the front of the body of the robot cleaner (100).

[0171] In an embodiment, when a depth sensor (113) for obtaining depth information is provided in the robot cleaner (100), a second IR light source (111) is added to the robot cleaner (100), and the second IR light source (111) and the IR receiver (112) of the depth sensor (113) can be used to detect liquid on the floor, thereby reducing the manufacturing cost of the robot cleaner (100).

[0172] In an embodiment, the robot cleaner (100) may include a first IR light source (114) for obtaining depth information and a second IR light source (111) for detecting liquid on the floor.

[0173] The processor (133) can control the overall operations of the robot cleaner (100) to obtain depth information and detect liquid on the floor.

[0174] The processor (133) can obtain depth information about objects around the robot cleaner (100) using the depth sensor (113) and detect liquid on the floor around the robot cleaner (100) using the second IR light source (111) and the IR receiver (112).

[0175] The operation of acquiring depth information may include an operation of acquiring depth information about an object around the robot cleaner (100). For example, the processor (133) may output IR light toward the front of the robot cleaner (100) using the first IR light source (114). At this time, the second IR light source (111) may be in an off state. In addition, the processor (133) may capture the front of the robot cleaner (100) using the IR receiver (112) and generate a depth image including depth information using the IR light received by the IR receiver (112). Accordingly, the processor (133) may detect an object in front of the robot cleaner (100) using the depth information.

[0176] The operation of detecting liquid may include an operation of identifying whether there is liquid on the floor in front of the robot cleaner (100). For example, the processor (133) may output IR light toward the front of the robot cleaner (100) using the second IR light source (111). At this time, the first IR light source (114) may be in an off state. In addition, the processor (133) may capture the front of the robot cleaner (100) using the IR receiver (112), obtain an IR image using the IR light received by the IR receiver (112), and identify whether there is liquid on the floor in front of the robot cleaner (100) based on the IR image.

[0177] The processor (133) can identify a ratio between the number of times an operation for acquiring depth information is performed and the number of times an operation for detecting liquid is performed, and perform the operation for acquiring depth information and the operation for detecting liquid based on the identified ratio.

[0178] In one embodiment, the processor (133) can identify a ratio between the number of times the robot cleaner (100) performs an operation to acquire depth information and the number of times the robot cleaner performs an operation to detect liquid based on an area within the space in which the robot cleaner (100) is located.

[0179] For example, the processor (133) can identify a ratio corresponding to an area where the robot cleaner (100) is located among a plurality of ratios corresponding to a plurality of areas within a space, and determine the identified ratio as a ratio between the number of times an operation for acquiring depth information is performed and the number of times an operation for detecting liquid is performed.

[0180] A space may include multiple areas. Areas may be separated from other areas by walls or other obstacles (e.g., door frames, windows, etc.). Areas may correspond to kitchens, living rooms, bathrooms, rooms, etc. Furthermore, if an area is connected to another area through an entrance, the other area may be divided into an area within a predetermined distance from the entrance and the remaining area. In this case, an area within a predetermined distance from the entrance may be referred to as an area adjacent to the area.

[0181] For example, ratio values ​​corresponding to each of the plurality of areas may be stored in the memory (132). In this case, the ratio values ​​corresponding to each of the plurality of areas may be stored in the memory (132) in the form of a lookup table.

[0182] In one example, the ratio for the first area may be set to 1:N1. For example, the first area may include a bathroom and a kitchen. In an embodiment, the ratio for the second area may be set to 1:N2. The second area may include an area adjacent to the first area. For example, the second area may include an area adjacent to a bathroom or a kitchen within the space. In one example, the bathroom or the kitchen may be connected to a room or a living room through an entrance within the space. In this case, the second area may include a portion of the room or living room within a preset distance from the entrance of the bathroom or kitchen. In addition, the ratio for the third area may be set to 1:N3. For example, if the bathroom or the kitchen is not connected to the room or living room, the third area may include the entire area of ​​the room or living room. In an embodiment, if the bathroom or the kitchen is connected to the room or living room, the third area may include the remaining area of ​​the entire area of ​​the room or living room excluding the area adjacent to the bathroom or the kitchen.

[0183] In this case, the ratio may mean the ratio between the number of times the robot cleaner (100) performs an operation to acquire depth information in an area and the number of times it performs an operation to detect liquid. In addition, N3 <N2<N1이다.

[0184] The processor (133) can identify an area in which the robot cleaner (100) is located among multiple areas within a space. In this case, identifying an area may include identifying a name of the area (e.g., bathroom, kitchen, room, living room, etc.).

[0185] For example, a user can control a robot vacuum cleaner (100) using an application installed on a mobile device.

[0186] For example, a user can connect to a server by executing an application installed on a mobile device, create a user account, and communicate with the server based on the logged-in user account to register a robot cleaner (100). The server can register the robot cleaner (100) to the user account by registering identification information of the robot cleaner (100) (e.g., serial number or MAC (medium access control) address, etc.) to the user account.

[0187] In addition, the user can control the robot cleaner (100) using an application installed on the mobile device. For example, a user interface (UI) screen related to the robot cleaner (100) may be displayed on the mobile device according to the user account. In this case, the UI screen may include a map of the space where the robot cleaner (100) is located. The user can input user input into the mobile device to set names for each of the multiple areas on the map. The server can receive the user input from the mobile device and transmit information about the names of the areas set according to the user input to the robot cleaner (100). Accordingly, the processor (133) can identify the location of the robot cleaner (100) on the map and the area where the robot cleaner (100) is located.

[0188] However, the present invention is not limited thereto, and the processor (133) may identify an area where the robot cleaner (100) is located by using an image acquired using a camera (e.g., an RGB camera). For example, an artificial intelligence model may be stored in the memory (132). The artificial intelligence model may include a neural network model trained to predict the type of an object in an image. The artificial intelligence model may include a neural network model configured with model parameters trained by applying images as input data and applying the type of an object included in the images as an output correct value.

[0189] The processor (133) can capture an image by using a camera to capture the surroundings of the robot cleaner (100), input the captured image into an artificial intelligence model, and obtain information about the type of object included in the image from the artificial intelligence model.

[0190] And, the processor (133) can identify the area where the robot cleaner (100) is located based on the type of the object.

[0191] For example, if the type of the object detected in the image is a “bathtub,” a “sink,” etc., the processor (133) can identify that the robot cleaner (100) is located in the bathroom. In an embodiment, if the type of the object detected in the image is a “sink,” a “table,” a “refrigerator,” etc., the processor (133) can identify that the robot cleaner (100) is located in the kitchen. In addition, if the type of the object detected in the image is a “bed,” a “closet,” etc., the processor (133) can identify that the robot cleaner (100) is located in the room. In an embodiment, if the type of the object detected in the image is a “sofa,” a “TV,” etc., the processor (133) can identify that the robot cleaner (100) is located in the living room. In an embodiment, the processor (133) may identify that the robot cleaner (100) is located in an area adjacent to the bathroom or kitchen when the robot cleaner (100) identifies an “entrance” to the kitchen or bathroom near the kitchen or bathroom.

[0192] The processor (133) can identify a ratio corresponding to the identified area as a ratio between the number of times the operation for acquiring depth information is performed and the number of times the operation for detecting liquid is performed, and can perform the number of times the operation for acquiring depth information is performed and the operation for detecting liquid based on the identified ratio.

[0193] For example, referring to FIG. 12, the map (1200) may include a first area (1210), a second area (1220), and a third area (1230).

[0194] When the robot cleaner (100) is located in the first area (1210), the processor (133) can identify the first ratio (e.g., 1:N1) corresponding to the first area (1210) as the ratio between the number of times the operation for acquiring depth information is performed and the number of times the operation for detecting liquid is performed. In addition, when the robot cleaner (100) is located in the second area (1220), the processor (133) can identify the second ratio (e.g., 1:N2) corresponding to the second area (1220) as the ratio between the number of times the operation for acquiring depth information is performed and the number of times the operation for detecting liquid is performed. In addition, when the robot cleaner (100) is located in the third area (1230), the processor (133) can identify the third ratio (e.g., 1:N3) corresponding to the third area (1230) as the ratio between the number of times the operation for acquiring depth information is performed and the number of times the operation for detecting liquid is performed. In this case, N3 <N2<N1이다.

[0195] The processor (133) can perform an operation of acquiring depth information based on the identified ratio and an operation of detecting liquid on the floor.

[0196] For example, if the identified ratio is M1:M2, the processor (133) may perform an operation of acquiring depth information M1 times and an operation of detecting liquid M2 times within one cycle, and may repeatedly perform these operations for multiple cycles. In this case, M1 and M2 are natural numbers.

[0197] At this time, the processor (133) may first perform the operation of acquiring depth information M1 times within one cycle, and then perform the operation of detecting liquid M2 times. In addition, the processor (133) may first perform the operation of detecting liquid M2 times within one cycle, and then perform the operation of acquiring depth information M1 times. In an embodiment, the processor (133) may perform these operations alternately within one cycle, or may first perform a part of one operation within one cycle, perform the entire number of other operations, and then perform the remaining number of operations within one cycle.

[0198] In the example of FIG. 12, when the robot cleaner (100) is located in the first area (1210), the processor (133) can perform an operation of acquiring depth information and an operation of detecting liquid based on a first ratio (e.g., 1:N1) corresponding to the first area (1210).

[0199] In addition, when the robot cleaner (100) is located in the second area (1220), the processor (133) can perform an operation of acquiring depth information and an operation of detecting liquid based on a second ratio (e.g., 1:N2) corresponding to the second area (1220).

[0200] In addition, when the robot cleaner (100) is located in the third area (1230), the processor (133) can perform an operation of acquiring depth information and an operation of detecting liquid based on a third ratio (e.g., 1:N3) corresponding to the third area (1230).

[0201] In this case, N3 <N2<N1이다. 따라서, 제1 영역(1210)에 대응되는 제1 비율(예: 1:N1)에 따라 로봇 청소기(100)가 액체를 감지하는 동작을 수행하는 횟수는 제2 영역(1220)에 대응되는 제2 비율(예: 1:N2)에 따라 로봇 청소기(100)가 액체를 감지하는 동작을 수행하는 횟수보다 많다. 또한, 제2 영역(1220)에 대응되는 제2 비율(예: 1:N2)에 따라 로봇 청소기(100)가 액체를 감지하는 동작을 수행하는 횟수는 제3 영역(1230)에 대응되는 제3 비율(예: 1:N3)에 따라 로봇 청소기(100)가 액체를 감지하는 동작을 수행하는 횟수보다 많다.

[0202] For example, N1=3, N2=2, N3=1. That is, the ratio corresponding to the first region may be 1:3, the ratio corresponding to the second region may be 1:2, and the ratio corresponding to the third region may be 1:1.

[0203] Referring to FIG. 13, the processor (133) can obtain depth information about an object at a constant time cycle (e.g., T). For example, the processor (133) can output IR light using the first IR light source (114) at time t and perform a photographing operation using the IR receiver (112). Then, the processor (133) can obtain depth information about the object using the IR light received through the IR receiver (112). Thereafter, the processor (133) can output IR light using the first IR light source (114) at time t+T and perform a photographing operation using the IR receiver (112). Then, the processor (133) can obtain depth information about the object using the IR light received through the IR receiver (112). T can be, for example, 100 ms. That is, the IR receiver (112) can perform shooting at 10 FPS (Frames Per Second). However, the present disclosure is not limited thereto. For example, 100 ms may be the minimum cycle for the robot cleaner (100) to search the surroundings using the depth sensor (110) to stably navigate the space. However, the present disclosure is not limited thereto, and for example, T may include 50 ms, 33 ms, etc.

[0204] If the ratio between the number of times the processor (133) performs the operation of acquiring depth information and the number of times the processor (133) performs the operation of detecting liquid is 1:1, the processor (133) can perform the operation of acquiring depth information once and the operation of detecting liquid once within one cycle (row with ratio = 1:1 in FIG. 13). In addition, if the ratio between the number of times the processor (133) performs the operation of acquiring depth information and the number of times the processor (133) performs the operation of acquiring depth information and the operation of detecting liquid is 1:2, the processor (133) can perform the operation of acquiring depth information once and the operation of detecting liquid twice within one cycle (row with ratio = 1:2 in FIG. 13). In addition, if the ratio between the number of times the processor (133) performs the operation of acquiring depth information and the number of times the processor (133) performs the operation of detecting liquid three times within one cycle (row with ratio = 1:3 in FIG. 13).

[0205] In general, bathrooms and kitchens are more likely to detect liquid on the floor. Therefore, in the present disclosure, when the robot cleaner (100) is in a bathroom or kitchen, the ratio of the area can be set so that it performs liquid detection operations more frequently. In an embodiment, areas adjacent to a bathroom or kitchen are also more likely to detect liquid than other areas. Therefore, in the present disclosure, when the robot cleaner (100) is in a bathroom or kitchen, the ratio of the area can be set so that it performs liquid detection operations more frequently, although less frequently than when the robot cleaner (100) is in a bathroom or kitchen. Since the robot cleaner (100) can optimally perform liquid detection operations, it is possible to effectively detect liquid while reducing sensor power consumption and resource consumption.

[0206] In one example, the processor (133) may update a ratio corresponding to an area based on the number of times liquid is detected in an area within the space.

[0207] Updating the ratio corresponding to the area may include adjusting the ratio corresponding to the area so that the robot cleaner (100) performs the action of detecting liquid in the area more or less than the ratio currently set for the area.

[0208] For example, if the number of times liquid is detected in an area is high, the robot cleaner (100) may perform more actions to detect liquid in the area, and if the number of times liquid is detected in the area is low, the ratio corresponding to the area may be updated so that the robot cleaner (100) may perform fewer actions to detect liquid in the area.

[0209] The processor (133) performs an operation to detect liquid while the robot cleaner (100) performs a cleaning operation, and when liquid is detected on the floor, the processor can update the history information stored in the memory (132).

[0210] The history information may include information about the time (e.g., date, time, etc.), number of times, etc., when liquid was detected by the robot cleaner (100) in each of the plurality of areas. When liquid is detected in an area, the processor (133) may update the history information by adding the time, number of times, etc., of detecting liquid to the history information.

[0211] And, the processor (133) can update the ratio corresponding to the area based on the history information.

[0212] For example, the processor (133) may identify the number of times liquid was detected in an area during a time interval from a first point in time to a second point in time based on historical information. The first point in time may be a past point in time. Additionally, the second point in time may be the present point in time. The past point in time may be a point in time prior to a preset time from the present point in time.

[0213] In addition, if the number of times identified is greater than the first reference value, the processor (133) can adjust the ratio corresponding to the area so that the robot cleaner (100) performs more operations of detecting liquid in the area. In addition, if the number of times identified is greater than the second reference value and less than or equal to the first reference value, the processor (133) can maintain the ratio corresponding to the current area. In addition, if the number of times identified is less than or equal to the second reference value, the processor (133) can update the ratio corresponding to the area so that the robot cleaner (100) performs fewer operations of detecting liquid in the area. In this case, the first reference value may be greater than the second reference value. In addition, the first reference value and the second reference value may be different from each other depending on the ratio corresponding to the area.

[0214] For example, the ratio corresponding to the area may be 1:N2. In this case, if the number of identified times is greater than the first reference value, the processor (133) may adjust the ratio corresponding to the area to 1:N1, and if the number of identified times is less than or equal to the second reference value, the ratio corresponding to the area may be adjusted to 1:N3. In this case, N3 <N2<N1이다.

[0215] In an embodiment, in order to adjust the detection range depending on whether the object is at a close range or a long range, the exposure time of the IR receiver (112) may be set differently. For example, when the robot cleaner (100) obtains depth information for a close range object, the exposure time of the IR receiver (112) (e.g., camera) may be set to exp_time 1 (=exp_time), and when obtaining depth information for a far range object, the exposure time of the IR receiver (112) (e.g., camera) may be set to exp_time 2 (=exp_time×a). a is a constant, and exp_time 1 may be smaller than exp_time 2.

[0216] As described above, the robot cleaner (100) may use the first IR light source (114) when acquiring depth information, and may use the second IR light source (111) when detecting liquid on the floor. At this time, the intensities of the light output from the first IR light source (114) and the second IR light source (111) may be different. In this case, the exposure time of the IR receiver (112) (e.g., camera) may be set according to the intensity of the light. For example, the intensity of the light output from the second IR light source (111) may be less than the intensity of the light output from the first IR light source (114). In this case, when the robot cleaner (100) detects liquid, the exposure time of the IR receiver (112) (e.g., camera) may be set to exp_time 3 (= exp_time × b). b is a constant, and exp_time 3 may be greater than exp_time 1.

[0217] Meanwhile, in the above-described example, it was explained that the ratio corresponding to the area is set during the manufacturing stage of the robot cleaner (100). However, this is not limited to this, and the ratio corresponding to the area may be set based on user input or history information.

[0218] In one example, the ratio corresponding to the area may be determined based on user input. The processor (133) may identify the ratio between the number of times the operation for obtaining depth information is performed and the number of times the operation for detecting liquid is performed based on the user input.

[0219] For example, referring to FIG. 14, the mobile device (200) may display a UI screen (1410) for setting a ratio. In one example, when a user input for selecting an area on a map is received, the mobile device (200) may display GUI (graphical user interface) elements for setting a ratio for the selected area. For example, the GUI elements may include high (1411), medium (1412), and low (1413). The user may input a user input for selecting one of the GUI elements into the mobile device (200). The server may receive the user input from the mobile device and transmit a control command corresponding to the user input to the robot cleaner (100).

[0220] The processor (133) can determine a ratio corresponding to the area based on a control command received from the server.

[0221] For example, if the user selects the ratio for the area as high (1411), the processor (133) may set the ratio for the area to 1:N1. In addition, if the user selects the ratio for the area as normal (1412), the processor (133) may set the ratio for the area to 1:N2. In addition, if the user selects the ratio for the area as low (1413), the processor (133) may set the ratio for the area to 1:N3. In this case, the ratio may mean the ratio between the number of times the robot cleaner (100) performs an operation to acquire depth information and the number of times it performs an operation to detect liquid. In addition, N3 <N2<N1이다.

[0222] In one example, the ratio corresponding to the area may be determined based on the history information. The processor (133) may identify the ratio between the number of times the operation for acquiring depth information is performed and the number of times the operation for detecting liquid is performed based on the history information.

[0223] For example, the processor (133) may identify the number of times liquid was detected in an area during a time interval from a first point in time to a second point in time based on historical information. The first point in time may be a past point in time. Additionally, the second point in time may be the present point in time. The past point in time may be a point in time prior to a preset time from the present point in time.

[0224] In addition, the processor (133) can identify a range to which the identified number of times belongs among multiple ranges, and identify that the ratio corresponding to the identified range is a ratio corresponding to the area. In this case, information regarding the ratio corresponding to each of the multiple ranges can be stored in the memory (132).

[0225] For example, the ratio corresponding to the first range may be 1:N1, the ratio corresponding to the second range may be 1:N2, and the ratio corresponding to the third range may be 1:N3. In this case, the lower limit of the first range may be greater than or equal to the upper limit of the second range. In addition, the lower limit of the second range may be greater than or equal to the upper limit of the third range. And, N3 <N2<N1이다.

[0226] In this case, if the identified number of times falls within the first range, the processor (133) can identify that the ratio corresponding to the area is 1:N1. In addition, if the identified number of times falls within the second range, the processor (133) can identify that the ratio corresponding to the area is 1:N2. In addition, if the identified number of times falls within the third range, the processor (133) can identify that the ratio corresponding to the area is 1:N3.

[0227] In an embodiment, the robot cleaner (100) can perform an operation of detecting liquid in the first mode.

[0228] The first mode may include a mode in which the ratio between the number of times the robot cleaner (100) performs an operation to acquire depth information and the number of times the robot cleaner (100) performs an operation to detect liquid is a fixed value. When the mode of the robot cleaner (100) is the first mode, the robot cleaner (100) may identify a ratio corresponding to an area in which the robot cleaner (100) is located, and perform an operation to acquire depth information and an operation to detect liquid based on the identified ratio.

[0229] And, when liquid is detected while the robot cleaner (100) is performing an operation to detect liquid in the first mode, the mode of the robot cleaner (100) can be changed to the second mode.

[0230] The second mode may include a mode in which the ratio between the number of times the robot cleaner (100) performs an operation to acquire depth information and the number of times the robot cleaner performs an operation to detect liquid is changed depending on the distance between the robot cleaner (100) and the liquid.

[0231] In this case, the ratio can be adjusted so that the closer the robot cleaner (100) gets to the liquid, the more liquid-detecting operations are performed, and the farther the robot cleaner (100) gets from the liquid, the less liquid-detecting operations are performed.

[0232] When the robot cleaner (100) moves in the direction of the liquid, the robot cleaner (100) may get closer to the liquid. The processor (133) may adjust the ratio so that the robot cleaner (100) performs more liquid-detecting operations as the robot cleaner (100) gets closer to the liquid. In addition, when the robot cleaner (100) moves in the opposite direction to the liquid, the robot cleaner (100) may move away from the liquid. The processor (133) may adjust the ratio so that the robot cleaner (100) performs less liquid-detecting operations as the robot cleaner (100) gets farther away from the liquid.

[0233] When liquid is detected in front of the robot cleaner (100), the processor (133) can identify the distance between the detected liquid and the robot cleaner (100). For example, the processor (133) can identify the distance between the robot cleaner (100) and the liquid using an IR image.

[0234] And, the processor (133) can identify the ratio based on the distance between the robot cleaner (100) and the liquid.

[0235] For example, the memory (132) may store ratio values ​​corresponding to each of a plurality of distance ranges between the robot cleaner (100) and the liquid in each of a plurality of areas. In this case, the ratio values ​​corresponding to the distance ranges may be stored in the memory (132) in the form of a lookup table.

[0236] For example, the plurality of regions may include a first region, a second region, and a third region.

[0237] In the memory (132), a plurality of ratio values ​​corresponding to a plurality of distance ranges may be stored when the robot cleaner (100) is in the first area. For example, in the memory (132), a ratio value (1:N) corresponding to a distance range in which the distance between the robot cleaner (100) and the liquid is less than d1 and greater than d2 1,1 ), a ratio value (1:N) corresponding to a distance range where the distance between the robot cleaner (100) and the liquid is less than d2 and greater than d3 1,2 ),..., the distance between the robot cleaner (100) and the liquid is d n-1 smaller than d n The ratio value corresponding to the ideal distance range (1:N) 1,n-1 ) can be stored. n is a natural number greater than 1, and d n <d n-1 <... <d2<d1이다. 그리고, N 1,1 <N 1,2 <... <N 1,n-2 <N 1,n-1 am.

[0238] In the memory (132), a plurality of ratio values ​​corresponding to a plurality of distance ranges may be stored when the robot cleaner (100) is in the second area. For example, in the memory (132), a ratio value (1:N) corresponding to a distance range in which the distance between the robot cleaner (100) and the liquid is less than d1 and greater than d2 2,1 ), a ratio value (1:N) corresponding to a distance range where the distance between the robot cleaner (100) and the liquid is less than d2 and greater than d3 2,2 ),..., the distance between the robot cleaner (100) and the liquid is d n-1 smaller than d n The ratio value corresponding to the ideal distance range (1:N) 2,n-1 ) can be stored. n is a natural number greater than 1, and d n <d n-1 <... <d2<d1이다. 그리고, N 2,1 <N 2,2 <... <N 2,n-2 <N 2,n-1 am.

[0239] In the memory (132), a plurality of ratio values ​​corresponding to a plurality of distance ranges may be stored when the robot cleaner (100) is in the third area. For example, in the memory (132), a ratio value (1:N) corresponding to a distance range in which the distance between the robot cleaner (100) and the liquid is less than d1 and greater than d2 3,1 ), a ratio value (1:N) corresponding to a distance range where the distance between the robot cleaner (100) and the liquid is less than d2 and greater than d3 3,2 ),..., the distance between the robot cleaner (100) and the liquid is d n-1 smaller than d n The ratio value corresponding to the ideal distance range (1:N) 3,n-1 ) can be stored. n is a natural number greater than 1, and d n <d n-1 <... <d2<d1이다. 그리고, N 3,1 <N 3,2 <... <N 3,n-2 <N 3,n-1 am.

[0240] The processor (133) can identify a distance range to which the distance between the robot cleaner (100) and the liquid belongs among a plurality of distance ranges, and can identify a ratio value corresponding to the identified distance range as a ratio between the number of times the robot cleaner (100) performs an operation to acquire depth information and the number of times the robot cleaner (100) performs an operation to detect the liquid.

[0241] For example, when liquid is detected in front of the robot cleaner (100) and the robot cleaner (100) moves forward, the distance between the robot cleaner (100) and the liquid may gradually decrease. In this case, the processor (133) may adjust the ratio so that the robot cleaner (100) performs more liquid detection operations as the robot cleaner (100) gets closer to the liquid.

[0242] When the robot cleaner (100) is identified as being in proximity to a liquid, it can avoid the liquid. For example, when the robot cleaner (100) is identified as being in proximity to a liquid, it can change its direction of travel and move in the opposite direction along a path that is a predetermined distance from the path that the robot cleaner (100) has already traveled. When the robot cleaner (100) moves in the opposite direction from the direction in which the liquid is detected, the distance between the robot cleaner (100) and the liquid can gradually increase. In this case, the processor (133) can adjust the ratio so that the robot cleaner (100) performs the liquid detection operation less frequently as the robot cleaner (100) moves away from the liquid.

[0243] Thereafter, the robot cleaner (100) may change its driving direction again and move in the direction where the liquid is detected along a path that is a certain distance from the path that the robot cleaner (100) has passed. As the robot cleaner (100) moves in the direction where the liquid is detected, the distance between the robot cleaner (100) and the liquid may gradually decrease. In this case, the processor (133) may adjust the ratio so that the robot cleaner (100) performs the operation of detecting the liquid more as the robot cleaner (100) gets closer to the liquid.

[0244] In this way, the robot cleaner (100) performs a liquid detection operation while performing a cleaning operation by repeating a zigzag pattern of movement, and when liquid is detected, the rate at which the liquid detection operation is performed can be adjusted according to the distance between the robot cleaner (100) and the liquid.

[0245] For example, referring to FIG. 15, the robot cleaner (100) may perform a cleaning operation while moving in a zigzag pattern while positioned in the first area. At this time, the robot cleaner (100) may perform an operation of detecting depth and an operation of detecting liquid based on a ratio corresponding to the first area, 1:N1.

[0246] The robot cleaner (100) can detect liquid (1). In this case, when the robot cleaner (100) moves in the direction where the liquid (1) is (①, ③ of FIG. 15), the robot cleaner (100) moves 1:N according to the distance between the robot cleaner (100) and the liquid (1). 1,1 , 1:N 1,2 ,...,1:N 1,n-2 , 1:N 1,n-1 The ratio between the number of times the motion for acquiring depth information is performed and the number of times the liquid is detected can be gradually adjusted. In addition, when the robot cleaner (100) moves in the opposite direction of the liquid (1) (② of FIG. 15), the ratio between the robot cleaner (100) and the liquid (1) is 1:N. 1,n-1 , 1:N 1,n-2 ,...,1:N1,2 ,1:N 1,1 The ratio between the number of times the action of acquiring depth information is performed and the number of times the liquid is detected can be gradually adjusted.

[0247] In this case, N 1,1 <N 1,2 <... <N 1,n-2 <N 1,n-1 In the embodiment, the closer the robot cleaner (100) gets to the liquid, the more it performs the liquid detection operation, thereby effectively detecting the liquid.

[0248] As described above, the IR receiver (112) may include one or more IR cameras. For example, the IR receiver (112) may include a left IR camera and a right IR camera. The left IR camera is a camera positioned in the left area of ​​the front of the body of the robot cleaner (100). The right IR camera is a camera positioned in the right area of ​​the front of the body of the robot cleaner (100).

[0249] When performing an operation to detect liquid, the processor (133) may perform photography using only one of the two IR cameras. For example, the processor (133) may perform photography using the left IR camera among the two IR cameras, or may perform photography using the right IR camera among the two IR cameras.

[0250] In an embodiment, when performing a liquid detection operation, the processor (133) may perform photography using two IR cameras alternately. In this case, the processor (133) may perform photography using one IR camera per cycle. For example, the processor (133) may perform photography using the left IR camera during one cycle, and perform photography using the right IR camera during the next cycle. Additionally, the processor (133) may perform photography using two IR cameras alternately throughout the entire cycle.

[0251] In an embodiment, when a liquid is detected while the processor (133) is performing an operation to detect a liquid, the processor (133) may perform a photographing operation using an IR camera corresponding to the direction in which the liquid is detected among the two IR cameras.

[0252] For example, when liquid is detected at the front right side of the robot cleaner (100), the processor (133) may perform photography using the right IR camera. In this case, the processor (133) may perform photography using the right IR camera until the robot cleaner (100) approaches the liquid. Then, when the robot cleaner (100) moves to avoid the liquid or moves in the opposite direction of the liquid, the processor (133) may perform photography using one of the two IR cameras or using the two IR cameras alternately in the same manner as before using the right IR camera.

[0253] In an embodiment, when liquid is detected at the front left side of the robot cleaner (100), the processor (133) may perform photography using the left IR camera. In this case, the processor (133) may perform photography using the left IR camera until the robot cleaner (100) approaches the liquid. Then, when the robot cleaner (100) moves to avoid the liquid or moves in the opposite direction of the liquid, the processor (133) may perform photography using one of the two IR cameras or using the two IR cameras alternately in the same manner as before using the left IR camera.

[0254] For example, referring to FIG. 16a, when the robot cleaner (100) performs an operation to detect a liquid (1), it can perform a photographing operation using the left IR camera (1611) among the two IR cameras (1611, 1612). At this time, as in FIG. 16b, the robot cleaner (100) can detect the liquid (1) at the front right side of the robot cleaner (100). In this case, when the robot cleaner (100) performs an operation to detect a liquid, it can perform a photographing operation using the right IR camera (1612) among the two IR cameras (1611, 1612).

[0255] In an embodiment, the robot cleaner (100) can perform an operation of detecting liquid using an IR camera corresponding to the direction in which the liquid is detected. Accordingly, liquid on the floor can be effectively detected.

[0256] FIG. 17 is a block diagram of a robot vacuum cleaner according to an embodiment of the present disclosure.

[0257] Referring to FIG. 17, the robot cleaner (100) may include a sensor (110), a driving unit (120), a main module (130), a cleaning device (140), an input interface (150), and an output interface (160). The configuration of the robot cleaner (100) illustrated in FIG. 17 is merely an example, and it is to be understood that new configurations may be added or some configurations may be omitted depending on the embodiment. A detailed description of configurations that overlap with those illustrated in FIG. 2 among the configurations illustrated in FIG. 17 will be omitted.

[0258] The sensor (110) can detect structures or objects in a space. The information obtained from the sensor (110) can be used to create a map of the space. In an embodiment, the sensor (110) can detect liquid on the floor.

[0259] The sensor (110) may include a depth sensor (113) and a second IR light source (111).

[0260] Additionally, the sensor (110) may include at least one of a light detection and ranging (LiDAR) sensor (115), an obstacle detection sensor (116), a driving detection sensor (117), and a camera (118).

[0261] The lidar sensor (115) outputs a laser in a 360-degree direction, and when the laser reflected from an object is received, the difference in time taken for the laser to reflect from the object and return, and the signal intensity of the received laser, etc. are analyzed to obtain geometry information about the space. The geometry information may include the position, distance, direction, etc. of the object. The lidar sensor (115) may provide the obtained geometry information to the processor (133).

[0262] The obstacle detection sensor (116) can detect objects around the robot cleaner (100). For example, the obstacle detection sensor (116) can include at least one of an ultrasonic sensor, an IR sensor, an RF (radio frequency) sensor, a geomagnetic sensor, and a PSD (Position Sensitive Device) sensor. The obstacle detection sensor (116) can detect objects existing in front, behind, on the side, or on the movement path of the robot cleaner (100). The obstacle detection sensor (116) can provide information about the detected object to the processor (133).

[0263] The driving detection sensor (117) can detect the driving of the robot cleaner (100). For example, the driving detection sensor (117) can include at least one of a gyro sensor, a wheel encoder, and an acceleration sensor. The gyro sensor can detect the rotation direction and rotation angle of the robot cleaner (100). The wheel encoder can detect the number of rotations of the wheels of the robot cleaner (100). The acceleration sensor can detect changes in the speed of the robot cleaner (100). The driving detection sensor (117) can provide detected driving information to the processor (133).

[0264] The camera (118) can capture images of the surroundings of the robot vacuum cleaner (100). For example, the camera (118) can include an RGB camera.

[0265] The cleaning device (140) may include a device for cleaning the floor. For example, the cleaning device (140) may include a cleaning module for sweeping dust from the floor and sucking up dust. In an embodiment, the cleaning device (140) may include a mop module for performing mopping. The sucked up foreign substances may be accommodated in a dust bin provided in the robot cleaner (100). The processor (133) may control the cleaning device (140) to suck up foreign substances from the floor and perform mopping cleaning while the robot cleaner (100) is stationary or moving. Accordingly, the robot cleaner (100) may clean a space.

[0266] The input interface (150) includes circuitry. The input interface (150) can receive user input and transmit the user input to the processor (133). For example, the input interface (150) can receive various user inputs for setting or selecting various functions supported by the robot cleaner (100).

[0267] The input interface (150) may include various types of input devices.

[0268] In one example, the input interface (150) may include a physical button. The physical button may include a function key or a dial button. The physical button may also be implemented as one or more keys.

[0269] In one example, the input interface (150) can receive user input using a touch method. For example, the input interface (150) can be implemented as a touch screen capable of performing the function of a display (161).

[0270] For example, the input interface (150) may receive a voice signal using a microphone. The processor (133) may perform a function corresponding to the voice signal. For example, the processor (133) may convert the voice signal into text data, obtain control command data corresponding to the voice signal based on the text data, and perform a function corresponding to the control command data.

[0271] The output interface (160) may include a display (161) and a speaker (162).

[0272] The display (161) can display various screens. The processor (133) can display various notifications, messages, information, etc. related to the operation of the robot cleaner (100) on the display (161).

[0273] The display (161) may be implemented as a display including a self-luminous element or a display including a non-luminous element and a backlight. For example, the display (161) may be implemented as various types of displays such as an LCD (Liquid Crystal Display), an OLED (Organic Light Emitting Diodes) display, an LED (Light Emitting Diodes) display, a micro LED display, a Mini LED display, a QLED (Quantum dot light-emitting diodes) display, etc.

[0274] The speaker (162) can output audio signals. The processor (133) can output warning sounds, notification messages, response messages corresponding to user input, etc. related to the operation of the robot cleaner (100) through the speaker (162).

[0275] The processor (133) can create a map of a space using information acquired through the sensor (110). The map can be created during the initial exploration of the space. For example, the processor (133) can explore the space using the lidar sensor (115), acquire topographic information about the space, and create a map of the space using the topographic information.

[0276] The map may include a grid map. A grid map is a map that divides space into cells of a certain size and expresses them. For example, a grid map may be a map that divides space into a plurality of cells of a predetermined size and indicates the presence or absence of an object in each cell. The plurality of cells may be divided into cells without objects (e.g., cells in which a robot cleaner (100) can drive) (free space) and cells in which objects exist (occupied space). A line connecting cells occupied by objects may represent a boundary of the space (e.g., an object, etc.).

[0277] The processor (133) can identify the location of the robot cleaner (100) on the map using SLAM (Simultaneous Localization and Mapping). For example, the processor (133) can obtain spatial topographic information using a lidar sensor (115), compare the obtained topographic information with pre-stored topographic information, or compare the obtained topographic information to identify the location of the robot cleaner (100) on the map. However, the present disclosure is not limited thereto, and the processor (133) can identify the location of the robot cleaner (100) on the map through SLAM using a camera (118).

[0278] The processor (133) can control the movement of the robot cleaner (100) using information acquired through the sensor (110).

[0279] For example, the processor (133) can control the driving unit (120) to allow the robot cleaner (100) to drive in space using a map stored in the memory (132). In addition, the processor (133) can obtain information using the sensor (110) while the robot cleaner (100) drives in space, and can detect objects around the robot cleaner (100) using the obtained information. When an object is detected, the processor (133) can control the driving unit (120) to allow the robot cleaner (100) to drive while avoiding the object.

[0280] In an embodiment, the processor (133) can identify driving information such as the moving speed of the robot cleaner (100) and the distance traveled by the robot cleaner (100) using information acquired by the sensor (110), and update the location of the robot cleaner (100) on the map based on the driving information.

[0281] Additionally, when liquid on the floor is detected, the processor (133) can control the robot cleaner (100) to move while avoiding the liquid or to clean the liquid and then move. In this case, when the robot cleaner (100) cleans the liquid, the processor (133) can control the driving unit (120) to clean the liquid using a mop or the like of the cleaning device (140) and to move the robot cleaner (100) past the area where the liquid was removed.

[0282] In an embodiment, the processor (133) can identify the type of liquid using an image acquired through the camera (118).

[0283] The type of liquid may be determined based on the color of the liquid. For example, if the color of the liquid is the same as the color of the ground surrounding the liquid, the processor (133) may identify the liquid as water. In an embodiment, if the color of the liquid is different from the color of the ground surrounding the liquid, the processor (133) may identify the liquid as not water. In this case, the same color may include a difference in RGB values ​​within a preset value, and a different color may include a difference in RGB values ​​exceeding a preset value.

[0284] For example, the processor (133) can match an IR image acquired through the IR receiver (112) with an image acquired through the camera (118).

[0285] According to one example, the processor (133) can identify the floor from an IR image acquired through the IR receiver (112) and identify the floor from an image acquired through the camera (118). Then, the processor (133) can match the IR image acquired through the IR receiver (112) and the image acquired through the camera (118) so that the floors are matched to each other based on the positions of the identified floors.

[0286] The processor (133) can identify an area in the image at the same location as an area containing liquid identified in the IR image based on the matched IR image and the image, and can identify that liquid is present in the area identified in the image. In an embodiment, the processor (133) can identify whether the liquid is water by comparing the colors of the area containing liquid and the surrounding area based on the RGB values ​​of the area containing liquid and the surrounding area in the image.

[0287] In one example, the processor (133) can input an image acquired through the camera (118) into an artificial intelligence model to identify the type of liquid.

[0288] An artificial intelligence model may be stored in the memory (132). The artificial intelligence model may include a neural network model trained to predict the type of liquid in an image. The artificial intelligence model may include a neural network model configured with model parameters trained by applying images as input data and applying the type of liquid contained in the images as an output correct value. The processor (133) inputs the image to the artificial intelligence model, obtains information about the type of liquid contained in the image from the artificial intelligence model, and can identify whether the liquid is water based on the information about the type of liquid.

[0289] The processor (133) can identify whether the robot cleaner (100) will perform cleaning or avoidance driving for the liquid based on the type of liquid.

[0290] For example, if the type of the mop is a panning type and the liquid is water, the processor (133) can identify that the robot cleaner (100) performs a cleaning operation for the liquid, and if the type of the mop is a panning type and the liquid is not water, the processor (133) can identify that the robot cleaner (100) performs an avoidance operation for the liquid.

[0291] FIG. 18 is a flowchart of a liquid detection method of a robot according to an embodiment of the present disclosure.

[0292] In Action S1810, the robot vacuum cleaner can move through space.

[0293] In operation S1820, the robot cleaner may output IR light using an IR light source while moving through a space, and when the IR light is reflected by an object and received by an IR receiver, the robot cleaner may perform an operation of detecting liquid on the floor around the robot cleaner based on the received IR light. In this case, the robot cleaner may perform an operation of detecting liquid in a first mode, and when liquid is detected, the robot cleaner may change its mode to a second mode and perform an operation of detecting the liquid in the second mode.

[0294] Here, the first mode may be a mode in which the operation of detecting the liquid is performed based on a specific cycle, and the second mode may be a mode in which the cycle of the operation of detecting the liquid is changed according to the distance between the robot cleaner and the liquid.

[0295] In operation S1820, the robot cleaner outputs IR light to the front of the robot cleaner using an IR light source, photographs the front of the robot cleaner using an IR receiver, obtains an IR image using the received IR light, and can identify whether there is liquid on the floor in front of the robot cleaner based on the IR image.

[0296] In operation S1820, when the mode of the robot cleaner is changed to the second mode, the robot cleaner may identify the distance between the robot cleaner and the liquid based on the received IR light, identify the cycle of the operation for detecting the liquid in the second mode based on the distance between the robot cleaner and the liquid, and perform an operation for detecting the liquid based on the identified cycle. In this case, the cycle of the second mode may have a smaller value as the distance between the robot cleaner and the liquid becomes closer.

[0297] In an embodiment, the cycle in which the robot cleaner performs the operation of detecting liquid in the second mode may be shorter than the cycle in which the robot cleaner performs the operation of detecting liquid in the first mode.

[0298] In operation S1820, when the robot cleaner performs a cleaning operation for a liquid, the robot cleaner performs cleaning for the liquid, and when the cleaning for the liquid is completed, the robot cleaner can perform an operation of detecting the liquid based on the currently set cycle in the second mode.

[0299] In operation S1820, the robot cleaner can change the mode of the robot cleaner to the first mode and perform an operation of detecting liquid in the first mode after the robot cleaner moves a preset distance after completing cleaning for the liquid.

[0300] In operation S1820, when the robot cleaner performs an avoidance operation for a liquid, the robot cleaner maintains the currently set cycle in the second mode while changing the driving direction, and when the robot cleaner changes the driving direction and moves away from the liquid, the mode of the robot cleaner can be changed to the first mode and an operation for detecting the liquid can be performed in the first mode.

[0301] In operation S1820, when the driving direction of the robot cleaner, which was moving away from the liquid, changes and the robot cleaner moves toward the liquid, the robot cleaner can change the mode of the robot cleaner to a second mode based on the distance between the robot cleaner and the liquid, and perform an operation of detecting the liquid in the second mode.

[0302] In operation S1820, the robot cleaner identifies a distance between the robot cleaner and the liquid while the robot cleaner moves toward the liquid along a path that is a predetermined distance from the path along which the robot cleaner moves in a direction away from the liquid, and if the identified distance is a preset distance, the mode of the robot cleaner can be changed to a second mode.

[0303] In an embodiment, a neural network model refers to an artificial intelligence model including a neural network and can be trained by deep learning. The neural network may include, for example, at least one of a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a generative adversarial network (GAN), and a deep Q-network. However, the neural network model is not limited to the examples described above.

[0304] Various embodiments of the present disclosure may be implemented in a computer-readable recording medium using software, hardware, or a combination thereof, or a computer or similar device. In some cases, the embodiments described herein may be implemented by the processor itself. In a software implementation, embodiments, such as the procedures and functions described in the present disclosure, may be implemented as separate software codes. Each of the software codes may perform one or more of the functions and operations described in the present disclosure.

[0305] Computer instructions for performing processing operations of an electronic device according to various embodiments of the present disclosure described above may be stored in a non-transitory computer-readable medium. When the computer instructions stored in such a non-transitory computer-readable medium are executed by a processor of a specific device, the computer instructions cause the specific device to perform processing operations in a robot cleaner (100) according to various embodiments described above.

[0306] A non-transitory computer-readable medium refers to a medium that permanently stores data and can be read 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 non-transitory computer-readable media include CDs, DVDs, hard disks, Blu-ray discs, USBs, memory cards, and ROMs.

[0307] Although the preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above, and various modifications may be made by a person having ordinary skill in the art to which the present disclosure pertains without departing from the gist of the present disclosure in the claims, and such modifications should not be understood individually from the technical idea or prospect of the present disclosure.

Claims

1. In robot vacuum cleaners, IR(infrared ray) light source; IR receiver; driving unit; and operatively connected to the above IR light source, the IR receiver and the driver, Control the driving unit so that the robot cleaner moves through space, While the above robot cleaner moves through space, it outputs IR light using the IR light source, One or more processors that perform an operation of detecting liquid on the floor around the robot cleaner based on IR light reflected by an object and received by the IR receiver; One or more of the above processors, In the first mode, an operation for detecting the liquid is performed, and when the liquid is detected, the mode of the robot cleaner is changed to the second mode, and an operation for detecting the liquid is performed in the second mode. In the above first mode, the operation of detecting the liquid is performed based on a specific cycle, A robot cleaner, wherein in the second mode, the cycle of the operation of detecting the liquid is changed based on the distance between the robot cleaner and the liquid.

2. In paragraph 1, One or more of the above processors, A robot cleaner that outputs IR light to the front of the robot cleaner using the IR light source, photographs the front of the robot cleaner using the IR receiver, obtains an IR image using the received IR light, and identifies whether there is liquid on the floor in front of the robot cleaner based on the IR image.

3. In paragraph 2, One or more of the above processors, When the mode of the robot cleaner is changed to the second mode, the distance between the robot cleaner and the liquid is identified based on the received IR light, Identifying the cycle of the operation of detecting the liquid in the second mode based on the distance between the robot cleaner and the liquid, An operation of detecting the liquid is performed based on the identified cycle, A robot cleaner wherein the period of the second mode becomes shorter as the distance between the robot cleaner and the liquid decreases.

4. In paragraph 3, A robot cleaner wherein a cycle in which the robot cleaner performs an operation to detect the liquid in the second mode is shorter than a cycle in which the robot cleaner performs an operation to detect the liquid in the first mode.

5. In paragraph 3, One or more of the above processors, A robot cleaner that, when the robot cleaner performs a cleaning operation for the liquid, cleans the liquid, and when the cleaning for the liquid is completed, performs an operation of detecting the liquid based on a cycle set in the second mode.

6. In paragraph 5, One or more of the above processors, A robot cleaner which changes the mode of the robot cleaner to the first mode and performs an operation of detecting the liquid in the first mode when the robot cleaner moves a preset distance after completing cleaning of the liquid.

7. In paragraph 3, One or more of the above processors, When the robot cleaner performs avoidance driving for the liquid, the robot cleaner maintains the cycle set in the second mode while changing the driving direction, A robot cleaner, which changes the mode of the robot cleaner to the first mode and performs an operation of detecting the liquid in the first mode when the robot cleaner changes its driving direction and moves away from the liquid.

8. In paragraph 7, One or more of the above processors, A robot cleaner, which changes the mode of the robot cleaner to the second mode based on the distance between the robot cleaner and the liquid when the driving direction of the robot cleaner, which was moving away from the liquid, is changed so that the robot cleaner moves toward the liquid, and performs an operation of detecting the liquid in the second mode.

9. In paragraph 8, One or more of the above processors, When the robot cleaner moves toward the liquid along a path that is the same distance as the path it moved in the direction away from the liquid, the distance between the robot cleaner and the liquid is identified, A robot cleaner that changes the mode of the robot cleaner to the second mode if the identified distance is a preset distance.

10. A liquid detection method performed by a robot cleaner, The step of the above robot cleaner moving through space; A step of outputting IR light using an IR (infrared ray) light source while the robot cleaner moves through the space; and A step of performing an operation of detecting liquid on the floor around the robot cleaner based on IR light reflected by an object and received by an IR receiver; The step of performing the above liquid detection operation is: In the first mode, an operation for detecting the liquid is performed, and when the liquid is detected, the mode of the robot cleaner is changed to the second mode, and an operation for detecting the liquid is performed in the second mode. In the above first mode, the operation of detecting the liquid is performed based on a specific cycle, A liquid detection method in which, in the second mode, the cycle of the operation of detecting the liquid is changed based on the distance between the robot cleaner and the liquid.

11. In paragraph 10, The step of performing the above liquid detection operation is: A step of outputting the IR light toward the front of the robot cleaner using the IR light source; A step of photographing the front of the robot cleaner using the IR receiver and obtaining an IR image using the received IR light; and A liquid detection method, comprising: a step of identifying whether there is liquid on the floor in front of the robot cleaner based on the IR image; 12. In paragraph 11, The step of performing the above liquid detection operation is: When the mode of the robot cleaner is changed to the second mode, a step of identifying the distance between the robot cleaner and the liquid based on the received IR light; A step of identifying a cycle of an operation of detecting the liquid in the second mode based on the distance between the robot cleaner and the liquid; and A step of performing an operation of detecting the liquid based on the identified cycle; A liquid detection method in which the period of the second mode decreases as the distance between the robot cleaner and the liquid decreases.

13. In paragraph 12, A liquid detection method wherein a period in which the robot cleaner performs an operation to detect the liquid in the second mode is shorter than a period in which the robot cleaner performs an operation to detect the liquid in the first mode.

14. In paragraph 12, The step of performing the above liquid detection operation is: A liquid detection method comprising: a step of performing an operation of detecting a liquid based on a cycle set in the second mode when the robot cleaner performs a cleaning operation for the liquid, and when the cleaning for the liquid is completed; 15. In paragraph 14, The step of performing the above liquid detection operation is: A liquid detection method, comprising: a step of changing the mode of the robot cleaner to the first mode and performing an operation of detecting the liquid in the first mode when the robot cleaner moves a preset distance after completing cleaning of the liquid.

Images