A method of constructing a dirt map, a cleaning method of a cleaning robot, a cleaning robot, a medium, and a program product

Abstract

The application relates to a dirty map construction method, a cleaning method of a cleaning robot, the cleaning robot, a medium and a program product. The method comprises the following steps: obtaining pollution distribution information collected in the process that the cleaning robot performs a patrol task; updating an original map according to the pollution distribution information to obtain a pollution distribution map; the pollution distribution map comprises a pollution type and a pollution position; and finally, the pollution distribution map is sent to a user terminal to instruct the user terminal to display the pollution distribution map. The user can remotely and intuitively check the specific type of the pollution and the distribution position of the pollution in the environment through the terminal, the use convenience and the interaction experience are improved, and the cleaning effect and the cleaning efficiency of the dirty area are improved.

Description

Technical Field

[0001] This application relates to the field of cleaning robot technology, and in particular to a method for constructing a dirt map, a cleaning method for a cleaning robot, a cleaning robot, media, and program products. Background Technology

[0002] With the rapid development of artificial intelligence and home service robot technology, smart home devices, especially cleaning robots, have gradually become common terminals in modern home environments. Currently, when performing cleaning tasks, cleaning robots typically perform full-coverage cleaning or partial cleaning of preset room areas based on a room layout map.

[0003] However, the aforementioned cleaning robots have the problem of poor cleaning performance. Summary of the Invention

[0004] Therefore, it is necessary to provide a method for constructing a dirt map that can improve cleaning effectiveness, a cleaning method for a cleaning robot, a cleaning robot, media, and program products to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for constructing a dirty map, the method comprising:

[0006] Acquire information on the distribution of pollutants collected by the cleaning robot during its inspection tasks;

[0007] The original map is updated based on the pollutant distribution information to obtain a pollutant distribution map; the pollutant distribution map includes pollutant types and pollutant locations;

[0008] The pollutant distribution map is sent to the user terminal to instruct the user terminal to display the pollutant distribution map.

[0009] In some embodiments, the method further includes:

[0010] When the cleaning robot meets the preset inspection conditions, control the cleaning robot to perform the inspection task;

[0011] The preset inspection conditions include: the time interval between the current time and the end time of the previous inspection reaches a preset time threshold, and / or the current time is within a preset time period.

[0012] In some embodiments, the method further includes:

[0013] When the current time falls within a preset time period, control the cleaning robot to perform inspection tasks in preset areas; the preset areas include the kitchen area and the dining area.

[0014] In some embodiments, the method further includes the following during the inspection task performed by the cleaning robot:

[0015] The cleaning robot is controlled to move to multiple pre-set patrol points, where it detects pollutants and obtains information on pollutant distribution.

[0016] In some embodiments, pollutant detection is performed at each patrol point to obtain pollutant distribution information, including:

[0017] At each patrol point, the cleaning robot is controlled to rotate its main unit and / or its camera to obtain information on the distribution of pollutants.

[0018] In some embodiments, the original map is updated based on pollutant distribution information to obtain a pollutant distribution map, including:

[0019] Extract pollutant types and locations from pollutant distribution information;

[0020] Based on the location of pollutants, visual markers of pollutant types are added to the corresponding locations on the original map to obtain a pollutant distribution map; pollutant types include liquid pollutants and solid pollutants.

[0021] In some embodiments, the contaminant type also includes feces.

[0022] In some embodiments, a visual identifier for the type of pollutant is added to the corresponding location on the original map, including:

[0023] Pollutants of the same type in adjacent areas are merged to obtain the merged pollutants;

[0024] Add a visual identifier for the merged pollutant type to the corresponding location on the original map.

[0025] In some embodiments, a visual identifier for the type of pollutant is added to the corresponding location on the original map, including:

[0026] The pollutants in the pollutant distribution map are screened according to preset screening conditions to obtain the screened pollutants; wherein, the preset screening conditions include the area of ​​the pollutant being greater than a preset area threshold, and / or, when the pollutant is a solid particle, the number of solid particles being greater than a preset number threshold.

[0027] Add visual markers for the filtered pollutant types to the corresponding locations on the original map.

[0028] In some embodiments, the method further includes the following during the inspection task performed by the cleaning robot:

[0029] If an unknown area that is not marked on the original map is detected, and it is determined that the unknown area can be entered, the cleaning robot is controlled to collect map information of the unknown area and add the map information of the unknown area to the original map.

[0030] In some embodiments, the method further includes:

[0031] Given a pollutant distribution map, obtain pollutant distribution information in unknown areas and add the pollutant distribution information to the pollutant distribution map.

[0032] Secondly, this application also provides a cleaning method for a cleaning robot, the method comprising:

[0033] The method for constructing a dirt map of any instance in the first aspect yields a pollutant distribution map; the pollutant distribution map includes pollutant type and pollutant location.

[0034] Determine the cleaning strategy based on the type of pollutant, and control the cleaning robot to perform the cleaning task according to the cleaning strategy.

[0035] In some embodiments, the contaminant types include liquid contaminants and solid contaminants, and a cleaning strategy is determined based on the contaminant type, including:

[0036] Cleaning should be carried out in descending order of cleaning priority; solid contaminants have a higher cleaning priority than liquid contaminants.

[0037] In some embodiments, the contaminant type also includes feces, and a cleaning strategy is determined based on the contaminant type, including:

[0038] The area containing feces is marked as the last area to be cleaned, a separate area to be cleaned, or a designated area to be cleaned; the designated area to be cleaned is used to prompt the user to clean the feces manually.

[0039] Thirdly, this application also provides an apparatus for constructing a dirt map, the apparatus comprising:

[0040] The information acquisition module is used to acquire information on the distribution of pollutants collected by the cleaning robot during its inspection tasks.

[0041] The map update module is used to update the original map based on pollutant distribution information to obtain a pollutant distribution map; the pollutant distribution map includes pollutant type and pollutant location;

[0042] The map sending module is used to send the pollutant distribution map to the user terminal, so that the user terminal can display the pollutant distribution map.

[0043] Fourthly, this application also provides a cleaning device for a cleaning robot, the device comprising:

[0044] The map acquisition module is used to acquire the pollutant distribution map obtained by the method for constructing the dirt map of any instance in the first aspect; the pollutant distribution map includes pollutant type and pollutant location;

[0045] The cleaning module is used to determine the cleaning strategy based on the type of contaminant and control the cleaning robot to perform cleaning tasks according to the cleaning strategy.

[0046] Fifthly, this application also provides a cleaning robot, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the method in any of the embodiments of the first to second aspects described above.

[0047] In a sixth aspect, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method of any of the embodiments of the first to second aspects described above.

[0048] In a seventh aspect, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the method in any of the embodiments of the first to second aspects described above.

[0049] The aforementioned method for constructing a dirt map, the cleaning method of a cleaning robot, the cleaning robot, media, and program products involve acquiring pollutant distribution information collected by the cleaning robot during its inspection tasks. This information is then used to update the original map, resulting in a pollutant distribution map. The map includes pollutant types and locations. Finally, the map is sent to the user terminal to instruct it to display the pollutant distribution map. In this method, the cleaning robot can autonomously collect pollutant distribution information during inspections and integrate this information into the original map in real time, generating a visualized pollutant distribution map that is pushed to the user terminal. Users can remotely and intuitively view the specific types of pollutants and their distribution locations in the environment through their terminals, thereby gaining timely insight into the pollution status of the cleaned area and improving ease of use and interactive experience. Furthermore, because the pollutant distribution map includes both pollutant type and location information, users can accurately identify which areas contain which types of pollutants, allowing for more targeted scheduling of subsequent cleaning tasks. This avoids missed or repeated ineffective cleaning due to a lack of pollutant distribution information, ultimately improving the cleaning effect and efficiency of dirty areas. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 These are internal structural diagrams of the cleaning robot in some embodiments;

[0052] Figure 2 This is one of the flowcharts illustrating the method for constructing a dirt map in some embodiments;

[0053] Figure 3 This is a second flowchart illustrating the method for constructing a dirt map in some embodiments;

[0054] Figure 4 This is the third flowchart illustrating the method for constructing a dirt map in some embodiments;

[0055] Figure 5 This is the fourth flowchart illustrating the method for constructing a dirt map in some embodiments;

[0056] Figure 6 This is the fifth flowchart illustrating the method for constructing a dirt map in some embodiments;

[0057] Figure 7 This is a structural block diagram of a device for constructing a dirt map in some embodiments;

[0058] Figure 8 This is a structural block diagram of the cleaning device of the cleaning robot in some embodiments. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more, and other quantifiers are similar. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The term "and / or" used in this application refers to one of the solutions, or any combination of multiple solutions. In the embodiments of this application, the term "at least one" means one or more.

[0061] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0062] With the rapid development of artificial intelligence and home service robot technology, smart home devices, especially cleaning robots, have gradually become common terminals in modern home environments. Currently, when performing cleaning tasks, cleaning robots typically perform full-coverage cleaning based on a room layout map or partial cleaning of preset room areas. However, these cleaning robots suffer from poor cleaning performance.

[0063] In view of this, this application proposes a method for constructing a dirt map, a cleaning method for a cleaning robot, a cleaning robot, media, and program products. The cleaning robot can autonomously collect the distribution of pollutants during inspections and integrate the pollutant information into the original map in real time, generating a visualized pollutant distribution map that is pushed to the user terminal. Users can remotely and intuitively view the specific types of pollutants and their distribution locations in the environment through their terminals, thereby understanding the pollution status of the cleaned area in a timely manner, improving ease of use and interactive experience, and thus helping to improve the cleaning effect and efficiency of dirty areas.

[0064] It should be noted that the beneficial effects or technical problems solved by the embodiments of this application are not limited to this one, but may also be other implicit or related problems. For details, please refer to the description of the embodiments below.

[0065] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0066] In some embodiments, the method for constructing a dirt map and the cleaning method for a cleaning robot provided in this application can be applied to, for example... Figure 1 The internal structure diagram of the cleaning robot shown can be as follows: Figure 1 As shown, the cleaning robot includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for constructing a dirt map and a cleaning method for the cleaning robot. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device for the cleaning robot can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the outer shell of the cleaning robot, or an external keyboard, touchpad, or mouse, etc.

[0067] Those skilled in the art will understand that Figure 1 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the cleaning robot to which the present application is applied. A specific cleaning robot may include more or fewer parts than shown in the figure, or combine certain parts, or have different part arrangements.

[0068] In some embodiments, such as Figure 2 As shown, a method for constructing a dirt map is provided, which can be applied to... Figure 1 Taking a cleaning robot as an example, the process includes the following steps:

[0069] S201, Obtain information on the distribution of pollutants collected by the cleaning robot during its inspection tasks.

[0070] Cleaning robots include, but are not limited to, sweeping robots, floor scrubbing robots, sweeping and mopping robots, lawnmowing robots, and snow removal robots. Pollutant distribution information refers to the pollution data identified by the cleaning robot after it perceives the ground environment in real time through its onboard sensors, including the type and location of pollutants. Inspection tasks refer to a working mode in which the cleaning robot moves within a preset area according to a preset path or patrol point to perform tasks such as security monitoring, regular inspections, environmental change detection, and home environment monitoring. In inspection task mode, the cleaning robot does not activate any cleaning mechanisms (such as roller brushes, side brushes, vacuum components, water pumps, and mopping components), but only acts as a mobile camera to collect environmental images, sensor data, and pollutant distribution information in real time. In other words, when cleaning is not required, the robot can act as a mobile monitoring terminal, enabling comprehensive inspection of the home or office area; when pollutants are detected and cleaning is required, the robot switches to cleaning mode and activates the corresponding cleaning mechanisms to perform sweeping, mopping, and other operations. This inspection task mode allows the robot to still perform environmental perception and monitoring functions during non-cleaning periods, avoiding the waste of idle hardware resources and improving the utilization rate of the robot.

[0071] In this embodiment, when the cleaning robot performs its inspection task, all cleaning components on its chassis, such as the roller brush, side brush, vacuum fan, water pump, and mopping assembly, remain off. Only the walking drive module and the contaminant detection module are activated. The contaminant detection module includes at least one of a camera, a lidar sensor, and a humidity sensor. The cleaning robot moves within a preset area according to a pre-set path or patrol point. During movement, the camera captures real-time ground images, which can be analyzed using a pre-trained classification model to identify the presence of large areas of liquid, particulate matter, or feces. The lidar assists in identifying areas of particulate matter accumulation by detecting differences in echo intensity. The humidity sensor detects areas of sudden humidity changes through contact or non-contact methods, assisting in identifying the presence of large areas of liquid. When a contaminant is identified, the cleaning robot determines its current pose using simultaneous localization and mapping (SLAM) technology and calculates the contaminant's coordinates in the map coordinate system based on sensor ranging data. The cleaning robot stores the type and coordinates of the contaminant as contaminant distribution information in its local cache.

[0072] S202, Update the original map based on the pollutant distribution information to obtain a pollutant distribution map; the pollutant distribution map includes pollutant type and pollutant location.

[0073] The original map refers to the map data about the preset area stored by the cleaning robot before performing this update. The original map can be in any of the following states: an initial blank map without any recorded environmental information; a geometric map containing only room layout, wall boundaries, and obstacle locations; an older map that already includes historical pollutant markers; or an incomplete map covering only a portion of the area and containing unmapped rooms. The pollutant distribution map is a new map generated by integrating the types and locations of pollutants identified during this inspection, based on the original map; it can also be called a dirt map. Pollutant types include liquid and solid pollutants, and may also include feces.

[0074] In this embodiment, the cleaning robot retrieves the original map from local storage or a preset storage location, and then updates it according to the content contained in the original map using an appropriate strategy, specifically including the following situations:

[0075] Scenario 1: When the original map is a blank map, during the cleaning robot's inspection, it uses LiDAR or visual sensors to perceive environmental boundaries, obstacles, and passable areas in real time, gradually constructing a geometric map of the preset area. During this construction process, each time a pollutant is identified, its type is converted into a corresponding visual marker: for example, large areas of liquid correspond to a blue water droplet icon, particulate matter to a small brown dot icon, and feces to a poop-shaped or brown icon. Based on the cleaning robot's current pose and sensor ranging data, the coordinates of the pollutant in the map coordinate system are calculated, and the corresponding icon is added at those coordinates. After the inspection, a pollutant distribution map is obtained, which includes both the room layout and pollutant markers.

[0076] Scenario 2: When the original map is a geometric structure map containing only the room layout, the cleaning robot directly reads this geometric structure map as the base map. Then, the type of each pollutant is converted into a corresponding visual label, and the location coordinates of the pollutants are mapped to the corresponding coordinate points on the base map, generating a marker icon at that location. The marker layer is stored independently of the base map layer, and finally, the pollutant distribution map is obtained by overlaying them.

[0077] Scenario 3: When the original map is an older version that already contains historical pollutant markers, the cleaning robot processes the pollutant markers according to a preset update strategy. The preset strategy includes at least one of the following: clearing all previous pollutant markers and regenerating the marker layer using the pollutant distribution information identified in the current inspection; merging newly identified pollutant markers with historical markers, covering the same location based on the current identification result, and retaining historical markers and adding new markers for different locations; based on the cleaning records, retaining only the pollutants in the historical markers that have not yet been processed (i.e., not cleaned), and overlaying them with newly identified pollutant markers. After the update is complete, a new pollutant distribution map is obtained.

[0078] Scenario 4: When the original map is incomplete (containing unmapped areas), during the inspection process, if the cleaning robot detects a passable unknown area outside the current map boundary using LiDAR, or visually identifies an unmapped room entrance, the cleaning robot will actively enter that area to explore and map it. The cleaning robot moves along the boundary of this area, constructing information about the walls, doorways, and obstacles of the new room in real time. It then stitches the newly constructed room boundary with the original map to obtain an expanded, complete original map. Finally, it adds markers for the pollutants identified in the new room to their corresponding locations, generating a pollutant distribution map containing the new room's information.

[0079] S203, send the pollutant distribution map to the user terminal to instruct the user terminal to display the pollutant distribution map.

[0080] The user terminal refers to an electronic device used by the user that has display and interactive functions, including but not limited to various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. The user terminal has an application (App) or mini-program installed to accompany the cleaning robot.

[0081] In this embodiment, the cleaning robot packages the generated pollutant distribution map into a data stream via a wireless communication module (including Wi-Fi, Bluetooth, or 4G / 5G networks) and sends it to the user terminal bound to the cleaning robot. Upon receiving the data stream, the user terminal displays the pollutant distribution map as a map in the APP interface. During display, the original map (or its extended version) serves as the background image, and pollutant markers are overlaid as icons at the corresponding coordinate positions. Different types of pollutants are distinguished using differentiated visual markers, and users can view detailed information about the pollutants through interactive operations. After the user clicks on any pollutant marker in the APP interface, a details window pops up, displaying the pollutant's type, location coordinates, discovery time, and recommended cleaning strategy.

[0082] Optionally, users can view details of contaminants in different areas through zooming, clicking, and other operations. For example, they can see which areas are clean, which areas are dirty (i.e., contain contaminants), and whether the dirt is concentrated in specific sub-areas (such as corners or under tables). Optionally, the cleaning robot can automatically send a contaminant distribution map after each inspection task, or respond to user queries initiated through the terminal by pushing the latest dirt map (i.e., contaminant distribution map) to the user's terminal. Optionally, the user terminal can also respond to the user's confirmation command for the contaminant distribution map by sending a cleaning task request to the cleaning robot or the cloud-based cleaning scheduling system. This request includes contaminant type and location information to instruct the cleaning robot to proceed to the marked location for targeted cleaning.

[0083] The method for constructing a dirt map provided in this application involves acquiring pollutant distribution information collected by a cleaning robot during its inspection tasks, updating the original map based on this information, and obtaining a pollutant distribution map. The pollutant distribution map includes pollutant types and locations. Finally, the pollutant distribution map is sent to a user terminal to instruct the user terminal to display the map. In this method, the cleaning robot can autonomously collect pollutant distribution information during inspections and integrate this information into the original map in real time, generating a visualized pollutant distribution map that is then pushed to the user terminal. Users can remotely and intuitively view the specific types of pollutants and their distribution locations in the environment through their terminals, thereby gaining timely insight into the pollution status of the cleaned area and improving ease of use and interactive experience. Furthermore, since the pollutant distribution map includes both pollutant type and location information, users can accurately identify which areas contain which types of pollutants, allowing for more targeted scheduling of subsequent cleaning tasks. This avoids missed or repeated ineffective cleaning due to a lack of information on pollutant distribution, thus contributing to improved cleaning effectiveness and efficiency in dirty areas.

[0084] In some embodiments, a method for controlling a cleaning robot to perform inspection tasks is also provided, the method further comprising:

[0085] When the cleaning robot meets the preset inspection conditions, control the cleaning robot to perform the inspection task.

[0086] The preset inspection conditions refer to the judgment rules that must be met to trigger the cleaning robot to start its inspection task. Preset inspection conditions include: the time interval between the current time and the end time of the previous inspection reaches a preset time threshold, and / or, the current time is within a preset time period. The preset time threshold can be set according to the frequency of contaminant generation in the cleaning area or user needs, such as 30 minutes, 1 hour, or 2 hours. The preset time period can be a fixed time interval, such as 12:30 to 13:00 after lunch, 18:30 to 19:00 after dinner, or the hourly intervals each day.

[0087] In this embodiment, the cleaning robot is equipped with a timer or clock module to record the timestamp of the previous inspection's end and provide the current system time. The cleaning robot judges preset inspection conditions according to a preset detection cycle (e.g., every minute). When the cleaning robot determines that the preset inspection conditions are met, it generates an inspection start command and sends this command to the cleaning robot's motion control module and pollutant detection module to control the cleaning robot to begin executing the inspection task. After triggering the inspection task, the cleaning robot performs pollutant detection and map update operations according to a preset inspection path or patrol points.

[0088] Specifically, the judgment of preset inspection conditions includes the following situations:

[0089] Scenario 1: If the preset inspection condition is "the time interval between the current time and the end time of the previous inspection reaches a preset time threshold," the cleaning robot obtains the timestamp recorded at the end time of the previous inspection, calculates the difference between the current time and that timestamp, and compares the difference with the preset time threshold. If the difference is greater than or equal to the preset time threshold, the condition is deemed met. This method is suitable for scenarios that require periodic inspections of the same area at a fixed frequency (e.g., every two hours).

[0090] Scenario 2: If the preset inspection condition is "the current time is within a preset time period", then the current system time is obtained and compared with the time range of the preset time period. If the current time falls within the preset time period (e.g., between 12:30 and 13:00 daily), the condition is considered met. This method is suitable for scenarios where specific areas are inspected during specific time periods (e.g., after meals or after get off work).

[0091] Scenario 3: If the preset inspection conditions include both of the above conditions and are combined in an "AND / OR" manner, then the inspection task will be triggered when at least one condition is met ("OR" logic), or when both conditions are met simultaneously. The specific logical relationship used can be pre-configured by the user on the application side or set by the system by default according to the inspection strategy.

[0092] The method described in this application automatically triggers inspection tasks when the cleaning robot meets preset inspection conditions, eliminating the need for manual initiation by the user each time and achieving automated scheduling of inspection tasks. The preset inspection conditions can be flexibly configured based on time intervals and / or time periods, supporting both periodic scheduled inspections and inspections performed within specific time windows. This improves the timeliness and targeting of inspection task execution while reducing the user's operational burden.

[0093] In some embodiments, another method for controlling a cleaning robot to perform inspection tasks is also provided, the method further comprising:

[0094] When the current time falls within a preset time period, control the cleaning robot to perform inspection tasks in preset areas; the preset areas include the kitchen area and the dining area.

[0095] The preset time period refers to a time window associated with a specific room area; the kitchen and dining areas are the target room areas corresponding to this time window. In other words, when the current time falls within the preset time period bound to the kitchen or dining area, the cleaning robot is triggered to perform an inspection task in that area. For example, the inspection time period for the kitchen area can be set from 12:30 to 13:00 after lunch each day, and the inspection time period for the dining area can be set from 18:30 to 19:00 after dinner each day.

[0096] In this embodiment, the cleaning robot's memory pre-stores a table corresponding to room areas and time periods. This table includes at least the kitchen area and its corresponding first time period, and the dining area and its corresponding second time period. The cleaning robot obtains the current system time in real time and determines its current room area. When the cleaning robot is in the kitchen or dining area, it obtains the preset time period corresponding to that area and determines whether the current time falls within that time period. If so, it controls the cleaning robot to immediately perform an inspection task on the currently located area.

[0097] Optionally, the cleaning robot does not rely on real-time positioning, but instead automatically navigates to the corresponding target area to perform inspections according to a preset schedule. Specifically, the cleaning robot stores a list of scheduled tasks, each task including the target room area (such as the kitchen or dining area), a preset time period, and an inspection path. When the current time reaches the start time of the preset time period for a task, the cleaning robot autonomously navigates to the target room area specified by the task and performs the inspection task within that area; when the current time exceeds the end time of the preset time period, the cleaning robot terminates the inspection or returns to the base station.

[0098] Optionally, if the preset time periods for the kitchen area and the dining area overlap, the cleaning robot can perform inspections sequentially according to preset priorities (e.g., kitchen priority over dining area), or use a multi-robot collaborative approach to perform inspections separately.

[0099] The method described in this application binds specific rooms such as kitchen and dining areas to preset time periods, enabling cleaning robots to automatically perform inspections during the time windows when these areas are most likely to be contaminated (such as after meals). This achieves precise inspections with spatiotemporal correlation, improves the targeting and timeliness of inspections, and avoids the waste of time and energy caused by full-area, full-coverage inspections.

[0100] In some embodiments, during the inspection task performed by the cleaning robot, the method further includes:

[0101] The cleaning robot is controlled to move to multiple pre-set patrol points, where it detects pollutants and obtains information on pollutant distribution.

[0102] Among them, the patrol point refers to one or more pre-set coordinate positions of the cleaning robot within a preset area, which are used as stopping and detection points during the inspection process.

[0103] In this embodiment, the cleaning robot pre-stores a list of patrol points, which includes the coordinates of each patrol point in the map coordinate system. After starting the patrol task, the cleaning robot plans a movement path from its current position to the target patrol point in the order of the point list, and controls its walking mechanism to move along the path. Upon reaching a patrol point, the cleaning robot stops moving and activates the pollutant detection module to detect the environment around that point. The pollutant detection module includes at least one of a camera, LiDAR, and a humidity sensor. After detection, the cleaning robot stores the identified pollutant type and the pollutant location calculated based on sensor ranging and current pose as part of the pollutant distribution information in its local cache. Subsequently, the cleaning robot continues to move to the next patrol point and repeats the above detection process until all patrol points have been traversed. After traversal, the cleaning robot uses the summarized pollutant distribution information for subsequent map update operations. It should be noted that the number and density of patrol points can be adjusted according to the area, layout and probability of pollution in the preset area. For example, patrol points can be densely set up in high-pollution areas such as near dining tables, kitchen entrances, and corridor corners, and sparsely set up in open areas.

[0104] Furthermore, the specific methods for pollutant detection at each patrol point include:

[0105] At each patrol point, the cleaning robot is controlled to rotate its main unit and / or its camera to obtain information on the distribution of pollutants.

[0106] Here, "host rotation" refers to the entire cleaning robot rotating in place around its vertical axis. "Camera rotation" refers to the rotation of the gimbal equipped with the pollutant detection module relative to the cleaning robot body, causing a change in the camera's orientation.

[0107] In this embodiment, after the cleaning robot reaches the patrol point, it performs a rotation operation according to a preset rotation strategy. The rotation strategy includes at least one of the following: controlling the cleaning robot's main unit to rotate 360 ​​degrees in place, while the camera continuously collects images and sensor data during the rotation; or controlling the cleaning robot's main unit to remain stationary, only controlling the gimbal to rotate the camera horizontally by a preset angle (e.g., 0 to 180 degrees or 0 to 360 degrees); or simultaneously controlling the main unit to rotate and the gimbal to form a composite scanning path. After the rotation is completed, the cleaning robot stitches and fuses the collected multi-directional perception data, identifies the pollutant distribution information and pollutant type in each direction, and then combines the robot's current pose and sensor ranging data to calculate the coordinate position of each pollutant in the map coordinate system, thereby obtaining the pollutant distribution information.

[0108] Specifically, the methods for controlling the cleaning robot to rotate its main unit and / or camera include the following:

[0109] Scenario 1: In the implementation where the main unit rotates in place, the cleaning robot sends a differential drive command to the walking mechanism, causing the left and right wheels to rotate at equal speeds in opposite directions, enabling the robot to rotate around its vertical axis. During rotation, the pollutant detection module collects real-time sensing data from the ground and surrounding environment. Through data fusion from different angles, pollutants in various directions within a radius of several meters centered on the patrol point can be identified.

[0110] Scenario 2: In the implementation where the camera rotates independently, the cleaning robot chassis remains stationary, while the gimbal mechanism mounted on top of the robot rotates horizontally. The gimbal contains a stepper motor for precise control of the rotation angle. The camera is fixed to the gimbal and changes its shooting direction as the gimbal rotates. This method is suitable for scenarios where the robot's docking position makes overall rotation inconvenient (e.g., in confined spaces).

[0111] Scenario 3: In an implementation that simultaneously employs host rotation and camera rotation, the host and camera can move independently or collaboratively according to their respective angular velocities and directions to cover a more complex detection area, such as simultaneously detecting ground pollutants and environmental information at height or on the side.

[0112] The method described in this application embodiment, by controlling the cleaning robot to move to multiple pre-set patrol points and detecting pollutants at each point, can cover a larger area with limited points, reducing the movement time for full-path coverage inspections and improving inspection efficiency. Furthermore, at each patrol point, by rotating the main unit and / or the camera, information on the distribution of pollutants in multiple directions is acquired, expanding the coverage of single-point detection and avoiding pollutant omissions due to limited sensor field of view, thus improving the comprehensiveness and accuracy of pollutant detection.

[0113] In some embodiments, such as Figure 3 As shown, the "updating the original map based on pollutant distribution information to obtain a pollutant distribution map" in S202 above includes:

[0114] S301, extract pollutant type and pollutant location from pollutant distribution information.

[0115] The types of pollutants include liquid pollutants and solid pollutants. Furthermore, the types of pollutants also include feces.

[0116] In this embodiment, after acquiring pollutant distribution information, the cleaning robot can extract the pollutant type and location from the pollutant distribution information. If the pollutant distribution information does not contain any records (i.e., no pollutants were found in this inspection), no adding operation is required.

[0117] S302. Based on the location of pollutants, add visual markers of pollutant types to the corresponding locations on the original map to obtain a pollutant distribution map.

[0118] Visual identifiers refer to graphic symbols, color marks, or icons used to distinguish different types of pollutants. The corresponding location on the original map refers to the raster or pixel in the original map coordinate system that matches the location coordinates of the pollutant.

[0119] In this embodiment, after acquiring the type and location of the contaminant, the cleaning robot can select the corresponding visual icon from a preset icon mapping table based on the contaminant type. For example, liquid contaminants (large areas of liquid) are mapped to blue water droplet icons, solid contaminants (particulate matter) are mapped to brown dot icons or small particle icons, and feces are mapped to brown star icons. If the contaminant type includes subcategories of liquid and solid, the icons can be further refined (e.g., oil stains are represented by orange water droplets, and water stains by blue water droplets). The cleaning robot transforms the contaminant location coordinates to the pixel coordinate system of the original map to determine the specific pixel location on the original map image. If the contaminant location is a point coordinate, an icon is drawn at that pixel; if the contaminant location is a polygonal area, the corresponding pattern is filled in the area or multiple small icons are evenly distributed.

[0120] When adding visual markers, the cleaning robot can use a layer overlay mechanism: create a new transparent marker layer, draw all visual markers on this layer, and then overlay the marker layer with the base layer of the original map to obtain a pollutant distribution map. This method preserves the original data of the original map, facilitating subsequent updates or removal of markers. If historical pollutant markers already exist at the same location in the original map, the cleaning robot can process them according to preset update rules: it can overwrite old markers (based on the current identification), merge old and new markers (e.g., display both old and new icons but with timestamps), or retain unprocessed old markers and overlay new markers. The update rules can be configured by the user in the application.

[0121] The method described in this application extracts pollutant types and locations from pollutant distribution information and adds different types of visual markers to the corresponding locations on the original map, thereby achieving an intuitive and graphical presentation of pollutant information. This method can transform the abstract pollution data perceived by the cleaning robot into map markers that are easy for users to understand, allowing users to quickly grasp the types and distribution of pollutants without parsing the original data.

[0122] In some embodiments, a specific implementation method for visually identifying pollutants is also provided, such as... Figure 4 As shown, "adding a visual identifier for the pollutant type at the corresponding location on the original map" in S302 above includes:

[0123] S401, merge pollutants of the same type in adjacent areas to obtain merged pollutants.

[0124] In this context, "adjacent areas" refers to locations where the distance between two or more pollutants is less than or equal to a preset merging threshold. "Same type" means the pollutants belong to the same category, including liquid pollutants, solid pollutants, or feces. The merged pollutant refers to combining multiple adjacent and similar pollutants into a single pollutant entity for subsequent unified identification.

[0125] In this embodiment, after the cleaning robot acquires the types of pollutants and their corresponding locations, it groups the pollutants according to their types, so that pollutants of the same category belong to the same group, resulting in multiple groups of pollutants of the same category. For each group of pollutants of the same category, the cleaning robot calculates the spatial distance between every two pollutants; specifically, if the pollutant location is a coordinate point, the straight-line distance between the two points is calculated; if the pollutant location is an area (such as a polygon), the shortest distance between the boundaries of the two areas is calculated.

[0126] Then, the cleaning robot compares the calculated spatial distance with a preset merging threshold. When the distance between two pollutants is not greater than the preset merging threshold, the two pollutants are determined to be in adjacent areas, and a merging operation is performed on all pollutants of the same type in the adjacent areas. The merging threshold can be preset according to map resolution or sensor accuracy, for example, 10 cm, 20 cm, or the actual length corresponding to two grid cells in the map. The merging method includes calculating the geometric center of each pollutant location to determine the representative point after merging, or calculating the minimum bounding rectangle or convex hull polygon containing all pollutant areas to determine the merged coverage area.

[0127] The cleaning robot repeats the above judgment and merging process until no adjacent pollutants of the same category meet the criteria. After merging, the merged pollutants are used as objects to be labeled with visual tags for subsequent unified labeling. If no adjacent pollutants of the same category exist among all pollutants, the merging result is consistent with the original pollutants.

[0128] S402, Add a visual identifier for the merged pollutant type to the corresponding location on the original map.

[0129] The corresponding location refers to the mapping point or mapping area of ​​the merged pollutant's location coordinates in the original map coordinate system.

[0130] In this embodiment of the application, after the cleaning robot obtains each pollutant after the merging operation, each pollutant contains category attributes and location information. The method in S302 can be used to add a visual label of the merged pollutant type to the corresponding location on the original map.

[0131] The method described in this application reduces the number of redundant and dense markers on the pollutant distribution map by merging pollutants of the same type in adjacent areas. This makes the map presentation simpler and clearer, allowing users to quickly identify the distribution range and concentration of pollutants. Simultaneously, the merging operation reduces the amount of map data, alleviating the rendering burden on user terminals and improving interaction response speed and user experience.

[0132] In some embodiments, another specific implementation for visually identifying pollutants is also provided, such as... Figure 5 As shown, "adding a visual identifier for the pollutant type at the corresponding location on the original map" in S302 above includes:

[0133] S501, the pollutants in the pollutant distribution map are screened according to the preset screening conditions to obtain the screened pollutants.

[0134] The preset screening criteria are used to filter out contaminants that are too small in area or too few in number, thereby reducing redundant markers on the map. These criteria include the area of ​​the contaminant being larger than a preset area threshold, and / or, when the contaminant is a solid particle, the number of solid particles being greater than a preset quantity threshold. Specifically, the preset area threshold applies to areas with liquid contaminants or aggregated particulate matter and can be set according to cleaning needs, such as 1 square centimeter, 5 square centimeters, or 10 square centimeters. The preset quantity threshold applies to discrete solid particles and can be set according to the degree of particle aggregation, such as 5, 10, or 20 particles.

[0135] In this embodiment of the application, after obtaining the pollutant distribution map, the cleaning robot can identify all pollutants in the pollutant distribution map. Each pollutant contains information on type, location, area or number of particles. Then, it traverses each pollutant to determine whether it meets the preset screening conditions.

[0136] For liquid contaminants or particulate matter accumulation areas with a defined region, the cleaning robot can calculate the area value of the contaminant by detecting the continuous area boundary through sensors, or by statistically analyzing the area value of the contaminant based on map pixel grids. Then, it compares the area value with a preset area threshold. If the area value of the contaminant is greater than the preset area threshold, the contaminant is determined to meet the screening criteria and is retained; if the area value of the contaminant is not greater than the preset area threshold, the contaminant is removed from the set to be identified.

[0137] For discrete solid particulate matter, the cleaning robot can analyze and statistically determine the number of particles in the image captured by the camera using an image recognition model. Then, it compares the number of particles with a preset threshold. If the number of particles is greater than the preset threshold, the pollutant is determined to meet the screening criteria and is retained; if the number of particles is not greater than the preset threshold, the pollutant is removed.

[0138] When the preset screening criteria include both area and quantity conditions and are expressed in an "AND / OR" manner, the cleaning robot executes the logic according to the actual conditions: if it is an "OR" logic, a pollutant is retained if it meets at least one of the area or quantity conditions; if it is an "AND" logic, a pollutant is retained only if it meets both the area and quantity conditions. After screening, the cleaning robot obtains a set of screened pollutants, which contains only pollutants that meet the preset screening criteria.

[0139] S502, Add visual markers for the filtered pollutant types to the corresponding locations on the original map.

[0140] In this embodiment of the application, after the cleaning robot obtains the screened pollutants, each pollutant contains category attributes and location information. The method in S302 can be used to add a visual label of the screened pollutant type to the corresponding location on the original map.

[0141] The method described in this application filters pollutants based on their area and / or the number of solid particles, retaining only those that meet a preset threshold. This effectively eliminates small liquid stains, scattered debris, and other contamination information that has little impact on cleaning decisions, avoiding a large number of redundant and trivial markings on the pollutant distribution map. Furthermore, the filtered map is clearer and more focused, allowing users to quickly concentrate on the main contaminated areas that need treatment, improving map readability and user experience.

[0142] In some embodiments, during the inspection task performed by the cleaning robot, the above method further includes:

[0143] If an unknown area that is not marked on the original map is detected, and it is determined that the unknown area can be entered, the cleaning robot is controlled to collect map information of the unknown area and add the map information of the unknown area to the original map.

[0144] In this context, an unknown area refers to a region outside the original map boundaries or marked as unexplored on the map, where the cleaning robot has not yet recorded structural information. Being able to enter an unknown area means that the cleaning robot detects a passable path through its sensors (e.g., a door is open, there are no obstructions), and the robot's size and mobility allow it to enter via that path. Map information includes at least one of the following: room boundaries, wall locations, obstacle distribution, and passable areas within the unknown area.

[0145] In this embodiment, the cleaning robot continuously detects its surrounding environment using LiDAR or cameras during its inspection tasks. When the sensors detect unrecorded continuous space outside the current original map boundary, the cleaning robot classifies this space as an unknown area. The cleaning robot further analyzes the path from its current position to this unknown area: if there is a continuous passable plane (e.g., no steps, drops, or obstacles on the ground), and the path width is greater than the width of the cleaning robot's body, then the cleaning robot determines that it can enter the unknown area. If entry is confirmed, the cleaning robot plans its entry path and moves along that path into the unknown area. Upon entry, the cleaning robot initiates a simultaneous localization and mapping (SMR) algorithm, using LiDAR or visual sensors to collect data on environmental boundaries, obstacle outlines, and passable areas in real time, gradually constructing a map of the unknown area. After data collection, the cleaning robot stitches the newly constructed map information with the original map: aligning the origin of the unknown area's coordinates with the coordinate system of the original map, and integrating newly added boundaries, obstacles, and other elements into the corresponding positions of the original map, thereby obtaining an expanded original map. Finally, the cleaning robot stores the expanded original map in its local memory for subsequent pollutant overlay and navigation positioning.

[0146] The method described in this application actively detects and enters unknown areas not marked on the original map during the inspection process, collects map information of these areas, and adds it to the original map. This achieves dynamic expansion and improvement of the map, solving the problem of incomplete maps caused by missing rooms or areas during initial mapping. This method enables the cleaning robot to autonomously adapt to environmental changes without requiring manual map updates by the user, improving map integrity and the coverage of the inspection task.

[0147] Furthermore, given the pollutant distribution map, information on the distribution of pollutants in unknown areas is obtained and added to the pollutant distribution map.

[0148] Among them, the information on the distribution of pollutants in the unknown area refers to the type and location of pollutants identified by the pollutant detection module after the cleaning robot enters the unknown area.

[0149] In this embodiment, the cleaning robot simultaneously performs pollutant detection while entering an unknown area and collecting map information. The cleaning robot uses its onboard camera, LiDAR, and humidity sensor to identify whether at least one pollutant exists in a large area of ​​liquid, particulate matter, or feces within the unknown area, and records the type of each pollutant and its position in the local coordinate system of the unknown area. Then, the cleaning robot converts the coordinates of the pollutants in the local coordinate system to coordinates in the unified coordinate system of the expanded original map. It then selects the corresponding visual identifier based on the pollutant type (e.g., blue water droplet icon for liquid, brown dot icon for particulate matter, and brown star icon for feces) and adds the identifier to the corresponding coordinate position on the expanded original map. If the cleaning robot has already generated a pollutant distribution map before entering the unknown area (i.e., pollutant markers already exist in the original map), the pollutant markers in the unknown area are overlaid as a new layer onto the existing pollutant distribution map, thus adding pollutant markers to the existing pollutant distribution map to obtain a complete pollutant distribution map including the unknown area.

[0150] The method described in this application, by acquiring pollutant distribution information in unknown areas and adding it to a pollutant distribution map, enables a cleaning robot to explore and simultaneously collect pollutant information in rooms or areas missed in the original map. This achieves dynamic expansion of the pollutant distribution map, avoiding missing pollutant information due to incomplete initial mapping, ensuring the integrity and accuracy of the pollutant distribution map, and allowing users to view the pollution status of all areas through their terminals.

[0151] In some embodiments, a cleaning method for a cleaning robot is also provided, such as... Figure 6 As shown, the method includes:

[0152] S601, Obtain the pollutant distribution map obtained by the method for constructing the dirt map of any of the above instances.

[0153] The pollutant distribution map includes the type and location of pollutants.

[0154] In this embodiment, before initiating a cleaning task or during its execution, the cleaning robot reads the most recent or a specified historical dirt map (i.e., the contaminant distribution map described in any of the above examples) from its local non-volatile memory via an internal communication interface. If the cleaning robot supports cloud synchronization, it can send a request to a cloud server via a wireless network, carrying a user account or device identifier, to download the corresponding contaminant distribution map file. The data format of the contaminant distribution map can be a structured file or a binary raster map. The cleaning robot can also receive a contaminant distribution map it constructs in real time during the execution of the current cleaning task. This map includes a base layer and a marker layer, with the marker layer recording the type of contaminant and its corresponding location coordinates. The cleaning robot parses the marker layer to extract the type of each contaminant (e.g., liquid, solid particles, or feces) and its location (point coordinates or polygonal area).

[0155] S602 determines the cleaning strategy based on the type of contaminant and controls the cleaning robot to perform cleaning tasks according to the cleaning strategy.

[0156] The cleaning strategy refers to the set of rules for cleaning methods, parameters, and sequences set for different types of contaminants. The cleaning task refers to the operation of the cleaning robot activating its cleaning mechanisms (including at least one of roller brushes, side brushes, vacuum fans, water pumps, or mopping components) to sweep, suck up, or wipe the area where contaminants are located.

[0157] In this embodiment, after acquiring a contaminant distribution map, the cleaning robot can extract the type and location of each contaminant. For each contaminant, a preset cleaning strategy is matched according to its type. For liquid contaminants, water suction or wet mopping is used, the roller brush and side brush are turned off, and the water pump and suction assembly are used to perform cleaning. For solid particles, dry cleaning is used, the roller brush, side brush, and vacuum fan are activated, but the water pump is not activated. For feces, disinfection wet mopping is used or the area is marked for manual disposal. Optionally, the cleaning robot also determines cleaning parameters based on the type of contaminant, including suction level, cleaning speed, and number of cleaning cycles.

[0158] Optionally, the above-mentioned pollutant types include liquid pollutants and solid pollutants, and "determining a cleaning strategy based on the pollutant type" in S602 above includes:

[0159] Cleaning should be carried out in descending order of cleaning priority; solid contaminants have a higher cleaning priority than liquid contaminants.

[0160] Cleaning priority refers to the order in which cleaning robots handle different types of contaminants when performing cleaning tasks. Solid contaminants have a higher cleaning priority than liquid contaminants; that is, solid particles are cleaned first, followed by liquid contaminants.

[0161] In this embodiment, after obtaining the type and location of the contaminants, the cleaning robot first traverses all locations of solid particles, performing a dry cleaning operation on each location. After all solid particles have been cleaned, it then traverses all locations of liquid contaminants, performing a wet suction or mopping operation on each location. The cleaning robot moves sequentially and performs the corresponding cleaning operations in this order until all contaminants have been treated.

[0162] Furthermore, the aforementioned types of contaminants include feces, and the "determining a cleaning strategy based on the type of contaminant" in S602 includes:

[0163] The area containing feces is marked as the last area to be cleaned, a separate area to be cleaned, or a designated area to be cleaned; the designated area to be cleaned is used to prompt the user to clean the feces manually.

[0164] The term "final cleaning area" refers to the cleaning robot cleaning the area containing feces last, after cleaning all other contaminants. "Separate cleaning area" means the cleaning robot isolates the feces area from other contaminated areas, initiating a dedicated cleaning program (such as high-temperature disinfection or powerful rinsing) to treat the feces area after cleaning the other areas. "Prompt cleaning area" means the cleaning robot does not automatically clean the feces but instead sends a prompt message to the user via the user terminal, suggesting manual cleaning.

[0165] In this embodiment, when the contaminant type includes feces, the cleaning robot marks the area containing the feces as a last-to-clean area, a separate-clean area, or a designated cleaning area, and then cleans the feces according to the corresponding strategy. If the strategy is "last-to-clean area," the cleaning robot cleans all other contaminants (solid particles and liquids) first, and then moves to the location of the feces to perform disinfection mopping. If the strategy is "separate-clean area," the cleaning robot avoids the feces area while cleaning other contaminants. After cleaning other areas, it automatically replaces cleaning components (e.g., changes the mop, injects disinfectant) before entering the feces area for specialized cleaning. If the strategy is "designated cleaning area," the cleaning robot does not perform automatic cleaning of the feces, but instead sends a prompt message to the user terminal via a wireless communication module. The message includes the location of the feces and a suggestion for manual cleaning. After receiving the prompt, the user terminal displays it in the form of a pop-up window or notification, and the cleaning robot simultaneously marks the area as "awaiting manual cleaning" on its stored map.

[0166] The method described in this application, by acquiring the type and location of pollutants in a pollutant distribution map and determining the corresponding cleaning strategy based on the pollutant type, achieves differentiated and precise cleaning treatment for different pollutants. Furthermore, a priority order is set for solid and liquid pollutants, with solids treated first and liquids treated later, avoiding cross-contamination and improving cleaning effectiveness. Additionally, for fecal pollutants, marking them as the last to be cleaned, requiring separate cleaning, or prompting for manual cleaning balances hygiene and safety requirements with user autonomy, improving the flexibility and safety of cleaning tasks.

[0167] In summary, based on all the above embodiments, a cleaning method for a cleaning robot based on a dirt map is also provided, the method comprising:

[0168] S701, when the cleaning robot meets preset inspection conditions, control the cleaning robot to perform inspection tasks. The preset inspection conditions include the time interval between the current time and the end time of the previous inspection reaching a preset time threshold, and / or, the current time falling within a preset time period. Further, when the current time falls within the preset time period, control the cleaning robot to perform inspection tasks on preset areas, including the kitchen area and the dining area.

[0169] S702, during the inspection process of the cleaning robot, controls the cleaning robot to move to multiple pre-set patrol points. At each patrol point, controls the cleaning robot to rotate the main unit and / or the camera to obtain information on the distribution of pollutants.

[0170] S703 acquires pollutant distribution information collected by the cleaning robot during its inspection tasks, and extracts pollutant type and location from the pollutant distribution information.

[0171] S704, based on the location of pollutants, merges pollutants of the same type in adjacent areas to obtain merged pollutants, and adds visual labels of the merged pollutant types to the corresponding locations on the original map to obtain a pollutant distribution map. The pollutant distribution map includes pollutant types and locations; pollutant types include liquid pollutants, solid pollutants, and also feces.

[0172] S705, the pollutants in the pollutant distribution map are filtered according to preset screening conditions to obtain the filtered pollutants, and a visual label of the filtered pollutant type is added to the corresponding position on the original map. The preset screening conditions include that the area of ​​the pollutant is greater than a preset area threshold, and / or, when the pollutant is a solid particle, the number of solid particles is greater than a preset number threshold.

[0173] S706: Upon detecting an unmarked unknown area on the original map and determining that entry into the unknown area is possible, the cleaning robot is controlled to collect map information of the unknown area and add this information to the original map. Further, if a pollutant distribution map is obtained, the pollutant distribution information within the unknown area is acquired and added to the pollutant distribution map.

[0174] S707 sends the pollutant distribution map to the user terminal to instruct the user terminal to display the pollutant distribution map.

[0175] S708, Obtain the pollutant distribution map obtained by the method for constructing the dirt map using S701-S707. The pollutant distribution map includes the pollutant type and the pollutant location.

[0176] S709: When the contaminants include both liquid and solid contaminants, cleaning is performed in descending order of cleaning priority. Solid contaminants have a higher cleaning priority than liquid contaminants, and the cleaning robot is controlled to perform cleaning tasks according to the cleaning strategy.

[0177] S710, when the contaminant type also includes feces, marks the area containing feces as a last-to-be-cleaned area, a separate-cleaned area, or a designated cleaning area. Designated cleaning areas are used to prompt the user to manually clean the feces.

[0178] The methods described in each of the above steps have been described in the foregoing embodiments. For details, please refer to the foregoing descriptions. They will not be repeated here.

[0179] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0180] Based on the same inventive concept, this application also provides a dirty map construction apparatus for implementing the dirty map construction method described above. The solution provided by this apparatus is similar to the solution described in the above method; therefore, the specific limitations of one or more dirty map construction apparatus embodiments provided below can be found in the limitations of the dirty map construction method described above, and will not be repeated here.

[0181] In some embodiments, such as Figure 7 As shown, a device for constructing a dirty map is provided, comprising:

[0182] Information acquisition module 71 is used to acquire pollutant distribution information collected by the cleaning robot during the inspection task;

[0183] The map update module 72 is used to update the original map based on the pollutant distribution information to obtain a pollutant distribution map; the pollutant distribution map includes pollutant type and pollutant location;

[0184] The map sending module 73 is used to send the pollutant distribution map to the user terminal so that the user terminal can display the pollutant distribution map.

[0185] In some embodiments, the apparatus for constructing the dirt map further includes:

[0186] The first control module is used to control the cleaning robot to perform inspection tasks when the cleaning robot meets the preset inspection conditions; wherein, the preset inspection conditions include the time interval between the current time and the end time of the previous inspection reaching a preset time threshold, and / or, the current time being within a preset time period.

[0187] In some embodiments, the apparatus for constructing the dirt map further includes:

[0188] The second control module is used to control the cleaning robot to perform inspection tasks in a preset area when the current time is within a preset time period; the preset area includes the kitchen area and the dining area.

[0189] In some embodiments, the apparatus for constructing the dirt map further includes:

[0190] The third control module is used to control the cleaning robot to move to multiple pre-set patrol points during the inspection process, and to detect pollutants at each patrol point to obtain pollutant distribution information.

[0191] In some embodiments, the third control module described above includes:

[0192] The control unit is used to control the cleaning robot to rotate its main unit and / or camera at each patrol point to obtain information on the distribution of pollutants.

[0193] In some embodiments, the map update module described above includes:

[0194] The extraction unit is used to extract pollutant type and pollutant location from pollutant distribution information.

[0195] The labeling unit is used to add a visual label of the pollutant type to the corresponding location on the original map based on the location of the pollutant, so as to obtain a pollutant distribution map; the pollutant types include liquid pollutants and solid pollutants; the pollutant types also include feces.

[0196] In some embodiments, the identification unit includes:

[0197] The merge sub-unit is used to merge pollutants of the same type in adjacent areas to obtain the merged pollutants.

[0198] The first identifier sub-unit is used to add a visual identifier for the merged pollutant type at the corresponding location on the original map.

[0199] In some embodiments, the above-mentioned identification unit further includes:

[0200] The screening subunit is used to screen pollutants in the pollutant distribution map according to preset screening conditions to obtain the screened pollutants; wherein, the preset screening conditions include the area of ​​the pollutant being greater than a preset area threshold, and / or, when the pollutant is a solid particle, the number of solid particles being greater than a preset number threshold.

[0201] The second identifier sub-unit is used to add a visual identifier for the filtered pollutant type to the corresponding location on the original map.

[0202] In some embodiments, the apparatus for constructing the dirt map further includes:

[0203] The third control module is used to control the cleaning robot to collect map information of the unknown area and add the map information of the unknown area to the original map when it detects an unknown area that is not marked on the original map and determines that it can enter the unknown area during the inspection task.

[0204] In some embodiments, the third control module described above includes:

[0205] The addition unit is used to obtain pollutant distribution information in unknown areas and add the pollutant distribution information to the pollutant distribution map, given a pollutant distribution map.

[0206] In some embodiments, such as Figure 8 As shown, a cleaning device for a cleaning robot is provided, comprising:

[0207] The map acquisition module 81 is used to acquire the pollutant distribution map obtained by the above-described method for constructing a dirt map; the pollutant distribution map includes pollutant type and pollutant location;

[0208] The cleaning module 82 is used to determine the cleaning strategy based on the type of contaminant and control the cleaning robot to perform cleaning tasks according to the cleaning strategy.

[0209] In some embodiments, the cleaning module described above includes:

[0210] The first cleaning unit is used to clean in order of highest to lowest cleaning priority when the types of contaminants include liquid and solid contaminants; the cleaning priority of solid contaminants is higher than that of liquid contaminants.

[0211] In some embodiments, the cleaning module further includes:

[0212] The second cleaning unit is used to mark the area where the feces are located as the last cleaning area, the independent cleaning area, or the prompt cleaning area when the type of contaminant also includes feces; the prompt cleaning area is used to prompt the user to manually clean the feces.

[0213] The modules in the aforementioned dirt map construction device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0214] In some embodiments, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the above embodiments.

[0215] In some embodiments, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0216] In some embodiments, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0217] The computer program product provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0218] It should be noted that the data involved in this application (including but not limited to data used for analysis, data stored, data displayed, etc.) are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0219] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0220] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0221] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for constructing a dirty map, characterized in that, The method includes: Acquire information on the distribution of pollutants collected by the cleaning robot during its inspection tasks; The original map is updated based on the pollutant distribution information to obtain a pollutant distribution map; the pollutant distribution map includes pollutant types and pollutant locations; The pollutant distribution map is sent to the user terminal to instruct the user terminal to display the pollutant distribution map.

2. The method according to claim 1, characterized in that, The method further includes: When the cleaning robot meets the preset inspection conditions, control the cleaning robot to perform the inspection task; The preset inspection conditions include: the time interval between the current time and the end time of the previous inspection reaches a preset time threshold, and / or the current time is within a preset time period.

3. The method according to claim 2, characterized in that, The method further includes: When the current time falls within the preset time period, the cleaning robot is controlled to perform the inspection task in a preset area; the preset area includes the kitchen area and the dining area.

4. The method according to any one of claims 1-3, characterized in that, During the inspection task performed by the cleaning robot, the method further includes: The cleaning robot is controlled to move to multiple pre-set patrol points, and pollutant detection is performed at each patrol point to obtain pollutant distribution information.

5. The method according to claim 4, characterized in that, The step of detecting pollutants at each of the aforementioned patrol points to obtain the pollutant distribution information includes: At each of the aforementioned patrol points, the cleaning robot is controlled to rotate its main unit and / or its camera to obtain information on the distribution of the pollutants.

6. The method according to claim 1, characterized in that, The step of updating the original map based on the pollutant distribution information to obtain a pollutant distribution map includes: Extract the pollutant type and the pollutant location from the pollutant distribution information; Based on the location of the pollutants, a visual identifier for the pollutant type is added to the corresponding location on the original map to obtain the pollutant distribution map; the pollutant types include liquid pollutants and solid pollutants.

7. The method according to claim 6, characterized in that, The types of pollutants also include feces.

8. The method according to claim 6, characterized in that, Adding a visual identifier for the pollutant type to the corresponding location on the original map includes: Pollutants of the same type in adjacent areas are merged to obtain the merged pollutants; Add a visual identifier for the merged pollutant type to the corresponding location on the original map.

9. The method according to any one of claims 6-8, characterized in that, Adding a visual identifier for the pollutant type to the corresponding location on the original map includes: The pollutants in the pollutant distribution map are screened according to preset screening conditions to obtain the screened pollutants; wherein, the preset screening conditions include the area of ​​the pollutant being greater than a preset area threshold, and / or, when the pollutant is a solid particle, the number of the solid particles being greater than a preset number threshold. Add a visual identifier for the filtered pollutant type to the corresponding location on the original map.

10. The method according to claim 1, characterized in that, During the inspection task performed by the cleaning robot, the method further includes: If an unknown area that is not marked on the original map is detected, and it is determined that the unknown area can be entered, the cleaning robot is controlled to collect map information of the unknown area and add the map information of the unknown area to the original map.

11. The method according to claim 10, characterized in that, The method further includes: Given the pollutant distribution map, obtain the pollutant distribution information in the unknown area and add the pollutant distribution information to the pollutant distribution map.

12. A cleaning method for a cleaning robot, characterized in that, The method includes: Obtain a pollutant distribution map obtained by the method for constructing a dirt map as described in any one of claims 1-11; the pollutant distribution map includes pollutant type and pollutant location; A cleaning strategy is determined based on the type of contaminant, and the cleaning robot is controlled to perform cleaning tasks according to the cleaning strategy.

13. The method according to claim 12, characterized in that, The types of contaminants include liquid contaminants and solid contaminants, and the step of determining a cleaning strategy based on the type of contaminant includes: Cleaning shall be carried out in descending order of cleaning priority; the cleaning priority of solid contaminants shall be higher than that of liquid contaminants.

14. The method according to claim 13, characterized in that, The contaminant types also include feces, and determining the cleaning strategy based on the contaminant types includes: The area containing the feces is marked as the last cleaning area, the independent cleaning area, or the prompt cleaning area; the prompt cleaning area is used to prompt the user to manually clean the feces.

15. A cleaning robot, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 14.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 14.

17. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 14.

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