Cleaning method of pool cleaning equipment and pool cleaning equipment

Abstract

The invention relates to the technical field of swimming pool cleaning, in particular to a cleaning method of pool cleaning equipment and the pool cleaning equipment. The method comprises the following steps: acquiring current image information of a target cleaning area; identifying smudginess data based on the current image information; switching a cleaning mode of the pool cleaning equipment according to the smudginess data; the cleaning modes of the pool cleaning equipment are switched in real time, so that the workload of the pool cleaning equipment is reduced, the energy consumption of the pool cleaning equipment is reduced, and the cleaning efficiency of the pool cleaning equipment is improved.

Description

Technical Field

[0001] This application relates to the field of swimming pool cleaning technology, and in particular to a cleaning method and a swimming pool cleaning device. Background Technology

[0002] With the development of technology, the demand for pool cleaning equipment is constantly increasing. Pool cleaning equipment refers to equipment used to clean pools, specifically, pool cleaning equipment can be a pool robot. Existing pool cleaning equipment usually performs full-coverage cleaning during the cleaning process, which means cleaning every part of the pool. Although full-coverage cleaning can effectively clean the pool, if a "deep cleaning" is performed every time, it will result in a large workload for the pool cleaning equipment, leading to low cleaning efficiency and high energy consumption. Summary of the Invention

[0003] To address the aforementioned problems in the prior art, the purpose of this application is to reduce the workload, energy consumption, and cleaning efficiency of the pool cleaning equipment by switching the cleaning mode of the pool cleaning equipment in real time.

[0004] To address the aforementioned problems, this application provides a method for cleaning a water tank cleaning device, the method comprising:

[0005] Obtain the current image information of the target cleaning area;

[0006] Identify dirty data based on the current image information;

[0007] The cleaning mode of the pool cleaning equipment is switched based on the amount of dirt.

[0008] In one possible embodiment, the dirt data includes dirt level information and dirt location information.

[0009] In one possible embodiment, the soiling information includes the type of contaminant, the area it occupies, the volume it occupies, or the quantity of the contaminant.

[0010] In one possible embodiment, the cleaning mode includes a main cleaning mode, a directional cleaning mode, and a full-coverage cleaning mode; switching the cleaning mode of the pool cleaning equipment according to the dirt data includes:

[0011] Based on the level of dirt, the cleaning mode of the pool cleaning equipment is switched from the main cleaning mode to either the directional cleaning mode or the full-coverage cleaning mode.

[0012] In one possible embodiment, the directional cleaning mode includes local path planning based on the location information of the dirt, and controlling the pool cleaning equipment to move from its current location to the area where the dirt is located for fixed-point cleaning based on the local path planning.

[0013] In one possible embodiment, the step of performing local path planning based on the location information of the dirt includes updating the map data of the pool based on the location information of the dirt, and planning a local path based on the updated map data.

[0014] In one possible embodiment, the local path includes a path along the edge of the pool where the cleaning equipment travels or a path where the cleaning equipment is closest to the dirt.

[0015] In one possible embodiment, after the directional cleaning mode or full-coverage cleaning mode is completed, the pool cleaning equipment returns to the path area of ​​the main cleaning mode.

[0016] In one possible embodiment, identifying dirt data based on the current image information includes comparing the current image information with preset image information.

[0017] In one possible embodiment, identifying the dirt data based on the current image information includes:

[0018] Feature extraction is performed on the current image information to obtain multiple target feature points;

[0019] When the number of multiple target feature points is greater than the preset number of features, semantic segmentation is performed on the current image information to determine target semantic information other than pool wall information and pool bottom information;

[0020] The target semantic information is semantically recognized to determine the dirty data.

[0021] On the other hand, this application also provides a pool cleaning device, which includes:

[0022] The image acquisition unit is configured to acquire image information of the target cleaning area;

[0023] The processing unit is configured to identify dirt data from the image information; and

[0024] The control unit is configured to control the pool cleaning equipment to switch cleaning modes based on the dirt data.

[0025] In one possible embodiment, the cleaning modes include a main cleaning mode, a directional cleaning mode, and a full-coverage cleaning mode, and the control unit is configured to control the pool cleaning equipment to switch from the main cleaning mode to the directional cleaning mode or the full-coverage cleaning mode based on the dirt data.

[0026] In one possible embodiment, in the main cleaning mode, the distance between two adjacent parallel walking paths of the pool cleaning device is greater than the cleaning width of the pool robot during its walking process and less than the width of the target cleaning area.

[0027] In one possible embodiment, in the full-coverage cleaning mode, the distance between two adjacent parallel walking paths of the pool cleaning device is less than or equal to the cleaning width of the pool cleaning device during its movement.

[0028] On the other hand, this application also provides an electronic device, the device including a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the cleaning method of the pool cleaning device described above.

[0029] On the other hand, this application also provides a computer storage medium storing at least one instruction or at least one program, wherein the at least one instruction or the at least one program is loaded and executed by a processor to implement the cleaning method of the pool cleaning equipment described above.

[0030] Due to the above technical solution, the cleaning method of the water tank cleaning equipment described in this application has the following beneficial effects:

[0031] By acquiring the current image information of the target cleaning area and identifying the dirt data in the target cleaning area based on the current image information, the cleaning mode of the pool cleaning equipment is switched according to the dirt data. This real-time switching of the cleaning mode of the pool cleaning equipment ensures that the working mode of the pool cleaning equipment matches the dirt data in the target area, avoiding ineffective work of the pool cleaning equipment, thereby reducing the workload of the pool cleaning equipment, reducing the energy consumption of the pool cleaning equipment, and improving the cleaning efficiency of the pool cleaning equipment. Attached Figure Description

[0032] To more clearly illustrate the technical solutions of this application, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0033] Figure 1This is a schematic diagram of the cleaning method of the pool cleaning equipment provided in the embodiments of this application;

[0034] Figure 2 This is a schematic diagram of the trajectory of the water tank cleaning equipment provided in the embodiments of this application under the main cleaning mode;

[0035] Figure 3 This is a schematic diagram of the trajectory of the pool cleaning equipment in full-coverage cleaning mode provided in the embodiments of this application;

[0036] Figure 4 This is a schematic diagram of a mode switching trajectory of the water tank cleaning equipment provided in the embodiments of this application;

[0037] Figure 5 This is a schematic diagram of another mode switching trajectory of the water tank cleaning equipment provided in the embodiments of this application;

[0038] Figure 6 This is a hardware structure block diagram of the cleaning method of the water tank cleaning equipment provided in the embodiments of this application. Detailed Implementation

[0039] 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 some embodiments of this application, and not all 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.

[0040] The term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of this application. In the description of this application, it should be understood that the terms "upper," "lower," "left," "right," "top," "bottom," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. Moreover, the terms "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein.

[0041] refer to Figure 1This application describes a cleaning method for a water tank cleaning device, which includes:

[0042] S1001. Obtain the current image information of the target cleaning area; the target cleaning area is the area to be cleaned by the pool cleaning equipment; specifically, the target cleaning area can be the area in front of the pool cleaning equipment, or the entire pool area; the current image information refers to the image information collected at the current time node.

[0043] In one possible embodiment, the pool cleaning equipment includes an image acquisition device and a control device. The current image information is acquired by the image acquisition device and sent to the control device. The image acquisition device can be a camera or a lidar.

[0044] S1002. Identify dirt data based on current image information; dirt data represents various dirt information within the target clean area.

[0045] In one possible embodiment, the dirt data includes dirt level information and dirt location information.

[0046] In one possible embodiment, the contamination level information includes the type of contaminant, the area it occupies, the volume it occupies, or the quantity of the contaminant.

[0047] In one possible embodiment, the types of pollutants include, but are not limited to, sediment pollutants, plastic pollutants, and large pollutants.

[0048] In one possible embodiment, the degree of soiling is different for different types of pollutants. For example, the degree of soiling for silt pollutants is assessed by the area occupied, while the degree of soiling for plastic pollutants and large pollutants is assessed by the volume or quantity occupied.

[0049] S1003. Switch the cleaning mode of the pool cleaning equipment according to the dirt data.

[0050] In one possible embodiment, the current image information of the target cleaning area is acquired, and the dirt data in the target cleaning area is identified based on the current image information. The cleaning mode of the pool cleaning equipment is switched according to the dirt data, thereby switching the cleaning mode of the pool cleaning equipment in real time so that the working mode of the pool cleaning equipment matches the dirt data in the target area, avoiding ineffective work of the pool cleaning equipment, thereby reducing the workload of the pool cleaning equipment, reducing the energy consumption of the pool cleaning equipment, and improving the cleaning efficiency of the pool cleaning equipment.

[0051] In one possible embodiment, the cleaning modes of the pool cleaning equipment include a main cleaning mode, a directional cleaning mode, and a full-coverage cleaning mode. The main cleaning mode represents the pool cleaning equipment performing a rough cleaning of the target cleaning area; the directional cleaning mode represents the pool cleaning equipment performing directional cleaning of target cleaning points within the target cleaning area; and the full-coverage cleaning mode represents the pool cleaning equipment performing a fine cleaning of the target cleaning area.

[0052] In one possible embodiment, in the main cleaning mode, the distance between two adjacent parallel walking paths of the pool cleaning device is greater than the cleaning width of the pool robot during its movement but less than the width of the target cleaning area.

[0053] In one possible embodiment, in full-coverage cleaning mode, the distance between two adjacent parallel walking paths of the pool cleaning device is less than or equal to the cleaning width of the pool cleaning device during its movement.

[0054] In one possible embodiment, assuming the pool cleaning device needs to clean the area to be cleaned, in the case of directional cleaning mode, the pool cleaning device will only clean a few points in the area to be cleaned; while in the case of main cleaning mode, the pool cleaning device can clean most of the area to be cleaned; and in the case of full coverage cleaning mode, the pool cleaning device can clean the entire area to be cleaned.

[0055] refer to Figure 2-3 In one possible implementation, it is assumed that both the main cleaning mode and the full coverage cleaning mode move in a "bow" shape, with the path spacing in the main cleaning mode being greater than that in the full coverage cleaning mode. Therefore, for the same area to be cleaned, the main cleaning mode has a lower turning frequency and fewer turns than the full coverage cleaning mode.

[0056] In one possible implementation, the trajectory of the pool cleaning equipment after switching from the main cleaning mode to the full-coverage cleaning mode is as follows: Figure 4 As shown.

[0057] In one possible embodiment, the pool cleaning device's trajectory for switching from main cleaning mode to directional cleaning mode, and then switching back to main cleaning mode after the directional cleaning mode has ended, is as follows: Figure 5 As shown.

[0058] In one possible embodiment, S1003 includes:

[0059] Based on the level of dirt, the cleaning mode of the pool cleaning equipment is switched from main cleaning mode to directional cleaning mode or full coverage cleaning mode.

[0060] In one possible embodiment, when the dirt level information indicates that there is relatively little dirt in the target cleaning area, the cleaning mode of the pool cleaning equipment is switched from the main cleaning mode to the directional cleaning mode.

[0061] In one possible embodiment, if the area occupied by silt pollution is less than a first preset area and the number of other types of pollutants is less than a first preset number, the degree of contamination information is determined to indicate that the target area is less contaminated. Other types of pollutants include, but are not limited to, plastic pollutants and large pollutants.

[0062] In one possible embodiment, if the dirt level information indicates that there is a lot of dirt in the target cleaning area, the cleaning mode of the pool cleaning equipment is switched from the main cleaning mode to the full coverage cleaning mode.

[0063] In one possible embodiment, if the area occupied by silt-like pollutants is greater than a second preset area, or the number of other types of pollutants is greater than a second preset number, the degree of contamination information is determined to indicate that there is a lot of contamination in the target area, wherein the second preset area is greater than or equal to the first preset area, and the second preset number is greater than or equal to the first preset number.

[0064] In one possible embodiment, by switching the pool cleaning equipment from the main cleaning mode to a directional cleaning mode or a full-coverage cleaning mode based on the degree of dirt, it can ensure comprehensive cleaning when there is a lot of dirt, spot cleaning when there is less dirt, and normal local cleaning when the amount of dirt is moderate. This avoids ineffective work of the pool cleaning equipment, thereby reducing the workload of the pool cleaning equipment, reducing the energy consumption of the pool cleaning equipment, and improving the cleaning efficiency of the pool cleaning equipment.

[0065] In one possible embodiment, the directional cleaning mode includes local path planning based on the location information of the dirt, and controlling the pool cleaning equipment to move from its current location to the area where the dirt is located for fixed-point cleaning based on the local path planning.

[0066] In one possible embodiment, assuming that the dirt data in the target area represents location area B with contaminant 1 and location area D with contaminant 2, in the main cleaning mode of the pool cleaning device, if no path planning is performed, the pool cleaning device will sequentially pass through location area A, location area B, location area C, location area D, and location area E; then, after the pool cleaning device switches from the main cleaning mode to the directional cleaning mode, the movement path of the pool cleaning device after local path planning becomes: the pool cleaning device will move from the current location area A to location area B, and then move from location area B to location area D.

[0067] In one possible embodiment, by performing local path planning based on the location information of the dirt, the pool cleaning equipment can perform targeted cleaning of the location to be cleaned, thereby avoiding ineffective work of the pool cleaning equipment, reducing the workload of the pool cleaning equipment, reducing the energy consumption of the pool cleaning equipment, and improving the cleaning efficiency of the pool cleaning equipment.

[0068] In one possible embodiment, the step of local path planning based on the location information of the dirt includes updating the map data of the pool based on the location information of the dirt, and planning a local path based on the updated map data.

[0069] In one possible embodiment, the pool cleaning device includes a storage module for storing map data of the pool to be cleaned; the location information of the dirt indicates the specific location area of ​​the dirt.

[0070] In one possible embodiment, the location information of the dirt can be obtained by identifying the current image information; specifically, it can be identified based on reference objects included in the current image information, such as the color of the pool wall.

[0071] In one possible embodiment, the location information of the dirt can be obtained by learning and recognizing the current image information through a deep learning model.

[0072] In one possible embodiment, assuming the pool's map data includes location areas A to N, the target cleaning area is the area in the direction the pool cleaning equipment moves, and the target cleaning area is location areas A to E, and the dirt location information indicates that the dirt is located in location areas B and D, then the map data can be updated to mark location areas B and D in the map data.

[0073] In one possible embodiment, since the pool cleaning device does not know its own location, it updates the pool's map data based on the location information of dirt, thereby enabling the pool cleaning device to perform local path planning based on pre-stored map data. This makes the local path planning more accurate and improves the cleaning efficiency of the pool cleaning device.

[0074] In one possible embodiment, the local path includes a path along the edge of the pool where the cleaning equipment travels or a path where the cleaning equipment is closest to the dirt.

[0075] In one possible embodiment, once the pool cleaning device obtains its current location area information, it directly determines the path closest to the dirt in the current location area as the local planning path.

[0076] In one possible embodiment, when the dirt location information represents multiple dirt location regions, the shortest path of the dirt is determined based on the current location region and the distance between any two location regions among the multiple dirt location regions.

[0077] In one possible embodiment, assuming the target cleaning area is location area A-location area E, the location information of the dirt indicates that the dirt is located in location areas B and D. The pool cleaning device knows that its current location area is location area C, and that the first distance length is greater than the second distance length. Here, the first distance length refers to the sum of the distance length from location area C to location area B and the distance length from location area B to location area D, and the second distance length refers to the sum of the distance length from location area C to location area D and the distance length from location area D to location area B. Therefore, it can be seen that the path closest to the dirt by the cleaning device is the path corresponding to the second distance length, that is, the pool cleaning device sequentially passes through location areas C-location area D-location area B.

[0078] In one possible embodiment, if the pool cleaning device cannot obtain its current location area, the pool cleaning device is controlled to walk along the edge of the pool until the pool cleaning device obtains its current location area.

[0079] In one possible embodiment, the location area of ​​the pool cleaning device is determined based on real-time image information as the device moves along the edge of the pool.

[0080] In one possible embodiment, the location area of ​​the pool cleaning equipment can be determined based on reference information in the acquired image information. The reference information includes, but is not limited to, items with distinctive features and colors with distinctive features. For example, the items with distinctive features may be base stations, and the colors with distinctive features may be colors that exist only within the target location area.

[0081] In one possible embodiment, the location area of ​​the pool cleaning equipment can also be determined based on information sent by the base station.

[0082] In one possible embodiment, by planning the path locally, walking along the edge or determining the shortest distance, the path planning accuracy of the pool cleaning equipment to the dirty area can be improved, thereby increasing the cleaning efficiency of the pool cleaning equipment.

[0083] In one possible embodiment, after the directional cleaning mode or the full-coverage cleaning mode is completed, the pool cleaning equipment returns to the path area of ​​the main cleaning mode.

[0084] In one possible embodiment, by returning the pool cleaning equipment to the main cleaning mode after the directional cleaning mode or the full-coverage cleaning mode has ended, it is possible to ensure that the pool cleaning equipment traverses the entire pool to be cleaned in the main cleaning mode, thereby improving the cleaning reliability and cleaning integrity of the pool cleaning equipment.

[0085] In one possible embodiment, assuming the target cleaning area is location area A to location area E, at location area B, the pool cleaning device switches from the main cleaning mode to the directional cleaning mode or the full coverage cleaning mode; and after the directional cleaning mode or the full coverage cleaning mode ends, the pool cleaning device is located at location area E, then at this time the pool cleaning device needs to be controlled to move from location area E to location area B.

[0086] In one possible embodiment, the path area for controlling the pool cleaning device to return to the main cleaning mode includes: the nearest location area for controlling the pool cleaning device to return to the main cleaning mode.

[0087] In one possible embodiment, by controlling the pool cleaning equipment to return to the nearest location area in the main cleaning mode, the path of the pool cleaning equipment is avoided from being too far, thereby improving the cleaning efficiency of the pool cleaning equipment and reducing the energy consumption of the pool cleaning equipment.

[0088] In one possible embodiment, if the pool cleaning device returns to the nearest location area in the main cleaning mode, the cleaning mode of the pool cleaning device is switched back to the main cleaning mode.

[0089] In one possible embodiment, assuming the target cleaning area is location area A to location area E, at location area B, the pool cleaning device switches from the main cleaning mode to the directional cleaning mode or the full coverage cleaning mode; after the directional cleaning mode or the full coverage cleaning mode ends, the pool cleaning device is located at location area E. At this time, the nearest location area in the main cleaning mode is location area C, so it is necessary to control the pool cleaning device to move from location area E to location area C.

[0090] In one possible embodiment, identifying dirt data based on current image information includes comparing current image information with preset image information, wherein the preset image information may include image information without dirt; the preset image information may also include image information with dirt, in order to compare and determine the type of dirt, etc.

[0091] In one possible embodiment, by comparing and identifying dirt data in the current image information, the process of dirt data identification can be simplified, the accuracy of dirt data identification can be improved, and the reliability of the pool cleaning equipment can be improved.

[0092] In another specific embodiment of this application, the dirty data identification can also be: inputting the current image information into the dirty data identification model to determine the dirty data corresponding to the current image information, wherein the dirty data identification model is a model obtained by deep learning based on preset image information and preset dirty data.

[0093] In another embodiment of this application, S1002 may include:

[0094] S10021. Perform feature extraction on the current image information to obtain multiple target feature points; wherein, feature extraction can be performed based on each pixel point, or it can be performed based on a feature extraction deep learning algorithm; the target feature points can represent the features of items in the pool, for example, the target feature points can represent the features corresponding to obstacles, garbage and pool walls, etc.

[0095] S10022. When the number of multiple target feature points is greater than the preset number of features, perform semantic segmentation on the current image information to determine the target semantic information other than pool wall information and pool bottom information. Here, semantic segmentation is based on deep learning algorithms to associate pixels in the current image information with target categories to achieve the labeling and classification of target feature points. Specifically, semantic segmentation can classify target feature points into feature information such as pool wall information, pool bottom information, and dirt data. Target semantic information includes, but is not limited to, dirt data and obstacle data.

[0096] S10023. Perform semantic recognition on the target semantic information to identify dirty data; semantic recognition refers to determining the required information, such as dirty data, from the target semantic information.

[0097] In one possible embodiment, dirt data is determined by feature extraction, semantic segmentation, and semantic recognition, thereby improving the accuracy of dirt data identification and thus improving the reliability of pool cleaning equipment.

[0098] The cleaning method for the water tank cleaning equipment provided in this application has the following beneficial effects:

[0099] By acquiring the current image information of the target cleaning area and identifying the dirt data in the target cleaning area based on the current image information, the cleaning mode of the pool cleaning equipment is switched according to the dirt data. This real-time switching of the cleaning mode of the pool cleaning equipment ensures that the working mode of the pool cleaning equipment matches the dirt data in the target area, avoiding ineffective work of the pool cleaning equipment, thereby reducing the workload of the pool cleaning equipment, reducing the energy consumption of the pool cleaning equipment, and improving the cleaning efficiency of the pool cleaning equipment.

[0100] This application also provides a water tank cleaning device, which includes:

[0101] The image acquisition unit is configured to acquire image information of the target cleaning area.

[0102] The processing unit is configured to identify image information to obtain dirt data; and

[0103] The control unit is configured to control the pool cleaning equipment to switch cleaning modes based on dirt data.

[0104] In one possible embodiment, the cleaning modes include a main cleaning mode, a directional cleaning mode, and a full-coverage cleaning mode, and the control unit is configured to control the pool cleaning equipment to switch from the main cleaning mode to the directional cleaning mode or the full-coverage cleaning mode based on the dirt data.

[0105] In one possible embodiment, in the main cleaning mode, the distance between two adjacent parallel walking paths of the pool cleaning device is greater than the cleaning width of the pool robot during its movement but less than the width of the target cleaning area.

[0106] In one possible embodiment, in full-coverage cleaning mode, the distance between two adjacent parallel walking paths of the pool cleaning device is less than or equal to the cleaning width of the pool cleaning device during its movement.

[0107] This application also provides an electronic device, which includes a processor and a memory. The memory stores at least one instruction or at least one program. The processor loads and executes the at least one instruction or at least one program to implement the cleaning method of the pool cleaning device described above.

[0108] Memory is used to store software programs and modules. The processor executes these stored software programs and modules to perform various functional applications and data processing. Memory can primarily consist of a program storage area and a data storage area. The program storage area stores the operating system, application programs required for functionality, etc.; the data storage area stores data created based on device usage, etc. Furthermore, memory can include high-speed random access memory (RAM) and non-volatile memory, such as at least one hard disk drive, flash memory, or other volatile solid-state storage devices. Correspondingly, memory can also include a memory controller to provide the processor with access to the memory.

[0109] The methods and embodiments provided in this application can be executed in electronic devices such as mobile terminals, computer terminals, servers, or similar computing devices. Figure 6 This is the electronic device provided in the embodiments of this application. For example... Figure 6As shown, the electronic device 900 can vary significantly due to differences in configuration or performance. It may include one or more central processing units (CPUs) 910 (CPUs 910 may include, but are not limited to, microprocessors (MCUs) or programmable logic devices (FPGAs), a memory 930 for storing data, and one or more storage media 920 (e.g., one or more mass storage devices) for storing application programs 923 or data 922. The memory 930 and storage media 920 may be temporary or persistent storage. The program stored in the storage media 920 may include one or more modules, each module may include a series of instruction operations on the electronic device. Furthermore, the CPU 910 may be configured to communicate with the storage media 920 and execute the series of instruction operations in the storage media 920 on the electronic device 900. Electronic device 900 may also include one or more power supplies 960, one or more wired or wireless network interfaces 950, one or more input / output interfaces 940, and / or one or more operating systems 921, such as Windows Server™, Mac OS™, Unix™, Linux™, FreeBSD™, etc.

[0110] The input / output interface 940 can be used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the electronic device 900. In one example, the input / output interface 940 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the input / output interface 940 may be a Radio Frequency (RF) module for wireless communication with the Internet.

[0111] Those skilled in the art will understand that Figure 6 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device described above. For example, the electronic device 900 may also include... Figure 6 The more or fewer components shown, or having the same Figure 6 The different configurations shown.

[0112] Embodiments of this application also provide a storage medium storing at least one instruction or at least one program, wherein the at least one instruction or at least one program is loaded and executed by a processor to implement the cleaning method of the pool cleaning device described above.

[0113] The foregoing description has fully disclosed the specific embodiments of this application. It should be noted that any modifications made by those skilled in the art to the specific embodiments of this application do not depart from the scope of the claims. Accordingly, the scope of the claims of this application is not limited to the foregoing specific embodiments.

Claims

1. A cleaning method for a water tank cleaning device, characterized in that, The method includes: Obtain the current image information of the target cleaning area; Identify dirty data based on the current image information; The cleaning mode of the pool cleaning equipment is switched based on the amount of dirt.

2. The cleaning method for the water tank cleaning equipment according to claim 1, characterized in that, The dirt data includes information on the degree of dirtiness and the location of dirt.

3. The cleaning method for the water tank cleaning equipment according to claim 2, characterized in that, The information on the degree of soiling includes the type of pollutant, the area it occupies, the volume it occupies, or the quantity of the pollutant.

4. The cleaning method for the water tank cleaning equipment according to claim 1, characterized in that, The cleaning modes include main cleaning mode, directional cleaning mode, and full coverage cleaning mode; The step of switching the cleaning mode of the pool cleaning equipment based on the dirt data includes: Based on the level of dirt, the cleaning mode of the pool cleaning equipment is switched from the main cleaning mode to either the directional cleaning mode or the full-coverage cleaning mode.

5. The cleaning method for the water tank cleaning equipment according to claim 4, characterized in that, The directional cleaning mode includes local path planning based on the location information of the dirt, and controlling the pool cleaning equipment to move from its current location to the location of the dirt for fixed-point cleaning based on the local path planning.

6. The cleaning method for the water tank cleaning equipment according to claim 5, characterized in that, The step of performing local path planning based on the location information of the dirt includes updating the map data of the pool based on the location information of the dirt, and planning a local path based on the updated map data.

7. The cleaning method for the water tank cleaning equipment according to claim 5, characterized in that, The local path includes the path along which the cleaning equipment walks along the edge of the pool or the path where the cleaning equipment is closest to the dirt.

8. The cleaning method of the pool cleaning equipment according to claim 4, characterized in that, After the directional cleaning mode or full-coverage cleaning mode is completed, the pool cleaning equipment returns to the path area of ​​the main cleaning mode.

9. The cleaning method for the water tank cleaning equipment according to any one of claims 1-8, characterized in that, The process of identifying dirt data based on the current image information includes comparing the current image information with preset image information.

10. The cleaning method for the water tank cleaning equipment according to claims 1-8, characterized in that, The method of identifying dirt data based on the current image information includes: Feature extraction is performed on the current image information to obtain multiple target feature points; When the number of multiple target feature points is greater than the preset number of features, semantic segmentation is performed on the current image information to determine target semantic information other than pool wall information and pool bottom information; The target semantic information is semantically recognized to determine the dirty data.

11. A pool cleaning device, comprising: The image acquisition unit is configured to acquire image information of the target cleaning area; The processing unit is configured to identify the dirt data from the image information; as well as The control unit is configured to control the pool cleaning equipment to switch cleaning modes based on the dirt data.

12. The water tank cleaning equipment according to claim 11, characterized in that, The cleaning modes include main cleaning mode, directional cleaning mode, and full coverage cleaning mode. The control unit is configured to control the pool cleaning equipment to switch from main cleaning mode to directional cleaning mode or full coverage cleaning mode based on the dirt data.

13. The water tank cleaning equipment according to claim 12, characterized in that, In the main cleaning mode, the distance between two adjacent parallel walking paths of the pool cleaning device is greater than the cleaning width of the pool robot during its walking process and less than the width of the target cleaning area.

14. The water tank cleaning equipment according to claim 12, characterized in that, In the full-coverage cleaning mode, the distance between two adjacent parallel walking paths of the pool cleaning device is less than or equal to the cleaning width of the pool cleaning device during its movement.

Images