Method for generating a dirt image, method for controlling a cleaning device, apparatus and system

Abstract

The embodiment of the application provides a dirty image generation method, a cleaning device control method, device and system. The dirty image generation method comprises the following steps: obtaining historical cleaning data of a cleaning device on a preset area, wherein the preset area comprises one or more preset sub-areas; and generating a dirty image of the preset area according to the historical cleaning data. The method improves the overall degree and convenience of the cleaning device in obtaining the dirty condition of the preset area, thereby improving the cleaning efficiency and cleaning effect of the cleaning device and improving the user experience of using the cleaning device.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cleaning, and in particular to a dirty image generation method, a cleaning device control method, device and system. BACKGROUND

[0002] The cleaning device can be used for automatic cleaning of the ground, and the application scenarios can be household indoor cleaning, large place cleaning, etc. At present, when the cleaning device cleans the ground, the cleaning efficiency of the cleaning device is easily reduced, and the cleaning effect is not good, which affects the user experience of using the cleaning device, because the cleaning device does not comprehensively obtain the dirty condition of the ground, or the convenience degree of obtaining the dirty condition of the ground is low. SUMMARY

[0003] The present application provides a dirty image generation method, a cleaning device control method, device and system, which aims to solve the technical problems that the cleaning efficiency of the cleaning device is easily reduced, and the cleaning effect is not good, which affects the user experience of using the cleaning device, because the cleaning device does not comprehensively obtain the dirty condition of the ground, or the convenience degree of obtaining the dirty condition of the ground is low.

[0004] In a first aspect, the embodiments of the present application provide a dirty image generation method, and the generation method comprises:

[0005] Obtaining historical cleaning data of a cleaning device on a preset area, wherein the preset area comprises one or more preset sub-areas;

[0006] Generating a dirty image of the preset area according to the historical cleaning data.

[0007] In a second aspect, the embodiments of the present application provide a cleaning device control method, and the control method comprises:

[0008] Obtaining a dirty image of a preset area, wherein the preset area comprises one or more preset sub-areas;

[0009] Controlling the cleaning device to clean the preset sub-area according to the dirty image of the preset area.

[0010] In a third aspect, the embodiments of the present application provide a dirty image generation device, and the generation device comprises a memory and a processor;

[0011] The memory is used for storing a computer program;

[0012] The processor is used for executing the computer program and realizing the steps of the dirty image generation method when executing the computer program.

[0013] In a fourth aspect, an embodiment of the present application provides a control device of a cleaning device, the control device comprising a memory and a processor;

[0014] The memory is configured to store a computer program.

[0015] The processor is configured to execute the computer program and implement the steps of the control method of the cleaning device when executing the computer program.

[0016] In a fifth aspect, an embodiment of the present application provides a cleaning device system, comprising:

[0017] a cleaning device, the cleaning device comprising a motion mechanism and a cleaning element, the motion mechanism being configured to drive the cleaning device to move so that the cleaning element cleans a preset cleaning area;

[0018] a base station, the base station being configured to at least clean the cleaning element of the cleaning device; and

[0019] the aforementioned dirty image generation device; and / or

[0020] the aforementioned control device of the cleaning device.

[0021] In a sixth aspect, an embodiment of the present application provides a cleaning device system, comprising:

[0022] a cleaning device, the cleaning device comprising a motion mechanism, a cleaning element and a maintenance mechanism, the motion mechanism being configured to drive the cleaning device to move so that the cleaning element cleans a preset cleaning area, and the maintenance mechanism being configured to clean the cleaning element; and

[0023] the aforementioned dirty image generation device; and / or

[0024] the aforementioned control device of the cleaning device.

[0025] In a seventh aspect, an embodiment of the present application provides a computer readable storage medium, the computer readable storage medium storing a computer program, the computer program being configured to cause a processor to implement the steps of the aforementioned dirty image generation method when executed by the processor, or the computer program being configured to cause the processor to implement the steps of the aforementioned control method of the cleaning device when executed by the processor.

[0026] The embodiment of the present application provides a dirty image generation method, a cleaning device control method, device and system, the dirty image generation method comprises the following steps: obtaining historical cleaning data of a cleaning device on a preset area, wherein the preset area comprises one or more preset sub-areas; generating a dirty image of the preset area according to the historical cleaning data, so as to improve the comprehensive degree and the convenience degree of the cleaning device in obtaining the dirty condition of the preset area, thereby facilitating the improvement of the cleaning efficiency and the cleaning effect of the cleaning device and the improvement of the experience of the user in using the cleaning device.

[0027] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the disclosure of the embodiments of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0029] Figure 1 is a flow diagram of a dirty image generation provided by the embodiments of the present application;

[0030] Figure 2 is a flow diagram of a cleaning device control method provided by the embodiments of the present application;

[0031] Figure 3 is a schematic block diagram of a dirty image generation device provided by the embodiments of the present application;

[0032] Figure 4 is a schematic block diagram of a cleaning device control device provided by the embodiments of the present application;

[0033] Figure 5 is a schematic block diagram of a cleaning device system provided by the embodiments of the present application;

[0034] Figure 6 is a schematic block diagram of a cleaning device system provided by another embodiment of the present application. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0036] The flowchart shown in the drawings is only an example and does not necessarily include all the contents and operations / steps, nor does it have to be executed in the order described. For example, some operations / steps can also be decomposed, combined or partially merged, so the actual execution order can be changed according to the actual situation.

[0037] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The following examples and features in the examples can be combined with each other without conflict.

[0038] Please refer to Figure 1 , Figure 1 is a flowchart of a dirty image generation method provided by an embodiment of the present application. The dirty image generation method can be applied in a cleaning device system, for generating a dirty image of a preset area according to historical cleaning data of the cleaning device in the system on the preset area. According to the dirty image of the preset area, the comprehensive degree and the convenience degree of the cleaning device obtaining the dirty condition of the preset area are improved, thereby facilitating to improve the cleaning efficiency and the cleaning effect of the cleaning device and improving the user experience of using the cleaning device.

[0039] As shown in Figure 1 , the dirty image generation method of the embodiment of the present application includes steps S110 to S120.

[0040] Step S110, obtaining historical cleaning data of a cleaning device on a preset area, wherein the preset area includes one or more preset sub-areas.

[0041] Illustratively, the preset area can be any one of a home space, a room unit of the home space, a partial area of the room unit, a large place or a partial area of the large place, etc. Optionally, the preset area can be established by the cleaning device in response to a mapping instruction to explore and map the current space, or can be updated by the cleaning device according to obstacles, carpets, etc. identified in the cleaning process; optionally, the preset area can be a user-specified area, for example, based on the mapping of the cleaning device, determining one or more rooms selected by the user as the preset area, wherein the plurality includes two or more, or based on the mapping of the cleaning device, determining a partial area of one or more rooms circled by the user as the preset area, wherein the plurality includes two or more, of course, the preset area is not limited thereto.

[0042] In some embodiments, the preset area includes one or more preset sub-areas, and the plurality of preset sub-areas includes two or more preset sub-areas. For example, the preset sub-areas can be determined according to a workload threshold of the cleaning device for the preset area. For example, the workload of the cleaning device for cleaning each preset sub-area is less than or equal to the workload threshold, which can be calculated by energy consumption or water consumption. The workload threshold is used to indicate that the cleaning device interrupts the current cleaning task and performs maintenance before completing the workload corresponding to the workload threshold. The cleaning task refers to the task of cleaning one or more preset sub-areas of the preset area by the cleaning device in response to a cleaning instruction. Of course, the preset sub-areas are not limited to this, for example, the preset sub-areas can be determined according to the user's division operation on the preset area, which is not limited herein.

[0043] Optionally, obtaining the historical cleaning data of the preset area by the cleaning device can include obtaining historical cleaning data in a preset time period. For example, the historical cleaning data can be periodically deleted, for example, according to the time interval between the historical cleaning date corresponding to the historical cleaning data and the current date being greater than the preset time period, deleting the historical cleaning data corresponding to the historical cleaning date whose time interval with the current date is greater than the preset time period; or, according to the time interval between the historical cleaning date corresponding to the historical cleaning data and the current date being less than or equal to the preset time period, retaining the historical cleaning data corresponding to the historical cleaning date whose time interval with the current date is less than or equal to the preset time period, so as to improve the timeliness of the historical cleaning data, while avoiding the decrease of the generation efficiency of the dirt image of the preset area and the decrease of the description accuracy of the dirt image of the preset area to the dirt condition of the preset area due to the excessive data amount of the historical cleaning data.

[0044] For example, by obtaining the historical cleaning data, it is beneficial to improve the overall degree and convenience of the cleaning device obtaining the dirt condition of the preset area, thereby improving the cleaning efficiency and cleaning effect of the cleaning device and improving the user experience of using the cleaning device.

[0045] Step S120, generating a dirt image of the preset area according to the historical cleaning data.

[0046] For example, the historical cleaning data includes at least one of historical dirt data of the preset sub-area at each cleaning, historical cleaning frequency of the preset sub-area, historical cleaning parameter of the preset sub-area at each cleaning, and floor parameter of the preset sub-area.

[0047] For example, the historical dirt data of the preset sub-region at each cleaning time can be used to describe the historical dirt condition of the preset region, such as the amount of dirt cleaned by the cleaning device from the preset sub-region at each cleaning time. The historical dirt data of the preset sub-region at each cleaning time can also be used to determine the estimated dirt value of the preset sub-region for describing the estimated dirt condition of the preset region, such as the amount of dirt cleaned by the cleaning device from the preset sub-region at the next cleaning time. Therefore, the comprehensive degree of the cleaning device obtaining the dirt condition of the preset region can be improved by the historical dirt data of the preset sub-region at each cleaning time.

[0048] In some embodiments, the historical cleaning frequency of the preset sub-region can be determined according to the number of historical cleaning dates corresponding to the historical dirt data of the preset sub-region at each cleaning time in a plurality of historical cleaning periods. For example, the historical cleaning period can include a week, a month or other periods, and is not limited thereto. The historical cleaning period can be pre-set or set by the user, and is not limited herein. For example, the historical cleaning period includes at least one historical cleaning date, and the number of historical cleaning dates corresponding to the historical dirt data of the preset sub-region at each cleaning time in each historical cleaning period can determine the historical cleaning frequency of the preset sub-region in each historical cleaning period, for example, according to any one of the highest frequency historical cleaning day, the average number of historical cleaning days, and the median number of historical cleaning days of the preset sub-region in a plurality of historical cleaning periods.

[0049] For example, by obtaining the historical cleaning frequency of the preset sub-region, the estimated dirtiness value of the preset sub-region can be determined for describing the estimated dirtiness condition of the preset region. For example, according to the historical cleaning frequency of the preset sub-region, it can be estimated whether the cleaning device needs to clean the preset sub-region next time soon. For example, if the historical cleaning frequency of the preset sub-region is high, for example, the time interval between the plurality of historical cleaning dates of the preset sub-region is short, for example, the time interval between the plurality of historical cleaning dates can be less than three days, then the cleaning device needs to clean the preset sub-region next time soon, that is, the time interval of the preset sub-region appearing dirty is short. Accordingly, if the historical cleaning frequency of the preset sub-region is low, for example, the time interval between the plurality of historical cleaning dates of the preset sub-region is long, for example, the time interval between the plurality of historical cleaning dates can be greater than or equal to three days, then the cleaning device needs to clean the preset sub-region next time slowly, that is, the time interval of the preset sub-region appearing dirty is long. Therefore, by obtaining the historical cleaning frequency of the preset sub-region, the comprehensive degree of the cleaning device obtaining the dirtiness condition of the preset region can be improved.

[0050] For example, the cleaning parameter includes at least one of the rotation speed of the cleaning element, the pressure of the cleaning element on the surface to be cleaned, the flow rate of water supplied to the cleaning element, the power of the fan suction, and other cleaning parameters. For example, by obtaining the historical cleaning parameter of the preset sub-region at each cleaning, the estimated dirtiness value of the preset sub-region can be determined for describing the estimated dirtiness condition of the preset region. For example, if the historical cleaning parameter of the preset sub-region is large, the cleaning degree of the cleaning device on the preset sub-region is high, and the possibility of the cleaning element of the cleaning device adsorbing a large amount of dirt is high. Accordingly, the smaller the historical cleaning parameter of the preset sub-region, the lower the cleaning degree of the cleaning device on the preset sub-region, and the possibility of the cleaning element of the cleaning device adsorbing a small amount of dirt is high. Therefore, by obtaining the historical cleaning parameter of the preset sub-region at each cleaning, the comprehensive degree of the cleaning device obtaining the dirtiness condition of the preset region can be improved.

[0051] For example, the floor parameter includes at least one of a floor material, floor slip data. In some embodiments, the floor parameter of the preset sub-region is preset, for example, determined by the cleaning device before each cleaning of the preset sub-region, or updated by exploration of the preset sub-region according to a preset exploration period. Generally, the floor parameter does not change frequently, for example, if the floor is covered with a carpet, at least one of the addition of the carpet and the movement of the position will cause the floor parameter of one or more preset sub-regions to change, of course, not limited to this, and therefore, the cleaning device can be set to explore the floor parameter of the preset sub-region at a preset exploration period to periodically update the floor parameter of the preset sub-region, thereby maintaining the timeliness of the floor parameter of the preset sub-region. By obtaining the floor parameter of the preset sub-region, it is beneficial to determine the factor of the floor parameter of the preset sub-region on the historical cleaning parameter of the preset sub-region, or beneficial to determine the factor of the floor parameter of the subsequent preset sub-region on the target cleaning parameter of the preset sub-region, more comprehensively determine the influencing factor of the estimated dirt value of the preset sub-region, so that the cleaning device can improve the comprehensiveness of obtaining the dirt condition of the preset region through the floor parameter of the preset sub-region.

[0052] Optionally, the dirt profile includes at least one of the estimated dirt value, the historical dirt data, the historical stubborn dirt data, the historical cleaning parameter, and the floor parameter of the preset sub-region.

[0053] For example, the dirt profile includes the historical dirt data of the preset sub-region, for example, the historical dirt data of the preset sub-region is determined according to the historical dirt data of the preset sub-region at each cleaning in the historical cleaning data. For example, the historical dirt data of the preset sub-region can be used to describe the historical dirt condition of the preset region, and can also be used to determine the estimated dirt value of the preset sub-region to describe the estimated dirt condition of the preset region, thereby the cleaning device can improve the comprehensiveness of obtaining the dirt condition of the preset region through the dirt profile.

[0054] For example, the dirt profile includes the historical cleaning parameter of the preset sub-region, for example, the historical cleaning parameter of the preset sub-region is determined according to the historical cleaning parameter of the preset sub-region at each cleaning in the historical cleaning data. For example, the historical cleaning parameter of the preset sub-region can be used to determine the estimated dirt value of the preset sub-region to describe the estimated dirt condition of the preset region, thereby the cleaning device can improve the comprehensiveness of obtaining the dirt condition of the preset region through the dirt profile.

[0055] In some embodiments, a dirt decay function corresponding to the preset sub-region is determined according to historical cleaning frequency of the preset sub-region in the historical cleaning data and / or historical dirt data of the preset sub-region at each cleaning; a dirt value estimation weight corresponding to the historical dirt data of the preset sub-region at each cleaning is determined according to historical cleaning parameters of the preset sub-region at each cleaning; an estimated dirt value of the preset sub-region is determined according to the dirt decay function corresponding to the preset sub-region, the historical dirt data of the preset sub-region at each cleaning, and the dirt value estimation weight corresponding to the historical dirt data of the preset sub-region at each cleaning; and a dirt image of the preset region is generated according to the estimated dirt value of the preset sub-region.

[0056] For example, the cleaning parameters include at least one of a rotation speed of a cleaning element, a pressure of the cleaning element on a surface to be cleaned, a flow rate of water supplied to the cleaning element, a power of a fan suction, and other cleaning parameters, wherein the surface to be cleaned includes at least one of the preset region and the preset sub-region. For example, under the action of different cleaning parameters, the dirt on the surface to be cleaned is attached to the cleaning element of the cleaning device with different degrees of difficulty, so that the cleaning degree of the cleaning element of the cleaning device on the surface to be cleaned is different. Accordingly, the historical dirt data obtained according to different historical cleaning parameters can correspond to different dirt value estimation weights when determining the estimated dirt value of the surface to be cleaned, which is beneficial to improve the accuracy of determining the estimated dirt value of the surface to be cleaned.

[0057] For example, the preset region includes a preset sub-region q, for example, the number of historical dirt data of the preset sub-region q on a current date T is n (n>0), the number of types of historical cleaning parameters is K, and the historical dirt data of the preset sub-region at each cleaning is v ij (1≤i≤K,1≤j≤n), wherein the dirt value estimation weight corresponding to different types of cleaning parameters is w i (i=1,2,…,K), then the estimated dirt value of the preset sub-region q can be determined according to the historical dirt data of the preset sub-region q on the date T and the historical cleaning parameters, wherein the calculation formula of the estimated dirt value of the preset sub-region q is, for example:

[0058]

[0059] For example, in order to improve the estimation accuracy of the estimated dirtiness value of the preset sub-region, the estimated dirtiness value of the preset sub-region q can be determined in combination with the historical dirtiness data and the historical cleaning parameters of the preset sub-region q before T day. For example, in order to reflect the timeliness of the historical cleaning data of different historical cleaning dates, the weight of the historical cleaning data of the current date in determining the estimated dirtiness value and the weight of the historical cleaning data before the current date in determining the estimated dirtiness value can be distinguished by a dirtiness decay function. For example, the estimated dirtiness value of the preset sub-region q is W T-1 , the dirtiness decay function is Therefore, the estimated dirtiness value of the preset sub-region q can be determined according to the historical dirtiness data and the historical cleaning parameters of the preset sub-region q at T day, the historical dirtiness data and the historical cleaning parameters of the preset sub-region q before T day, and the dirtiness decay function in combination with the dirtiness decay function, wherein the calculation formula of the estimated dirtiness value of the preset sub-region q is, for example:

[0060]

[0061] For example, γ is used to indicate the dirtiness decay rate of the dirtiness decay function. According to different values of γ, the dirtiness decay rate of the dirtiness decay function is different, wherein the value of γ is, for example, different constants, and of course is not limited thereto.

[0062] Optionally, according to the historical cleaning frequency of the preset sub-region in the historical cleaning data, the dirtiness decay function corresponding to the preset sub-region is determined, including: according to the historical cleaning frequency of the preset sub-region being greater than or equal to a preset cleaning frequency threshold, determining the dirtiness decay function of the preset sub-region as a first dirtiness decay function; according to the historical cleaning frequency of the preset sub-region being less than the preset cleaning frequency threshold, determining the dirtiness decay function of the preset sub-region as a second dirtiness decay function, wherein the dirtiness decay rate of the second dirtiness decay function is higher than the dirtiness decay rate of the first dirtiness decay function.

[0063] For example, the higher the cleaning frequency of the preset sub-region is, the higher the frequency of dirtiness appearing in the preset sub-region is. Therefore, when determining the estimated dirtiness value of the preset sub-region, the dirtiness decay rate of the preset sub-region is lower, the time interval of dirtiness appearing in the preset sub-region can be shorter, or the time of dirtiness appearing is longer, the historical dirtiness data of the preset sub-region can be weighted slower, and therefore the frequency of determining that the cleaning equipment needs to be controlled to clean the preset sub-region according to the estimated dirtiness value of the preset sub-region is higher.

[0064] For example, the lower the preset sub-region's cleaning frequency, the lower the frequency of dirt appearing in the preset sub-region, and thus, the higher the preset sub-region's dirt decay rate when determining the preset sub-region's estimated dirt value, the longer the time interval of dirt appearing in the preset sub-region, or the shorter the time of dirt appearing, the faster the historical dirt data of the preset sub-region can be de-weighted, and thus, the lower the frequency of determining that the cleaning device needs to control cleaning of the preset sub-region according to the preset sub-region's estimated dirt value.

[0065] For example, according to the size relationship between the preset sub-region's historical cleaning frequency and the preset cleaning frequency threshold, the dirt decay rate of the preset sub-region's dirt decay function is distinguished, the dirt decay rate of the first dirt decay function is, for example, 1.5, and the dirt decay rate of the second dirt decay function is, for example, 6.75, so as to improve the estimation accuracy of the preset sub-region's estimated dirt value according to the different dirt decay rates of the dirt decay function.

[0066] Optionally, according to the historical dirt data of the preset sub-region at each cleaning in the historical cleaning data, the preset sub-region's corresponding dirt decay function is determined, including: according to the historical dirt data of the preset sub-region at the last cleaning being greater than or equal to the preset dirt data threshold, and the proportion between the number of historical dirt data of the preset sub-region at each cleaning being greater than or equal to the preset dirt data threshold and the total number of historical dirt data being greater than or equal to the first proportion threshold, the preset sub-region's dirt decay function is determined as the first dirt decay function; according to the historical dirt data of the preset sub-region at the last cleaning being greater than or equal to the preset dirt data threshold, and the proportion between the number of historical dirt data of the preset sub-region at each cleaning being greater than or equal to the preset dirt data threshold and the total number of historical dirt data being less than the first proportion threshold, the preset sub-region's dirt decay function is determined as the second dirt decay function, wherein the dirt decay rate of the second dirt decay function is higher than the dirt decay rate of the first dirt decay function.

[0067] For example, according to the historical dirt data of the preset sub-region at the last cleaning being greater than or equal to the preset dirt data threshold, and the proportion between the number of historical dirt data of the preset sub-region at each cleaning being greater than or equal to the preset dirt data threshold and the total number of historical dirt data being greater than or equal to the first proportion threshold, it is equivalent to most of the historical dirt data of the preset sub-region being a higher dirt value, and a higher dirt value also appears at the last cleaning, in order to maintain the estimation accuracy of the preset dirt value, the historical cleaning data can be de-weighted more slowly.

[0068] For example, according to the historical dirt data of the preset sub-region at each cleaning time in the historical cleaning data, the dirt decay function of the preset sub-region is divided into different dirt decay rates. For example, the value of the dirt decay rate of the first dirt decay function is 1.5, and the value of the dirt decay rate of the second dirt decay function is 6.75, so as to improve the estimation accuracy of the estimated dirt value of the preset sub-region according to the different dirt decay rates of the dirt decay function.

[0069] For example, according to the historical dirt data of the preset sub-region at each cleaning time in the historical cleaning data, the dirt decay function of the preset sub-region is divided into different dirt decay rates. For example, the value of the dirt decay rate of the first dirt decay function is 1.5, and the value of the dirt decay rate of the second dirt decay function is 6.75, so as to improve the estimation accuracy of the estimated dirt value of the preset sub-region according to the different dirt decay rates of the dirt decay function.

[0070] Optionally, according to the historical dirt data of the preset sub-region at each cleaning time in the historical cleaning data, the dirt decay function corresponding to the preset sub-region is determined, including: according to the historical dirt data of the preset sub-region at the last cleaning time being less than the preset dirt data threshold, and the proportion between the number of historical dirt data of the preset sub-region at each cleaning time being less than the preset dirt data threshold and the total number of historical dirt data being greater than or equal to the first proportion threshold, determining the dirt decay function of the preset sub-region as the first dirt decay function; according to the historical dirt data of the preset sub-region at the last cleaning time being less than the preset dirt data threshold, and the proportion between the number of historical dirt data of the preset sub-region at each cleaning time being less than the preset dirt data threshold and the total number of historical dirt data being less than the first proportion threshold, determining the dirt function of the preset sub-region as the second dirt decay function, wherein the dirt decay rate of the second dirt decay function is higher than the dirt decay rate of the first dirt decay function.

[0071] For example, according to the historical dirt data of the preset sub-region at each cleaning time in the historical cleaning data, the dirt decay function of the preset sub-region is divided into different dirt decay rates. For example, the value of the dirt decay rate of the first dirt decay function is 1.5, and the value of the dirt decay rate of the second dirt decay function is 6.75, so as to improve the estimation accuracy of the estimated dirt value of the preset sub-region according to the different dirt decay rates of the dirt decay function.

[0072] For example, according to the historical dirt data of the preset sub-region at each cleaning time in the historical cleaning data, if the historical dirt data of the preset sub-region at the last cleaning time is less than the preset dirt data threshold, and the ratio between the number of historical dirt data less than the preset dirt data threshold and the total number of historical dirt data is less than the first ratio threshold, it means that most of the historical dirt data of the preset sub-region is a relatively high dirt value, and a relatively low dirt value suddenly appears at the last cleaning time. In order to reduce the adverse effect of the suddenly appearing relatively low dirt value on the estimation accuracy of the estimated dirt value, the suddenly appearing relatively low dirt value needs to be weighted more quickly.

[0073] For example, according to the historical dirt data of the preset sub-region at each cleaning time in the historical cleaning data, the dirt decay rate of the preset sub-region is divided into different dirt decay rates of the dirt decay function. For example, the value of the dirt decay rate of the first dirt decay function is 1.5, and the value of the dirt decay rate of the second dirt decay function is 6.75. In this way, the estimation accuracy of the estimated dirt value of the preset sub-region can be improved according to the different dirt decay rates of the dirt decay function.

[0074] Optionally, the dirt image includes historical stubborn dirt data of the preset sub-region. For example, according to the historical cleaning data, the dirt image of the preset region is generated, including: according to the historical dirt data of the preset sub-region at each cleaning time in the historical cleaning data, determining the difference between the historical dirt data; if the difference between the historical dirt data of the preset sub-region is greater than or equal to the preset difference threshold, and the ratio between the number of differences greater than or equal to the preset difference threshold and the total number of differences is greater than or equal to the second ratio threshold, it is determined that the historical stubborn dirt data of the preset sub-region is the first historical stubborn dirt data; if the difference between the historical dirt data of the preset sub-region is less than the preset difference threshold, and the ratio between the number of differences less than the preset difference threshold and the total number of differences is greater than or equal to the second ratio threshold, it is determined that the historical stubborn dirt data of the preset sub-region is the second historical stubborn dirt data, wherein the second historical stubborn dirt data is lower than the first historical stubborn dirt data; and generating the dirt image of the preset region according to the historical stubborn dirt data of the preset sub-region.

[0075] For example, if the difference between the historical dirt data of the preset sub-region is greater than or equal to the preset difference threshold, and the ratio between the number of differences greater than or equal to the preset difference threshold and the total number of differences is greater than or equal to the second ratio threshold, it means that the change between the historical dirt data of the preset sub-region is small after the cleaning device cleans the preset sub-region for multiple times, and the frequency of the small change between the historical dirt data of the preset sub-region is high. Therefore, the dirt in the preset sub-region is not easy to be cleaned by the cleaning device, and the stubborn dirt data of the preset sub-region is high, for example, the historical stubborn dirt data of the preset sub-region is determined as the first historical stubborn dirt data.

[0076] For example, if the difference between the historical dirt data of the preset sub-region is less than the preset difference threshold, and the ratio between the number of differences less than the preset difference threshold and the total number of differences is greater than or equal to the second ratio threshold, it means that the historical dirt data of the preset sub-region changes greatly after the cleaning device cleans the preset sub-region multiple times, and the frequency of the change of the historical dirt data of the preset sub-region is high. The dirt in the preset sub-region is more likely to be cleaned by the cleaning device, and the dirt stubborn data of the preset sub-region is low. For example, the historical dirt stubborn data of the preset sub-region is determined as the second historical dirt stubborn data.

[0077] For example, the estimated dirt value, the historical dirt data, the historical dirt stubborn data, the historical cleaning parameter, and the floor parameter of the preset sub-region can be obtained through the dirt image, which is beneficial to improve the convenience of the cleaning device in obtaining the dirt condition of the preset region. For example, the estimated dirt value, the historical dirt data, the historical dirt stubborn data, the historical cleaning parameter, and the floor parameter of the preset sub-region included in the dirt image can be used to describe at least one of the historical dirt condition, the estimated dirt condition, and the influencing factor of the historical dirt condition of the preset region. The cleaning device can more comprehensively obtain the dirt condition of the preset region, thereby improving the cleaning efficiency and the cleaning effect of the cleaning device, and improving the user experience of using the cleaning device.

[0078] Optionally, the dirt image further includes the estimated cleaning parameter of the preset region. For example, according to the historical cleaning data, generating the dirt image of the preset region further includes: determining the set cleaning parameter of the preset region in the plurality of first preset periods according to the historical cleaning data; and determining the estimated cleaning parameter of the preset region according to the set cleaning parameter of the preset region in the plurality of first preset periods.

[0079] The first preset period may include, for example, one day, one week, one month, or other periods, and is not limited to this. The first preset period may be preset or set by the user, and is not limited herein. For example, the setting cleaning parameter may be a setting cleaning parameter carried by an instruction received by the cleaning device for cleaning the preset area. The estimated cleaning parameter of the preset area may be determined according to any one of a setting cleaning parameter with the highest frequency of occurrence of the preset area in a plurality of first preset periods, an average of setting cleaning parameters of the preset area in the plurality of first preset periods, and a median of setting cleaning parameters of the preset area in the plurality of first preset periods. For example, when the user uses the cleaning device, the user may set the cleaning parameter of the cleaning device. In general, the setting cleaning parameter in the historical cleaning data may reflect the cleaning parameter preference or cleaning parameter habit of the user. Therefore, determining the estimated cleaning parameter of the preset area is beneficial to better meet the setting requirement of the user for the cleaning parameter of the cleaning device, thereby improving the user experience of using the cleaning device.

[0080] Optionally, the dirt image further includes an estimated cleaning frequency of the preset area. For example, the dirt image of the preset area is generated according to the historical cleaning data, and further includes: determining a setting cleaning frequency of the preset area in a plurality of second preset periods according to the historical cleaning data; and determining an estimated cleaning frequency of the preset area according to the setting cleaning frequency of the preset area in the plurality of second preset periods.

[0081] The second preset period may include, for example, one day, one week, one month, or other periods, and is not limited to this. The second preset period may be preset or set by the user, and is not limited herein. For example, the setting cleaning frequency may be a setting cleaning frequency carried by an instruction received by the cleaning device for cleaning the preset area. The estimated cleaning frequency of the preset area may be determined according to any one of a setting cleaning frequency with the highest frequency of occurrence of the preset area in a plurality of second preset periods, an average of setting cleaning frequencies of the preset area in the plurality of first preset periods, and a median of setting cleaning parameters of the preset area in the plurality of first preset periods. For example, when the user uses the cleaning device, the user may set the cleaning frequency of the preset area. In general, the setting cleaning frequency in the historical cleaning data may reflect the cleaning frequency preference or cleaning frequency habit of the user. Therefore, determining the estimated cleaning frequency of the preset area is beneficial to better meet the setting requirement of the user for the cleaning frequency of the cleaning device, thereby improving the user experience of using the cleaning device.

[0082] Optionally, the generating method further comprises: in response to the cleaning of the preset sub-region in the preset region by the cleaning device, acquiring at least one of a target cleaning parameter of the preset sub-region, and cleaning dirt data of the preset sub-region; and updating at least one of the estimated dirt value of the preset sub-region in the dirt image of the preset region, the historical dirt data, the historical stubborn dirt data, and the historical cleaning parameter of the preset sub-region according to the at least one of the target cleaning parameter of the preset sub-region and the cleaning dirt data of the preset sub-region.

[0083] For example, the target cleaning parameter of the preset sub-region is a cleaning parameter determined when the cleaning device cleans the preset sub-region in the preset region, and the historical cleaning parameter of the preset sub-region in the dirt image of the preset region can be updated by acquiring the target cleaning parameter of the preset sub-region. The target cleaning parameter of the preset sub-region is equivalent to the historical cleaning parameter of the preset sub-region at the last cleaning.

[0084] For example, the cleaning dirt data of the preset sub-region is dirt data determined after the cleaning device cleans the preset sub-region in the preset region, and the historical dirt data of the preset sub-region in the dirt image of the preset region can be updated by acquiring the cleaning dirt data of the preset sub-region. The cleaning dirt data of the preset sub-region is equivalent to the historical dirt data of the preset sub-region at the last cleaning.

[0085] In some embodiments, after the dirt image of the preset region is updated according to the at least one of the target cleaning parameter of the preset sub-region and the cleaning dirt data of the preset sub-region, the estimated dirt value or the historical stubborn dirt data of the preset sub-region in the dirt image of the preset region may or may not change. For example, at least one of the estimated dirt value, the historical dirt data, the historical stubborn dirt data, and the historical cleaning parameter of the preset sub-region in the dirt image of the preset region is updated to improve the overall degree and convenience of the cleaning device obtaining the dirt condition of the preset region, thereby improving the cleaning efficiency and cleaning effect of the cleaning device and improving the user experience of using the cleaning device.

[0086] The generating method of the dirt image provided in the above embodiments comprises: acquiring historical cleaning data of a cleaning device for a preset region, wherein the preset region comprises one or more preset sub-regions; and generating a dirt image of the preset region according to the historical cleaning data. According to the dirt image of the preset region, the overall degree and convenience of the cleaning device obtaining the dirt condition of the preset region are improved, thereby improving the cleaning efficiency and cleaning effect of the cleaning device and improving the user experience of using the cleaning device.

[0087] Please refer to Figure 2 , Figure 2is a flowchart of a control method of a cleaning device provided by an embodiment of the present application. The control method of the cleaning device can be applied in a cleaning device system, and is used to control the cleaning device to clean one or more preset sub-areas included in a preset area according to a dirt image of the preset area, so as to improve the cleaning efficiency and cleaning effect of the cleaning device, thereby prolonging the service life of a cleaning element of the cleaning device, improving the effective utilization rate of the cleaning element of the cleaning device, and improving the experience of a user using the cleaning device.

[0088] For example, the cleaning parameter includes at least one of a rotation speed of the cleaning element, a pressure of the cleaning element on a surface to be cleaned, a flow rate of water supplied to the cleaning element, a power of a fan, and other cleaning parameters, wherein the surface to be cleaned includes at least one of the preset area and the preset sub-area. Generally, the cleaning device cleans the preset area with the same cleaning parameter, for example, cleans the preset sub-area in the preset area according to a set cleaning parameter. For example, for the preset sub-area with less dirt or the preset sub-area with more dirt, the cleaning device still cleans them with the set cleaning parameter. For example, in the case that the cleaning device has already cleaned the preset sub-area with less dirt to be clean according to a cleaning parameter smaller than the set cleaning parameter, the cleaning device still cleans the preset sub-area with less dirt with the set cleaning parameter. Or, in the case that the cleaning device needs to clean the preset sub-area with more dirt with a cleaning parameter larger than the set cleaning parameter, the cleaning device still cleans the preset sub-area with more dirt with the set cleaning parameter, which is easy to cause the cleaning efficiency and cleaning effect of the cleaning device to be poor, and is not conducive to the service life of the cleaning element of the cleaning device, reduces the effective utilization rate of the cleaning element of the cleaning device, and thus affects the experience of the user using the cleaning device.

[0089] In general, the cleaning device cleans the preset area according to the same cleaning frequency. For example, the preset sub-area with less dirt or the preset sub-area with more dirt is cleaned according to the set cleaning frequency. For example, in the case that the preset sub-area with less dirt is cleaned by the cleaning device according to the cleaning frequency less than the set cleaning frequency, the preset sub-area with less dirt is still cleaned by the cleaning device according to the set cleaning frequency. For example, in the case that the preset sub-area with more dirt needs to be cleaned by the cleaning device according to the cleaning frequency more than the set cleaning frequency, the preset sub-area with more dirt is still cleaned by the cleaning device according to the set cleaning frequency, which easily leads to poor cleaning efficiency and cleaning effect of the cleaning device, adversely affects the service life of the cleaning part of the cleaning device, reduces the effective utilization rate of the cleaning part of the cleaning device, and thus affects the user experience of using the cleaning device.

[0090] For example, according to the dirt image of the preset area, when the cleaning device cleans the preset sub-area, the cleaning parameter of the cleaning device can be adjusted based on at least one of the estimated dirt value, the historical dirt data, the historical stubborn dirt data, the historical cleaning parameter, and the floor parameter of the corresponding preset sub-area in the dirt image of the preset area, so as to improve the cleaning efficiency and cleaning effect of the cleaning device on the preset sub-area, thereby prolonging the service life of the cleaning part of the cleaning device, improving the effective utilization rate of the cleaning part of the cleaning device, and improving the user experience of using the cleaning device.

[0091] As shown in Figure 2 The control method of the cleaning device of the embodiment of the present application includes steps S210 to S220.

[0092] In step S210, the dirt image of the preset area is obtained, wherein the preset area includes one or more preset sub-areas.

[0093] For example, the plurality of preset sub-areas includes two or more. For example, the obtained dirt image of the preset area can refer to the method for generating the dirt image described in the foregoing embodiments, which will not be described here.

[0094] In step S220, the cleaning device is controlled to clean the preset sub-area according to the dirt image of the preset area.

[0095] For example, the dirt image includes at least one of the estimated dirt value, the historical dirt data, the historical stubborn dirt data, the historical cleaning parameter, and the floor parameter of the preset sub-area.

[0096] Optionally, the cleaning device is controlled to clean the preset sub-region according to the dirt image, including: determining a cleaning parameter influence parameter of the preset sub-region according to at least one of an estimated dirt value of the preset sub-region in the dirt image, historical dirt data, historical stubborn dirt data, historical cleaning parameters, and floor parameters; and controlling the cleaning device to clean the preset sub-region according to the cleaning parameter influence parameter of the preset sub-region.

[0097] Optionally, the cleaning parameter influence parameter is used to indicate how to adjust the estimated cleaning parameter of the cleaning device for the preset region when the cleaning device is controlled to clean different preset sub-regions in the preset region. For example, the cleaning parameter influence parameter can be used to indicate to adjust at least one of a rotation speed of the cleaning element, a pressure of the cleaning element on the preset sub-region, a water flow rate for the cleaning element, a power of the air blower, and other cleaning parameters, but is not limited thereto.

[0098] For example, the higher the estimated dirt value of the preset sub-region, the cleaning parameter influence parameter is used to indicate that at least one of the rotation speed of the cleaning element, the pressure of the cleaning element on the preset sub-region, the water flow rate for the cleaning element, the power of the air blower, and other cleaning parameters needs to be increased to improve the cleaning efficiency of the cleaning device for the preset sub-region while ensuring the cleaning effect of the cleaning device for the preset sub-region. Correspondingly, the lower the estimated dirt value of the preset sub-region, the cleaning parameter influence parameter is used to indicate that at least one of the rotation speed of the cleaning element, the pressure of the cleaning element on the preset sub-region, the water flow rate for the cleaning element, the power of the air blower, and other cleaning parameters needs to be reduced. The cleaning parameter influence parameter of the preset sub-region determined according to the estimated dirt value of the preset sub-region improves the cleaning efficiency and the cleaning effect of the cleaning device for the preset sub-region, thereby prolonging the service life of the cleaning element of the cleaning device, improving the effective utilization rate of the cleaning element of the cleaning device, and improving the user experience of using the cleaning device.

[0099] For example, the higher the historical stubborn stain data of the preset sub-region, the more likely that the dirt in the preset sub-region is not easily cleaned by the cleaning device, and the cleaning parameter influence parameter, for example, at least one of the speed of the cleaning element, the pressure of the cleaning element on the preset sub-region, the flow of water supplied to the cleaning element, the power of the fan suction, or other cleaning parameters, is increased to improve the cleaning efficiency of the cleaning device on the preset sub-region while ensuring the cleaning effect of the cleaning device on the preset sub-region. Correspondingly, the lower the historical stubborn stain data of the preset sub-region, the more likely that the dirt in the preset sub-region is easily cleaned by the cleaning device, and the cleaning parameter influence parameter, for example, at least one of the speed of the cleaning element, the pressure of the cleaning element on the preset sub-region, the flow of water supplied to the cleaning element, the power of the fan suction, or other cleaning parameters, is reduced. The cleaning parameter influence parameter of the preset sub-region determined according to the historical stubborn stain data of the preset sub-region improves the cleaning efficiency and effect of the cleaning device on the preset sub-region, thereby prolonging the service life of the cleaning element of the cleaning device, improving the effective utilization rate of the cleaning element of the cleaning device, and improving the user experience of using the cleaning device.

[0100] For example, when the floor parameter of the preset sub-region indicates that the floor material is not easily wet, or the floor smoothness data is low, for example, the floor is relatively rough, the cleaning parameter influence parameter, for example, at least one of the speed of the cleaning element, the pressure of the cleaning element on the preset sub-region, the flow of water supplied to the cleaning element, the power of the fan suction, or other cleaning parameters, is increased to improve the cleaning efficiency of the cleaning device on the preset sub-region while ensuring the cleaning effect of the cleaning device on the preset sub-region. Correspondingly, when the floor parameter of the preset sub-region indicates that the floor material is easily wet, or the floor smoothness data is high, for example, the floor is relatively smooth, the cleaning parameter influence parameter, for example, at least one of the speed of the cleaning element, the pressure of the cleaning element on the preset sub-region, the flow of water supplied to the cleaning element, the power of the fan suction, or other cleaning parameters, is reduced. The cleaning parameter influence parameter of the preset sub-region determined according to the floor parameter of the preset sub-region improves the cleaning efficiency and effect of the cleaning device on the preset sub-region, thereby prolonging the service life of the cleaning element of the cleaning device, improving the effective utilization rate of the cleaning element of the cleaning device, and improving the user experience of using the cleaning device. In some embodiments, if a carpet is laid in the preset sub-region, at least one of the speed of the cleaning element, the pressure of the cleaning element on the preset sub-region, the flow of water supplied to the cleaning element, the power of the fan suction, or other cleaning parameters is increased to clean the preset sub-region.

[0101] For example, when the cleaning parameter influence parameter of the preset sub-region is determined according to at least one of the estimated dirt value of the preset sub-region in the dirt image, the historical dirt data, the historical stubborn dirt data, the historical cleaning parameter, and the floor parameter, the determination conditions of the cleaning parameter influence parameter are different, and the cleaning parameter influence parameters of the preset sub-region obtained may be the same or different. Of course, the present disclosure is not limited to this. The cleaning parameter influence parameters corresponding to different determination conditions may be pre-set or set by the user, which is not limited herein. In some embodiments, when a plurality of cleaning parameter influence parameters are obtained according to a plurality of determination conditions, the plurality of cleaning parameter influence parameters may be superimposed to determine the cleaning parameter influence parameter of the preset sub-region, thereby facilitating more comprehensive determination of the target cleaning parameter of the preset sub-region.

[0102] Optionally, the dirt image further includes an estimated cleaning parameter of the preset region. For example, the preset sub-region is cleaned by the cleaning device according to the cleaning parameter influence parameter of the preset sub-region, including: determining a target cleaning parameter of the preset sub-region according to the estimated cleaning parameter of the preset region and the cleaning parameter influence parameter of the preset sub-region; and cleaning the preset sub-region by the cleaning device according to the target cleaning parameter of the preset sub-region.

[0103] For example, before the preset sub-region is cleaned, the estimated cleaning parameter may be adjusted according to the cleaning parameter influence parameter of the preset sub-region to obtain the target cleaning parameter of the preset sub-region. Accordingly, for different preset sub-regions, the estimated cleaning parameter is adjusted according to the cleaning parameter influence parameter of each preset sub-region to improve the cleaning efficiency and cleaning effect of the cleaning device on the preset sub-region, thereby facilitating prolonging the service life of the cleaning element of the cleaning device, improving the effective utilization rate of the cleaning element of the cleaning device, and improving the user experience of using the cleaning device.

[0104] In some embodiments, the cleaning parameter influence parameter of the preset sub-region is determined according to the estimated dirtiness value of the preset sub-region in the dirtiness image, including: according to the estimated dirtiness value of the preset sub-region being greater than or equal to an estimated dirtiness value threshold, determining the cleaning parameter influence parameter of the preset sub-region as a first cleaning parameter influence parameter, the first cleaning parameter influence parameter being used to increase the estimated cleaning parameter, i.e., when the cleaning parameter influence parameter of the preset sub-region is the first cleaning parameter influence parameter, the estimated cleaning parameter is increased, and the amount of increase can be set according to actual conditions; according to the estimated dirtiness value of the preset sub-region being less than the preset estimated dirtiness value threshold, determining the cleaning parameter influence parameter of the preset sub-region as a second cleaning parameter influence parameter, the second cleaning parameter influence parameter being used to decrease the estimated cleaning parameter, i.e., when the cleaning parameter influence parameter of the preset sub-region is the second cleaning parameter influence parameter, the estimated cleaning parameter is decreased, and the amount of decrease can be set according to actual conditions. The estimated cleaning parameter includes at least one of the rotational speed of the cleaning element, the pressure of the cleaning element on the surface to be cleaned, the flow rate of water supplied to the cleaning element, and the power of the fan suction.

[0105] For example, the estimated dirtiness value of the preset sub-region being greater than or equal to the estimated dirtiness value threshold means that the estimated dirtiness value of the preset sub-region is relatively high, and the cleaning parameter influence parameter of the preset sub-region is determined as the first cleaning parameter influence parameter to increase the estimated cleaning parameter, and the amount of increase can be set according to actual conditions; the estimated dirtiness value of the preset sub-region being less than the estimated dirtiness value threshold means that the estimated dirtiness value of the preset sub-region is relatively low, and the cleaning parameter influence parameter of the preset sub-region is determined as the second cleaning parameter influence parameter to decrease the estimated cleaning parameter, and the amount of decrease can be set according to actual conditions. By distinguishing the cleaning parameter influence parameters of different preset sub-regions in the preset region, the cleaning effect and cleaning efficiency of each preset sub-region are improved, the service life of the cleaning element of the cleaning equipment is prolonged, the effective utilization rate of the cleaning element of the cleaning equipment is improved, and the user experience of using the cleaning equipment is improved.

[0106] In some embodiments, the cleaning parameter influence parameter of the preset sub-region is determined according to the historical stubborn dirt data of the preset sub-region in the dirt image, including: when the historical stubborn dirt data of the preset sub-region is the first historical stubborn dirt data, the cleaning parameter influence parameter of the preset sub-region is determined as the third cleaning parameter influence parameter, the third cleaning parameter influence parameter is used to increase the estimated cleaning parameter, that is, when the cleaning parameter influence parameter of the preset sub-region is the third cleaning parameter influence parameter, the estimated cleaning parameter is increased, and the amount of increase can be set according to actual conditions; when the historical stubborn dirt data of the preset sub-region is the second historical stubborn dirt data, the cleaning parameter influence parameter of the preset sub-region is determined as the fourth cleaning parameter influence parameter, the fourth cleaning parameter influence parameter is used to decrease the estimated cleaning parameter, that is, when the cleaning parameter influence parameter of the preset sub-region is the fourth cleaning parameter influence parameter, the estimated cleaning parameter is decreased, and the amount of decrease can be set according to actual conditions.

[0107] For example, when the historical stubborn dirt data of the preset sub-region is the first stubborn dirt data, the possibility that the dirt in the preset sub-region is not easily cleaned by the cleaning equipment is larger, the cleaning parameter influence parameter of the preset sub-region is determined as the third cleaning parameter influence parameter to increase the estimated cleaning parameter, and the amount of increase can be set according to actual conditions; when the historical stubborn dirt data of the preset sub-region is the second historical stubborn dirt data, the possibility that the dirt in the preset sub-region is easily cleaned by the cleaning equipment is larger, the cleaning parameter influence parameter of the preset sub-region is determined as the fourth cleaning parameter influence parameter to decrease the estimated cleaning parameter, and the amount of decrease can be set according to actual conditions. By distinguishing the cleaning parameter influence parameters of different preset sub-regions in the preset region, the cleaning effect and cleaning efficiency of each preset sub-region are improved, the service life of the cleaning part of the cleaning equipment is prolonged, the effective utilization rate of the cleaning part of the cleaning equipment is improved, and the user experience of using the cleaning equipment is improved.

[0108] Optionally, the dirt image further includes the estimated cleaning times of the preset region. For example, the control method of the cleaning equipment further includes: ending the cleaning of the preset region when the cleaning times of the preset region by the cleaning equipment reach the estimated cleaning times.

[0109] For example, taking the estimated cleaning times of the preset region as one time as an example, when the estimated cleaning times of the preset region is one time, the actual cleaning times of the preset sub-region by the cleaning equipment can not be one time, that is, the actual cleaning times of each preset sub-region by the cleaning equipment can be different from the estimated cleaning times of the preset region.

[0110] For example, in a case where the cleaning device receives an instruction to clean the preset area, if the number of times of cleaning the preset area by the cleaning device does not reach the estimated number of times of cleaning, it can be determined whether the preset sub-area needs to be cleaned according to the estimated dirt value of the preset sub-area in the dirt image.

[0111] For example, if the estimated dirt value of the preset sub-area is less than the estimated dirt threshold, it is determined that the preset sub-area does not need to be cleaned. At this time, if the estimated number of times of cleaning the preset area is one, the actual number of times of cleaning the preset sub-area is 0.

[0112] For example, if the estimated dirt value of the preset sub-area is greater than or equal to the estimated dirt threshold, it is determined that the preset sub-area needs to be cleaned. After cleaning the preset sub-area that needs to be cleaned, the cleaning dirt data of the preset sub-area can also be obtained, and it can be determined whether the preset sub-area needs to be cleaned repeatedly according to the cleaning dirt data of the preset sub-area. At this time, if the estimated number of times of cleaning the preset area is one, the actual number of times of cleaning the preset sub-area is at least one.

[0113] Therefore, based on the actual number of times of cleaning each preset sub-area by the cleaning device, which can be different from the estimated number of times of cleaning the preset area, the historical cleaning frequency of each preset sub-area included in the preset area can be different.

[0114] In some embodiments, in a case where the number of times of cleaning the preset area by the cleaning device does not reach the estimated number of times of cleaning, as the number of times of cleaning the preset area by the cleaning device increases, the dirt image of the preset area can be updated accordingly, for example, according to the estimated dirt value of the preset sub-area in the updated dirt image, it can be determined whether the preset sub-area needs to be cleaned in this number of times of cleaning the preset area. Therefore, the preset sub-area that needs to be cleaned can be different in different numbers of times of cleaning the preset area by the cleaning device, thereby facilitating to improve the cleaning effect and cleaning efficiency of each preset sub-area, prolong the service life of the cleaning part of the cleaning device, improve the effective utilization rate of the cleaning part of the cleaning device, and thereby improve the user experience of using the cleaning device.

[0115] Optionally, the dirt image further comprises an estimated cleaning parameter of the preset area; and the method further comprises: after controlling the cleaning device to clean the preset sub-area according to the dirt image, obtaining cleaning dirt data of the preset sub-area; determining whether the preset sub-area needs to be repeatedly cleaned according to the cleaning dirt data of the preset sub-area, and determining a repeated cleaning parameter influence parameter corresponding to the preset sub-area in a case where it is determined that the preset sub-area needs to be repeatedly cleaned; determining a target repeated cleaning parameter of the preset sub-area according to the estimated cleaning parameter and the repeated cleaning parameter influence parameter corresponding to the preset sub-area; and controlling the cleaning device to repeatedly clean the preset sub-area according to the target repeated cleaning parameter of the preset sub-area.

[0116] Optionally, the repeated cleaning parameter influence parameter is used to indicate how to adjust the estimated cleaning parameter of the preset area when controlling the cleaning device to repeatedly clean different preset sub-areas in the preset area. For example, the repeated cleaning parameter influence parameter can be used to indicate that at least one of the rotation speed of the cleaning element, the pressure of the cleaning element on the preset sub-area, the flow rate of water supplied to the cleaning element, the power of the air blower, or other cleaning parameters is adjusted, and the application is not limited thereto.

[0117] For example, after controlling the cleaning device to clean the preset sub-area, the cleaning dirt data of the preset sub-area can be used to determine whether the preset sub-area needs to be repeatedly cleaned, and a repeated cleaning parameter influence parameter corresponding to the preset sub-area can be determined in a case where it is determined that the preset sub-area needs to be repeatedly cleaned, so as to adjust the estimated cleaning parameter according to the cleaning dirt data of the preset sub-area, thereby improving the efficiency and effect of repeated cleaning of the preset sub-area, prolonging the service life of the cleaning element of the cleaning device, improving the effective utilization rate of the cleaning element of the cleaning device, and improving the user experience of using the cleaning device.

[0118] In some embodiments, if the cleaning dirt data of the preset sub-area is less than a first preset cleaning dirt data threshold, it is determined that the preset sub-area does not need to be repeatedly cleaned. For example, according to the cleaning dirt data of the preset sub-area being less than the first preset cleaning dirt data threshold, it can be determined that the preset sub-area is relatively clean and does not need to be repeatedly cleaned.

[0119] In some embodiments, if the cleaning dirt data of the preset sub-region is greater than or equal to the first preset cleaning dirt data threshold and less than the second preset cleaning dirt data threshold, it is determined that the preset sub-region needs to be repeatedly cleaned, and the repeated cleaning parameter influence parameter corresponding to the preset sub-region is determined to be the first repeated cleaning parameter influence parameter. The first repeated cleaning parameter influence parameter is used to reduce the estimated cleaning parameter, that is, when the repeated cleaning parameter influence parameter of the preset sub-region is the first repeated cleaning parameter influence parameter, the estimated cleaning parameter is reduced, and the amount of reduction can be set according to actual conditions. For example, according to the cleaning dirt data of the preset sub-region being greater than or equal to the first preset cleaning dirt data threshold and less than the second preset dirt data threshold, it can be determined that there is less dirt in the preset sub-region. In order to prolong the service life of the cleaning element of the cleaning device and improve the effective utilization rate of the cleaning element of the cleaning device, the repeated cleaning parameter influence parameter of the preset sub-region can be determined to be the first repeated cleaning parameter influence parameter, so that the estimated cleaning parameter is reduced, and the amount of reduction can be set according to actual conditions.

[0120] In some embodiments, if the cleaning dirt data of the preset sub-region is greater than or equal to the second preset cleaning dirt data threshold and less than the third preset cleaning dirt data threshold, it is determined that the preset sub-region needs to be repeatedly cleaned, and the repeated cleaning parameter influence parameter corresponding to the preset sub-region is determined to be the third repeated cleaning parameter influence parameter. The third repeated cleaning parameter influence parameter is used to keep the estimated cleaning parameter unchanged, that is, when the repeated cleaning parameter influence parameter of the preset sub-region is the third repeated cleaning parameter influence parameter, the estimated cleaning parameter is kept unchanged. For example, according to the cleaning dirt data of the preset sub-region being greater than or equal to the second preset cleaning dirt data threshold and less than the third preset dirt data threshold, it can be determined that the dirt in the preset sub-region is about the same as the estimated dirt value of the preset sub-region. The repeated cleaning parameter influence parameter of the preset sub-region can be determined to be the third repeated cleaning parameter influence parameter, so that the estimated cleaning parameter is kept unchanged.

[0121] In some embodiments, if the cleaning dirtiness data of the preset sub-region is greater than or equal to a third preset cleaning dirtiness data threshold, it is determined that the preset sub-region needs to be repeatedly cleaned, and the repeated cleaning parameter influence parameter corresponding to the preset sub-region is determined to be a second repeated cleaning parameter influence parameter. The second repeated cleaning parameter influence parameter is used to increase the estimated cleaning parameter, that is, when the repeated cleaning parameter influence parameter of the preset sub-region is the second repeated cleaning parameter influence parameter, the estimated cleaning parameter is increased, and the amount of increase can be set according to actual conditions. For example, according to the cleaning dirtiness data of the preset sub-region being greater than or equal to the third preset cleaning dirtiness data threshold, it can be determined that the dirt in the preset sub-region is more than the estimated dirt value of the preset sub-region. It can be determined that the repeated cleaning parameter influence parameter of the preset sub-region is the second repeated cleaning parameter influence parameter, so as to increase the estimated cleaning parameter. The amount of increase can be set according to actual conditions.

[0122] For example, by distinguishing the repeated cleaning parameter influence parameters of different preset sub-regions in the preset region, the repeated cleaning parameters of the preset sub-regions are adjusted, the repeated cleaning effect and efficiency of the preset sub-regions are improved, the service life of the cleaning components of the cleaning device is prolonged, the effective utilization rate of the cleaning components of the cleaning device is improved, and the user experience of using the cleaning device is improved.

[0123] Optionally, before the cleaning device is controlled to repeatedly clean the preset sub-region according to the target repeated cleaning parameter of the preset sub-region, the method further includes: detecting whether the dirt image of the preset region is updated; and if the dirt image of the preset region is updated, determining the movement path of the cleaning device according to the historical dirtiness data of each preset sub-region in the updated dirt image.

[0124] For example, if the dirt image of the preset region is updated, the historical dirtiness data of each preset sub-region in the updated dirt image includes the historical dirtiness data of the preset sub-region at the last cleaning. For example, the corresponding preset sub-region can be bypassed according to the historical dirtiness data of the preset sub-region at the last cleaning, so as to reduce the risk of dirtying the cleaned preset sub-region, thereby prolonging the service life of the cleaning components of the cleaning device, improving the effective utilization rate of the cleaning components of the cleaning device, and improving the user experience of using the cleaning device.

[0125] The control method of the cleaning device provided in the above embodiments includes obtaining a dirt image of a preset region, wherein the preset region includes one or more preset sub-regions; and controlling a cleaning device to clean the preset sub-region according to the dirt image of the preset region, so as to improve the cleaning efficiency and effect of the cleaning device, thereby prolonging the service life of the cleaning components of the cleaning device, improving the effective utilization rate of the cleaning components of the cleaning device, and improving the user experience of using the cleaning device.

[0126] Please refer to the above embodiments Figure 3 , Figure 3 A schematic block diagram of a dirty image generation device 300 provided by an embodiment of the present application is shown. The generation device 300 comprises a processor 301 and a memory 302.

[0127] For example, the processor 301 and the memory 302 are connected by a bus 303, such as an I2C (Inter-integrated Circuit) bus.

[0128] Specifically, the processor 301 can be a microcontroller unit (MCU), a central processing unit (CPU) or a digital signal processor (DSP), etc.

[0129] Specifically, the memory 302 can be a flash chip, a read-only memory (ROM) disk, an optical disk, a U disk or a mobile hard disk, etc.

[0130] The processor 301 is configured to run a computer program stored in the memory 302, and implement the steps of the dirty image generation method described above when executing the computer program.

[0131] For example, the processor 301 is configured to run a computer program stored in the memory 302, and implement the following steps when executing the computer program:

[0132] Obtain historical cleaning data of a cleaning device on a preset area, wherein the preset area comprises one or more preset sub-areas;

[0133] According to the historical cleaning data, generate a dirty image of the preset area.

[0134] The specific principles and implementation manners of the generation device 300 provided by the embodiment of the present application are similar to the dirty image generation method of the above-mentioned embodiments, and will not be repeated here.

[0135] Please refer to the above embodiments Figure 4 , Figure 4 A schematic block diagram of a control device 400 of a cleaning device provided by an embodiment of the present application is shown. The control device 400 comprises a processor 401 and a memory 402.

[0136] The processor 401 and the memory 402 are connected by a bus 403, such as an I2C (Inter-integrated Circuit) bus.

[0137] Specifically, the processor 401 can be a micro-controller unit (MCU), a central processing unit (CPU), or a digital signal processor (DSP), etc.

[0138] Specifically, the memory 402 can be a flash chip, a read-only memory (ROM) disk, an optical disk, a U disk, or a mobile hard disk, etc.

[0139] The processor 401 is configured to run a computer program stored in the memory 402, and implement the steps of the control method of the cleaning device when executing the computer program.

[0140] The processor 401 is configured to run a computer program stored in the memory 402, and implement the following steps when executing the computer program.

[0141] Obtain a dirt image of a preset area, wherein the preset area includes one or more preset sub-areas.

[0142] Control the cleaning device to clean the preset sub-areas according to the dirt image of the preset area.

[0143] The specific principles and implementation manners of the control device 400 provided by the embodiments of the present application are similar to the control method of the cleaning device of the foregoing embodiments, and will not be described here.

[0144] Please refer to Figure 5 , Figure 5 is a schematic block diagram of a cleaning device system provided by the embodiments of the present application.

[0145] As Figure 5 shown, the cleaning device system includes one or more cleaning devices 100, one or more base stations 200, a dirt image generation device 300, and / or a control device 400 of the cleaning device. The cleaning device 100 includes a movement mechanism and a cleaning piece, for example. The movement mechanism of the cleaning device 100 is configured to drive the cleaning device 100 to move, so that the cleaning piece cleans a preset cleaning area. For example, when the movement mechanism drives the cleaning device 100 to move, the cleaning piece contacts the preset cleaning area to clean the preset cleaning area during the movement of the cleaning device 100.

[0146] In some embodiments, the base station 200 is configured to cooperate with the cleaning device 100, for example, the base station 200 can charge the cleaning device 100, the base station 200 can provide a parking position for the cleaning device 100, etc. The base station 200 can also clean the cleaning element of the cleaning device 100.

[0147] Referring to Figure 6 , Figure 6 is a schematic block diagram of a cleaning device system according to another embodiment of the present application.

[0148] As shown in Figure 6 , the cleaning device system comprises one or more cleaning devices 100, a dirty map generation apparatus 300, and / or a cleaning device control apparatus 400.

[0149] For example, the cleaning device 100 comprises a movement mechanism, a cleaning element, and a maintenance mechanism. The movement mechanism is configured to drive the cleaning device 100 to move so that the cleaning element cleans a preset cleaning area. The maintenance mechanism is configured to clean the cleaning element.

[0150] Referring to Figure 5 and Figure 6 , the dirty map generation apparatus 300 can be configured to implement the steps of the dirty map generation method according to the embodiments of the present application; the cleaning device control apparatus 400 can be configured to implement the steps of the cleaning device control method according to the embodiments of the present application.

[0151] Optionally, the cleaning device 100 is provided with a device controller for controlling the cleaning device 100, and the base station 200 is provided with a base station controller for controlling the base station 200. In some embodiments, the device controller of the cleaning device 100 and / or the base station controller of the base station 200 can be used alone or in combination as the dirt image generation apparatus 300 for implementing the steps of the dirt image generation method of the embodiments of the present application; in some embodiments, the device controller of the cleaning device 100 and / or the base station controller of the base station 200 can be used alone or in combination as the cleaning device control apparatus 400 for implementing the steps of the cleaning device control method of the embodiments of the present application. In other embodiments, the cleaning device system includes a separate dirt image generation apparatus 300 for implementing the steps of the dirt image generation method of the embodiments of the present application, which can be provided on the cleaning device 100 or on the base station 200; in other embodiments, the cleaning device system includes a separate cleaning device control apparatus 400 for implementing the steps of the cleaning device control method of the embodiments of the present application, which can be provided on the cleaning device 100 or on the base station 200; of course, it is not limited thereto, for example, at least one of the dirt image generation apparatus 300 and the cleaning device control apparatus 400 can be an apparatus other than the cleaning device 100 and the base station 200, such as a home smart terminal, a master control device, etc.

[0152] The cleaning device 100 can be used to automatically clean a preset area, and the application scenarios of the cleaning device 100 can be household indoor cleaning, large-scale site cleaning, etc.

[0153] The specific principles and implementation manners of the cleaning device system provided by the embodiments of the present application are similar to at least one of the aforementioned dirt image generation method and cleaning device control method, which will not be described herein.

[0154] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to make the processor implement the steps of the aforementioned dirt image generation method, or the computer program is executed by a processor to make the processor implement the steps of the aforementioned cleaning device control method.

[0155] The computer readable storage medium can be an internal storage unit of at least one of the dirt map generation apparatus and the control apparatus of the cleaning device, for example, a hard disk or a memory of at least one of the dirt map generation apparatus and the control apparatus of the cleaning device. The computer readable storage medium can also be an external storage device of at least one of the dirt map generation apparatus and the control apparatus of the cleaning device, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like.

[0156] In some embodiments, the dirt map generation apparatus can be configured to implement the steps of the dirt map generation method according to the embodiments of the present application, and the control apparatus of the cleaning device can be configured to implement the steps of the control method of the cleaning device according to the embodiments of the present application.

[0157] The specific principles and implementation manners of the cleaning device system provided by the embodiments of the present application are similar to at least one of the dirt map generation method and the control method of the cleaning device of the foregoing embodiments, and thus will not be described herein.

[0158] It should be understood that the terms used in the present application are merely for the purpose of describing specific embodiments and are not intended to limit the present application.

[0159] It should also be understood that the term "and / or" used in the present application and the appended claims means any combination of one or more of the associated listed terms and all possible combinations, and includes these combinations.

[0160] The above merely describes specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method of generating a dirty map, characterized by, The method comprises: obtaining historical cleaning data of a cleaning device for a preset area, wherein the preset area comprises one or more preset sub-areas; generating a dirt image of the preset area according to the historical cleaning data; the dirt image comprises an estimated dirt value of the preset sub-area; the generating of the dirt image of the preset area according to the historical cleaning data comprises: determining a dirt decay function corresponding to the preset sub-area according to a historical cleaning frequency of the preset sub-area and / or historical dirt data of the preset sub-area at each cleaning in the historical cleaning data; determining a dirt value estimation weight corresponding to the historical dirt data of the preset sub-area at each cleaning according to a historical cleaning parameter of the preset sub-area at each cleaning in the historical cleaning data; determining the estimated dirt value of the preset sub-area according to the dirt decay function corresponding to the preset sub-area, the historical dirt data of the preset sub-area at each cleaning, and the dirt value estimation weight corresponding to the historical dirt data of the preset sub-area at each cleaning; generating the dirt image of the preset area according to the estimated dirt value of the preset sub-area.

2. The generation method of claim 1, wherein, The determining of the dirt decay function corresponding to the preset sub-area according to the historical cleaning frequency of the preset sub-area in the historical cleaning data comprises: determining that the dirt decay function of the preset sub-area is a first dirt decay function according to that the historical cleaning frequency of the preset sub-area is greater than or equal to a preset cleaning frequency threshold; determining that the dirt decay function of the preset sub-area is a second dirt decay function according to that the historical cleaning frequency of the preset sub-area is less than the preset cleaning frequency threshold, wherein a dirt decay rate of the second dirt decay function is higher than a dirt decay rate of the first dirt decay function.

3. The generation method of claim 1, wherein, The determining of the dirt decay function corresponding to the preset sub-area according to the historical dirt data of the preset sub-area at each cleaning in the historical cleaning data comprises: determining that the dirt decay function of the preset sub-area is a first dirt decay function according to that the historical dirt data of the preset sub-area at the last cleaning is greater than or equal to a preset dirt data threshold, and a proportion between a number of the historical dirt data of the preset sub-area that is greater than or equal to the preset dirt data threshold and a total number of the historical dirt data is greater than or equal to a first proportion threshold; determining that the dirt decay function of the preset sub-area is a second dirt decay function according to that the historical dirt data of the preset sub-area at the last cleaning is greater than or equal to the preset dirt data threshold, and the proportion between the number of the historical dirt data of the preset sub-area that is greater than or equal to the preset dirt data threshold and the total number of the historical dirt data is less than the first proportion threshold, wherein a dirt decay rate of the second dirt decay function is higher than a dirt decay rate of the first dirt decay function.

4. The generation method of claim 1, wherein, The determining of the dirt decay function corresponding to the preset sub-area according to the historical dirt data of the preset sub-area at each cleaning in the historical cleaning data comprises: determining the dirt decay function of the preset sub-region as a first dirt decay function according to the historical dirt data of the preset sub-region at the last cleaning being less than a preset dirt data threshold and a ratio between a number of historical dirt data less than the preset dirt data threshold and a total number of historical dirt data being greater than or equal to a first ratio threshold; determining the dirt decay function of the preset sub-region as a second dirt decay function according to the historical dirt data of the preset sub-region at the last cleaning being less than a preset dirt data threshold and a ratio between a number of historical dirt data less than the preset dirt data threshold and a total number of historical dirt data being less than a first ratio threshold, wherein an attenuation speed of the second dirt decay function is higher than a dirt decay speed of the first dirt decay function.

5. The generation method of claim 1, wherein, the dirt image further comprises historical dirt stubborn data of the preset sub-region; the generating the dirt image of the preset region according to the historical cleaning data comprises: determining a difference between the historical dirt data of the preset sub-region at each cleaning according to the historical cleaning data; determining the historical dirt stubborn data of the preset sub-region as first historical dirt stubborn data according to the difference between the historical dirt data of the preset sub-region being greater than or equal to a preset difference threshold and a ratio between a number of differences greater than or equal to the preset difference threshold and a total number of differences being greater than or equal to a second ratio threshold; determining the historical dirt stubborn data of the preset sub-region as second historical dirt stubborn data according to the difference between the historical dirt data of the preset sub-region being less than a preset difference threshold and a ratio between a number of differences less than the preset difference threshold and a total number of differences being greater than or equal to a second ratio threshold, wherein the second historical dirt stubborn data is lower than the first historical dirt stubborn data; generating the dirt image of the preset region according to the historical dirt stubborn data of the preset sub-region.

6. The generation method of claim 1, wherein, the dirt image further comprises an estimated cleaning parameter of the preset region; the generating the dirt image of the preset region according to the historical cleaning data further comprises: determining a set cleaning parameter of the preset region in a plurality of first preset periods according to the historical cleaning data; determining the estimated cleaning parameter of the preset region according to the set cleaning parameter of the preset region in the plurality of first preset periods.

7. The generation method of claim 1, wherein, the dirt image further comprises an estimated cleaning frequency of the preset region; the generating the dirt image of the preset region according to the historical cleaning data further comprises: determining a set cleaning frequency of the preset region in a plurality of second preset periods according to the historical cleaning data; determining the estimated cleaning frequency of the preset region according to the set cleaning frequency of the preset region in the plurality of second preset periods.

8. The generation method of any one of claims 1 to 7, wherein, the generating method further comprises: in response to the cleaning of the preset sub-region in the preset region by the cleaning device, acquiring at least one of a target cleaning parameter of the preset sub-region and cleaning dirt data of the preset sub-region; Based on at least one of the target cleaning parameters of the preset sub-region and the cleaning and dirt data of the preset sub-region, update at least one of the following in the dirt profile of the preset region: the estimated dirt value of the preset sub-region, historical dirt data, historical stubborn dirt data, and historical cleaning parameters of the preset sub-region.

9. A control method of a cleaning apparatus, characterized by, include: Obtain a dirty image of a preset area, wherein the preset area includes one or more preset sub-areas; Based on the dirt image of the preset area, control the cleaning equipment to clean the preset sub-area; The dirt image of the preset area is generated based on the estimated dirt value of the preset sub-area; The estimated dirt value of the preset sub-region is determined based on the dirt decay function corresponding to the preset sub-region, the historical dirt data of the preset sub-region during each cleaning, and the estimated dirt value weight corresponding to the historical dirt data of the preset sub-region during each cleaning. The dirt decay function corresponding to the preset sub-area is determined based on the historical cleaning frequency of the preset sub-area in the historical cleaning data of the preset area by the cleaning equipment and / or the historical dirt data of the preset sub-area during each cleaning. The estimated weight of the dirt value corresponding to the historical dirt data of the preset sub-area during each cleaning is determined based on the historical cleaning parameters of the preset sub-area during each cleaning in the historical cleaning data.

10. The control method according to claim 9, characterized by The dirt profile includes at least one of the following: estimated dirt value of a preset sub-area, historical dirt data, historical stubborn dirt data, historical cleaning parameters, and floor parameters; The step of controlling the cleaning equipment to clean the preset sub-area based on the dirt image includes: Based on at least one of the following: the estimated dirt value of the preset sub-area in the dirt profile, historical dirt data, historical stubborn dirt data, historical cleaning parameters, and floor parameters, determine the cleaning parameter influence parameters of the preset sub-area. Based on the cleaning parameters of the preset sub-area, the cleaning equipment is controlled to clean the preset sub-area.

11. The control method according to claim 10, characterized by, The dirty image also includes estimated cleaning parameters for a preset area; The step of controlling the cleaning equipment to clean the preset sub-area based on the cleaning parameter influence parameters of the preset sub-area includes: Based on the estimated cleaning parameters of the preset area and the cleaning parameter influence parameters of the preset sub-area, the target cleaning parameters of the preset sub-area are determined; Based on the target cleaning parameters of the preset sub-area, the cleaning equipment is controlled to clean the preset sub-area.

12. The control method according to claim 10, characterized by, The step of determining the cleaning parameter influencing parameters of the preset sub-region based on the estimated dirt value of the preset sub-region in the dirt image includes: Based on the fact that the estimated dirt value of the preset sub-region is greater than or equal to the preset estimated dirt value threshold, the cleaning parameter influence parameter of the preset sub-region is determined as the first cleaning parameter influence parameter, which is used to increase the estimated cleaning parameter. If the estimated dirt value of the preset sub-region is less than the preset estimated dirt value threshold, the cleaning parameter influencing parameter of the preset sub-region is determined as the second cleaning parameter influencing parameter. The second cleaning parameter influencing parameter is used to reduce the estimated cleaning parameter.

13. The control method according to claim 10, characterized by, The step of determining the cleaning parameter influencing parameters of the preset sub-area based on the historical stubborn dirt data of the preset sub-area in the dirt profile includes: Based on the historical stubborn dirt data of the preset sub-area as the first historical stubborn dirt data, the cleaning parameter influence parameter of the preset sub-area is determined as the third cleaning parameter influence parameter, which is used to increase the estimated cleaning parameter. Based on the historical stubborn dirt data of the preset sub-area as the second historical stubborn dirt data, the cleaning parameter influencing parameter of the preset sub-area is determined as the fourth cleaning parameter influencing parameter. The fourth cleaning parameter influencing parameter is used to reduce the estimated cleaning parameter.

14. The control method according to claim 9, characterized by, The dirty image also includes an estimated number of cleaning cycles for the preset area; The control method further includes: The cleaning of the preset area ends when the cleaning equipment has cleaned the preset area a predetermined number of times.

15. The control method according to any one of claims 9 to 14, characterized by, The dirty image also includes estimated cleaning parameters for a preset area; After controlling the cleaning equipment to clean the preset sub-area according to the dirt image, the process further includes: Obtain the cleaning and dirt data of the preset sub-area; Based on the cleaning and dirt data of the preset sub-area, determine whether the preset sub-area needs to be cleaned repeatedly, and if it is determined that the preset sub-area needs to be cleaned repeatedly, determine the repeat cleaning parameter influence parameter corresponding to the preset sub-area. Based on the estimated cleaning parameters and the repeated cleaning parameter influence parameters corresponding to the preset sub-area, the target repeated cleaning parameters of the preset sub-area are determined; Based on the target repeated cleaning parameters of the preset sub-area, the cleaning equipment is controlled to repeatedly clean the preset sub-area.

16. The control method according to claim 15, characterized by The step of determining whether the preset sub-area needs repeated cleaning based on the cleaning and dirt data of the preset sub-area, and determining the repeated cleaning parameter influencing parameters corresponding to the preset sub-area when it is determined that the preset sub-area needs repeated cleaning, includes: If the cleaning and dirt data of the preset sub-area is greater than or equal to the first preset cleaning and dirt data threshold and less than the second preset cleaning and dirt data threshold, it is determined that the preset sub-area needs to be cleaned repeatedly, and the repeated cleaning parameter influence parameter corresponding to the preset sub-area is determined to be the first repeated cleaning parameter influence parameter, which is used to reduce the estimated cleaning parameter. If the cleaning and dirt data of the preset sub-region is greater than or equal to the third preset cleaning and dirt data threshold, it is determined that the preset sub-region needs to be cleaned repeatedly, and the repeated cleaning parameter influence parameter corresponding to the preset sub-region is determined to be the second repeated cleaning parameter influence parameter, which is used to increase the estimated cleaning parameter.

17. The control method according to claim 15, characterized by, Before controlling the cleaning device to repeatedly clean the preset sub-area according to the target repeat cleaning parameters of the preset sub-area, the method further includes: Detect whether the dirty image of the preset area has been updated; If the dirt image of the preset area is updated, the movement path of the cleaning equipment is determined based on the historical dirt data corresponding to each preset sub-area in the updated dirt image.

18. A device for generating a dirty map, characterized by The generation apparatus comprises a memory and a processor; The memory is configured to store a computer program; The processor is configured to execute the computer program and implement the steps of the method for generating a dirty map according to any one of claims 1 to 8 when executing the computer program.

19. A control device for a cleaning apparatus, characterized in that The control apparatus comprises a memory and a processor; The memory is configured to store a computer program; The processor is configured to execute the computer program and implement the steps of the method for controlling a cleaning device according to any one of claims 9 to 17 when executing the computer program.

20. A cleaning apparatus system characterized by, The method comprises: a cleaning device comprising a movement mechanism and a cleaning element, the movement mechanism being configured to drive the cleaning device to move so that the cleaning element cleans a preset cleaning area; a base station configured to clean the cleaning element of the cleaning device; the generation apparatus for generating a dirty map according to claim 18; and / or the control apparatus for a cleaning device according to claim 19.

21. A cleaning apparatus system characterized by, The method comprises: a cleaning device comprising a movement mechanism, a cleaning element, and a maintenance mechanism, the movement mechanism being configured to drive the cleaning device to move so that the cleaning element cleans a preset cleaning area, and the maintenance mechanism being configured to clean the cleaning element; the generation apparatus for generating a dirty map according to claim 18; and / or the control apparatus for a cleaning device according to claim 19.

22. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program, when executed by a processor, causes the processor to implement the steps of the method for generating a dirty map according to any one of claims 1 to 8, or the computer program, when executed by a processor, causes the processor to implement the steps of the method for controlling a cleaning device according to any one of claims 9 to 17.

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