A setting method of a robot sweeper, the robot sweeper and a storage medium

Abstract

The application discloses a setting method of a sweeping robot, the sweeping robot and a computer readable storage medium. The setting method of the sweeping robot comprises the following steps: obtaining historical data; wherein the historical data comprises date information, time period information, environment information and setting parameters, the date information is used for indicating a workday or a holiday, the time period information is used for indicating a time period in a day, the environment information is used for indicating a working environment of the sweeping robot, and the setting parameters comprise at least one of suction setting parameters and water speed setting parameters; determining setting probabilities corresponding to different setting parameters according to the historical data; determining a setting parameter corresponding to a maximum setting probability as a recommended setting parameter, so that the sweeping robot is set by using the recommended setting parameter. In the foregoing manner, the maximum probability setting parameter of the sweeping robot used by the user under different conditions is counted, the default setting parameter of the sweeping robot is more suitable for actual application, and therefore, the user can use the sweeping robot conveniently.

Description

Technical Field

[0001] This application relates to the field of smart home appliance technology, and in particular to a method for setting up a robotic vacuum cleaner, the robotic vacuum cleaner itself, and a computer-readable storage medium. Background Technology

[0002] With the continuous development of artificial intelligence technology, more and more smart products are being widely used in daily life, such as intelligent voice control, smart home assistants, robot vacuums, electric curtains, and other smart home products. Among them, robot vacuums, also known as sweeping robots, can automatically clean the floors of areas that need cleaning without user intervention through intelligent control.

[0003] Currently, cleaning robots typically plan their cleaning route across the entire area. However, due to the cyclical and habitual nature of user usage, coupled with external environmental factors and holidays, cleaning robots may not be able to perform targeted and effective cleaning based on their default operating parameters. This can lead to the robot repeatedly traversing the cleaning process multiple times, resulting in low cleaning efficiency and unsatisfactory cleaning results. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method for setting up a robotic vacuum cleaner, the robotic vacuum cleaner itself, and a computer-readable storage medium, which enables the default settings parameters of the robotic vacuum cleaner to be more diverse and better suited to actual application scenarios, facilitating user operation and enhancing the user experience.

[0005] One technical solution adopted in this application is: providing a method for setting up a robotic vacuum cleaner, the method comprising: acquiring historical data; wherein the historical data includes date information, time period information, environmental information, and setting parameters, the date information being used to represent weekdays or rest days, the time period information representing a time period within a day, the environmental information being used to represent the working environment of the robotic vacuum cleaner, and the setting parameters including at least one of suction setting parameters and water speed setting parameters; determining the setting probability corresponding to different setting parameters based on the historical data; and determining the setting parameter corresponding to the maximum setting probability as the recommended setting parameter, so that the robotic vacuum cleaner can be set using the recommended setting parameter.

[0006] Optionally, acquiring historical data includes: acquiring historical data within a first preset number of days; determining the most recent setting parameter within the first preset number of days that is a weekday or rest day for each historical data within a second preset number of days; arranging the historical data within the second preset number of days and the most recent setting parameter within the first preset number of days that is a weekday or rest day according to different time periods of each day to form a historical data wide table; wherein, a preset number of days from any one day to the end date is extracted within the first preset number of days to form the second preset number of days range.

[0007] Optionally, obtaining historical data within a first preset number of days includes: obtaining date information, time period information, environmental information, and setting parameters within the first preset number of days; wherein, the date information includes the usage dates of the robot vacuum cleaner within the first preset number of days, the time period information includes the corresponding usage time period within the usage dates, the environmental information includes the corresponding environmental humidity and / or environmental temperature within the usage dates, and the setting parameters include at least one of the suction setting parameters and water speed setting parameters set within the usage dates.

[0008] Optionally, the historical data within the second preset number of days and the most recent setting parameters within the first preset number of days that are both on weekdays or rest days are arranged in sections according to different time periods of each day to form a historical data wide table. This includes: classifying environmental information according to environmental humidity and / or environmental temperature to obtain historical environmental levels; and arranging at least one of the following: the usage date is a weekday or rest day; the time period corresponding to the usage date; the historical environmental level corresponding to the usage date; the suction setting parameter and water speed setting parameter set on the usage date; and the most recent setting parameters within the first preset number of days that are both on weekdays or rest days, according to different time periods of each day to form a historical data wide table.

[0009] Optionally, after acquiring historical data, the method further includes: acquiring environmental information for the next day; and classifying the environmental information for the next day according to environmental humidity and / or environmental temperature to obtain the environmental level for the next day.

[0010] Optionally, determining the setting probability corresponding to different setting parameters based on historical data includes: using the most recent setting parameter within the first preset number of days in historical environmental information, time period information, and date information that the usage date is a weekday or rest day, as well as the setting parameter that is a weekday or rest day within the first preset number of days in historical data, as feature conditions to determine the setting probability of the setting parameter corresponding to different time periods; and determining the setting probability of the setting parameter corresponding to different time periods on the next day based on the setting probability of the setting parameter corresponding to different time periods and the environmental level of the next day.

[0011] Optionally, the method further includes: in response to the existence of no most recent setting parameter that is a workday or rest day within a first preset number of days in the historical data, filling the most recent setting parameter of the date corresponding to the date that is not a most recent setting parameter that is a workday or rest day into the most recent setting parameter that is a workday or rest day within the first time range.

[0012] Optionally, the method further includes: in response to the existence of a setting parameter in the historical data that is not most recently set on the same workday or rest day within a first time range, deleting the setting parameter in the historical data that is most recently set on the same workday or rest day within the first time range.

[0013] Another technical solution adopted in this application is: to provide a sweeping robot, which includes a processor and a memory connected to the processor, wherein the memory stores program data, and the processor retrieves the program data stored in the memory to execute the sweeping robot setting method as described above.

[0014] Another technical solution adopted in this application is to provide a computer-readable storage medium that stores program data, which, when executed by a processor, is used to implement the above-described method for setting up a sweeping robot.

[0015] The method for setting up a robotic vacuum cleaner provided in this application includes: acquiring historical data; wherein the historical data includes date information, time period information, environmental information, and setting parameters, the date information represents weekdays or rest days, the time period information represents a time period within a day, the environmental information represents the working environment of the robotic vacuum cleaner, and the setting parameters include at least one of suction setting parameters and water speed setting parameters; determining the setting probability corresponding to different setting parameters based on the historical data; and determining the setting parameter corresponding to the maximum setting probability as the recommended setting parameter, so that the robotic vacuum cleaner can use the recommended setting parameter for setup. Through the above method, the maximum probability of a user using different setting parameters of the robotic vacuum cleaner under different date information, time period information, environmental information, and setting parameter conditions is statistically analyzed, making the default setting parameters of the robotic vacuum cleaner more diverse and closer to actual application scenarios, thereby facilitating user use and enhancing the user experience. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0017] Figure 1This is a flowchart illustrating an embodiment of the method for setting up a robotic vacuum cleaner provided in this application;

[0018] Figure 2 This is a flowchart illustrating an embodiment of acquiring historical data;

[0019] Figure 3 This is a flowchart illustrating an embodiment of creating a wide table of historical data;

[0020] Figure 4 This is a schematic diagram of an embodiment of a historical data wide table;

[0021] Figure 5 This is a flowchart illustrating an embodiment of obtaining the environmental level for the following day;

[0022] Figure 6 This is a flowchart illustrating the first embodiment of determining the setting probability corresponding to different setting parameters;

[0023] Figure 7 This is a flowchart illustrating the second embodiment for determining the setting probability corresponding to different setting parameters;

[0024] Figure 8 This is a flowchart illustrating the third embodiment for determining the setting probability corresponding to different setting parameters;

[0025] Figure 9 This is a schematic diagram of an embodiment of generating a recommended setting parameter table;

[0026] Figure 10 This is a structural schematic diagram of a sweeping robot provided in this application;

[0027] Figure 11 This is a schematic diagram of an embodiment of the computer-readable storage medium provided in this application. Detailed Implementation

[0028] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It is understood that the specific embodiments described herein are only for explaining this application and not for limiting it. Furthermore, it should be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all structures. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0029] The terms "first," "second," etc., used in this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0030] The term "embodiment" as used in this application means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0031] Furthermore, although the terms "first," "second," etc., are used repeatedly in this application to describe various thresholds (or various components, or various applications, or various instructions, or various operations), these thresholds (or components, or applications, or instructions, or operations) should not be limited by these terms. These terms are only used to distinguish one threshold (or component, or application, or instruction, or operation) from another threshold (or component, or application, or instruction, or operation). For example, a first preset number of days range can be referred to as a second preset number of days range, and a second preset number of days range can also be referred to as a first preset number of days range, without departing from the scope of this application. Both the first preset number of days range and the second preset number of days range are operations, only they are not the same preset number of days range.

[0032] The steps in the embodiments of this application are not necessarily processed in the order described. The steps can be rearranged, deleted, or added as needed. The step descriptions in the embodiments of this application are only optional combinations of sequences and do not represent all possible combinations of steps in the embodiments of this application. The order of steps in the embodiments should not be considered as a limitation of this application.

[0033] The term "and / or" in the embodiments of this application refers to any and all possible combinations including one or more of the associated listed items. It should also be noted that, when used in this specification, "including / comprising" specifies the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, and / or components and / or groups thereof.

[0034] Users' use of robot vacuums is somewhat cyclical and habitual, and is also easily affected by external environment, holidays and other factors. Traditional robot vacuums directly use the suction power and water speed settings from the most recent settings, without taking into account the impact of external environment and holidays on user settings. As a result, the recommended suction power and water speed settings are not ideal, and users are unaware of them.

[0035] Therefore, this application provides a method for setting up a robotic vacuum cleaner, which can statistically determine the maximum probability of a user setting the suction power and water speed of the robotic vacuum cleaner under different conditions (weekdays, rest days, time of day, ambient humidity, etc.), and then, when the device is started, it will default to running at the maximum probability water speed and suction power.

[0036] See Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the method for setting up a robotic vacuum cleaner provided in this application. The method includes:

[0037] Step 11: Obtain historical data.

[0038] Specifically, it acquires historical data recorded and statistically analyzed by the robot vacuum itself. This historical data includes date information, time period information, environmental information, and setting parameters.

[0039] Optionally, historical data can be obtained from a cloud server or locally from sensors mounted on the robot vacuum. For example, to obtain environmental information from historical data, the robot vacuum can connect to a weather forecast server via a network and receive current, past, or future environmental information from the server, such as weather conditions for a future period or historical rain tables for a past period. Alternatively, the robot vacuum can be equipped with a recorder, sensors, and a positioning module. The sensors and positioning module can obtain the robot's current environmental information and location, and the recorder can record various data daily to form historical data.

[0040] The date information includes the date the robot vacuum cleaner worked, indicating whether it was a weekday or a day off. For example, if a date in the historical data is December 12th, it means that the robot vacuum cleaner worked on December 12th (Sunday), a day off.

[0041] The time period information includes the working time period of the robot vacuum cleaner on a specific date, that is, the time period within a day. For example, if a time period in the historical data is T2, it means that the robot vacuum cleaner performed cleaning work during the T2 time period of the corresponding date. Optionally, each day can be divided into four time periods, where T1 represents 0-5 am, T2 represents 6-11 am, T3 represents 12-5 pm, and T4 represents 6-11 pm.

[0042] The settings parameters include at least one of the following: suction power settings and water flow settings. The suction power setting parameter indicates the robot's strength in picking up debris, while the water flow setting parameter indicates the amount of water used for mopping. These settings can be manually configured by the user or automatically generated by the robot based on probability values ​​of the maximum set parameters.

[0043] Environmental information describes the working environment of the robotic vacuum cleaner, including factors such as the type of floor surface to be cleaned, ambient temperature, humidity, and PM2.5 levels. For example, in actual use, robotic vacuum cleaners often encounter various floor conditions. Most household floors are made of ceramic tiles, which allow for a relatively large water flow rate without damaging the floor. However, some household floors are made of wood, requiring a lower water flow rate to prevent softening, swelling, and deformation. When cleaning carpeted floors, the water flow rate should be zero; the robot should only sweep and not mop. Besides these examples, other floor types impose restrictions on water flow rate. Therefore, before setting the water flow rate, the type of floor the robotic vacuum cleaner will be cleaning should be determined first.

[0044] For example, in actual use, the daily ambient humidity may vary. When the ambient humidity is relatively dry, the water consumption for cleaning should be greater, and the water flow rate should also be set higher. When the ambient humidity is relatively humid, the water consumption for cleaning should be less, and the water flow rate should also be set lower.

[0045] Optionally, environmental information may include not only the type of surface being cleaned, ambient temperature, ambient humidity, or PM2.5 levels, but also geographical location, weather conditions, and seasonal characteristics. For example, on rainy days, high humidity makes it difficult for surface moisture to evaporate, leading to water accumulation exceeding safe limits and causing damage. Therefore, the water flow rate should be reduced during rainy weather. Similarly, in hot regions, both high ambient temperature and high humidity make surface moisture difficult to evaporate, and the water flow rate should also be reduced in these areas.

[0046] Optionally, the robotic vacuum cleaner in this application may include multiple devices located in multiple different areas. For example, acquiring historical data may involve simultaneously acquiring historical data from two robotic vacuum cleaners and their two different locations. The two robotic vacuum cleaners are designated by numbers 01 and 02, and the two different locations of 01 and 02 are designated by codes a1 and a2.

[0047] See Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of acquiring historical data. Step 11 specifically includes:

[0048] Step 111: Obtain historical data within the first preset number of days.

[0049] Specifically, date information, time period information, environmental information, and setting parameters are obtained within the first preset number of days.

[0050] The first preset number of days is the range of days from a previous date to the current date. For example, if the current date is December 28th, the first preset number of days is set to 28 days, meaning that the first preset number of days includes all days from December 1st to December 28th.

[0051] The date information includes the usage dates of the robot vacuum cleaner within a first preset number of days (e.g., the usage dates include each day from December 1st to December 28th), the time period information includes the corresponding usage time period for each usage date, the environmental information includes the corresponding environmental humidity and / or environmental temperature for each usage date, and the setting parameters include at least one of the suction setting parameters and water speed setting parameters set for each usage date.

[0052] Step 112: Determine the most recent setting parameter for each historical data within the second preset number of days, which is either a weekday or a rest day within the first preset number of days.

[0053] Specifically, a second preset number of days is formed by selecting any one day from the first preset number of days to the end date. For example, the first preset number of days includes all days from December 1st to December 28th. The second number of days is the range of days starting from any one day (such as December 15th) within the period from December 1st to December 28th, and ending on the end date (December 28th). In other words, the second number of days includes all days from December 15th to December 28th.

[0054] Specifically, the setting parameters for the most recent historical data for each day within the second preset number of days that falls on either a weekday or a rest day within the first preset number of days need to be determined. For example, the first preset number of days includes all days from December 1st to December 28th. The second preset number of days includes all days from December 15th to December 28th. It is necessary to determine the setting parameters for the most recent historical data for December 28th (a weekday) that falls on either a weekday within the range of December 1st to December 28th. This means determining the setting parameters for December 27th (December 27th is the most recent weekday among December 28th). Alternatively, it is necessary to determine the setting parameters for the most recent historical data for December 18th (a rest day) that falls on either a rest day within the range of December 1st to December 28th. This means determining the setting parameters for December 11th (December 11th is the most recent rest day among December 18th).

[0055] Step 113: Arrange the historical data within the second preset number of days and the most recent setting parameters within the first preset number of days that are both weekdays or rest days into a wide historical data table by partitioning the data according to different time periods of each day.

[0056] See Figure 3 , Figure 3 This is a flowchart illustrating an embodiment of forming a historical data wide table. Step 113 specifically includes:

[0057] Step 1131: Classify the ambient humidity and / or ambient temperature in the environmental information to obtain the historical environmental level.

[0058] Specifically, the robotic vacuum cleaner categorizes the ambient humidity and / or ambient temperature from the environmental information into high and low levels to obtain the historical environmental level for each day within a second preset number of days. The historical environmental level includes temperature and / or humidity levels.

[0059] Optionally, humidity levels are set from low to high as 0, 1, and 2. Humidity level 0 is when the maximum humidity is below 40%; humidity level 2 is when the minimum humidity is above 80%; and humidity level 1 is when the minimum humidity is above 40% and the maximum humidity is below 80%. Temperature levels are set from low to high as a, b, and c. Temperature level a is when the maximum temperature is below 10℃; temperature level c is when the minimum temperature is above 30℃; and temperature level b is when the minimum temperature is above 10℃ and the maximum temperature is below 30℃. For example, if the minimum humidity on December 11th is 45% and the maximum humidity is 60%, then the humidity level on December 11th is 1. If the minimum temperature on December 11th is 15℃ and the maximum humidity is 28℃, then the temperature level on December 11th is b.

[0060] Step 1132: Arrange the following parameters according to different time periods of each day: whether the usage date is a weekday or a rest day, the time period corresponding to the usage date, the historical environmental level corresponding to the usage date, at least one of the suction setting parameters and water speed setting parameters set during the usage date, and the most recent setting parameter within the first preset number of days that is a weekday or a rest day, to form a historical data wide table.

[0061] See Figure 4 , Figure 4 This is a schematic diagram of an embodiment of a historical data wide table. The historical data wide table has 10 columns. The first column is the device ID, used to distinguish different robotic vacuum cleaners; in this embodiment, there is only one robotic vacuum cleaner, 01. The second column is the region where the corresponding robotic vacuum cleaner is located, represented by a1 to an. The third column is the water speed setting parameter for each day within a second preset number of days for the corresponding robotic vacuum cleaner. The fourth column is the suction power setting parameter for each day within the second preset number of days for the corresponding robotic vacuum cleaner. The fifth column is the usage time period for each day within the second preset number of days for the corresponding robotic vacuum cleaner, represented by T1, T2, T3, and T4. The sixth column is the usage date of the corresponding robotic vacuum cleaner within the second preset number of days for the corresponding robotic vacuum cleaner. The seventh column indicates whether the corresponding usage date is a weekday or a rest day. The eighth column is the most recent water speed setting parameter for the corresponding usage date that is also a weekday or a rest day. The ninth column is the most recent suction power setting parameter for the corresponding usage date that is also a weekday or a rest day. The tenth column is the humidity level in the historical environmental ratings for each day within the second preset number of days for the corresponding robotic vacuum cleaner.

[0062] Optionally, the water speed setting parameters and suction power setting parameters in the historical data wide table can be represented by the mode based on the same time period. For example, within the second preset number of days, if the robot vacuum cleaner was used on the dates D1, D2, and D3 within the first time period, and the mode of its water speed setting parameter is w2, then the water speed setting parameter for the first time period in the historical data wide table will all be w2.

[0063] Following the historical data wide table, the probability of each different setting parameter appearing under different characteristic conditions can be calculated. If the environmental level of the following day is obtained, the probability of different setting parameters appearing within different time periods under the environmental level of the following day can be derived.

[0064] See Figure 5 , Figure 5 This is a flowchart illustrating an embodiment of obtaining the environmental level for the following day.

[0065] Step a1: Obtain environmental information for the following day.

[0066] Step a2: Classify the environmental humidity and / or environmental temperature in the environmental information of the next day to obtain the environmental level of the next day.

[0067] The methods for obtaining environmental information and determining the environmental level of the following day are similar to those for obtaining environmental information and determining the corresponding environmental level from historical data in the above embodiments, and will not be described again here.

[0068] Step 12: Determine the setting probability corresponding to different setting parameters based on historical data.

[0069] See Figure 6 , Figure 6 This is a flowchart illustrating the first embodiment for determining the setting probability corresponding to different setting parameters. Step 12 specifically includes:

[0070] Step 121a: Using the historical environment information, time period information, and date information where the usage date is a weekday or rest day, and the most recent setting parameter within the first preset number of days in the historical data that is also a weekday or rest day, as feature conditions, determine the setting probability of the setting parameter corresponding to different time periods.

[0071] Specifically, the historical environment information, time period information, and date information in the historical data wide table, where the usage date is a weekday or rest day, and the most recent setting parameter within the first preset number of days in the historical data that is also a weekday or rest day, are used as the feature conditions of the conditional feature function to calculate the setting probability of the setting parameter corresponding to different time periods.

[0072] In one embodiment, the conditional characteristic function is:

[0073] P(waterlevel=wx, fanlevel=fy|(area=au, time_level=time_level_i, if_holiday=dj, humidity_level=hk, fanlevel_before_sim=fsm, waterlevel_before_sim=wsn)).

[0074] In this formula, `waterlevel` represents the water speed parameter setting, denoted as `wx`, where `wx` takes the values ​​`w1`, `w2`, `w3`, and `w4`. `fanlevel` represents the suction parameter setting, denoted as `fy`, where `fy` takes the values ​​`f1`, `f2`, `f3`, and `f4`. `area` represents the region where the robot vacuum is located, where `au` takes the values ​​`a1` through `an`. `Level` represents the time period information, where `time_level_i` takes the values ​​`time_level_1`, `time_level_2`, `time_level_3`, and `time_level_4`. `if_holiday` indicates whether it is a rest day, where `dj` takes the values ​​`d0` (for rest days) and `d1` (for weekdays). `humidity_level` represents the humidity level, where `hk` takes the values ​​`h0`, `h1`, and `h2`. `fanlevel_before_sim` represents the most recent suction setting parameter for a weekday or rest day, where the suction setting parameter `fsm` takes the values ​​`fs1`, `fs2`, `fs3`, and `fs4`. `waterlevel_before_sim` represents the water speed setting parameters for the most recent weekday or rest day, with the setting value `wsn` taking the values ​​`ws1`, `ws2`, `ws3`, and `ws4`. Specifically, the suction parameter setting value for time period `time_level_1` is `f1`, and the water speed parameter setting value is `w1`; the suction parameter setting value for time period `time_level_2` is `f2`, and the water speed parameter setting value is `w2`; the suction parameter setting value for time period `time_level_3` is `f3`, and the water speed parameter setting value is `w3`; and the suction parameter setting value for time period `time_level_4` is `f4`, and the water speed parameter setting value is `w4`. `P(waterlevel = wx, fanlevel = fy)` represents the probability that `wx` takes the value of `w1`, `w2`, `w3`, or `w4`, and `fy` takes the values ​​of `f1`, `f2`, `f3`, and `f4`.

[0075] In another embodiment, assuming that the region, whether it is a weekday or not, time period, humidity level, the most recent suction setting on a weekday or rest day, and the most recent water speed setting on a weekday or rest day are independent of each other, the conditional probability of water speed setting under different characteristic conditions can be expressed by Equation 1-1:

[0076] P0(wh)=P(waterlevel=wh|(area=ai, time_level=time_level_i, if_holiday=dj, humidity_level=hk, fanlevel_before_sim=fsm, waterlevel_before_sim=wsn)).

[0077] In Formula 1-1, the values ​​of wh are w1, w2, w3, and w4; the value of ai is the code of all cities; the values ​​of dj are d0 (rest day) and d1 (work day); the values ​​of hk are h0, h1, and h2; the values ​​of time_level_i are time_level_1, time_level_2, time_level_3, and time_level_4; the values ​​of fsm are fs1, fs2, fs3, and fs4; and the values ​​of wsn are ws1, ws2, ws3, and ws4.

[0078] Furthermore, from Formula 1-1, Formula 1-2 can be derived as follows:

[0079] P0(wh)=P((area=ai, time_level=time_level_i, if_holiday=dj, humidity_level=hk, fanlevel_before_sim=fsm, waterlevel_before_sim=wsn)|waterlevel=w h)*P(waterlevel=wh) / P(area=ai, time_level=time_level_i, if_holiday=dj, humidity_level=hk, fanlevel_before_sim=fsm, waterlevel_before_sim=wsn).

[0080] Furthermore, due to the assumption of independence, Formula 1-3 can be derived from Formula 1-2, as follows:

[0081] P0((area=ai, time_level=time_level_i, if_holiday=dj, humidity_level=hk, fanlevel_before_sim=fsm, waterlevel_before_sim=wsn)|waterlevel=wh)=P(area=ai|waterlevel=wh)*P(time_level=tim e_level_i|waterlevel=wh)*P(if_holiday=dj|waterlevel=wh)*P(humidity_level=hk|waterlevel=wh)*P(fanlevel_before_sim=fsm|waterlevel=wh)*P(waterlevel_before_sim=wsn|waterlevel=wh).

[0082] Furthermore, from formula 1-3, formula 1-4 can be derived as follows:

[0083] P0(area=ai, time_level=time_level_i, if_holiday=dj, humidity_level=hk, fanlevel_before_sim=fsm, waterlevel_before_sim=wsn)=P(area= ai)*P(time_level=time_level_i)*P(if_holiday=dj)*P(humidity_level=hk)*P(fanlevel_before_sim=fsm)*P(waterlevel_before_sim=wsn).

[0084] Combining formulas 1-1 to 1-4 above, the conditional probabilities of water velocity settings under different characteristic conditions can be obtained, as expressed by formula 1-5, as follows:

[0085] P(wh)=P(area=ai|waterlevel=wh)*P(time_level=time_level_i|waterlevel=wh)*P(if_holiday=dj|waterlevel=wh)*P(humidity_level=hk|waterlevel=wh)*P(fanlevel_before_sim=fsm|waterlevel=wh)*P(waterl evel_before_sim=wsn|waterlevel=wh)*P(waterlevel=wh) / ((P(area=ai)*P(time_level=time_level_i)*P(if_holiday=dj)*P(humidity_level=hk)*P(fanlevel_before_sim=fsm)*P(waterlevel_before_sim=wsn)).

[0086] Similarly, the conditional probabilities of suction settings under different characteristic conditions can be obtained, as expressed by Formula 1-6, as follows:

[0087] P(fp)=P(area=ai|fanlevel=fp)*P(time_level=time_level_i|fanlevel=fp)*P(if_holiday=dj|fanlevel=fp)*P(humidity_level=hk|fanlevel=fp)*P(fanlevel_before_sim=fsm|fanlevel=fp)*P(waterlevel l_before_sim=wsn|fanlevel=fp)*P(fanlevel=fp) / ((P(area=ai)*P(time_level=time_level_i)*P(if_holiday=dj)*P(humidity_level=hk)*P(fanlevel_before_sim=fsm)*P(waterlevel_before_sim=wsn)).

[0088] In formulas 1-6, the values ​​of fp are f1, f2, f3, and f4.

[0089] Step 122a: Determine the setting probability of the setting parameters for different time periods on the following day based on the setting probability of the setting parameters for different time periods and the environmental level of the following day.

[0090] In one embodiment, if the environmental level of the following day is represented by humidity level h1, then, under the condition of humidity level h1, the setting probability P of the setting parameter corresponding to different time periods of the following day is calculated based on the setting probability P (waterlevel = wx, fanlevel = fy) or P(wh) and P(fp) corresponding to different time periods obtained from historical data. In one embodiment, the calculated setting probability P of the setting parameter corresponding to different time periods of the following day includes: P1(wh = w1), P1(wh = w2), P1(wh = w3), P1(wh = w4), P2(fp = f1), P2(fp = f2), P2(fp = f3), and P2(fp = f4).

[0091] Optionally, for each historical data within the second preset number of days, the values ​​of the most recent suction setting and the most recent water speed setting within the first preset number of days, which are both on a weekday or a rest day, are the settings for the same usage time period of the corresponding robot vacuum cleaner on the corresponding usage date.

[0092] For example, within the second preset number of days (December 15 to December 28), the historical data for December 18 (a rest day) shows that the most recent suction setting or the most recent water speed setting that was a rest day within the first preset number of days (December 1 to December 28) is the value of the most recent suction setting or water speed setting that was a workday or rest day within the same time period of the four rest days of December 4, 5, 11 and 12.

[0093] Please continue reading. Figure 4 If, within the second preset number of days, historical data for at least one day contains no recent suction setting or water speed setting that was a weekday or rest day within the first preset number of days—meaning there are empty values ​​for either the most recent suction setting or water speed setting that was a weekday or rest day across the historical data tables—then the conditional probability value obtained by the calculation function in the above embodiment is inaccurate. To correct this inaccuracy, this application also provides two correction methods.

[0094] See Figure 7 , Figure 7 This is a flowchart illustrating the second embodiment for determining the setting probability corresponding to different setting parameters. Step 12 specifically includes:

[0095] Step 121b: In response to the existence of no most recent setting parameter that is a workday or rest day within the first preset number of days in the historical data, fill the most recent setting parameter of the date corresponding to the date that is not a most recent setting parameter that is a workday or rest day into the most recent setting parameter that is a workday or rest day within the first time range.

[0096] For example, within the second preset number of days (December 15th to December 28th), the historical data for December 18th (a rest day) does not contain any suction settings that were most recent on a rest day, or any water speed settings that were most recent on a workday or rest day within the first preset number of days (December 1st to December 28th). Specifically, there are no suction settings or water speed settings for the same time period on the four rest days of December 4th, 5th, 11th, and 12th. Therefore, the suction setting or water speed setting value corresponding to the most recent date of December 18th (i.e., December 17th) will be filled into the historical data wide table's most recent setting parameters for the same workday or rest day on December 18th.

[0097] Step 122b: Using the historical environment information, time period information, and date information where the usage date is a weekday or rest day, and the most recent setting parameter within the first preset number of days in the historical data that is also a weekday or rest day, as feature conditions, determine the setting probability of the setting parameter corresponding to different time periods.

[0098] Step 123b: Based on the setting probability of the setting parameters corresponding to different time periods and the environmental level of the following day, determine the setting probability of the setting parameters corresponding to different time periods of the following day.

[0099] Steps 122b and 123b are similar to steps 121a and 122a in the above embodiments, and will not be described again here.

[0100] See Figure 8 , Figure 8 This is a flowchart illustrating the third embodiment for determining the setting probability corresponding to different setting parameters. Step 12 specifically includes:

[0101] Step 121c: In response to the existence of a setting parameter in the historical data that is not most recent on the same workday or rest day within the first time range, delete the setting parameter most recent on the same workday or rest day within the first time range of the historical data.

[0102] For example, within the second preset number of days (December 15th to December 28th), the historical data for December 18th (a rest day) shows no recent suction setting or water speed setting that was also a rest day within the first preset number of days (December 1st to December 28th). Specifically, there are no suction settings or water speed settings for the same time period on the four rest days of December 4th, 5th, 11th, and 12th. Therefore, all historical data within the second preset number of days will have their corresponding most recent setting parameters for the same workday or rest day deleted from the first time period. This means deleting the two columns of data in the historical data wide table that show the most recent setting parameters for the same workday or rest day.

[0103] Step 122c: Use the usage date (working day or rest day) from the historical environment information, time period information, and date information as a feature condition to determine the setting probability of the setting parameters corresponding to different time periods.

[0104] In one embodiment, its conditional characteristic function is:

[0105] P1(waterlevel=wx,fanlevel=fy|(area=au,time_level=time_level_i,if_holiday=dj,humidity_level=hk)). Here, P1 represents the probability that wx takes the values ​​w1, w2, w3, or w4, and fy takes the values ​​f1, f2, f3, or f4.

[0106] In another embodiment, the conditional probability of suction setting under different characteristic conditions can be calculated according to formulas 1-1 to 1-6 in the above embodiments:

[0107] P2(fp)=P(area=ai|fanlevel=fp)*P(time_level=time_level_i|fanlevel=fp)*P(if_holiday=dj|fanlevel=fp)*P(humidity_lev el=hk|fanlevel=fp)*P(fanlevel=fp) / ((P(area=ai)*P(time_level=time_level_i)*P(if_holiday=dj)*P(humidity_level=hk)).

[0108] And the conditional probabilities of water velocity settings under different characteristic conditions:

[0109] P1(wh)=P(area=ai|waterlevel=wh)*P(if_holiday=dj|waterlevel=wh)*P(humidity_level=hk|waterlevel=wh)*P(waterlevel=wh)*P( time_level=time_level_i|waterlevel=wh) / ((P(area=ai)*P(time_level=time_level_i)*P(if_holiday=dj)*P(humidity_level=hk)).

[0110] Step 123c: Based on the setting probability of the setting parameters corresponding to different time periods and the environmental level of the following day, determine the setting probability of the setting parameters corresponding to different time periods of the following day.

[0111] Steps 122c and 123c are similar to steps 121a and 122a in the above embodiments, and will not be described again here.

[0112] Step 13: Determine the setting parameters corresponding to the maximum setting probability as the recommended setting parameters so that the robot vacuum cleaner can use the recommended setting parameters for settings.

[0113] Specifically, given the environmental level of the following day, the setting probabilities P of the setting parameters for different time periods are calculated based on the setting probabilities of different time periods derived from historical data. For each time period, the setting parameter with the highest setting probability is set as the recommended setting parameter. This yields the recommended suction power and / or water speed setting parameters for the device at different time periods of the following day, ensuring that the robot vacuum cleaner uses these recommended suction power and / or water speed setting parameters by default when starting operation at different times of the following day.

[0114] In one embodiment, the calculated probabilities P of setting parameters for different time periods on the following day include: P1(wh=w1), P1(wh=w2), P1(wh=w3), P1(wh=w4), P2(fp=f1), P2(fp=f2), P2(fp=f3), and P2(fp=f4). Among these, the wh with the highest probability value among P1(wh=w1), P1(wh=w2), P1(wh=w3), and P1(wh=w4) is the recommended water speed setting, and the fp with the highest probability value among P2(fp=f1), P2(fp=f2), P2(fp=f3), and P2(fp=f4) is the recommended suction setting.

[0115] Optionally, the recommended suction power and / or water speed settings for different time periods on the following day can be calculated and stored by the processor and memory mounted on the robot vacuum, or they can be calculated by a cloud server connected to the robot vacuum and pushed to the robot vacuum with the corresponding ID for storage. After the robot vacuum obtains the recommended suction power and / or water speed settings for different time periods on the following day, it can integrate the recommended values, the corresponding date, and the corresponding time period to generate a recommended setting parameter table, so that it can operate according to the settings in the recommended setting parameter table during the corresponding time period on the following day.

[0116] See Figure 9 , Figure 9This is a schematic diagram illustrating an embodiment of generating a recommended setting parameter table. The recommended setting parameter table has five columns of data. The first column is the device ID, used to distinguish different robotic vacuum cleaners; in this embodiment, there is only one robotic vacuum cleaner, 01. The second column is the corresponding time period for the robotic vacuum cleaner on the following day, represented by T1, T2, T3, and T4. The third column is the usage date of the following day, i.e., December 29th. The fourth column is the recommended water speed setting parameter for the corresponding time period on the following day. The fifth column is the recommended suction power setting parameter for the corresponding time period on the following day.

[0117] Unlike existing technologies, the robot vacuum cleaner setting method provided in this application includes: acquiring historical data; wherein the historical data includes date information, time period information, environmental information, and setting parameters, the date information represents weekdays or rest days, the time period information represents a time period within a day, the environmental information represents the working environment of the robot vacuum cleaner, and the setting parameters include at least one of suction setting parameters and water speed setting parameters; determining the setting probability corresponding to different setting parameters based on the historical data; and determining the setting parameter corresponding to the maximum setting probability as the recommended setting parameter, so that the robot vacuum cleaner can use the recommended setting parameter for setting. Through the above method, on the one hand, considering various factors such as different usage time periods, environmental levels, and whether the usage time is a weekday or rest day, the maximum probability of a user using the corresponding setting parameters of the robot vacuum cleaner is calculated, making the default setting parameters of the robot vacuum cleaner more diverse and closer to actual application scenarios, thereby facilitating user use and enhancing the user experience. On the other hand, by filling in missing setting parameters from the most recent time that are also from a weekday or rest day, or deleting the most recent setting parameters from the most recent time that are also from a weekday or rest day, the calculated maximum probability setting parameter value can be corrected, thereby improving the practicality of the robot vacuum cleaner.

[0118] See Figure 10 , Figure 10 This is a schematic diagram of the structure of a sweeping robot provided in this application. The sweeping robot 100 includes a processor 101 and a memory 102 connected to the processor 101. The memory 102 stores program data. The processor 101 retrieves the program data stored in the memory 102 to execute the above-described setting method for the sweeping robot.

[0119] In one embodiment, the sweeping robot 100 can be a cleaning robot, or it can be converted into a detection robot, a guidance robot, a path inspection robot, or other intelligent terminal, depending on its parameter setting method; no limitation is made here. The sweeping robot 100 may include a communication module, such as 4G, 5G, or WIFI, for establishing a wireless communication connection with a server, enabling the server to remotely control and interact with the sweeping robot 100. For example, the sweeping robot 100 can be used in public places such as service halls, or in private places such as homes. It establishes a wireless communication connection with a server and can receive control commands sent by the server or control commands derived from its own programs and algorithms, executing corresponding working parameters and tasks according to the control commands.

[0120] Optionally, in one embodiment, the processor 101 is used to execute program data to implement the following method: acquiring historical data; wherein the historical data includes date information, time period information, environmental information, and setting parameters, the date information is used to represent a weekday or rest day, the time period information is used to represent a time period in a day, the environmental information is used to represent the working environment of the robot vacuum cleaner, and the setting parameters include at least one of suction setting parameters and water speed setting parameters; determining the setting probability corresponding to different setting parameters based on the historical data; determining the setting parameter corresponding to the maximum setting probability as the recommended setting parameter, so that the robot vacuum cleaner can use the recommended setting parameter for setting.

[0121] The processor 101 can also be referred to as a CPU (Central Processing Unit). The processor 101 may be an electronic chip with signal processing capabilities. The processor 101 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0122] The memory 102 can be a RAM stick, TF card, etc., and can store all the information in the robot vacuum cleaner 100, including the input raw data, computer program, intermediate running results, and final running results. It stores and retrieves information according to the location specified by the processor 101. With the memory 102, the robot vacuum cleaner 100 has a memory function and can ensure normal operation. The memory 102 of the robot vacuum cleaner 100 can be classified according to its purpose as main memory (RAM) and auxiliary memory (external memory), or it can be classified as external memory and internal memory. External memory is usually magnetic media or optical discs, which can store information for a long time. RAM refers to the storage component on the motherboard, used to store currently executing data and programs, but it is only used for temporary storage of programs and data; the data will be lost when the power is turned off or disconnected.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed methods and apparatus can be implemented in other ways. The implementation of the sweeping robot 100 described above is merely illustrative. For example, the categories and quantity of historical data, or the calculation method for determining the setting probability corresponding to different setting parameters based on historical data, are merely one set of methods. In actual implementation, there may be other ways of dividing the data, such as combining multiple types of historical data with other relevant data, or integrating them into another system, or ignoring or not executing some features.

[0124] Furthermore, the functional units (such as processor 101, memory 102, or environmental data acquisition module) in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0125] See Figure 11 , Figure 11 This is a schematic diagram of an embodiment of a computer-readable storage medium provided in this application. The computer-readable storage medium 110 stores program instructions 111 capable of implementing all the above methods.

[0126] If the integrated units of the various functional units in the various embodiments of this application are implemented as software functional units and sold or used as independent products, they can be stored in the computer-readable storage medium 110. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer-readable storage medium 110 includes several instructions in a program instruction 111 to cause a computer device (which may be a personal computer, system server, or network device, etc.), an electronic device (e.g., MP3, MP4, etc., or a mobile terminal such as a mobile phone, tablet, or wearable device, or a desktop computer, etc.) or a processor to execute all or part of the steps of the methods of the various embodiments of this application.

[0127] Optionally, in one embodiment, when the program instruction 111 is executed by the processor, it is used to implement the following method: acquiring historical data; wherein the historical data includes date information, time period information, environmental information, and setting parameters, the date information is used to represent a weekday or rest day, the time period information is used to represent a time period in a day, the environmental information is used to represent the working environment of the sweeping robot, and the setting parameters include at least one of suction setting parameters and water speed setting parameters; determining the setting probability corresponding to different setting parameters based on the historical data; determining the setting parameter corresponding to the maximum setting probability as the recommended setting parameter, so that the sweeping robot can use the recommended setting parameter for setting.

[0128] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media 110 (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0129] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable storage medium 110. These computer-readable storage media 110 can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that program instructions 111, executable by the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0130] These computer-readable storage media 110 may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that program instructions 111 stored in the computer-readable storage medium 110 produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0131] These computer-readable storage media 110 may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing program instructions 111 that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0132] The above description is merely an embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for setting up a robotic vacuum cleaner, characterized in that, include: Acquire historical data and environmental information for the following day; wherein, the historical data includes date information, time period information, environmental information and setting parameters, the date information is used to represent a weekday or rest day, the time period information represents a time period in a day, the environmental information is used to represent the working environment of the sweeping robot, and the setting parameters include at least one of suction setting parameters and water speed setting parameters; The environmental humidity and / or environmental temperature in the environmental information of the following day are classified to obtain the environmental level of the following day; Using the environmental information, the time period information, the date information (where the usage date is a weekday or a rest day), and the most recent setting parameter within a first preset number of days in the historical data that is also a weekday or a rest day as feature conditions, the setting probability of setting parameters corresponding to different time periods is determined. Based on the setting probability of the setting parameters corresponding to different time periods and the environmental level of the following day, determine the setting probability of the setting parameters corresponding to different time periods of the following day. The setting parameter corresponding to the maximum setting probability is determined as the recommended setting parameter, so that the robot vacuum cleaner can use the recommended setting parameter for setting; The acquisition of historical data includes: Obtain the historical data within a first preset number of days; For each historical data point within the second preset number of days, the most recent setting parameter that is a weekday or rest day within the first preset number of days is determined. The historical data within the second preset number of days and the most recent setting parameters within the first preset number of days that are both weekdays or rest days are arranged in partitions according to different time periods of each day to form a wide historical data table. Specifically, a preset number of days is selected from any one day to the end date within the first preset number of days range to form the second preset number of days range.

2. The method according to claim 1, characterized in that, The acquisition of the historical data within the first preset number of days includes: Obtain the date information, time period information, environmental information, and setting parameters within the first preset number of days; The date information includes the usage dates of the robot vacuum cleaner within the first preset number of days; the time period information includes the usage time period corresponding to the usage dates; the environmental information includes the environmental humidity and / or environmental temperature corresponding to the usage dates; and the setting parameters include at least one of the suction setting parameters and the water speed setting parameters corresponding to the usage dates.

3. The method according to claim 2, characterized in that, The step of arranging the historical data within the second preset number of days and the most recent setting parameters within the first preset number of days that are both weekdays or rest days into a wide historical data table by partitioning them according to different time periods of each day includes: The ambient humidity and / or ambient temperature are classified to obtain historical environmental levels; The historical data wide table is formed by arranging the usage date (whether it is a weekday or a rest day), the time period corresponding to the usage date, the historical environmental level corresponding to the usage date, at least one of the suction setting parameter and the water speed setting parameter set on the usage date, and the most recent setting parameter that is a weekday or a rest day within the first preset number of days, according to different time periods of each day.

4. The method according to claim 1, characterized in that, The method further includes: In response to the existence of no most recent setting parameter that is a workday or rest day within a first preset number of days in the historical data, the most recent setting parameter of the date corresponding to the setting parameter that is not a workday or rest day is filled into the most recent setting parameter that is a workday or rest day within the first time range.

5. The method according to claim 1, characterized in that, The method further includes: In response to the presence of a setting parameter in the historical data that has no most recent occurrence on a workday or rest day within a first preset number of days, the setting parameter that has most recent occurrence on a workday or rest day within the first time range of the historical data is deleted.

6. A robotic vacuum cleaner, characterized in that, The robotic vacuum cleaner includes a processor and a memory connected to the processor, wherein the memory stores program data, and the processor retrieves the program data stored in the memory to execute the setting method of the robotic vacuum cleaner as described in any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program instructions that, when executed by a processor, implement the setup method for the sweeping robot as described in any one of claims 1-5.

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