Intelligent cleaning device control method and apparatus, device, and storage medium

Abstract

The application provides a smart cleaning device control method and device, equipment and storage medium. The method comprises the following steps: acquiring map data of a target cleaning area and a preset cleaning direction; dividing the target cleaning area into at least two pre-partition areas according to the map data and the preset cleaning direction; determining a target cleaning direction of each pre-partition area according to the estimated cleaning time of at least two cleaning directions of each pre-partition area, at least one of the at least two cleaning directions being the preset cleaning direction; dividing a pre-partition area with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold into at least two first sub cleaning areas according to the target cleaning direction, the average cleaning length and / or the area of the pre-partition area; and performing a cleaning operation on the target cleaning area according to the target cleaning direction of each first sub cleaning area. The method improves the working effect and efficiency of the smart cleaning device.

Description

Technical Field

[0001] This application relates to the field of mobile robots, and more particularly to a method, apparatus, device, and storage medium for controlling intelligent cleaning equipment. Background Technology

[0002] With the development of technology, mobile robots have been applied in various fields, such as lawnmowers based on mobile robots. With the advancement of sensing, localization, and sensor technologies, existing lawnmowers are transitioning from random mowing to planned mowing. Currently, most planned lawnmowers use a bow-shaped mowing planning method, operating according to this mowing path. However, current mowing planning methods suffer from low efficiency and poor performance.

[0003] Therefore, improving the mowing efficiency and effectiveness of lawnmowers is an urgent problem to be solved. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for controlling intelligent cleaning equipment, in order to solve the problems of low mowing efficiency and poor mowing effect of current lawnmowers.

[0005] To achieve the above objectives, the embodiments of this application provide the following technical solutions:

[0006] In a first aspect, embodiments of this application provide a method for controlling an intelligent cleaning device, including:

[0007] Acquire map data of the target cleanup area, as well as the preset cleanup direction;

[0008] Based on the map data and the preset cleaning direction, the target cleaning area is divided into at least two pre-partitioned areas;

[0009] Based on the estimated cleaning time of at least two cleaning directions for each pre-partitioned region, the target cleaning direction of the pre-partitioned region is determined, wherein at least one of the at least two cleaning directions is the preset cleaning direction;

[0010] Based on the target cleaning direction, and the average cleaning length and / or area of ​​the pre-partitioned region, the pre-partitioned region with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold is divided into at least two first sub-cleaning regions.

[0011] Cleaning operations are performed on the target cleaning area according to the target cleaning direction of each first sub-cleaning area.

[0012] Optionally, based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned region, the pre-partitioned region with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold is divided into at least two first sub-cleaning regions, including:

[0013] Obtain the average cleanup length in the target cleanup direction for each of the pre-partitioned regions;

[0014] If the average cleaning length is greater than the preset length threshold, then the pre-partitioned region is divided into at least two first sub-cleaning regions based on the average cleaning length and the preset length threshold.

[0015] If the average cleaning length is less than or equal to the preset length threshold, then the pre-partitioned region is used as the first sub-cleaning region.

[0016] Optionally, obtaining the average cleaning length in the target cleaning direction for each of the pre-partitioned regions includes:

[0017] Obtain the cleaning path corresponding to the target cleaning direction, wherein the cleaning path is a bow-shaped path;

[0018] Obtain the cleaning length of each long side of the cleaning path;

[0019] The average cleanup length is determined based on the cleanup lengths of all long sides of the cleanup path.

[0020] Optionally, the step of dividing the pre-partitioned region into at least two first sub-cleaning regions based on the average cleanup length and the preset length threshold includes:

[0021] Based on the average cleaning length and the preset length threshold, the pre-partitioned region is divided into at least two second sub-cleaning regions;

[0022] Obtain the area of ​​each second sub-cleaning region;

[0023] If the area of ​​the second sub-cleaning region is greater than the preset area threshold, then the second sub-cleaning region is divided into at least two first sub-cleaning regions based on the area of ​​the second sub-cleaning region and the preset area threshold.

[0024] If the area of ​​the second sub-cleaning region is less than or equal to the preset area threshold, then the second sub-cleaning region is used as the first sub-cleaning region.

[0025] Optionally, dividing the pre-partitioned region into at least two first sub-partitioned regions based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned region includes:

[0026] Obtain the area of ​​each of the pre-partitioned regions;

[0027] If the area of ​​the pre-partitioned region is greater than a preset area threshold, then the pre-partitioned region is divided into at least two first sub-cleaning regions based on the area of ​​the pre-partitioned region and the preset area threshold.

[0028] If the area of ​​the pre-partitioned region is less than or equal to the preset area threshold, then the pre-partitioned region is used as the first sub-cleaning region.

[0029] Optionally, the map data also includes restricted areas that do not require clearing; the step of dividing the target clearing area into at least two pre-partitioned areas based on the map data and the preset clearing direction includes:

[0030] Obtain the boundaries of the target clearing area and the boundaries of the restricted area from the map data;

[0031] Based on the boundaries of the target cleaning area, the boundaries of the restricted area, and the preset cleaning direction, the target cleaning area is divided into at least two pre-partitioned areas.

[0032] Optionally, determining the target cleaning direction of each pre-partitioned region based on the estimated cleaning time of at least two cleaning directions for each pre-partitioned region includes:

[0033] Based on the preset cleaning direction, candidate cleaning directions are obtained;

[0034] The first estimated cleaning time for the pre-partitioned area is obtained according to the preset cleaning direction;

[0035] The second estimated cleaning time for the pre-partitioned region is obtained based on the candidate cleaning direction;

[0036] If the ratio of the first estimated cleaning time to the second estimated cleaning time is greater than a preset ratio threshold, then the candidate cleaning direction is taken as the target cleaning direction.

[0037] Optionally, obtaining the first estimated cleaning time for the pre-partitioned area based on the preset cleaning direction includes:

[0038] Obtain the number of straight paths, the length of the straight paths, and the single turning time of the intelligent cleaning device in the preset cleaning direction in the pre-partitioned area;

[0039] The cleaning time for cleaning the pre-partitioned area is determined based on the number of straight paths and the length of the straight paths.

[0040] The turning time for clearing the pre-partitioned area is determined based on the number of straight paths and the single turning time.

[0041] The first estimated cleaning time is determined based on the straight-line cleaning time and the turning time.

[0042] Optionally, the step of performing a cleaning operation on the target cleaning area according to the target cleaning direction of each first sub-cleaning area includes:

[0043] Clean the first sub-cleaning area according to the target cleaning direction of the first sub-cleaning area;

[0044] After completing the cleaning operation in the first sub-cleaning area, obtain the current location of the intelligent cleaning device;

[0045] Based on the current position, determine the next uncleaned first sub-cleaning area that is closest to the current position;

[0046] Clean the next uncleaned first sub-cleaning area according to the target cleaning direction of the next uncleaned first sub-cleaning area, until all uncleaned first sub-cleaning areas are completed.

[0047] Secondly, embodiments of this application provide an intelligent cleaning device control apparatus, the apparatus comprising:

[0048] The acquisition module is used to acquire map data of the target cleanup area and the preset cleanup direction;

[0049] The processing module is used to divide the target cleaning area into at least two pre-partitioned areas based on the map data and the preset cleaning direction;

[0050] The determining module is configured to determine the target cleaning direction of the pre-partitioned region based on the estimated cleaning time of at least two cleaning directions of each pre-partitioned region, wherein at least one of the cleaning directions is the preset cleaning direction; and to divide the pre-partitioned region into at least two first sub-cleaning regions based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned region.

[0051] The control module is used to perform cleaning operations on the target cleaning area according to the target cleaning direction of each first sub-cleaning area.

[0052] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0053] The memory stores computer-executed instructions;

[0054] The processor executes computer execution instructions stored in the memory to implement the method as described in any one of the first aspects.

[0055] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the intelligent cleaning device control method as described in any one of the first aspects.

[0056] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method as described in any one of the first aspects.

[0057] The intelligent cleaning device control method, apparatus, equipment, and storage medium provided in this application acquire map data of the target cleaning area and preset cleaning directions. Based on the map data and preset cleaning directions, the target cleaning area is divided into at least two pre-partitioned areas. Based on the estimated cleaning time of at least two cleaning directions in each pre-partitioned area, the target cleaning direction of the pre-partitioned area is determined. Based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned area, the pre-partitioned area with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold is divided into at least two first sub-cleaning areas. Based on the target cleaning direction of each first sub-cleaning area, a cleaning operation is performed on the target cleaning area to segment the target cleaning area. This ensures that each first sub-cleaning area is a regular area, the target cleaning direction of the cleaning operation is the most efficient direction, and each cleaning path is short, with less influence from positioning signal quality and cumulative errors, thereby improving the cleaning efficiency and cleaning effect of the intelligent cleaning device. Attached Figure Description

[0058] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0059] Figure 1 A schematic diagram illustrating the application scenarios of a planned lawnmower;

[0060] Figure 2 A flowchart illustrating an intelligent cleaning device control method provided in an embodiment of this application;

[0061] Figure 3 This is a schematic diagram of a target cleaning area provided in an embodiment of this application;

[0062] Figure 4 This application provides a schematic diagram of a scene after the target cleanup area has been segmented.

[0063] Figure 5A flowchart illustrating another intelligent cleaning device control method provided in this application embodiment;

[0064] Figure 6 This is a schematic diagram of another target cleanup area provided in an embodiment of this application;

[0065] Figure 7 A flowchart illustrating another intelligent cleaning device control method provided in this application embodiment;

[0066] Figure 8 This is a schematic diagram of another scenario after the target cleanup area is segmented, provided as an embodiment of this application;

[0067] Figure 9 A flowchart illustrating another intelligent cleaning device control method provided in an embodiment of this application;

[0068] Figure 10 A flowchart illustrating another intelligent cleaning device control method provided in an embodiment of this application;

[0069] Figure 11 This is a schematic diagram of the structure of an intelligent cleaning equipment control device provided in an embodiment of this application;

[0070] Figure 12 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0071] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concepts of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0072] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0073] First, we will explain the application scenarios of planned lawnmowers for mowing operations. Figure 1 This is a schematic diagram illustrating an application scenario for a planned lawnmower. For example... Figure 1 As shown, the scene includes: the lawn mowing area and the lawnmower's running path.

[0074] The planned path of a lawnmower can be a pre-set path based on actual needs, or a fixed path determined by the mower itself based on parameters such as the size, shape, and actual conditions of the receiving mowing area. This pre-set path can be a zigzag pattern or a circular path. Currently, most planned lawnmowers use a zigzag path for mowing. In this mode, the mower can perform mowing operations within the designated area according to a pre-set initial mowing direction and the zigzag path. For example... Figure 1 If the initial mowing direction is upward, the mower will first proceed in that direction. Upon reaching the upper edge of the mowing area, the mower will turn (mowing can continue during the turn), changing the mowing direction to downward along a bow-shaped path, parallel to the previous mowing path. In other words, the shorter side of this bow-shaped path is the path used for turning, and the longer side is the main mowing path (hereinafter referred to as the long side or straight path).

[0075] However, current lawn mowing methods have the following three drawbacks:

[0076] Disadvantage 1: For irregularly shaped mowing areas, using a "bow" shaped path for mowing may result in missed areas, leading to poor mowing results.

[0077] Disadvantage 2: For a relatively long and narrow mowing area, if the mowing direction is perpendicular to the long side of the mowing area, the mower will have to perform more turning movements when working in that area. Turning movements generally take a long time, so performing more turning movements will result in lower mowing efficiency.

[0078] Disadvantage 3: In areas where the lawnmower's operating path is long, the mowing path on the "bow" shaped path will also be long. Due to the influence of positioning signal quality and cumulative errors, the two parallel mowing paths will be offset, resulting in the actual mowing paths not being parallel, thus causing missed mowing and poor mowing effect.

[0079] In view of this, this application provides a control method for an intelligent cleaning device, which divides the target cleaning area into multiple sub-cleaning areas, determines the target cleaning direction of each sub-cleaning area based on the estimated cleaning time of each sub-cleaning area, and sequentially completes the cleaning of each sub-cleaning area according to the target cleaning direction to complete the cleaning operation of the target cleaning area, thereby improving the working effect and efficiency of the intelligent cleaning device.

[0080] The executing entity of this application can be the intelligent cleaning device, the processing chip within the intelligent cleaning device, or a device or cloud platform providing operational instructions to the intelligent cleaning device. The intelligent cleaning device can be, for example, a lawnmower, sweeper, sweeper-mop combo, snowplow, or other autonomously operating equipment. When the executing entity is the intelligent cleaning device or its processing chip, the intelligent cleaning device can autonomously divide the target cleaning area and determine the target cleaning direction for each sub-area, thereby cleaning the target cleaning area according to the sub-areas and the target cleaning direction. When the executing entity is a device or cloud platform providing operational instructions, the device or cloud platform can divide the target cleaning area and determine the target cleaning direction for each sub-area, thereby controlling the intelligent cleaning device to clean the target cleaning area according to the sub-areas and the target cleaning direction.

[0081] The following describes the technical solution of this application and how it solves the aforementioned technical problems, using the intelligent cleaning device as the executing entity as an example, with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0082] Figure 2 This is a flowchart illustrating an intelligent cleaning device control method provided in an embodiment of this application.

[0083] like Figure 2 As shown, the method may include:

[0084] S201. Obtain map data of the target cleanup area and preset cleanup direction.

[0085] The map data can be pre-stored in the storage medium of the smart cleaning device, or imported by the user before using the smart cleaning device for cleaning operations. The map data includes parameters of the target cleaning area, such as the boundary of the target cleaning area and the type of the target cleaning area. Taking a lawnmower as an example, the type of the target cleaning area may include, for example, the type of grass in the area and the density of the grass, so that the lawnmower can determine the parameters for the mowing operation based on the type of the target cleaning area.

[0086] The preset cleaning direction can be determined automatically by the intelligent cleaning device based on the target cleaning area, or it can be determined based on the cleaning direction input by the user. When the preset cleaning direction is determined automatically by the intelligent cleaning device based on the target cleaning area, for example, it can be determined based on the length of the target cleaning area, with the direction parallel to that length being the preset cleaning direction.

[0087] S202. Based on map data and preset cleaning direction, divide the target cleaning area into at least two pre-partitioned areas.

[0088] The target area to be cleaned is an irregular area, such as an area composed of multiple polygons. Figure 3 This is a schematic diagram of a target cleaning area provided in an embodiment of this application, such as... Figure 3 As shown, the target cleanup area is an irregular region composed of multiple polygons.

[0089] Using existing grid map segmentation methods, based on the boundary and a preset cleaning direction, the interior of the target cleaning area is traversed. For example, the grid map segmentation method could be Boustrophed on Cellular Decomposition (BCD). Based on the preset cleaning direction, the BCD method is used to traverse the interior of the target cleaning area, dividing the irregular region into at least two regular pre-partitioned regions. (Continue referring to the above...) Figure 3 The target cleanup area shown is divided into... Figure 4 The multiple pre-partitioned regions are shown. Figure 4 This is a schematic diagram of a scene after target cleaning region segmentation, provided as an embodiment of this application. The segmentation using the BCD method can be found in existing technologies and will not be described in detail here.

[0090] By pre-dividing the target cleaning area, an irregular target cleaning area can be divided into multiple regular pre-divided areas, which makes it easier for intelligent cleaning devices to perform path planning in each pre-divided area, avoiding the problem of difficulty in path planning for irregular target cleaning areas.

[0091] S203. Determine the target cleaning direction for each pre-partitioned area based on the estimated cleaning time of at least two cleaning directions for each pre-partitioned area.

[0092] At least one of the cleaning directions is a preset cleaning direction. This cleaning direction can be preset in the smart cleaning device or input by the user. For example, the preset cleaning direction can be a direction perpendicular to the preset cleaning direction, or a direction at any angle to the preset cleaning direction, etc., and the angle can be determined according to the pre-configuration.

[0093] Taking a "bow"-shaped path as an example, based on at least two cleaning directions, a "bow"-shaped path is determined within that cleaning direction. The estimated cleaning time for that direction is calculated based on the "bow"-shaped path and the operating parameters of the intelligent cleaning device. The direction of the longer side of the "bow"-shaped path (i.e., the straight path within the "bow"-shaped path excluding turning paths) is either the same as or 180 degrees opposite to the cleaning direction. These operating parameters may include, for example, the speed at which the intelligent cleaning device performs straight-line cleaning operations and the duration of a single turn. The time consumed for the straight path is determined based on the straight path within the "bow"-shaped path and the speed at which the intelligent cleaning device performs straight-line cleaning operations. The total turning time for the "bow"-shaped path is determined based on the number of turns and the duration of a single turn. Finally, the estimated cleaning time for that direction is determined based on the time consumed for all straight paths within the "bow"-shaped path and the total turning time.

[0094] To improve the cleaning efficiency of the intelligent cleaning device, the cleaning direction corresponding to the shortest estimated cleaning time in each pre-partition area is taken as the target cleaning direction for that pre-partition area. This ensures that each pre-partition area can perform cleaning operations through the most efficient target cleaning direction, resulting in better cleaning efficiency for all areas in the target cleaning area, and thus optimizing the efficiency of the intelligent cleaning device in cleaning the target cleaning area.

[0095] S204. Based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned area, divide the pre-partitioned area with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold into at least two first sub-cleaning areas.

[0096] One possible implementation involves dividing the pre-partitioned area into at least two first sub-partitioned areas based on the target cleaning direction and the average cleaning length of the pre-partitioned area. In this implementation, the average cleaning length can be obtained from the cleaning lengths of all straight lines along the target cleaning direction by the intelligent cleaning device. Then, based on the relationship between the average cleaning length along the target cleaning direction and a preset length threshold, it can be determined whether the pre-partitioned area needs to be divided. For example, if the average cleaning length is greater than the preset length threshold, the pre-partitioned area needs to be divided at least once according to the preset length threshold. For instance, if the average cleaning length is 20 meters and the preset length threshold is 6 meters, the pre-partitioned area needs to be divided every 6 meters from a direction perpendicular to the target cleaning direction. In this example, it needs to be divided 3 times to obtain 4 first sub-partitioned areas.

[0097] In this implementation, by dividing each pre-partitioned area where the average cleaning length is greater than a preset length threshold, the length of the long side of the "bow"-shaped path planned by the intelligent cleaning device in the first sub-cleaning area is reduced. This reduces the positioning deviation caused by the excessive length of the long side path and the offset of the intelligent cleaning device along the path. Consequently, the path accuracy of the intelligent cleaning device's cleaning operation is improved, and the missed cleaning caused by the short distance between two adjacent long side paths is reduced, thus improving the cleaning effect and cleaning coverage.

[0098] Another possible implementation involves dividing the pre-partitioned region into at least two first sub-partitioned regions based on the target cleaning direction and the area of ​​the pre-partitioned region. In this implementation, pre-partitioned regions larger than a preset area threshold can be divided into at least two first sub-partitioned regions based on the size of each pre-partitioned region and a preset area threshold.

[0099] In this implementation, by dividing each pre-partitioned area into areas larger than a preset area threshold, the problem of long transfer paths when the intelligent cleaning device moves between the first sub-cleaning areas due to the large size of the first sub-cleaning area is reduced. By reducing the length of the transfer path, the transfer time of the intelligent cleaning device when moving between the first sub-cleaning areas is shortened, thereby shortening the total cleaning operation time of the intelligent cleaning device and improving the efficiency of the intelligent cleaning device in cleaning the target cleaning area.

[0100] Another possible implementation is to first divide the pre-partitioned region according to the target cleaning direction and the average cleaning length of the pre-partitioned region, and then further divide the divided region according to the target cleaning direction and the area of ​​the pre-partitioned region to divide the pre-partitioned region into multiple first sub-cleaning regions.

[0101] S205. Perform cleaning operations on the target cleaning area according to the target cleaning direction of each first sub-cleaning area.

[0102] Based on the target cleaning direction of each first sub-cleaning area, the cleaning operation is performed on the first sub-cleaning area. After completing the cleaning operation of one first sub-cleaning area, the operation is moved to the next first sub-cleaning area that has not been cleaned, and the cleaning operation is performed until all first sub-cleaning areas are cleaned.

[0103] One possible implementation is to pre-set the cleaning order of the first sub-cleaning area. This cleaning order can be determined by the user operating the smart cleaning device, or it can be determined automatically by the smart cleaning device. When the cleaning order is determined automatically by the smart cleaning device, it can determine the cleaning order based on the adjacency relationship between the first sub-cleaning areas. For example, other first sub-cleaning areas that are adjacent to the first first sub-cleaning area and have not yet been cleaned can be selected as the next first sub-cleaning area to be cleaned. If there are multiple adjacent areas, any one of them can be selected as the next first sub-cleaning area to be cleaned.

[0104] Another possible implementation is that after the intelligent cleaning device completes the cleaning operation of the current first sub-cleaning area, based on the current location of the intelligent cleaning device, the first sub-cleaning area that has not been cleaned is determined as the next area to be cleaned.

[0105] The intelligent cleaning device control method provided in this application embodiment acquires map data of the target cleaning area and a preset cleaning direction. Based on the map data and the preset cleaning direction, the target cleaning area is divided into at least two pre-partitioned areas. Based on the estimated cleaning time of at least two cleaning directions in each pre-partitioned area, the target cleaning direction of the pre-partitioned area is determined. Based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned area, the pre-partitioned area with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold is divided into at least two first sub-cleaning areas. Based on the target cleaning direction of each first sub-cleaning area, a cleaning operation is performed on the target cleaning area to segment the target cleaning area. This ensures that each first sub-cleaning area is a regular area, the target cleaning direction of the cleaning operation is the most efficient direction, each cleaning path is short, and it is less affected by the quality of the positioning signal and cumulative errors. Furthermore, the small area of ​​each first sub-cleaning area results in a shorter transfer path length, shortening the transfer time of the intelligent cleaning device and thus shortening the total cleaning operation time of the intelligent cleaning device, thereby improving the cleaning efficiency and cleaning effect of the intelligent cleaning device.

[0106] The following section will take an irregular target cleaning area as an example to explain in detail how, in the aforementioned step S204, a pre-partitioned area with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold is divided into at least two first sub-cleaning areas based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned area.

[0107] Figure 5 This is a flowchart illustrating another intelligent cleaning device control method provided in an embodiment of this application. Figure 5As shown, the aforementioned step S204 may include:

[0108] S501. Obtain the average cleanup length in the target cleanup direction for each pre-partitioned region.

[0109] In this pre-zoned area, the intelligent cleaning device plans its path in a "bow" shape according to the target cleaning direction. The direction of the long side of the "bow" shape (i.e., the straight path in the "bow" shape excluding the turning path) is the same as or opposite to the target cleaning direction. How to plan the "bow" shape in this pre-zoned area according to the target cleaning direction can be referred to the existing technology, which will not be elaborated here.

[0110] The average cleaning length can be obtained, for example, by dividing the total length of the "bow"-shaped path by the number of long sides of the "bow"-shaped path, or by dividing the total length of all long sides of the "bow"-shaped path by the number of long sides of the "bow"-shaped path.

[0111] The following example illustrates how to obtain the average cleanup length in the target cleanup direction for each pre-partitioned region, using the example that the average cleanup length is obtained by dividing the total length of all long sides of the "bow"-shaped path by the number of long sides of the "bow"-shaped path. This method can be implemented through the following steps:

[0112] S5011. Obtain the cleaning path corresponding to the target cleaning direction.

[0113] The cleaning path is a "bow"-shaped path. The direction of the longer side of this "bow"-shaped path is the same as or opposite to the target cleaning direction. How to plan the "bow"-shaped path according to the target cleaning direction within this pre-partitioned area can be found in existing technologies, and will not be elaborated here.

[0114] S5012. Obtain the cleanup length of each long side of the cleanup path.

[0115] The cleanup length of each long side can be obtained, for example, by acquiring the length of the long side in the map data and calculating the cleanup length of each long side according to the map data scale. Alternatively, it can be obtained by parsing the data in the map data and using a corresponding parsing library or tool to extract the cleanup length of each long side of the path.

[0116] S5013. Determine the average cleanup length based on the cleanup lengths of all long sides of the cleanup path.

[0117] The total cleaning length is obtained by summing the cleaning lengths of all the long sides of the cleaning path. This total cleaning length is then divided by the number of long sides in the cleaning path to obtain the average cleaning length. For example, assuming the "bow"-shaped path includes 5 long sides with lengths of 5 meters, 6 meters, 7 meters, 8 meters, and 9 meters, the average cleaning length is (5+6+7+8+9) / 5, which is 7 meters.

[0118] S502. If the average cleaning length is greater than the preset length threshold, the pre-partitioned area is divided into at least two first sub-cleaning areas according to the average cleaning length and the preset length threshold.

[0119] The preset length threshold characterizes the impact of the positioning signal quality and cumulative error of the intelligent cleaning device. The smaller the impact of the positioning signal quality and cumulative error, the larger the preset length threshold can be set; conversely, the larger the impact of the positioning signal quality and cumulative error, the smaller the preset length threshold needs to be set, thus ensuring that the intelligent cleaning device experiences minimal deviation during cleaning operations. This preset length threshold can be set according to actual needs, and this application does not impose any restrictions on it.

[0120] One possible implementation involves dividing the pre-partitioned area into at least two first sub-cleaning regions based solely on the average cleaning length and a preset length threshold. The pre-partitioned area is divided into at least two first sub-cleaning regions according to the preset length threshold. In the map data, the relationship between the length of the path of the intelligent cleaning device in the preset cleaning direction and the preset length threshold determines whether the pre-partitioned area needs to be divided. For example, if the path length is greater than the preset length threshold, the pre-partitioned area needs to be divided at least once according to the preset length threshold. For instance, if the path length is 20 meters and the preset length threshold is 6 meters, the target cleaning area needs to be divided once every time the path reaches 6 meters, from a direction perpendicular to the path. In this example, it needs to be divided 3 times, resulting in 4 first sub-cleaning regions. This division method ensures that the longer side of the "bow"-shaped path in each divided first sub-cleaning region is less than the preset length threshold, reducing the path offset problem of the intelligent cleaning device and improving the cleaning effect.

[0121] Another possible implementation involves dividing the area into a second sub-cleaning region based on the average cleanup length and a preset length threshold, and then dividing the area of ​​the second sub-cleaning region into at least two first sub-cleaning regions. This implementation can be achieved through the following steps:

[0122] S5021. Based on the average cleaning length and the preset length threshold, the pre-partitioned area is divided into at least two second sub-cleaning areas.

[0123] The method of dividing the pre-partitioned region into at least two second sub-partitioned regions based on the average cleanup length and a preset length threshold is the same as the aforementioned method of dividing the pre-partitioned region into at least two first cleanup regions based on the average cleanup length and a preset length threshold, and will not be repeated here.

[0124] S5022, Obtain the area of ​​each second sub-cleaning region.

[0125] The length and width of each second sub-cleaning region are obtained from the map data, and the area of ​​the second sub-cleaning region is calculated based on its length and width. For example, if the second sub-cleaning region is rectangular, its area is obtained by multiplying its length by its width; if the second sub-cleaning region is parallelogram or trapezoidal, its area is obtained by calculating the perpendicular distance from the perpendicular line based on its length and width, and then using these dimensions.

[0126] The above is just one example of how to obtain the area of ​​each second sub-cleaning area. This application does not limit the shape of the second sub-cleaning area or the specific method of calculating the area, as long as the area can be obtained based on the map data and the boundary of the second sub-cleaning area.

[0127] S5023. If the area of ​​the second sub-cleaning region is greater than the preset area threshold, then the second sub-cleaning region is divided into at least two first sub-cleaning regions according to the area of ​​the second sub-cleaning region and the preset area threshold.

[0128] If the area of ​​the second sub-cleaning area is larger than a preset area threshold, it indicates that the area of ​​the partition is too large. When the intelligent cleaning device moves between sub-cleaning areas, the transfer path is longer, resulting in more time spent on the transfer path. Therefore, further partitioning the larger second sub-cleaning area can reduce the length of the transfer path, shorten the transfer time, and further improve the efficiency of the cleaning operation. The preset area threshold can be determined according to actual needs, and this application does not impose any restrictions on it.

[0129] The number of first sub-cleaning regions that need to be divided from the area of ​​the second sub-cleaning region is determined by dividing the area by the preset area threshold. If there is a remainder after the division, the result of the division is incremented by one, and this number is taken as the number of first sub-cleaning regions that need to be divided from the second sub-cleaning region.

[0130] This splitting action can be performed sequentially based on the cumulative area within the second sub-cleaning area. For example, splitting can begin from one side of the second sub-cleaning area. Once the cumulative area reaches a preset area threshold, that cumulative area is designated as the first first sub-cleaning area, and so on, until the aforementioned number of first sub-cleaning areas are successfully split. This segmentation method ensures that the area of ​​each segmented first sub-cleaning area is smaller than the preset area threshold, reducing the problem of excessively long transfer paths between first sub-cleaning areas for the intelligent cleaning device, reducing transfer time, and thus shortening the total cleaning time of the intelligent cleaning device and improving cleaning efficiency.

[0131] S5024. If the area of ​​the second sub-cleaning region is less than or equal to the preset area threshold, then the second sub-cleaning region shall be used as the first sub-cleaning region.

[0132] S503. If the average cleaning length is less than or equal to the preset length threshold, the pre-partitioned area is taken as the first sub-cleaning area.

[0133] The method provided in this application divides the target cleaning area into multiple smaller sub-cleaning areas, either with straight paths less than or equal to a preset length threshold, or with multiple straight paths less than or equal to a preset length threshold and areas less than or equal to a preset area threshold. It then controls an intelligent cleaning device to sequentially clean the target cleaning area according to these smaller sub-cleaning areas. This reduces the offset problem caused by excessively long straight paths of the intelligent cleaning device, and also addresses the low efficiency problem caused by long transfer paths when the intelligent cleaning device moves between sub-cleaning areas, thereby improving the cleaning effect and efficiency of the intelligent cleaning device.

[0134] In another possible implementation, the pre-partitioned region can be divided into at least two first sub-cleaning regions based solely on the target cleaning direction and the area of ​​the pre-partitioned region. In this implementation, the area of ​​each pre-partitioned region can be obtained and judged. If the area of ​​the pre-partitioned region is greater than a preset area threshold, then the pre-partitioned region is divided into at least two first sub-cleaning regions based on its area and the preset area threshold; if the area of ​​the pre-partitioned region is less than or equal to the preset area threshold, then the pre-partitioned region is considered the first sub-cleaning region.

[0135] The method of dividing the first sub-cleaning area based on the area of ​​the pre-partitioned area is similar to the method of dividing the first sub-cleaning area based on the area of ​​the second sub-cleaning area in steps S5021 to S5024, and will not be described again here.

[0136] In addition, the target cleaning area may contain areas that do not need to be cleaned, or areas that cannot be cleaned; these areas are referred to as restricted areas in this article. For example, a restricted area could be an obstacle present in the target cleaning area, or an area that does not need to be cleaned for the time being. In such cases, the intelligent cleaning device needs to avoid the restricted area during cleaning. Figure 6 This is a schematic diagram illustrating another target cleanup area provided in an embodiment of this application. For example... Figure 6 As shown, the target clearing area also includes restricted areas, as detailed below. Figure 6 This document provides a detailed explanation of how to control the intelligent cleaning equipment in this situation.

[0137] Figure 7 This is a flowchart illustrating another intelligent cleaning device control method provided in an embodiment of this application. Figure 7 As shown, the aforementioned step S202 may further include:

[0138] S701. Obtain the boundaries of the target clearing area and the boundaries of the restricted area from the map data.

[0139] Since the map data can include the boundaries of the target cleaning area and the boundaries of the restricted area, the boundaries of the target cleaning area and the restricted area can be obtained directly from the map data. If the boundaries obtained from the map data are not accurate enough, the user can operate the intelligent cleaning device to correct the boundaries after obtaining them.

[0140] For example, the map data includes grid cells. The grid cells belonging to the target clearing area and the grid cells that form the boundary of the restricted area can be determined by the attributes of the grid cells. The grid cells where the boundary is located can be determined by identifying the grid cells adjacent to the target clearing area and the non-target clearing area, and these grid cells are used as the boundary of the target clearing area. The grid cells where the boundary of the restricted area is located can be determined by identifying the grid cells that form the boundary of the restricted area and the grid cells that form the boundary of the non-restricted area, and these grid cells are used as the boundary of the restricted area.

[0141] S702. Based on the boundaries of the target cleanup area, the boundaries of the restricted area, and the preset cleanup direction, divide the target cleanup area into at least two pre-partitioned areas.

[0142] Based on the boundaries of the target cleanup area, the boundaries of the restricted areas, and the preset cleanup direction, the BCD algorithm is used to traverse the target cleanup area. When the boundary of the restricted area is reached, the traversal from the starting position of the current traversal to the boundary of the restricted area is taken as a partition result, and the next traversal starts from the boundary on the opposite side of the restricted area boundary to obtain the next partition result.

[0143] After obtaining the BCD partitioning results in the case of restricted areas, each sub-cleaning region in the partitioning results is divided by a preset length threshold, or by a preset length threshold and a preset area threshold, to obtain at least two pre-partitioned regions.

[0144] For example, Figure 8 This is a schematic diagram of another scenario after target cleanup region segmentation, provided as an embodiment of this application. For example... Figure 8 As shown, the pre-partitioned areas marked 4 and 6 are the pre-partitioned areas on both sides of the restricted area, and the pre-partitioned areas marked 3 and 5 are the pre-partitioned areas adjacent to the upper and lower edges of the restricted area.

[0145] The method provided in this application embodiment can divide the target cleaning area into at least two pre-partitioned areas when there are restricted areas that do not need to be cleaned or cannot be cleaned. This allows the intelligent cleaning device to bypass the restricted areas and perform cleaning operations on the target cleaning area sequentially according to the smaller sub-cleaning areas. This reduces the offset problem caused by the excessively long straight path of the intelligent cleaning device, as well as the low efficiency problem caused by the long transfer path when the intelligent cleaning device moves between sub-cleaning areas, thereby improving the cleaning effect and cleaning efficiency of the intelligent cleaning device.

[0146] The following section provides a detailed explanation of how step S203 determines the target cleaning direction of a pre-partitioned area based on the estimated cleaning time of at least two cleaning directions for each pre-partitioned area. Figure 9 This is a flowchart illustrating another intelligent cleaning device control method provided in an embodiment of this application. Figure 9 As shown, the aforementioned step S203 may further include:

[0147] S901. Obtain candidate cleaning directions according to preset cleaning directions.

[0148] The candidate cleaning direction differs from the preset cleaning direction and can be any other direction. There can be one or more candidate cleaning directions; this is not inherently limited. For example, when there is only one candidate cleaning direction, it can be perpendicular to the preset cleaning direction or at any angle. When multiple candidate cleaning directions exist, they can be multiple directions different from the preset cleaning direction, such as a 45-degree counterclockwise rotation, a 90-degree rotation, or a 135-degree rotation, etc.

[0149] One possible implementation is that the candidate cleanup direction can be obtained based on the preset cleanup direction and the mapping relationship between the preset cleanup direction and the candidate cleanup direction. This mapping relationship can be a relational table or a function relation, etc.

[0150] Another possible implementation is that the candidate cleaning direction can be entered temporarily by the user or preset in the smart cleaning device.

[0151] S902. Obtain the first estimated cleaning time for the pre-partitioned area according to the preset cleaning direction.

[0152] The system obtains the number of straight paths, the length of each straight path, and the single-turn time of the intelligent cleaning device within the pre-zoned area in the preset cleaning direction. The number of straight paths and the length of each straight path can be obtained from the paths corresponding to the preset cleaning direction, and the single-turn time can be determined based on the operating parameters of the intelligent cleaning device.

[0153] Based on the number and length of the straight paths, the total length of the straight paths corresponding to the preset cleaning direction is determined. Then, based on the speed of the intelligent cleaning device during straight-line cleaning and the total path length, the straight-line cleaning time for the intelligent cleaning device to clean the pre-zoned area is calculated. Alternatively, based on the speed of the intelligent cleaning device during straight-line cleaning and the length of each straight path, the straight-line cleaning time for each straight path is determined, and then the straight-line cleaning time for the intelligent cleaning device to clean the pre-zoned area is calculated based on the number of straight paths and the straight-line cleaning time for each straight path.

[0154] Based on the number of straight paths, determine the number of turns the intelligent cleaning device needs to make to clean the pre-zoned area. Based on the number of turns and the single turning time of the intelligent cleaning device, determine the turning time for cleaning the pre-zoned area.

[0155] The first estimated cleaning time is determined based on the straight-line cleaning time and the turning time.

[0156] S903. Obtain the second estimated cleaning time for the pre-partitioned area based on the candidate cleaning direction.

[0157] The second estimated cleaning time corresponds to the candidate cleaning direction. When there are multiple candidate cleaning directions, there are multiple second estimated cleaning times.

[0158] The method for obtaining the second estimated cleaning time of the pre-partitioned area based on the candidate cleaning direction is the same as the method for obtaining the first estimated cleaning time of the pre-partitioned area based on the preset cleaning direction in step S902 above, and will not be repeated here.

[0159] S904. If the ratio of the first estimated cleaning time to the second estimated cleaning time is greater than the preset ratio threshold, then the candidate cleaning direction is taken as the target cleaning direction.

[0160] The preset ratio threshold is greater than 0 and less than 1. The preset ratio threshold can be set according to actual needs, and this application does not impose any restrictions on it.

[0161] If the ratio of the first estimated cleaning time to the second estimated cleaning time is greater than a preset ratio threshold, it indicates that the first estimated cleaning time is greater than the second estimated cleaning time, the cleaning efficiency of the cleaning path in the preset cleaning direction is low, and the cleaning efficiency of the cleaning path in the candidate cleaning direction is high. Therefore, the candidate cleaning direction needs to be used as the target cleaning direction.

[0162] Furthermore, when there are multiple candidate cleaning directions, the candidate cleaning direction with the shortest second estimated cleaning time or any candidate cleaning direction with a shorter first estimated cleaning time can be selected as the target cleaning direction to further improve the cleaning efficiency of the intelligent cleaning device.

[0163] The following section provides a detailed explanation of how step S205 involves performing a cleaning operation on the target cleaning area based on the target cleaning direction of each first sub-cleaning area. Figure 10 This is a flowchart illustrating another intelligent cleaning device control method provided in an embodiment of this application. Figure 10 As shown, the aforementioned step S205 may include:

[0164] S1001. Clean the first sub-cleaning area according to the target cleaning direction of the first sub-cleaning area.

[0165] Based on the target cleaning direction of the first sub-cleaning area, obtain the cleaning path of the first sub-cleaning area, and perform cleaning operations on the first sub-cleaning area according to the cleaning path.

[0166] The cleaning path of the first sub-cleaning area can be a straight path with the target cleaning direction of the first sub-cleaning area as the direction of the straight path. The distance, turning points, number of turns, etc. of the straight path can be determined according to the boundary of the first sub-cleaning area.

[0167] S1002. After completing the cleaning operation of the first sub-cleaning area, obtain the current location of the intelligent cleaning device.

[0168] The current location of the smart cleaning device can be obtained using Global Positioning System (GPS) technology, determined by the surrounding Wi-Fi network, or obtained through communication with a mobile network base station, etc. Alternatively, it can be obtained using a positioning device deployed on the smart cleaning device, etc.

[0169] S1003. Based on the current location, determine the next uncleaned first sub-cleaning area that is closest to the current location.

[0170] Obtain the uncluttered first sub-cleaning areas near the first sub-cleaning area where the current position is located, and the starting position of the cleaning path of each uncluttered first sub-cleaning area. Based on the distance between the current position and multiple starting positions, determine the starting position that is closest to the current position among these starting positions, and take the uncluttered first sub-cleaning area where the starting position is located as the next uncluttered first sub-cleaning area that is closest to the current position.

[0171] S1004. Clean the next uncleaned first sub-cleaning area according to the target cleaning direction of the next uncleaned first sub-cleaning area, until all uncleaned first sub-cleaning areas are completed.

[0172] Obtain the cleaning path of the first sub-cleaning area based on the target cleaning direction of the next uncleaned first sub-cleaning area, and perform cleaning operations on the first sub-cleaning area according to the cleaning path.

[0173] Repeat the above steps to clean up all the uncleaned first sub-cleaning areas in turn, until there are no more uncleaned first sub-cleaning areas.

[0174] Figure 11 This is a schematic diagram of the structure of an intelligent cleaning equipment control device provided in an embodiment of this application. Figure 11 As shown, it includes: an acquisition module 11, a processing module 12, a determination module 13, and a control module 14.

[0175] The acquisition module 11 is used to acquire map data of the target cleanup area and the preset cleanup direction.

[0176] Processing module 12 is used to divide the target cleaning area into at least two pre-partitioned areas based on the map data and the preset cleaning direction.

[0177] The determining module 13 determines the target cleaning direction for each pre-partitioned region based on the estimated cleaning time of at least two cleaning directions. Based on the target cleaning direction, and the average cleaning length and / or area of ​​the pre-partitioned region, pre-partitioned regions with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold are divided into at least two first sub-cleaning regions, wherein at least one of the at least two cleaning directions is the preset cleaning direction.

[0178] Control module 14 is used to perform cleaning operations on the target cleaning area according to the target cleaning direction of each first sub-cleaning area.

[0179] In one possible implementation, the determining module 13 is specifically used to obtain the average cleanup length in the target cleanup direction for each pre-partitioned region. If the average cleanup length is greater than a preset length threshold, the pre-partitioned region is divided into at least two first sub-cleanup regions based on the average cleanup length and the preset length threshold. If the average cleanup length is less than or equal to the preset length threshold, the pre-partitioned region is taken as the first sub-cleanup region.

[0180] In this implementation, optionally, the acquisition module 11 is used to acquire the cleaning path corresponding to the target cleaning direction, which is a bow-shaped path. It acquires the cleaning length of each long side of the cleaning path. The determination module 13 is used to determine the average cleaning length based on the cleaning lengths of all long sides of the cleaning path.

[0181] Optionally, the determining module 13 is specifically used to divide the pre-partitioned area into at least two second sub-cleaning areas based on the average cleaning length and the preset length threshold. The area of ​​each second sub-cleaning area is obtained. If the area of ​​the second sub-cleaning area is greater than a preset area threshold, then the second sub-cleaning area is divided into at least two first sub-cleaning areas based on the area of ​​the second sub-cleaning area and the preset area threshold. If the area of ​​the second sub-cleaning area is less than or equal to the preset area threshold, then the second sub-cleaning area is used as the first sub-cleaning area.

[0182] In another possible implementation, the acquisition module 11 is specifically used to acquire the area of ​​each pre-partitioned region. The determination module 13 is specifically used to, if the area of ​​the pre-partitioned region is greater than a preset area threshold, divide the pre-partitioned region into at least two first sub-cleaning regions based on the area of ​​the pre-partitioned region and the preset area threshold. If the area of ​​the pre-partitioned region is less than or equal to the preset area threshold, then the pre-partitioned region is taken as the first sub-cleaning region.

[0183] In another possible implementation, if the map data also includes restricted areas that do not need to be cleared, the processing module 12 is specifically used to obtain the boundary of the target clearing area and the boundary of the restricted area from the map data. Based on the boundary of the target clearing area, the boundary of the restricted area, and the preset clearing direction, the target clearing area is divided into at least two pre-partitioned areas.

[0184] In any of the above implementations, the determining module 13 is specifically used to obtain candidate cleaning directions based on the preset cleaning direction. It also obtains a first estimated cleaning time for the pre-partitioned region based on the preset cleaning direction. Finally, it obtains a second estimated cleaning time for the pre-partitioned region based on the candidate cleaning direction. If the ratio of the first estimated cleaning time to the second estimated cleaning time is greater than a preset ratio threshold, then the candidate cleaning direction is taken as the target cleaning direction.

[0185] In this implementation, optionally, the determining module 13 is specifically used to obtain the number of straight paths, the length of the straight paths, and the single turning time of the intelligent cleaning device in the preset cleaning direction within the pre-partitioned area. Based on the number of straight paths and the length of the straight paths, the straight-line cleaning time for cleaning the pre-partitioned area is determined. Based on the number of straight paths and the single turning time, the turning time for cleaning the pre-partitioned area is determined. Based on the straight-line cleaning time and the turning time, the first estimated cleaning time is determined.

[0186] In any of the above implementations, the control module 14 is specifically used to clean the first sub-cleaning area according to the target cleaning direction of the first sub-cleaning area. After completing the cleaning operation of the first sub-cleaning area, the current position of the intelligent cleaning device is obtained. Based on the current position, the next uncleaned first sub-cleaning area closest to the current position is determined. Based on the target cleaning direction of the next uncleaned first sub-cleaning area, the next uncleaned first sub-cleaning area is cleaned until all uncleaned first sub-cleaning areas are cleaned.

[0187] The intelligent cleaning device control device provided in this application embodiment can execute the intelligent cleaning device control method in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0188] Figure 12 This is a schematic diagram of an electronic device provided in an embodiment of this application. The intelligent electronic device is used to execute the aforementioned intelligent cleaning device control method. The electronic device may be, for example, the aforementioned intelligent cleaning device, or a processing chip within the intelligent cleaning device, or a device or cloud platform for providing operating instructions to the intelligent cleaning device. Figure 12 As shown, the electronic device 1200 may include at least one processor 1201 and a memory 1202, and in one possible implementation, may also include a communication interface 1203.

[0189] The memory 1202 is used to store programs. Specifically, the program may include program code, which includes computer operation instructions.

[0190] The memory 1202 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0191] The processor 1201 is used to execute computer execution instructions stored in the memory 1202 to implement the method described in the foregoing method embodiments. The processor 1201 may be a CPU, an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0192] Optionally, the processor 1201 can communicate with external devices via the communication interface 1203. When the electronic device is a device or cloud platform used to provide operating instructions to the intelligent cleaning device, the external device mentioned herein may be, for example, the intelligent cleaning device.

[0193] In practical implementation, if the communication interface 1203, memory 1202, and processor 1201 are implemented independently, they can be interconnected via a bus to complete communication. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc., but this does not imply that there is only one bus or one type of bus.

[0194] Optionally, in a specific implementation, if the communication interface 1203, memory 1202 and processor 1201 are integrated on a single chip, then the communication interface 1203, memory 1202 and processor 1201 can communicate through an internal interface.

[0195] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores program instructions, which are used in the methods described in the above embodiments.

[0196] This application also provides a computer program product including executable instructions stored in a readable storage medium. At least one processor of an electronic device can read the executable instructions from the readable storage medium, and the at least one processor executes the executable instructions to cause the electronic device to implement the intelligent cleaning device control method provided in the various embodiments described above.

[0197] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for controlling an intelligent cleaning device, characterized in that, include: Acquire map data of the target cleanup area, as well as the preset cleanup direction; Based on the map data and the preset cleaning direction, the target cleaning area is divided into at least two pre-partitioned areas; Based on the estimated cleaning time of at least two cleaning directions for each pre-partitioned region, the target cleaning direction of the pre-partitioned region is determined, wherein at least one of the at least two cleaning directions is the preset cleaning direction; Based on the target cleaning direction, and the average cleaning length and / or area of ​​the pre-partitioned region, the pre-partitioned region with an average cleaning length greater than a preset length threshold and / or an area greater than a preset area threshold is divided into at least two first sub-cleaning regions. Cleaning operations are performed on the target cleaning area according to the target cleaning direction of each first sub-cleaning area; The step of determining the target cleaning direction of each pre-partitioned region based on the estimated cleaning time of at least two cleaning directions for each pre-partitioned region includes: Based on the preset cleaning direction, candidate cleaning directions are obtained; The first estimated cleaning time for the pre-partitioned area is obtained according to the preset cleaning direction; The second estimated cleaning time for the pre-partitioned region is obtained based on the candidate cleaning direction; If the ratio of the first estimated cleaning time to the second estimated cleaning time is greater than a preset ratio threshold, then the candidate cleaning direction is taken as the target cleaning direction.

2. The method according to claim 1, characterized in that, The step of dividing a pre-partitioned region whose average cleaning length is greater than a preset length threshold and / or whose area is greater than a preset area threshold into at least two first sub-cleaning regions based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned region; includes: Obtain the average cleanup length in the target cleanup direction for each of the pre-partitioned regions; If the average cleaning length is greater than the preset length threshold, then the pre-partitioned region is divided into at least two first sub-cleaning regions based on the average cleaning length and the preset length threshold. If the average cleaning length is less than or equal to the preset length threshold, then the pre-partitioned region is used as the first sub-cleaning region.

3. The method according to claim 2, characterized in that, The step of obtaining the average cleanup length in the target cleanup direction for each of the pre-partitioned regions includes: Obtain the cleaning path corresponding to the target cleaning direction, wherein the cleaning path is a bow-shaped path; Obtain the cleaning length of each long side of the cleaning path; The average cleanup length is determined based on the cleanup lengths of all long sides of the cleanup path.

4. The method according to claim 2, characterized in that, The step of dividing the pre-partitioned region into at least two first sub-cleaning regions based on the average cleanup length and the preset length threshold includes: Based on the average cleaning length and the preset length threshold, the pre-partitioned region is divided into at least two second sub-cleaning regions; Obtain the area of ​​each second sub-cleaning region; If the area of ​​the second sub-cleaning region is greater than the preset area threshold, then the second sub-cleaning region is divided into at least two first sub-cleaning regions based on the area of ​​the second sub-cleaning region and the preset area threshold. If the area of ​​the second sub-cleaning region is less than or equal to the preset area threshold, then the second sub-cleaning region is used as the first sub-cleaning region.

5. The method according to claim 1, characterized in that, The step of dividing the pre-partitioned region into at least two first sub-partitioned regions based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned region includes: Obtain the area of ​​each of the pre-partitioned regions; If the area of ​​the pre-partitioned region is greater than a preset area threshold, then the pre-partitioned region is divided into at least two first sub-cleaning regions based on the area of ​​the pre-partitioned region and the preset area threshold. If the area of ​​the pre-partitioned region is less than or equal to the preset area threshold, then the pre-partitioned region is used as the first sub-cleaning region.

6. The method according to claim 1, characterized in that, The map data also includes restricted areas that do not require clearing; the step of dividing the target clearing area into at least two pre-partitioned areas based on the map data and the preset clearing direction includes: Obtain the boundaries of the target clearing area and the boundaries of the restricted area from the map data; Based on the boundaries of the target cleaning area, the boundaries of the restricted area, and the preset cleaning direction, the target cleaning area is divided into at least two pre-partitioned areas.

7. The method according to any one of claims 1-6, characterized in that, The step of obtaining the first estimated cleaning time for the pre-partitioned area according to the preset cleaning direction includes: Obtain the number of straight paths, the length of the straight paths, and the single turning time of the intelligent cleaning device in the preset cleaning direction in the pre-partitioned area; The cleaning time for cleaning the pre-partitioned area is determined based on the number of straight paths and the length of the straight paths. The turning time for clearing the pre-partitioned area is determined based on the number of straight paths and the single turning time. The first estimated cleaning time is determined based on the straight-line cleaning time and the turning time.

8. The method according to any one of claims 1-6, characterized in that, The step of performing a cleaning operation on the target cleaning area according to the target cleaning direction of each first sub-cleaning area includes: Clean the first sub-cleaning area according to the target cleaning direction of the first sub-cleaning area; After completing the cleaning operation in the first sub-cleaning area, obtain the current location of the intelligent cleaning device; Based on the current position, determine the next uncleaned first sub-cleaning area that is closest to the current position; Clean the next uncleaned first sub-cleaning area according to the target cleaning direction of the next uncleaned first sub-cleaning area, until all uncleaned first sub-cleaning areas are completed.

9. A control device for an intelligent cleaning equipment, characterized in that, The device includes: The acquisition module is used to acquire map data of the target cleanup area and the preset cleanup direction; The processing module is used to divide the target cleaning area into at least two pre-partitioned areas based on the map data and the preset cleaning direction; The determining module is configured to determine the target cleaning direction of each pre-partitioned region based on the estimated cleaning time of at least two cleaning directions of each pre-partitioned region, wherein at least one of the at least two cleaning directions is the preset cleaning direction; and, based on the target cleaning direction and the average cleaning length and / or area of ​​the pre-partitioned region, divide the pre-partitioned region whose average cleaning length is greater than a preset length threshold and / or whose area is greater than a preset area threshold into at least two first sub-cleaning regions. The control module is used to perform cleaning operations on the target cleaning area according to the target cleaning direction of each first sub-cleaning area; The determining module is specifically used for: Based on the preset cleaning direction, candidate cleaning directions are obtained; The first estimated cleaning time for the pre-partitioned area is obtained according to the preset cleaning direction; The second estimated cleaning time for the pre-partitioned region is obtained based on the candidate cleaning direction; If the ratio of the first estimated cleaning time to the second estimated cleaning time is greater than a preset ratio threshold, then the candidate cleaning direction is taken as the target cleaning direction.

10. An electronic device, characterized in that, The electronic device includes: a processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the intelligent cleaning device control method as described in any one of claims 1-8.

12. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, is used to implement the intelligent cleaning device control method as described in any one of claims 1-8.

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