CN114098534B - Cleaning area identification method and device of sweeper, storage medium and electronic equipment - Google Patents
Cleaning area identification method and device of sweeper, storage medium and electronic equipment Download PDFInfo
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- CN114098534B CN114098534B CN202111445394.8A CN202111445394A CN114098534B CN 114098534 B CN114098534 B CN 114098534B CN 202111445394 A CN202111445394 A CN 202111445394A CN 114098534 B CN114098534 B CN 114098534B
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/24—Floor-sweeping machines, motor-driven
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
- A47L11/4002—Installations of electric equipment
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
- A47L11/4011—Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
- A47L2201/04—Automatic control of the travelling movement; Automatic obstacle detection
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
- A47L2201/06—Control of the cleaning action for autonomous devices; Automatic detection of the surface condition before, during or after cleaning
Abstract
The application discloses sweeping area identification method, device, storage medium and electronic equipment of sweeper, and relates to the technical field of internet of things, the method comprises the following steps: acquiring area information of a cleaning forbidden area set for the sweeper, and acquiring map data corresponding to a target cleaning area; performing edge point extraction processing based on the map data to obtain area edge points of the target cleaning area; judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judgment result; and determining the cleaning type of the target cleaning area according to the judgment result. This application can promote the machine of sweeping the floor to the discernment accuracy of cleaning the region, promotes the performance of cleaning of machine of sweeping the floor, and reduces the restriction that sets up of cleaning the type to the user, promotes user experience.
Description
Technical Field
The application relates to the technical field of Internet of things, in particular to a cleaning area identification method and device of a sweeper, a storage medium and electronic equipment.
Background
At present, a sweeper in smart home equipment can generate map data of a cleaning area through scanning, the sweeper can clean the cleaning area (for example, a cleaning area divided by a certain room) according to the map data, and when the cleaning area is cleaned, a cleaning class of the cleaning area needs to be identified according to a cleaning limit forbidden zone set by a user.
At present, due to the change of furniture and the like in each room, cleaning areas are often irregular in shape, a common quadrangle covering all subareas is generated by taking map data of the cleaning areas from the upper extreme value, the lower extreme value, the left extreme value and the right extreme value of the map data when the cleaning areas are identified, meanwhile, a cleaning limit forbidden area set by a user is also processed into a quadrangle, and the two quadrangles are compared to identify the cleaning type of the cleaning areas.
However, the actually divided cleaning area and the cleaning restricted forbidden zone set by the user are often irregular, and in the current mode, the accuracy is low when the area is cleaned during recognition, abnormal judgment can occur, which leads to abnormal cleaning, and the user is restricted from cleaning category setting operation, which leads to poor experience.
Disclosure of Invention
The embodiment of the application provides a scheme, can promote the machine of sweeping the floor to the discernment accuracy in cleaning the region, promotes the performance of cleaning of machine of sweeping the floor, and reduces the restriction that sets up to the user type of cleaning, promotes user experience.
The embodiment of the application provides the following technical scheme:
according to an embodiment of the present application, a cleaning area identification method of a sweeper includes: acquiring area information of a cleaning forbidden zone set for the sweeper, and acquiring map data corresponding to a target cleaning area; performing edge point extraction processing based on the map data to obtain regional edge points of the target cleaning region; judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judgment result; and determining the cleaning type of the target cleaning area according to the judgment result.
In some embodiments of the present application, the performing an edge point extraction process based on the map data to obtain an area edge point corresponding to the target cleaning area includes: dividing pixel points with the same abscissa in the map data into a pixel point subset; and acquiring pixel points corresponding to the maximum vertical coordinate and the minimum vertical coordinate in each pixel point subset to obtain area edge points corresponding to the target cleaning area.
In some embodiments of the present application, the obtaining of the map data corresponding to the target cleaning area includes: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and determining the target cleaning area to be cleaned, and acquiring map data corresponding to the cleaning area matched with the target cleaning area from the area map data.
In some embodiments of the present application, the obtaining of the map data corresponding to the target cleaning area includes: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and taking each cleaning area as the target cleaning area, and acquiring map data corresponding to each target cleaning area from the area map data.
In some embodiments of the present application, the determining the cleaning category of the target cleaning area according to the determination result includes: if the judgment result indicates that the edge points in the area edge points are all located in the cleaning forbidden zone, determining that the target cleaning zone is a non-cleanable zone; and if the judgment result indicates that the edge points outside the cleaning forbidden zone exist in the zone edge points, determining that the target cleaning zone is a cleanable zone.
In some embodiments of the present application, the performing an edge point extraction process based on the map data to obtain an area edge point of the target cleaning area includes: carrying out contour analysis based on the map data to obtain the region contour shape of the target cleaning region; analyzing the area outline shape by adopting an edge point analysis model to obtain the acquisition position of the area edge point; and extracting the regional edge points of the target cleaning region from the map data according to the acquisition position.
In some embodiments of the present application, before analyzing and processing the contour shape of the region by using the edge point analysis model to obtain the acquisition position of the edge point of the region, the method further includes: carrying out complexity analysis on the region outline shape to obtain the complexity of the region outline shape; and determining whether the edge point analysis model is adopted to analyze the area outline shape or not according to the complexity.
According to an embodiment of the present application, a cleaning area recognition device of a sweeper includes: the acquisition module is used for acquiring the area information of a cleaning forbidden zone set for the sweeper and acquiring the map data corresponding to the target cleaning area; the extraction module is used for extracting and processing the edge points based on the map data to obtain the regional edge points of the target cleaning region; the judging module is used for judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judging result; and the identification module is used for determining the cleaning type of the target cleaning area according to the judgment result.
In some embodiments of the present application, the extraction module comprises a first extraction unit for: dividing pixel points with the same abscissa in the map data into a pixel point subset; and acquiring the maximum ordinate and the pixel point corresponding to the minimum ordinate in each pixel point subset to obtain the regional edge point corresponding to the target cleaning region.
In some embodiments of the present application, the obtaining module comprises a first obtaining unit configured to: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and determining the target cleaning area to be cleaned, and acquiring map data corresponding to the cleaning area matched with the target cleaning area from the area map data.
In some embodiments of the present application, the obtaining module includes a second obtaining unit configured to: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and taking each cleaning area as the target cleaning area, and acquiring map data corresponding to each target cleaning area from the area map data.
In some embodiments of the present application, the identification module comprises: the first identification unit is used for determining that the target cleaning area is an unclonable area if the judgment result indicates that the edge points in the edge points of the area are all located in the cleaning forbidden area; and the second identification unit is used for determining that the target cleaning area is a cleanable area if the judgment result indicates that the edge points outside the cleaning forbidden area exist in the area edge points.
In some embodiments of the present application, the extraction module comprises a second extraction unit for: carrying out contour analysis based on the map data to obtain the region contour shape of the target cleaning region; analyzing the area outline shape by adopting an edge point analysis model to obtain the acquisition position of the area edge point; and extracting the regional edge points of the target cleaning region from the map data according to the acquisition position.
In some embodiments of the present application, the apparatus further comprises an analysis processing unit for: carrying out complexity analysis on the region outline shape to obtain the complexity of the region outline shape; and determining whether to adopt the edge point analysis model to analyze the area outline shape according to the complexity.
According to another embodiment of the present application, a storage medium has stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform the method of an embodiment of the present application.
According to another embodiment of the present application, an electronic device may include: a memory storing a computer program; and the processor reads the computer program stored in the memory to execute the method in the embodiment of the application.
In the embodiment of the application, the regional information of a cleaning forbidden zone set for a sweeper is obtained, and the map data corresponding to the target cleaning region is obtained; performing edge point extraction processing based on the map data to obtain regional edge points of the target cleaning region; judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judgment result; and determining the cleaning type of the target cleaning area according to the judgment result.
In this way, the edge point extraction processing is performed based on the map data of the target cleaning area to obtain the area edge point of the target cleaning area, and when the cleaning type is determined based on the determination result of whether the area edge point is located in the no-clean area, the cleaning type can be accurately determined whether the shapes of the cleaning area and the no-clean area are regular, and the user can optionally set the shape of the no-clean area. And then promote the machine of sweeping the floor and to the discernment accuracy in cleaning the region, promote the performance of sweeping the machine of sweeping the floor, and reduce the restriction that sets up to user's type of cleaning, promote user experience.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 shows a schematic diagram of a system to which embodiments of the present application may be applied.
Fig. 2 shows a flowchart of a cleaning area identification method of a sweeper according to an embodiment of the present application.
Fig. 3 shows a block diagram of a cleaning area recognition device of a sweeper according to an embodiment of the present application.
FIG. 4 shows a block diagram of an electronic device according to an embodiment of the application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the description that follows, specific embodiments of the present application will be described with reference to steps and symbols executed by one or more computers, unless otherwise indicated. Accordingly, these steps and operations will be referred to, several times, as being performed by a computer, the computer performing operations involving a processing unit of the computer in electronic signals representing data in a structured form. This action transforms the data or maintains it at locations in the computer's memory system, which may be reconfigured or otherwise altered in a manner well known to those skilled in the art. The data maintains a data structure that is a physical location of the memory that has particular characteristics defined by the data format. However, the principles of the present application are described in the foregoing text and are not meant to be limiting, as those of ordinary skill in the art will appreciate that various steps and operations described below may be implemented in hardware.
FIG. 1 shows a schematic diagram of a system 100 to which embodiments of the present application may be applied. As shown in fig. 1, the system 100 may include a sweeper 101 and a control device 102. The control device 102 may be any computer device, such as a computer, a mobile phone, a smart watch, a household appliance other than a sweeper, and the like. In one example, the control device 102 is a mobile phone of the target user, an application (app) for controlling the sweeper 101 may be installed in the mobile phone, and a control operation such as a cleaning limit forbidden zone may be set for the sweeper 101 through the app.
In one embodiment of the present example, the sweeper 101 or the control device 102 may: acquiring area information of a cleaning forbidden zone set for the sweeper, and acquiring map data corresponding to a target cleaning area; performing edge point extraction processing based on the map data to obtain area edge points of the target cleaning area; judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judgment result; and determining the cleaning type of the target cleaning area according to the judgment result.
Fig. 2 schematically shows a flowchart of a cleaning area identification method of a sweeper according to an embodiment of the present application. The main body of the sweeper for the cleaning area identification method can be any equipment, such as the sweeper 101 or the control equipment 102 shown in fig. 1.
As shown in fig. 2, the cleaning area recognition method of the sweeper may include steps S210 to S240.
Step S210, acquiring regional information of a cleaning forbidden region set for the sweeper, and acquiring map data corresponding to a target cleaning region; step S220, performing edge point extraction processing based on the map data to obtain regional edge points of the target cleaning region; step S230, judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judgment result; and step S240, determining the cleaning type of the target cleaning area according to the judgment result.
The cleaning forbidden zone is an area where the sweeper is not allowed to clean, a user can select or draw the cleaning forbidden zone in the control application, and the area information of the cleaning forbidden zone is information describing the range of the cleaning forbidden zone, such as area map data of the cleaning forbidden zone.
The target cleaning area may be an area divided by the sweeper scanning the position map data of a certain position, for example, a room is divided into a cleaning area by the sweeper scanning the whole room. The target cleaning area may be an area to be cleaned by the sweeper designated by the user or one cleaning area changed from all the cleaning areas when the user sets the cleaning prohibition area, or the like. The map data may be obtained locally from a server or device that stores the map data.
After the map data is acquired, the map data is subjected to edge point extraction processing, so that the area edge point of the target cleaning area can be obtained, and the area edge point is the position point located at the edge of the target cleaning area.
And comparing the area information of the cleaning forbidden zone with the position of the area edge point to judge whether the extracted area edge point is positioned in the cleaning forbidden zone. According to the judgment result, whether the target cleaning area is included by the cleaning forbidden area or not can be accurately and efficiently determined, and then the cleaning type of the target cleaning area, for example, whether the cleaning type can be carried out or not can be accurately and efficiently determined.
In this way, based on steps S210 to S240, the edge point extraction processing is performed based on the map data of the target cleaning area to obtain the area edge point of the target cleaning area, and when the cleaning type is determined based on the determination result of whether the area edge point is located in the non-cleaning area, whether the shapes of the cleaning area and the non-cleaning area are regular can accurately determine the cleaning type, and the user can optionally set the shape of the non-cleaning area. And then promote the machine of sweeping the floor and to the discernment accuracy in cleaning the region, promote the performance of sweeping the machine of sweeping the floor, and reduce the restriction that sets up to user's type of cleaning, promote user experience.
The following describes a specific process of each step performed when the cleaning area recognition of the sweeper is performed.
In step S210, area information of a cleaning prohibition area set for the sweeper is acquired, and map data corresponding to a target cleaning area is acquired.
The cleaning forbidden zone is an area where the sweeper is not allowed to clean, a user can select or draw the cleaning forbidden zone in the control application, and the area information of the cleaning forbidden zone is information describing the range of the cleaning forbidden zone, such as area map data of the cleaning forbidden zone. It can be understood that the number of the cleaning forbidden zones can be set according to actual requirements.
The target cleaning area may be an area divided by the sweeper after scanning the position map data of a certain position, for example, a room is divided into a cleaning area by the sweeper after scanning the whole room. The target cleaning area may be a cleaning area that a user designates to clean with the sweeper or one cleaning area that is traversed from all cleaning areas when the user sets a cleaning forbidden area, etc. The map data may be obtained locally from a server or device that stores the map data.
In one embodiment, in step S210, the obtaining of the map data corresponding to the target cleaning area includes: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and determining the target cleaning area to be cleaned, and acquiring map data corresponding to the cleaning area matched with the target cleaning area from the area map data.
The target area may be an area of a certain location pair, such as an area of a whole house pair. The target area is divided into a plurality of cleaning areas, for example, each room is divided into one cleaning area after the sweeper scans the whole room. The target cleaning area to be cleaned can be a cleaning area which is cleaned by a sweeper and is appointed by a user, after the cleaning area to be cleaned is appointed, map data corresponding to the cleaning area matched with the target cleaning area can be obtained from the area map data in a matching mode, then the cleaning type can be identified in the cleaning process based on the follow-up steps, and whether the sweeper is used for cleaning or not can be controlled.
In one embodiment, in step S210, the obtaining of the map data corresponding to the target cleaning area includes: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and taking each cleaning area as the target cleaning area, and acquiring map data corresponding to each target cleaning area from the area map data.
The target area may be an area of a certain location pair, such as an area of a full house pair. The target area is divided into a plurality of cleaning areas, for example, each room is divided into one cleaning area after the sweeper scans the whole room. The target cleaning area may be a cleaning area traversed from all cleaning areas when a user sets a cleaning forbidden area, corresponding map data may be obtained from the area map data when the user traverses to one cleaning forbidden area, and then the cleaning category may be identified in the forbidden area setting process based on the subsequent steps, and whether the forbidden area setting is appropriate or not may be further determined.
In step S220, an edge point extraction process is performed based on the map data to obtain an area edge point of the target cleaning area.
After the map data is acquired, the map data is subjected to edge point extraction processing, so that the area edge points of the target cleaning area can be obtained, and the area edge points are position points located at the edge of the target cleaning area.
In one embodiment, in step S220, performing edge point extraction processing based on the map data to obtain an area edge point corresponding to the target cleaning area includes: dividing pixel points with the same abscissa in the map data into a pixel point subset; and acquiring pixel points corresponding to the maximum vertical coordinate and the minimum vertical coordinate in each pixel point subset to obtain area edge points corresponding to the target cleaning area.
Each pixel point in the map data corresponds to an abscissa X and an ordinate Y, firstly, the pixel points with the same abscissa X are divided into a pixel point subset to obtain at least one pixel point subset, then, the pixel points corresponding to the maximum ordinate Ymax and the minimum ordinate Ymin in each pixel point subset are determined, the pixel points are all marginal area edge points of a target cleaning area, and the extraction method is efficient and accurate.
In one embodiment, in step S220, performing an edge point extraction process based on the map data to obtain an area edge point of the target cleaning area includes: carrying out contour analysis based on the map data to obtain the region contour shape of the target cleaning region; analyzing the shape of the area outline by adopting an edge point analysis model to obtain the acquisition position of the edge point of the area; and extracting the regional edge points of the target cleaning region from the map data according to the acquisition position.
Performing contour analysis based on the map data may include: dividing pixel points with the same abscissa in the map data into a pixel point subset; and acquiring the maximum vertical coordinate and the pixel point corresponding to the minimum vertical coordinate in each pixel point subset to obtain the longitudinal zone edge point corresponding to the target cleaning zone. Dividing pixel points with the same vertical coordinate in map data into a pixel point subset; and acquiring the maximum abscissa and the pixel point corresponding to the minimum abscissa in each pixel point subset to obtain the transverse region edge point corresponding to the target cleaning region. The region contour shape of the target cleaning region can be drawn based on the longitudinal region edge points and the transverse region edge points.
The edge point analysis model can be a pre-trained machine learning-based analysis model, the area outline shape is converted into an input matrix (for example, the element of the corresponding position of each pixel point corresponding to the area outline shape in the matrix is set as 1, and other elements in the matrix are set as 0 to obtain the input matrix), the input matrix is input into the edge point analysis model to obtain the acquisition position of the area edge point, comparison operation of subsequent steps can be performed only by acquiring a small number of area edge points according to the acquisition position, and the cleaning category can be accurately identified while the identification efficiency is effectively improved.
In an embodiment, before the analyzing and processing the contour shape of the region by using the edge point analysis model to obtain the collection position of the edge point of the region, the method further includes: carrying out complexity analysis on the region outline shape to obtain the complexity of the region outline shape; and determining whether the edge point analysis model is adopted to analyze the area outline shape or not according to the complexity.
After the area outline shape is obtained, the complexity of the area outline shape can be determined according to the ratio of the number of pixels forming the area outline shape and the number area enclosed by the area outline shape by statistics, for example, when the ratio of the number area is smaller, the complexity of the area outline shape is higher, and the complexity is higher than a predetermined threshold (namely, the ratio of the number area is smaller than a predetermined size), an edge point analysis model can be adopted to analyze and process the area outline shape, so that unnecessary calculation processing can be further avoided, and particularly, when the sweeper is subjected to identification processing, the performance of the sweeper can be effectively improved.
In step S230, it is determined whether the area edge point is located in the no-clean zone according to the area information, so as to obtain a determination result.
And comparing the area information of the cleaning forbidden zone with the position of the area edge point to judge whether the extracted area edge point is positioned in the cleaning forbidden zone. When comparing the area information of the cleaning forbidden zone with the position of the area edge point, the area edge point can be traversed in sequence, whether the traversed area edge point is positioned in the cleaning forbidden zone or not is judged, and when the certain area edge point is positioned outside the cleaning forbidden zone, the judgment can be stopped quickly.
In step S240, the cleaning type of the target cleaning area is determined according to the determination result.
According to the judgment result, whether the target cleaning area is included by the cleaning forbidden area or not can be accurately and efficiently determined, and then the cleaning type of the target cleaning area, for example, whether the cleaning type can be carried out or not can be accurately and efficiently determined.
In one embodiment, the step S240 of determining the cleaning category of the target cleaning area according to the determination result includes: if the judgment result indicates that the edge points in the area edge points are all located in the cleaning forbidden zone, determining that the target cleaning zone is a non-cleanable zone; and if the judgment result indicates that the edge points outside the cleaning forbidden zone exist in the zone edge points, determining that the target cleaning zone is a cleanable zone.
The non-cleanable area is the area that cannot be cleaned by the sweeper, and the cleanable area is the area that can be cleaned by the sweeper, and in this way, the sweeper can be accurately controlled.
In order to better implement the method for identifying the cleaning area of the sweeper provided by the embodiment of the application, the embodiment of the application also provides a device for identifying the cleaning area of the sweeper based on the method for identifying the cleaning area of the sweeper. The meaning of the noun is the same as that in the cleaning area identification method of the sweeper, and specific implementation details can refer to the description in the method embodiment. Fig. 3 shows a block diagram of a cleaning area recognition device of a sweeper according to an embodiment of the present application.
As shown in fig. 3, the cleaning area recognition device 300 of the sweeper may include an obtaining module 310, an extracting module 320, a determining module 330, and a recognition module 340.
The obtaining module 310 may be configured to obtain area information of a restricted cleaning area set for the sweeper, and obtain map data corresponding to a target cleaning area; the extraction module 320 may be configured to perform edge point extraction processing based on the map data to obtain an area edge point of the target cleaning area; the determining module 330 may be configured to determine whether the area edge point is located in the no-clean zone according to the area information, so as to obtain a determination result; the identification module 340 may be configured to determine the cleaning category of the target cleaning area according to the determination result.
In some embodiments of the present application, the extraction module comprises a first extraction unit for: dividing pixel points with the same abscissa in the map data into a pixel point subset; and acquiring pixel points corresponding to the maximum vertical coordinate and the minimum vertical coordinate in each pixel point subset to obtain area edge points corresponding to the target cleaning area.
In some embodiments of the present application, the obtaining module comprises a first obtaining unit configured to: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and determining the target cleaning area to be cleaned, and acquiring map data corresponding to the cleaning area matched with the target cleaning area from the area map data.
In some embodiments of the present application, the obtaining module includes a second obtaining unit configured to: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and taking each cleaning area as the target cleaning area, and acquiring map data corresponding to each target cleaning area from the area map data.
In some embodiments of the present application, the identification module comprises: the first identification unit is used for determining that the target cleaning area is an unclonable area if the judgment result indicates that the edge points in the edge points of the area are all located in the cleaning forbidden area; and the second identification unit is used for determining that the target cleaning area is a cleanable area if the judgment result indicates that the edge points outside the cleaning forbidden area exist in the area edge points.
In some embodiments of the present application, the extraction module comprises a second extraction unit for: carrying out contour analysis based on the map data to obtain the region contour shape of the target cleaning region; analyzing the area outline shape by adopting an edge point analysis model to obtain the acquisition position of the area edge point; and extracting the regional edge points of the target cleaning region from the map data according to the acquisition position.
In some embodiments of the present application, the apparatus further comprises an analysis processing unit for: carrying out complexity analysis on the region outline shape to obtain the complexity of the region outline shape; and determining whether to adopt the edge point analysis model to analyze the area outline shape according to the complexity.
In this way, the cleaning area recognition device 300 based on the sweeper performs edge point extraction processing based on the map data of the target cleaning area to obtain the area edge point of the target cleaning area, and when the cleaning type is determined based on the determination result of whether the area edge point is located in the no-clean-area, whether the shapes of the cleaning area and the no-clean-area are regular can accurately determine the cleaning type, and the user can set the shape of the no-clean-area at will. And then promote the machine of sweeping the floor and to the discernment accuracy in cleaning the region, promote the performance of sweeping the machine of sweeping the floor, and reduce the restriction that sets up to user's type of cleaning, promote user experience.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
In addition, an embodiment of the present application further provides an electronic device, where the electronic device may be a terminal or a server, as shown in fig. 4, which shows a schematic structural diagram of the electronic device according to the embodiment of the present application, and specifically:
the electronic device may include components such as a processor 401 of one or more processing cores, memory 402 of one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 4 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components. Wherein:
the processor 401 is a control center of the electronic device, connects various parts of the entire computer device using various interfaces and lines, performs various functions of the computer device and processes data by operating or executing software programs and/or modules stored in the memory 402 and calling data stored in the memory 402, thereby integrally monitoring the electronic device. Optionally, processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles operating systems, user pages, application programs, and the like, and the modem processor mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 401.
The memory 402 may be used to store software programs and modules, and the processor 401 executes various functional applications and data processing by operating the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to use of the computer device, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 access to the memory 402.
The electronic device further comprises a power supply 403 for supplying power to the various components, and preferably, the power supply 403 is logically connected to the processor 401 through a power management system, so that the functions of charging, discharging, and power consumption management are managed through the power management system. The power supply 403 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
The electronic device may further include an input unit 404, and the input unit 404 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
Although not shown, the electronic device may further include a display unit and the like, which are not described in detail herein. Specifically, in this embodiment, the processor 401 in the electronic device loads the executable file corresponding to the process of one or more computer programs into the memory 402 according to the following instructions, and the processor 401 runs the computer program stored in the memory 402, so as to implement various functions in the foregoing embodiments of the present application, for example, the processor 401 may execute the following steps:
acquiring area information of a cleaning forbidden area set for the sweeper, and acquiring map data corresponding to a target cleaning area; performing edge point extraction processing based on the map data to obtain area edge points of the target cleaning area; judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judgment result; and determining the cleaning type of the target cleaning area according to the judgment result.
In some embodiments of the application, when performing the edge point extraction processing based on the map data to obtain the edge point of the area corresponding to the target cleaning area, the processor 401 may perform: dividing pixel points with the same abscissa in the map data into a pixel point subset; and acquiring pixel points corresponding to the maximum vertical coordinate and the minimum vertical coordinate in each pixel point subset to obtain area edge points corresponding to the target cleaning area.
In some embodiments of the present application, when obtaining the map data corresponding to the target cleaning area, the processor 401 may perform: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and determining the target cleaning area to be cleaned, and acquiring map data corresponding to the cleaning area matched with the target cleaning area from the area map data.
In some embodiments of the application, when obtaining the map data corresponding to the target cleaning area, the processor 401 may perform: acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region; and taking each cleaning area as the target cleaning area, and acquiring map data corresponding to each target cleaning area from the area map data.
In some embodiments of the application, when determining the cleaning category of the target cleaning area according to the determination result, the processor 401 may perform: if the judgment result indicates that the edge points in the area edge points are all located in the cleaning forbidden zone, determining that the target cleaning area is an uncleanable area; and if the judgment result indicates that the edge points outside the cleaning forbidden zone exist in the zone edge points, determining that the target cleaning zone is a cleanable zone.
In some embodiments of the present application, when performing the edge point extraction processing based on the map data to obtain the area edge point of the target cleaning area, the processor 401 may perform: carrying out contour analysis based on the map data to obtain the region contour shape of the target cleaning region; analyzing the area outline shape by adopting an edge point analysis model to obtain the acquisition position of the area edge point; and extracting the regional edge points of the target cleaning region from the map data according to the acquisition position.
In some embodiments of the present application, the processor 401 may perform: carrying out complexity analysis on the region outline shape to obtain the complexity of the region outline shape; and determining whether to adopt the edge point analysis model to analyze the area outline shape according to the complexity.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be implemented by a computer program, which may be stored in a computer-readable storage medium and loaded and executed by a processor, or by a computer program controlling associated hardware.
To this end, the present application further provides a storage medium, in which a computer program is stored, where the computer program can be loaded by a processor to execute the steps in any one of the methods provided in the present application.
Wherein the storage medium may include: read Only Memory (ROM), random Access Memory (RAM), magnetic or optical disks, and the like.
Since the computer program stored in the storage medium can execute the steps in any method provided in the embodiments of the present application, the beneficial effects that can be achieved by the methods provided in the embodiments of the present application can be achieved, for details, see the foregoing embodiments, and are not described herein again.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.
It will be understood that the present application is not limited to the embodiments that have been described above and shown in the drawings, but that various modifications and changes can be made without departing from the scope thereof.
Claims (8)
1. A cleaning area recognition method of a sweeper is characterized by comprising the following steps:
acquiring area information of a cleaning forbidden zone set for the sweeper, and acquiring map data corresponding to a target cleaning area;
performing edge point extraction processing based on the map data to obtain area edge points of the target cleaning area;
judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judgment result;
determining the cleaning type of the target cleaning area according to the judgment result;
the performing edge point extraction processing based on the map data to obtain the area edge point of the target cleaning area includes:
carrying out contour analysis based on the map data to obtain the region contour shape of the target cleaning region;
analyzing the shape of the area outline by adopting an edge point analysis model to obtain the acquisition position of the edge point of the area;
extracting area edge points of the target cleaning area from the map data according to the acquisition position;
before the analyzing the area contour shape by using the edge point analyzing model to obtain the collecting position of the area edge point, the method further comprises the following steps:
carrying out complexity analysis on the region outline shape to obtain the complexity of the region outline shape;
and determining whether the edge point analysis model is adopted to analyze the area outline shape or not according to the complexity.
2. The method according to claim 1, wherein the performing edge point extraction processing based on the map data to obtain an area edge point corresponding to the target cleaning area comprises:
dividing pixel points with the same abscissa in the map data into a pixel point subset;
and acquiring pixel points corresponding to the maximum vertical coordinate and the minimum vertical coordinate in each pixel point subset to obtain area edge points corresponding to the target cleaning area.
3. The method according to claim 1, wherein the obtaining map data corresponding to the target cleaning area comprises:
acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region;
and determining the target cleaning area to be cleaned, and acquiring map data corresponding to the cleaning area matched with the target cleaning area from the area map data.
4. The method according to claim 1, wherein the obtaining map data corresponding to the target cleaning area comprises:
acquiring regional map data of a target region, wherein the target region is divided into a plurality of cleaning regions, and the regional map data comprises map data of each cleaning region;
and taking each cleaning area as the target cleaning area, and acquiring map data corresponding to each target cleaning area from the area map data.
5. The method as claimed in claim 1, wherein the determining the cleaning category of the target cleaning area according to the judgment result comprises:
if the judgment result indicates that the edge points in the area edge points are all located in the cleaning forbidden zone, determining that the target cleaning zone is a non-cleanable zone;
and if the judgment result indicates that the edge points outside the cleaning forbidden zone exist in the zone edge points, determining that the target cleaning zone is a cleanable zone.
6. The utility model provides a regional recognition device cleans of machine of sweeping floor which characterized in that includes:
the acquisition module is used for acquiring the area information of a cleaning forbidden zone set for the sweeper and acquiring the map data corresponding to the target cleaning area;
the extraction module is used for extracting and processing the edge points based on the map data to obtain the regional edge points of the target cleaning region; the performing edge point extraction processing based on the map data to obtain the area edge point of the target cleaning area includes: carrying out contour analysis based on the map data to obtain the region contour shape of the target cleaning region; analyzing the shape of the area outline by adopting an edge point analysis model to obtain the acquisition position of the edge point of the area; extracting area edge points of the target cleaning area from the map data according to the acquisition position; before the analyzing the area contour shape by using the edge point analyzing model to obtain the collecting position of the area edge point, the method further comprises the following steps: carrying out complexity analysis on the region outline shape to obtain the complexity of the region outline shape; determining whether the edge point analysis model is adopted to analyze the area outline shape or not according to the complexity;
the judging module is used for judging whether the area edge point is positioned in the cleaning forbidden zone according to the area information to obtain a judging result;
and the identification module is used for determining the cleaning type of the target cleaning area according to the judgment result.
7. A storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to carry out the method of any one of claims 1 to 5.
8. An electronic device, comprising: a memory storing a computer program; a processor reading a computer program stored in the memory to perform the method of any of claims 1 to 5.
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