Intelligent recovery method for cleaning habit

Abstract

The invention relates to an intelligent recovery method for cleaning habits. The original forbidden zone setting information is obtained according to the forbidden zone setting of the user for the original map, and the user cleaning habit about the forbidden zone setting is obtained through accurate analysis, so that after the original map is damaged or not applicable and the new map is obtained again, on one hand, the original forbidden zone setting can be intelligently recovered according to the original forbidden zone setting information; on the other hand, corresponding forbidden zones can be intelligently set according to cleaning habits of the user, user requirements are met, and the use complexity of the user is reduced.

Description

Technical Field

[0001] The present disclosure relates to the technical field of cleaning robots, and in particular to an intelligent recovery method for cleaning habits. Background Art

[0002] A cleaning robot is a common intelligent cleaning device. Usually, in order to prevent the cleaning robot from getting stuck or entangled during operation, a cleaning restricted area is often set to prevent the cleaning robot from entering scenes that the user does not need to clean.

[0003] Patent document CN112526985A discloses a method for planning walking restricted areas, which uses a robot to automatically identify scenes in a map, and automatically sets certain specific scenes (such as easily trapped areas, areas with dense obstacles, kitchens and toilets) as restricted areas based on scene labels such as the number of times the robot is trapped, the total number of obstacle grids, the density of obstacles, and closed areas. Although this method can automatically set restricted areas in a map, it can only be set for scenes with fixed features, and cannot fit the user's personalized cleaning habits well; if the user wants the cleaning robot's cleaning area to fully meet their own usage habits, the user needs to manually set the cleaning restricted area on the application side.

[0004] However, this setting method is usually accompanied by a fixed scene map. If the original scene map is no longer applicable or damaged due to changes in the home environment or improper use of the cleaning robot, the corresponding cleaning configurations such as cleaning restricted areas will become unusable, requiring users to reconfigure, increasing the complexity of user use. Summary of the invention

[0005] In order to solve the above technical problems, the present disclosure provides an intelligent recovery method for cleaning habits to reduce the complexity of user use.

[0006] The intelligent recovery method of cleaning habits provided by the embodiment of the present disclosure includes:

[0007] Acquire an original map corresponding to the cleaning work environment and original cleaning configuration information corresponding to the original map, wherein the original cleaning configuration information includes original restricted area setting information and user cleaning habit information;

[0008] After the original map is unusable, re-constructing a map of the cleaning work environment to obtain a newly constructed map corresponding to the cleaning work environment;

[0009] Transferring the original cleaning configuration information to the newly created map;

[0010] According to the original cleaning configuration information, a restricted area is automatically set in the newly created map to obtain a restricted area restoration result of the newly created map.

[0011] In some embodiments, the obtaining of the original map corresponding to the cleaning working environment and the original cleaning configuration information corresponding to the original map includes:

[0012] Performing scene segmentation on the original map to determine a plurality of scenes included in the original map;

[0013] Based on the user's confirmation information on the restricted area in the multiple scenes, original cleaning configuration information of the original map is determined.

[0014] In some embodiments, the original restricted area setting information includes first restricted area configuration information; and determining the original cleaning configuration information of the original map based on the user's confirmation information of the restricted area in the multiple scenes includes:

[0015] In response to a user's operation of selecting a restricted area of ​​a first area in the multiple scenes, obtaining a reason why the user sets a restricted area of ​​the first area;

[0016] The configuration information of the first restricted area of ​​the first area is saved, and the scene attribute of the first area and the reason for setting the restricted area are stored in the user cleaning habit information.

[0017] In some embodiments, before determining the original cleaning configuration information of the original map based on the user's confirmation information of the restricted area in the multiple scenes, the method further includes:

[0018] According to the motor current data and camera data of the cleaning robot, the fault-prone areas in the multiple scenes are marked.

[0019] In some embodiments, the original restricted area setting information further includes second restricted area configuration information, and the determining of the original cleaning configuration information of the original map based on the user's confirmation information of the restricted area in the multiple scenes includes:

[0020] If there is a second area in the fault-prone area, confirm with the user whether the second area needs to be set as a restricted area, and the scene attribute similarity between the second area and any restricted area in the original restricted area setting information is greater than a first similarity threshold;

[0021] If the user confirms to set the second area as a restricted area, the second restricted area configuration information of the second area is saved, and the scene attributes of the second area are stored in the user cleaning habit information.

[0022] In some embodiments, the method further comprises:

[0023] If there is a third area in the prone-to-failure area, confirm the scene attribute of the third area with the user to obtain a scene attribute confirmation result, wherein the third area is any area in the prone-to-failure area except the second area;

[0024] The scene attribute of the third area and the scene attribute confirmation result are stored in the user cleaning habit information.

[0025] In some embodiments, automatically setting a restricted area in the newly created map according to the original cleaning configuration information includes:

[0026] Matching the newly created map with the original map to obtain a map matching degree;

[0027] If the map matching degree is greater than or equal to a first matching degree threshold, automatically setting a restricted area in the newly created map according to the original restricted area setting information; or,

[0028] If the map matching degree is less than a first matching degree threshold, a restricted area is automatically set in the newly created map according to the scene recognition result of the newly created map and the user's cleaning habit information.

[0029] In some embodiments, matching the newly created map with the original map to obtain a map matching degree includes:

[0030] Determining a matching weight for each matching feature, the matching features including map area, map shape, and number of rooms;

[0031] Comparing the matching features of the newly created map with the matching features of the original map to obtain a feature similarity of each matching feature;

[0032] The map matching degree is calculated based on the feature similarity of each matching feature and the matching weight of each matching feature.

[0033] In some embodiments, the user cleaning habit information includes a correspondence between scene attributes of each scene in the original map and original restricted area setting information of the scene; the automatically setting restricted areas in the newly created map according to the scene recognition result of the newly created map and the user cleaning habit information includes:

[0034] For the target scene in the newly created map, determining the scene attribute of the target scene according to the scene recognition result;

[0035] Based on the user's cleaning habit information, determining target original restricted area setting information corresponding to the scene attribute;

[0036] A restricted area is automatically set in the newly created map according to the target original restricted area setting information.

[0037] In some embodiments, the original map includes a first scene, and the newly created map includes a plurality of second scenes; and automatically setting a restricted area in the newly created map according to the scene recognition result of the newly created map and the user's cleaning habit information includes:

[0038] If it is determined according to the scene recognition result that the scene attributes of the plurality of second scenes are the same as the first scene, a restricted area is automatically set in each of the second scenes according to the original restricted area setting information of the first scene.

[0039] The intelligent recovery method of cleaning habits provided by the embodiment of the present disclosure obtains original restricted area setting information according to the restricted area settings of the original map by the user, and accurately analyzes the user's cleaning habits regarding the restricted area settings. Then, when the original map is damaged or no longer applicable, after re-obtaining a new map, on the one hand, it can intelligently restore the original restricted area settings according to the original restricted area setting information, and on the other hand, it can also intelligently set corresponding restricted areas according to the user's cleaning habits, which is close to user needs and reduces the complexity of user use.

[0040] In some embodiments, the present disclosure not only sets restricted areas based on user selection operations and obtains corresponding user cleaning habits, but can also remind users for unselected areas similar to restricted areas manually set by users, thereby improving the flexibility of restricted area setting and user cleaning habit acquisition processes.

[0041] In some embodiments, when the similarity between the original map and the newly created map is high, the restricted area setting information in the newly created map is directly restored based on the original restricted area setting information. When the similarity between the original map and the newly created map is low, the restricted area settings in the newly created map are intelligently analyzed and restored based on the user's cleaning habits. The accuracy of the restricted area settings in the newly created map can also be guaranteed when the cleaning working environment changes significantly. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 A flow chart of a smart recovery method for cleaning habits provided by an embodiment of the present disclosure;

[0045] Figure 2 A flow chart of a method for intelligently restoring cleaning habits provided by another embodiment of the present disclosure;

[0046] Figure 3 A flow chart of a method for intelligently restoring cleaning habits provided by another embodiment of the present disclosure;

[0047] Figure 4 A schematic diagram of the structure of an intelligent cleaning habit recovery device provided in an embodiment of the present disclosure;

[0048] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0049] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0050] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0051] The disclosed embodiment provides an intelligent method for restoring cleaning habits, which is introduced below in conjunction with specific embodiments.

[0052] Figure 1 This is a flow chart of the intelligent recovery method for cleaning habits provided in the embodiment of the present disclosure. The method can be applied to a cleaning robot. It is understandable that the intelligent recovery method for cleaning habits provided in the embodiment of the present disclosure can also be applied in other scenarios.

[0053] Below Figure 1 The smart recovery method of cleaning habits shown in the figure is introduced, and the specific steps of the method are as follows:

[0054] S101. Acquire an original map corresponding to a cleaning work environment and original cleaning configuration information corresponding to the original map, wherein the original cleaning configuration information includes original restricted area setting information and user cleaning habit information.

[0055] The cleaning work environment is the working environment of the cleaning robot. Before the cleaning robot performs a task in the cleaning work environment for the first time, it is necessary to first collect environmental information of the cleaning work environment and construct a map to obtain an original map corresponding to the cleaning work environment.

[0056] For example, the cleaning robot scans and records the surrounding environment information through the laser radar and other information collection devices it carries, and generates an original map based on the collected information.

[0057] The restricted area setting information corresponding to the original map indicates the areas in the cleaning work environment that the cleaning robot is not required to enter. In the cleaning work environment, there may be areas that the user does not want the cleaning robot to enter, such as the area around the wires / ropes on the ground, the area around the threshold strips, the area around the carpet, etc. These areas are restricted areas. When the cleaning robot performs task path planning based on the original map, it needs to bypass the restricted areas.

[0058] Optionally, the restricted area setting information corresponding to the original map is obtained based on manual settings of the original map by the user, and / or automatically identified, wherein the restricted area obtained by automatic identification needs to be saved after secondary confirmation by the user.

[0059] The user's cleaning habit information refers to the habits that the user exhibits when setting a restricted area. These habits are related to the location of the restricted area and other features, and may also be related to the cleaning time period. For example, the user may set a room as a restricted area because there is a blanket in the room; or the user may set the bedroom as a restricted area during the night time period because the bedroom needs to be kept quiet during sleep.

[0060] S102: after the original map is unusable, re-constructing a map of the cleaning work environment to obtain a newly constructed map corresponding to the cleaning work environment.

[0061] When the cleaning work environment changes, for example, the layout of the furniture in the room changes, or the data of the original map is damaged, the cleaning work environment needs to be remapped to obtain a new map. At this time, the new map only includes the actual environment information such as obstacles in the cleaning work environment.

[0062] S103: Transfer the original cleaning configuration information to the newly created map.

[0063] When the original map is damaged, the original cleaning configuration information corresponding to the original map still exists in the storage space of the cleaning robot. The cleaning robot can transfer the original cleaning configuration information to the newly created map so that the newly created map can restore relevant settings according to the original cleaning configuration information.

[0064] S104. Automatically set a restricted area in the newly created map according to the original cleaning configuration information, and obtain a restricted area restoration result of the newly created map.

[0065] As described above, the newly created map corresponds to the cleaning work environment (or the updated cleaning work environment), but the user has not set the restricted area therein. The cleaning robot automatically restores the restricted area setting in the newly created map based on the original cleaning information to obtain the restricted area restoration result.

[0066] Specifically, the original cleaning configuration information is matched with the newly created map. For areas where the matching degree is higher than the preset matching degree threshold, the restricted area settings of the area are restored directly based on the original restricted area setting information in the original cleaning configuration information; for areas where the matching degree is not higher than the preset matching degree threshold, the restricted area settings of the area are restored based on the user cleaning habit information in the original cleaning configuration information.

[0067] The disclosed embodiment obtains an original map corresponding to a cleaning work environment and original cleaning configuration information corresponding to the original map, wherein the original cleaning configuration information includes original restricted area setting information and user cleaning habit information; after the original map cannot be used, the cleaning work environment is re-mapped to obtain a newly created map corresponding to the cleaning work environment; the original cleaning configuration information is transferred to the newly created map; according to the original cleaning configuration information, restricted areas are automatically set in the newly created map to obtain a restricted area recovery result of the newly created map; the original restricted area setting information is obtained according to the restricted area setting of the original map by the user, and the user's cleaning habits regarding the restricted area setting are accurately analyzed, and then when the original map is damaged or no longer applicable, after the newly created map is re-acquired, on the one hand, the original restricted area setting can be intelligently restored according to the original restricted area setting information, and on the other hand, the corresponding restricted area can be intelligently set according to the user's cleaning habits, which is close to user needs and reduces the complexity of user use.

[0068] Figure 2 A flow chart of a smart recovery method for cleaning habits provided by another embodiment of the present disclosure is as follows: Figure 2 As shown, the method includes the following steps:

[0069] S201. Acquire an original map corresponding to a cleaning work environment and original cleaning configuration information corresponding to the original map.

[0070] The original cleaning configuration information includes original restricted area setting information and user cleaning habit information.

[0071] S202: Segment the original map into scenes to determine a plurality of scenes included in the original map.

[0072] Multiple scenes include different rooms. After obtaining the original map, the cleaning robot will automatically divide different room areas, such as kitchen, bathroom, bedroom, living room, etc., according to the collected environmental data (such as furniture layout, wall position, etc.), and distinguish them with different colors.

[0073] S203: Mark the fault-prone areas in the multiple scenes according to the motor current data and camera data of the cleaning robot.

[0074] Fault-prone areas refer to areas where the cleaning robot is prone to malfunction, such as areas where floor wires / cords are entangled, areas where door sills are located, areas where carpets are located, and the like.

[0075] The cleaning robot can collect the current data of the wheels, side brushes, roller brushes and other motors in real time through the built-in motor current sensor, and process and analyze the collected motor current data to identify the current changes of the motors in different working states. By comparing the current data under normal conditions with the current data under abnormal conditions, it can identify whether the motor has faults such as overload and stall, and determine whether the area where the cleaning robot is currently located is a difficult-to-cross fault-prone area.

[0076] In addition, the cleaning robot collects image data of the surrounding environment in real time through image information acquisition modules such as cameras, and uses stereo vision technology, object recognition algorithms and other technologies to identify and distinguish different types of obstacles, so as to identify scene features that may cause failures (such as uneven ground, densely placed furniture, etc.) and mark the corresponding fault-prone areas.

[0077] S204: Determine original cleaning configuration information of the original map based on the user's confirmation information on the restricted area in the multiple scenes.

[0078] The restricted area setting information in the original cleaning configuration information includes the restricted areas manually selected by the user, and also includes the fault-prone areas automatically marked by the cleaning robot after confirmation by the user. The following describes each type of restricted area setting information separately.

[0079] In some embodiments, the original restricted area setting information includes first restricted area configuration information. In response to a user selecting a restricted area of ​​a first area in the multiple scenes, a user's reason for setting a restricted area for the first area is obtained; the first restricted area configuration information of the first area is saved, and the scene attribute of the first area and the reason for setting the restricted area are stored in the user's cleaning habit information.

[0080] The first restricted area configuration information is the restricted area manually selected by the user.

[0081] After the cleaning robot completes the mapping and obtains the initial map, it can remind the user to confirm the scene segmentation results and marking results in the application. The user can manually select the area that the cleaning robot does not want to enter in the application to obtain the first area. Specifically, the first area can be the entire scene, or a part of the scene, which is not limited in the embodiments of the present disclosure.

[0082] After the user makes a restricted area selection operation for the first area, restricted area confirmation information is displayed in the application to guide the user to enter the reason for setting the restricted area, such as anti-entanglement, anti-water accumulation, anti-noise, etc.

[0083] The scene attributes include one or more of the size, position, marking result, and obstacle arrangement characteristics of the scene / area, etc. The scene attribute of the first area is associated with the reason for setting the restricted area of ​​the first area, and stored in the user's cleaning habits.

[0084] In some other embodiments, the original restricted area setting information further includes second restricted area configuration information. If there is a second area in the fault-prone area, the user is asked whether the second area needs to be set as a restricted area, and the scene attribute similarity between the second area and any restricted area in the original restricted area setting information is greater than a first similarity threshold; if the user confirms setting the second area as a restricted area, the second restricted area configuration information of the second area is saved, and the scene attribute of the second area is stored in the user cleaning habit information.

[0085] The second area is automatically identified by the cleaning robot and has a scene attribute similarity with any restricted area greater than the first similarity threshold. Optionally, the scene attribute similarity between the second area and the first area is greater than the first similarity threshold.

[0086] When there is a second area in the fault-prone area, and the user has not set a restricted area for the second area, the system actively confirms with the user whether the second area needs to be set as a restricted area, for example, by confirming with the user through the application "Do you want to set the XX area / room as a restricted area?" When the user confirms to set the second area as a restricted area, the scene attribute of the second area is also stored in the user's cleaning habit information.

[0087] Optionally, the cleaning robot confirms with the user the reason why the second area is set as a restricted area based on the second area, for example, by asking the user “Is this area prone to entanglement?”, thereby collecting the reason why the restricted area is set in the second area, and associating the scene attributes of the second area with the reason why the restricted area is set in the second area, and storing them in the user's cleaning habits.

[0088] In other embodiments, if there is a third area in the fault-prone area, the scene attributes of the third area are confirmed with the user to obtain a scene attribute confirmation result, and the third area is any area in the fault-prone area except the second area; the scene attributes of the third area and the scene attribute confirmation result are stored in the user's cleaning habit information.

[0089] As described above, after the cleaning robot completes the mapping and obtains the initial map, it can remind the user in the application to confirm the scene segmentation results and marking results, where the marking results include scene division marking results (such as kitchen, bathroom, bedroom, living room, etc.) and also include the marking results of the prone area. After determining the second area, if there is a third area in the prone area that is not marked as a restricted area, the scene attributes of the third area are confirmed to the user, that is, whether the scene attribute recognition of the third area is accurate. For example, for the third area identified as the threshold bar area, the user is asked "whether there is a threshold in this area" to optimize the marking results of the prone area.

[0090] S205: after the original map is unusable, re-map the cleaning work environment to obtain a new map corresponding to the cleaning work environment.

[0091] S206: Transfer the original cleaning configuration information to the newly created map.

[0092] S207. Automatically set a restricted area in the newly created map according to the original cleaning configuration information, and obtain a restricted area restoration result of the newly created map.

[0093] Specifically, the implementation process and principle of S205-S207 and S102-S104 are consistent and will not be repeated here.

[0094] The disclosed embodiment not only sets restricted areas based on user selection operations and obtains corresponding user cleaning habits, but can also remind users of unselected areas similar to restricted areas manually set by users, thereby improving the flexibility of restricted area setting and user cleaning habit acquisition processes.

[0095] Figure 3 A flow chart of a smart recovery method for cleaning habits provided by another embodiment of the present disclosure is as follows: Figure 3 As shown, the method includes the following steps:

[0096] S301: Acquire an original map corresponding to a cleaning work environment and original cleaning configuration information corresponding to the original map.

[0097] The original cleaning configuration information includes original restricted area setting information and user cleaning habit information.

[0098] S302: after the original map is unusable, re-map the cleaning work environment to obtain a new map corresponding to the cleaning work environment.

[0099] S303: Transfer the original cleaning configuration information to the newly created map.

[0100] S304: Match the newly created map with the original map to obtain a map matching degree.

[0101] The map matching degree characterizes the degree of change of the cleaning working environment. The cleaning robot evaluates the matching degree between the original map and the newly created map based on multiple matching features to determine the degree of change between the cleaning working environment corresponding to the original map and the working environment corresponding to the newly created map, thereby determining the applicable strategy of the original cleaning configuration information in the newly created map.

[0102] Specifically, a matching weight of each matching feature is determined, wherein the matching features include map area, map shape, and the number of rooms; the matching features of the newly created map are compared with the matching features of the original map to obtain the feature similarity of each matching feature; and the map matching degree is calculated based on the feature similarity of each matching feature and the matching weight of each matching feature.

[0103] The cleaning robot obtains the map area of ​​the original map and the map area of ​​the newly created map respectively for comparison to obtain the map area similarity; obtains the map shape of the original map and the map shape of the newly created map for comparison to obtain the map shape similarity; obtains the number of rooms of the original map and the number of rooms of the newly created map for comparison to obtain the room number similarity; further, according to the feature weights of the map area, map shape and number of rooms, the map area similarity, map shape similarity and room number similarity are weighted summed or averaged to obtain the map matching degree.

[0104] Optionally, the map area feature weight and the map shape feature weight are each 80%, and the room quantity feature weight is 20%.

[0105] S305: Determine whether the map matching degree is less than a first matching degree threshold. If so, execute S307; if not, execute S306.

[0106] S306: If the map matching degree is greater than or equal to a first matching degree threshold, automatically setting a restricted area in the newly created map according to the original restricted area setting information.

[0107] When the map matching degree is greater than or equal to the first matching degree threshold, it indicates that the cleaning working environment corresponding to the original map is similar to the working environment corresponding to the newly created map. At this time, the restricted area setting information in the newly created map can be directly used to automatically restore the restricted area setting in the newly created map.

[0108] Specifically, the restricted area settings of the corresponding scenes in the newly created map are restored according to the restricted area settings of each scene in the original restricted area setting information. For example, in the original restricted area setting information, Room A is set as a restricted area, then a scene corresponding to the location, size and other features of Room A is determined in the newly created map and set as a restricted area.

[0109] S307: If the map matching degree is less than a first matching degree threshold, automatically setting a restricted area in the newly created map according to the scene recognition result of the newly created map and the user's cleaning habit information.

[0110] When the map matching degree is less than the first matching degree threshold, it indicates that there is a large gap between the cleaning working environment corresponding to the original map and the working environment corresponding to the newly created map. At this time, if the original restricted area setting information is directly used to automatically restore the restricted area settings in the newly created map, it may cause restricted area setting errors or recovery failures, affecting the user experience.

[0111] In this case, it is necessary to analyze the scene attributes of each scene in the newly created map, and automatically set a restricted area for each scene in the newly created map based on the user's cleaning habit information and the scene attributes.

[0112] In some embodiments, the user's cleaning habit information includes the correspondence between the scene attributes of each scene in the original map and the original restricted area setting information of the scene; the automatic setting of the restricted area in the newly created map based on the scene recognition result of the newly created map and the user's cleaning habit information includes: for the target scene in the newly created map, determining the scene attributes of the target scene according to the scene recognition result; determining the target original restricted area setting information corresponding to the scene attributes based on the user's cleaning habit information; and automatically setting the restricted area in the newly created map according to the target original restricted area setting information.

[0113] The target scene is any scene in the newly created map. The cleaning robot determines the scene attributes of the target scene based on the scene recognition results of the target scene, including the shape, size, and obstacle arrangement characteristics of the target scene, and searches for similar scene attributes in the user's cleaning habit information, and uses the original restricted area setting information corresponding to the scene attribute in the user's cleaning habit as the target original restricted area setting information corresponding to the target scene.

[0114] The above process is repeated until each target scene in the newly created map has obtained the corresponding target original restricted area setting information, and the restricted area setting of the newly created map is completed.

[0115] For example, in the user's cleaning habit information, the carpet scene in room B is set as a restricted area. When the target scene is a carpet with a similar position and size to the carpet in room B in the original map, the cleaning robot determines that the target original restricted area setting information is a restricted area based on the restricted area setting of the carpet scene in room B in the user's cleaning habit information, and then sets the target scene (carpet) in the newly created map as a restricted area.

[0116] In some other embodiments, the original map includes a first scene, and the newly created map includes multiple second scenes; the restricted areas are automatically set in the newly created map based on the scene recognition result of the newly created map and the user's cleaning habit information, including: if it is determined that the scene attributes of the multiple second scenes are the same as the first scene based on the scene recognition result, then the restricted areas are automatically set in each of the second scenes based on the original restricted area setting information of the first scene.

[0117] After the map is rebuilt, due to changes in the cleaning work environment, for the first scene in the original map, there may be multiple second scenes with the same attributes as the first scene in the newly created map. For each second scene in the newly created map, the cleaning robot sets a restricted area for the second scene according to the restricted area setting information corresponding to the first scene in the original map.

[0118] For example, in the original map, there is a carpet only in room B, but in the newly created map, there are carpets in both rooms B and C. Then, the scenes in the newly created map corresponding to the carpets in rooms B and C are all set as restricted areas.

[0119] The disclosed embodiment directly restores the restricted area setting information in the newly created map based on the original restricted area setting information when the similarity between the original map and the newly created map is high; and intelligently analyzes and restores the restricted area settings in the newly created map based on the user's cleaning habits when the similarity between the original map and the newly created map is low. This ensures the accuracy of the restricted area settings in the newly created map even when the cleaning working environment changes significantly.

[0120] Figure 4 The structure diagram of the intelligent recovery device for cleaning habits provided in the embodiment of the present disclosure is shown in FIG. The intelligent recovery device for cleaning habits may be a cleaning robot as described in the above embodiment, or the intelligent recovery device for cleaning habits may be a component or assembly in the cleaning robot. The intelligent recovery device for cleaning habits provided in the embodiment of the present disclosure may execute the processing flow provided in the embodiment of the intelligent recovery method for cleaning habits, such as Figure 4 As shown, the intelligent recovery device 40 for cleaning habits includes: an acquisition module 41, a mapping module 42, a transfer module 43, and a recovery module 44. Among them, the acquisition module 41 is used to obtain the original map corresponding to the cleaning work environment, and the original cleaning configuration information corresponding to the original map, and the original cleaning configuration information includes the original restricted area setting information and the user's cleaning habit information; the mapping module 42 is used to re-map the cleaning work environment after the original map cannot be used, and obtain a new map corresponding to the cleaning work environment; the transfer module 43 is used to transfer the original cleaning configuration information to the new map; the recovery module 44 is used to automatically set the restricted area in the new map according to the original cleaning configuration information, and obtain the restricted area recovery result of the new map.

[0121] Optionally, the acquisition module 41 includes a segmentation unit 411 and a confirmation unit 412; the segmentation unit 411 is used to perform scene segmentation on the original map to determine multiple scenes included in the original map; the confirmation unit 412 is used to determine the original cleaning configuration information of the original map based on the user's confirmation information on the restricted area in the multiple scenes.

[0122] Optionally, the original restricted area setting information includes first restricted area configuration information; the confirmation unit 412 is used to obtain the reason why the user sets the restricted area for the first area in the multiple scenes in response to the user's restricted area selection operation on the first area; save the first restricted area configuration information of the first area, and store the scene attributes of the first area and the reason for setting the restricted area in the user's cleaning habit information.

[0123] Optionally, the acquisition module 41 further includes a marking unit 413, which is used to mark the fault-prone areas in the multiple scenes according to the motor current data and camera data of the cleaning robot.

[0124] Optionally, the original restricted area setting information also includes second restricted area configuration information, and the confirmation unit 412 is used to confirm with the user whether the second area needs to be set as a restricted area if there is a second area in the fault-prone area, and the similarity of the scene attributes of the second area and any restricted area in the original restricted area setting information is greater than a first similarity threshold; if the user confirms setting the second area as a restricted area, the second restricted area configuration information of the second area is saved, and the scene attributes of the second area are stored in the user's cleaning habit information.

[0125] Optionally, the confirmation unit 412 is used to confirm the scene attributes of the third area to the user if there is a third area in the trouble-prone area, and obtain a scene attribute confirmation result, wherein the third area is any area in the trouble-prone area except the second area; and store the scene attributes of the third area and the scene attribute confirmation result in the user's cleaning habit information.

[0126] Optionally, the recovery module 44 includes a matching unit 441 and a setting unit 442; the matching unit 441 is used to automatically set a restricted area in the newly created map according to the original restricted area setting information if the map matching degree is greater than or equal to a first matching degree threshold; or, if the map matching degree is less than the first matching degree threshold, automatically set a restricted area in the newly created map according to the scene recognition result of the newly created map and the user's cleaning habit information.

[0127] Optionally, the matching unit 441 is used to determine the matching weight of each matching feature, wherein the matching features include map area, map shape, and number of rooms; compare the matching features of the newly created map with the matching features of the original map to obtain the feature similarity of each matching feature; and calculate the map matching degree based on the feature similarity of each matching feature and the matching weight of each matching feature.

[0128] Optionally, the user cleaning habit information includes the correspondence between the scene attributes of each scene in the original map and the original restricted area setting information of the scene; the setting unit 442 is used to determine the scene attributes of the target scene in the newly created map according to the scene recognition result; based on the user cleaning habit information, determine the target original restricted area setting information corresponding to the scene attributes; and automatically set the restricted area in the newly created map according to the target original restricted area setting information.

[0129] Optionally, the original map includes a first scene, and the newly created map includes multiple second scenes; the setting unit 442 is used to automatically set a restricted area in each of the second scenes according to the original restricted area setting information of the first scene if it is determined, based on the scene recognition result, that the scene attributes of the multiple second scenes are the same as the first scene.

[0130] Figure 4 The intelligent recovery device for cleaning habits of the illustrated embodiment can be used to execute the technical solution of the above-mentioned method embodiment. Its implementation principle and technical effect are similar and will not be repeated here.

[0131] Figure 5 The electronic device provided in the embodiment of the present disclosure can execute the processing flow provided in the embodiment of the intelligent recovery method for cleaning habits, such as Figure 5 As shown, the electronic device 50 includes: a memory 51, a processor 52, a computer program and a communication interface 53; wherein the computer program is stored in the memory 51 and is configured so that the processor 52 executes the intelligent recovery method of cleaning habits as described above.

[0132] In addition, an embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program is stored. The computer program is executed by a processor to implement the intelligent recovery method of cleaning habits described in the above embodiment.

[0133] In addition, an embodiment of the present disclosure also provides a computer program product, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, the intelligent recovery method of cleaning habits as described above is implemented.

[0134] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0135] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent method for restoring cleaning habits, characterized in that: The method comprises: Acquire an original map corresponding to the cleaning work environment and original cleaning configuration information corresponding to the original map, wherein the original cleaning configuration information includes original restricted area setting information and user cleaning habit information; After the original map is unusable, re-constructing a map of the cleaning work environment to obtain a newly constructed map corresponding to the cleaning work environment; Transferring the original cleaning configuration information to the newly created map; According to the original cleaning configuration information, a restricted area is automatically set in the newly created map to obtain a restricted area restoration result of the newly created map.

2. The method according to claim 1, characterized in that The obtaining of the original map corresponding to the cleaning working environment and the original cleaning configuration information corresponding to the original map includes: Performing scene segmentation on the original map to determine a plurality of scenes included in the original map; Based on the user's confirmation information on the restricted area in the multiple scenes, original cleaning configuration information of the original map is determined.

3. The method according to claim 2, characterized in that The original restricted area setting information includes first restricted area configuration information; the original cleaning configuration information of the original map is determined based on the user's confirmation information of the restricted area in the multiple scenes, including: In response to a user's operation of selecting a restricted area of ​​a first area in the multiple scenes, obtaining a reason why the user sets a restricted area of ​​the first area; The configuration information of the first restricted area of ​​the first area is saved, and the scene attribute of the first area and the reason for setting the restricted area are stored in the user cleaning habit information.

4. The method according to claim 2, characterized in that: Before determining the original cleaning configuration information of the original map based on the user's confirmation information of the restricted area in the multiple scenes, the method further includes: According to the motor current data and camera data of the cleaning robot, the fault-prone areas in the multiple scenes are marked.

5. The method according to claim 4, characterized in that The original restricted area setting information also includes second restricted area configuration information, and the original cleaning configuration information of the original map is determined based on the user's confirmation information of the restricted area in the multiple scenes, including: If there is a second area in the fault-prone area, confirm with the user whether the second area needs to be set as a restricted area, and the scene attribute similarity between the second area and any restricted area in the original restricted area setting information is greater than a first similarity threshold; If the user confirms to set the second area as a restricted area, the second restricted area configuration information of the second area is saved, and the scene attributes of the second area are stored in the user cleaning habit information.

6. The method according to claim 4, characterized in that The method further comprises: If there is a third area in the prone-to-failure area, confirming the scene attribute of the third area with the user to obtain a scene attribute confirmation result, wherein the third area is any area in the prone-to-failure area except the second area; The scene attribute of the third area and the scene attribute confirmation result are stored in the user cleaning habit information.

7. The method according to claim 1, characterized in that The automatically setting a restricted area in the newly created map according to the original cleaning configuration information includes: Matching the newly created map with the original map to obtain a map matching degree; If the map matching degree is greater than or equal to a first matching degree threshold, automatically setting a restricted area in the newly created map according to the original restricted area setting information; or, If the map matching degree is less than a first matching degree threshold, a restricted area is automatically set in the newly created map according to the scene recognition result of the newly created map and the user's cleaning habit information.

8. The method according to claim 7, characterized in that Matching the newly created map with the original map to obtain a map matching degree includes: Determining a matching weight for each matching feature, the matching features including map area, map shape, and number of rooms; Comparing the matching features of the newly created map with the matching features of the original map to obtain a feature similarity of each matching feature; The map matching degree is calculated based on the feature similarity of each matching feature and the matching weight of each matching feature.

9. The method according to claim 7, characterized in that: The user cleaning habit information includes a correspondence between scene attributes of each scene in the original map and original restricted area setting information of the scene; The automatically setting a restricted area in the newly created map according to the scene recognition result of the newly created map and the user's cleaning habit information includes: For the target scene in the newly created map, determining the scene attribute of the target scene according to the scene recognition result; Based on the user's cleaning habit information, determining target original restricted area setting information corresponding to the scene attribute; A restricted area is automatically set in the newly created map according to the target original restricted area setting information.

10. The method according to claim 7, characterized in that The original map includes a first scene, and the newly created map includes a plurality of second scenes; and the step of automatically setting a restricted area in the newly created map according to the scene recognition result of the newly created map and the user's cleaning habit information includes: If it is determined according to the scene recognition result that the scene attributes of the plurality of second scenes are the same as the first scene, a restricted area is automatically set in each of the second scenes according to the original restricted area setting information of the first scene.

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