CN117312345A

CN117312345A - Carpet information processing method, cleaning robot, and storage medium

Info

Publication number: CN117312345A
Application number: CN202311282392.0A
Authority: CN
Inventors: 王锦涛
Original assignee: Yunjing Intelligent Innovation Shenzhen Co ltd; Yunjing Intelligent Shenzhen Co Ltd
Current assignee: Yunjing Intelligent Innovation Shenzhen Co ltd; Yunjing Intelligent Shenzhen Co Ltd
Priority date: 2023-09-28
Filing date: 2023-09-28
Publication date: 2023-12-29

Abstract

The embodiment of the invention provides a carpet information processing method, a cleaning robot and a storage medium. The carpet information processing method is applied to the cleaning robot, and comprises the following steps: acquiring position information of each unknown carpet detected in the execution process of the cleaning target task; determining a positional relationship between the unknown carpets based on the acquired positional information of the unknown carpets; merging unknown carpets with the position relationship meeting the first target requirement to obtain carpet information of at least one target merged unknown carpet after merging, and adding the carpet information of the at least one target merged unknown carpet into a target map; for an unknown carpet which does not meet the first target requirement in the position relation with other unknown carpets, adding the carpet information of the unknown carpet into a target map; wherein the first target requirement includes carpeting intersecting each other. This approach is advantageous for determining carpet information for an entire carpet more accurately.

Description

Carpet information processing method, cleaning robot, and storage medium

Technical Field

The present invention relates to the technical field of cleaning apparatuses, and more particularly, to a carpet information processing method, a cleaning robot, and a computer-readable storage medium.

Background

The cleaning robot can be used for automatically cleaning the ground, and the application scene can be household indoor cleaning, large-scale place cleaning and the like. In some applications, carpets are laid in the area to be cleaned. In cleaning carpeted and non-carpeted areas in an area to be cleaned, the cleaning robot typically needs to employ a different cleaning mode.

In the related art, when cleaning a cleaning area where a carpet is laid, a cleaning robot processes a currently detected carpet portion (e.g., cleans, evades, or spans based on a corresponding cleaning mode, etc.) immediately after detecting the carpet. The processing mode can not grasp the full view of the complete carpet, so that the information such as the position of the complete carpet is difficult to accurately determine, and a good carpet cleaning effect is difficult to obtain.

Disclosure of Invention

The present invention has been made in view of the above-described problems. According to an aspect of the present invention, there is provided a carpet information processing method, applied to a cleaning robot, including: acquiring position information of each unknown carpet detected in the execution process of a target task; determining a positional relationship between the unknown carpets based on the acquired positional information of the unknown carpets; merging unknown carpets with the position relationship meeting the first target requirement to obtain carpet information of at least one target merged unknown carpet after merging, and adding the carpet information of the at least one target merged unknown carpet into a target map; for an unknown carpet which does not meet the first target requirement in the position relation with other unknown carpets, adding the carpet information of the unknown carpet into a target map; the target task is at least a task for detecting an unknown carpet, the target map is a map according to which the cleaning robot performs the cleaning task, the first target requirement comprises that the carpets intersect each other, and the carpet information comprises position information.

Illustratively, when the detected current carpet is an unknown carpet, determining a positional relationship between the unknown carpets based on the acquired positional information of the unknown carpets includes: determining a positional relationship between the current carpet and the previously unknown carpet based on the positional information of the current carpet and the positional information of the previously unknown carpet when the previously unknown carpet exists in the target map; the unknown carpet is added on the target map before the current carpet is detected in the execution process of the target task.

Illustratively, merging unknown carpets whose positional relationship satisfies a first target requirement, obtaining carpet information of the merged at least one target merged unknown carpet, and adding the carpet information of the at least one target merged unknown carpet to the target map, including: when a target unknown carpet exists in the target map, merging the current carpet and the target unknown carpet to obtain carpet information of the temporary merged unknown carpet corresponding to the current carpet; adding the carpet information of the temporary combined unknown carpet to the target map and deleting the carpet information of the target unknown carpet in the target map; wherein the target unknown carpeting is a prior unknown carpeting whose positional relationship with the current carpeting satisfies a first target requirement, and the at least one target merge unknown carpeting comprises target merge unknown carpeting in one-to-one correspondence with one or more sets of unknown carpeting, the positional relationship between the unknown carpeting in each set of unknown carpeting satisfying the first target requirement, the target merge unknown carpeting corresponding to each set of unknown carpeting being a temporary merge unknown carpeting corresponding to the last detected unknown carpet in the set of unknown carpeting.

Illustratively, for an unknown carpet whose positional relationship with other unknown carpets does not satisfy the first target requirement, adding carpet information of the unknown carpet to the target map includes: when there is no prior unknown carpet or there is a prior unknown carpet but no target unknown carpet in the target map, the carpet information of the current carpet is added to the target map.

Illustratively, the target map is a map of at least two preset areas; the carpet information also comprises attribution information of the corresponding carpet; the attribution information is used for indicating attribution areas corresponding to the corresponding carpets, the attribution areas are one or more preset areas in at least two preset areas, and the operation of cleaning any carpet by the cleaning robot is executed under the condition that the cleaning robot cleans the attribution area corresponding to the carpet; the at least one target merging unknown carpet comprises target merging unknown carpets which are in one-to-one correspondence with one or more groups of unknown carpets, and the position relationship between the unknown carpets in each group of unknown carpets meets the first target requirement; combining unknown carpets with the position relationship meeting the first target requirement to obtain carpet information of at least one target combined unknown carpet after combination, wherein the carpet information comprises: combining, for any one of the one or more sets of unknown carpets, the areas occupied by each of the unknown carpets in the set of unknown carpets based on the location information of each of the unknown carpets in the set of unknown carpets, determining the location information of the target combined unknown carpets corresponding to the set of unknown carpets; a home zone determination operation is performed on the target consolidated unknown carpet corresponding to the set of unknown carpets to determine home information for the target consolidated unknown carpets corresponding to the set of unknown carpets.

Illustratively, the target map is a map of at least two preset areas; the carpet information also comprises attribution information of the corresponding carpet; the attribution information is used for indicating attribution areas corresponding to the corresponding carpets, the attribution areas are one or more preset areas in at least two preset areas, and the operation of cleaning any carpet by the cleaning robot is executed under the condition that the cleaning robot cleans the attribution area corresponding to the carpet; the at least one target merging unknown carpet comprises target merging unknown carpets which are in one-to-one correspondence with one or more groups of unknown carpets, and the position relationship between the unknown carpets in each group of unknown carpets meets the first target requirement; when the detected current carpet is an unknown carpet, the method further comprises: a home zone determination operation is performed on the current carpet to determine home information for the current carpet.

Illustratively, the target map is a map of at least two preset areas; the carpet information also comprises attribution information of the corresponding carpet; the attribution information is used for indicating attribution areas corresponding to the corresponding carpets, the attribution areas are one or more preset areas in at least two preset areas, and the operation of cleaning any carpet by the cleaning robot is executed under the condition that the cleaning robot cleans the attribution area corresponding to the carpet; combining the current carpet and the target unknown carpet to obtain carpet information of the temporary combined unknown carpet corresponding to the current carpet, including: combining the area occupied by the current carpet and the area occupied by the target unknown carpet based on the position information of the current carpet and the position information of the target unknown carpet, and determining the position information of the temporary combined unknown carpet; and executing a home area determining operation on the temporary merging unknown carpet to determine the home information of the temporary merging unknown carpet, or determining the home area corresponding to the current carpet and the home area corresponding to the target unknown carpet as the home area corresponding to the temporary merging unknown carpet to determine the home information of the temporary merging unknown carpet.

Illustratively, the home region determination operation includes: determining a preset area corresponding to the carpet to be determined in the target map based on the position information of the carpet to be determined, wherein the preset area corresponding to the carpet to be determined is a preset area in which at least one part of the carpet to be determined exists; when the number of the preset areas corresponding to the carpet to be determined is at least two, judging whether the occupied area of the carpet to be determined in the preset areas is larger than a first area threshold or not for each preset area corresponding to the carpet to be determined, and if the occupied area of the carpet to be determined in the preset areas is larger than the first area threshold, determining the preset areas as attribution areas corresponding to the carpet to be determined; and/or if the occupied area of the carpet to be determined in each corresponding preset area is not greater than the first area threshold value, determining the preset area with the largest occupied area of the carpet to be determined as the attribution area corresponding to the carpet to be determined; wherein the carpet to be determined is the carpet for which the home zone determination operation is directed.

Illustratively, the carpet information further includes a cleaning mode for indicating a treatment mode employed by the cleaning robot when performing the cleaning task with respect to the corresponding carpet, and when the detected current carpet is an unknown carpet, the method further includes: determining a positional relationship between the current carpet and the known carpet based on the positional information of the current carpet and the positional information of the known carpet in the target map; determining a current carpet cleaning mode based on the cleaning mode of the at least one target known carpet when the at least one target known carpet is present in the target map; wherein the target known carpet represents a known carpet in which a positional relationship with a current carpet in the target map satisfies a second target requirement including the carpets intersecting each other; the at least one target merging unknown carpet comprises target merging unknown carpets which are in one-to-one correspondence with one or more groups of unknown carpets, the position relation among the unknown carpets in each group of unknown carpets meets the first target requirement, and the cleaning mode of the current carpet is used for determining the cleaning mode of the target merging unknown carpets corresponding to the group of unknown carpets where the current carpet is located.

Illustratively, determining the current cleaning pattern of the carpet based on the cleaning pattern of the at least one target known carpet comprises: determining that the cleaning mode of the current carpet is the cleaning mode of the target known carpet when the number of the target known carpets is one; when the number of the target known carpets is at least two, if the cleaning modes of the target known carpets are the same, determining that the cleaning mode of the current carpet is the cleaning mode of the target known carpets; if the cleaning modes of the carpets known by the targets are different, outputting reminding information corresponding to the current carpet and/or determining that the cleaning mode of the current carpet is a first default cleaning mode.

Illustratively, the method further comprises: and when the target known carpet does not exist in the target map, outputting reminding information corresponding to the current carpet and/or determining that the cleaning mode of the current carpet is a second default cleaning mode.

Illustratively, merging a current carpet and a target unknown carpet to obtain carpet information for a temporary merged unknown carpet corresponding to the current carpet, including: combining the area occupied by the current carpet and the area occupied by the target unknown carpet based on the position information of the current carpet and the position information of the target unknown carpet, and determining the position information of the temporary combined unknown carpet corresponding to the current carpet; when the cleaning mode of the current carpet is the same as the cleaning mode of the target unknown carpet, determining that the cleaning mode of the current carpet is the temporarily combined unknown carpet corresponding to the current carpet; outputting reminding information corresponding to the temporary merging unknown carpet and/or determining that the cleaning mode of the temporary merging unknown carpet corresponding to the current carpet is a third default cleaning mode when the cleaning mode of the current carpet is different from the cleaning mode of the target unknown carpet.

Illustratively, the target task is a cleaning task, the method further comprising: acquiring area identification information of an area to be cleaned before executing a cleaning task; acquiring a global map; generating a target map corresponding to a cleaning task based on the region identification information of the region to be cleaned and the global map; preloading the position information of at least part of carpets meeting preset conditions in the global map into a target map; determining attribution information of a carpet to be cleaned in at least part of carpets based on the area identification information of the area to be cleaned, and adding the attribution information of the carpet to be cleaned into a target map; the global map is a map of one or more preset areas, the one or more preset areas comprise areas to be cleaned, the attribution information is used for indicating an attribution area corresponding to the carpet, the attribution area is at least one preset area in the one or more preset areas, and the operation of cleaning any carpet by the cleaning robot is performed under the condition that the cleaning robot cleans the attribution area corresponding to the carpet.

Illustratively, the preset conditions include: the area of the carpet is greater than a second area threshold; the preset conditions comprise: the carpet cleaning mode is a carpet evasion mode; the preset conditions comprise: the area of the carpet is greater than the second area threshold, and/or the cleaning mode of the carpet is an evasion carpet mode; the evasion carpet mode is used to instruct the cleaning robot to avoid the position of the corresponding carpet during traveling while performing the cleaning task.

Illustratively, preloading carpet information of at least a portion of carpets in the global map meeting preset requirements into the target map includes: carpet information of carpets which meet preset conditions in the global map and intersect with a movement path when the cleaning robot performs a cleaning task is preloaded into the target map.

Illustratively, the method further comprises: acquiring map point type information detected for each map point in at least part of map points in a target map in the execution process of the target task; for each known carpet in the target map, judging whether the known carpet is shifted or not based on map point type information corresponding to map points at the position of the known carpet; deleting carpet information of any known carpet from the target map when the known carpet is shifted; wherein the map point type information is used to indicate whether the corresponding map point belongs to a carpet.

Illustratively, determining whether the known carpet is shifted based on map point type information corresponding to map points at the location of the known carpet includes: calculating the ratio between the occupied area of the non-carpet map points at the position of the known carpet and the total area of the known carpet based on the map point type information corresponding to the map points at the position of the known carpet; judging whether the ratio is larger than a ratio threshold; when the ratio is greater than the ratio threshold, the known carpet is determined to be shifted.

According to a second aspect of the present invention there is provided a cleaning method, the cleaning tasks comprising a first cleaning sub-task for cleaning non-carpeted areas, the non-carpeted areas being areas located outside the carpeted areas where the carpeted is located, and a second cleaning sub-task for cleaning carpeted areas, wherein the cleaning method comprises: in the execution process of the first cleaning subtask, executing the carpet information processing method, wherein the non-carpet area is an area outside the carpet area where the carpet is located; in the execution process of the second cleaning subtask, performing carpet cleaning operation by using the target map; the cleaning tasks comprise a first cleaning subtask and a second cleaning subtask, and the target task is the first cleaning subtask.

According to a third aspect of the present invention, there is also provided a cleaning robot including: a processor and a memory, in which a computer program is stored, the processor executing the computer program to implement the carpet information handling method or the cleaning method described above.

According to a fourth aspect of the present invention there is also provided a computer readable storage medium storing a computer program/instruction which when executed by a processor implements the carpet information handling method or cleaning method described above.

According to the scheme, the unknown carpets meeting the first target requirement are combined, so that a complete target combined unknown carpet can be obtained, the overall appearance of the whole carpet can be mastered, the carpet information of the whole carpet can be determined accurately, and the carpet can be accurately processed in the process of cleaning the whole carpet, so that a good carpet cleaning effect is obtained.

The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.

Drawings

The above and other objects, features and advantages of the present invention will become more apparent from the following more particular description of embodiments of the present invention, as illustrated in the accompanying drawings. The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, and not constitute a limitation to the invention. In the drawings, like reference numerals generally refer to like parts or steps.

FIG. 1 illustrates a carpet information processing method according to one embodiment of the present application;

FIG. 2 illustrates a schematic of the location of each unknown carpet in a target map according to one embodiment of the present application;

FIG. 3 illustrates a schematic diagram of merging unknown carpets according to one embodiment of the present application;

FIG. 4 shows a schematic diagram of combining an unknown carpet with a first known carpet according to another embodiment of the present application;

FIG. 5 illustrates an exemplary flow chart of a carpet information handling method according to one specific embodiment of the present application;

FIG. 6 shows a schematic flow chart of a cleaning method according to one embodiment of the present application; and

fig. 7 shows a schematic block diagram of a cleaning robot according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present invention and not all embodiments of the present invention, and it should be understood that the present invention is not limited by the example embodiments described herein. Based on the embodiments of the invention described in the present application, all other embodiments that a person skilled in the art would have without inventive effort shall fall within the scope of the invention.

Cleaning robots are widely used in daily life, and commonly used cleaning robots such as a sweeping robot and the like. Since the cleaning robot generally has different cleaning modes on carpets and normal floors, it is necessary to identify and process a carpet area in an area to be cleaned when the cleaning robot cleans the area to be cleaned. In the related art, a cleaning robot typically processes a carpet portion (possibly an incomplete carpet) in real time after identifying the carpet portion. However, this method cannot draw a complete carpet in a target map in combination with the recognition behavior of the cleaning robot, and cannot grasp the full view of the complete carpet, so that it is difficult to accurately determine the information such as the position of the complete carpet, and it is also difficult to obtain a good carpet cleaning effect. In view of the above, the present application provides a carpet information processing method, a cleaning robot, and a computer-readable storage medium to solve the above technical problems.

According to one aspect of the present application, a carpet information processing method is provided. The method is applied to a cleaning robot. The carpet information processing method described herein may be run on any processing device, for example, on a master control device of a cleaning robot, in particular, for example, a master control Microcontroller (MCU) of the cleaning robot. Alternatively, the carpet information processing method may also be run on an associated device, which may be, for example, a personal computer, a server or the like, which is communicatively connected to the cleaning robot. Fig. 1 illustrates a carpet information processing method according to one embodiment of the present application. As shown in fig. 1, the carpet information processing method 100 may include the following steps S110, S120, S130, and S140.

In step S110, position information of each unknown carpet detected during execution of the target task is acquired.

In step S120, the positional relationship between the unknown carpets is determined based on the acquired positional information of the unknown carpets.

In step S130, unknown carpets whose positional relationship satisfies the first target requirement are merged, carpet information of at least one target merged unknown carpet is obtained after merging, and the carpet information of at least one target merged unknown carpet is added to the target map.

In step S140, for an unknown carpet whose positional relationship with other unknown carpets does not satisfy the first target requirement, carpet information of the unknown carpet is added to the target map. The target task is at least a task for detecting an unknown carpet, and the target map is a map according to which the cleaning robot executes the cleaning task. The first target requirement includes carpeting intersecting each other, and the carpet information includes location information.

Optionally, in an embodiment of the present application, the carpet includes, in addition to the carpet in the narrow sense, a floor medium different from a hard floor material such as a foot mat, yoga mat, rubber mat, straw plaited, bamboo plaited, and the like.

Optionally, the target task may be a carpet detection task that simply detects an unknown carpet, for example, a task that searches for an area to be detected where the cleaning robot is currently located in response to a mapping instruction. The carpet detection task is mainly used for detecting carpets in an area to be detected, and a map of the area to be detected is established and can be a global map or a target map and the like. Alternatively, the area to be cleaned described herein may be at least a part of the above-described area to be detected. That is, after the to-be-detected area is explored and the map of the to-be-detected area is acquired, at least part of the to-be-detected area is cleaned. Alternatively, the target task may also be a cleaning task, which may be a task of cleaning the area to be cleaned. Alternatively, the carpet may be detected while cleaning the region to be cleaned, i.e., a map of at least the region to be cleaned may be acquired in real time during cleaning.

By way of example, the various areas described herein (such as the area to be cleaned and the overall area to which the global map corresponds, etc.) may refer to areas that are located on the floor. The area to be cleaned described herein may be any area that the cleaning robot needs to clean, including but not limited to: an entire home space, one or more rooms, a partial area in one or more rooms, or at least a partial area in a large venue, etc. In some embodiments, the area to be cleaned may include a carpet area and a non-carpet area. Alternatively, the cleaning tasks may include a first cleaning sub-task that cleans non-carpet areas and a second cleaning sub-task that cleans carpet areas. In this way, the non-carpeted areas and the carpeted areas can be cleaned separately. Of course, alternatively, cleaning may be performed for both non-carpet areas and carpet areas while performing the cleaning task. In the description herein, a carpet area is an area where a carpet is located, and can be understood as an area surrounded by the contour of the carpet. The non-carpeted area is an area located outside the carpeted area.

The target map is a map on which the cleaning robot performs a cleaning task, and may include one or more of a global map, a planning map, and an obstacle map. The global map is a map of an entire area, and the area to be cleaned is at least a part of the entire area. The planning map is a map containing at least a planned action path within the area to be cleaned, for instructing the cleaning robot to act on the planned action path when performing the cleaning task. The obstacle map is a map containing at least obstacle information in the area to be cleaned, for instructing the cleaning robot to avoid an obstacle when performing a cleaning task.

Alternatively, the region corresponding to the target map may be any one region such as a home space, one room unit of the home space, a partial region of one room unit, a large-sized place, or a partial region of the large-sized place. From another perspective, the region to which the target map corresponds may refer to a larger region, such as an entire room unit; but also to a partial area in a larger area, for example a certain room in a room unit. A room unit described herein may include one or more rooms.

Optionally, the target map may be set up by searching for the region to be detected where the cleaning robot is currently located in response to the mapping instruction. Alternatively, the target map may be established based on an object such as an obstacle, a carpet, or the like, which is recognized by the cleaning robot in the area to be detected during the cleaning process. Alternatively, the previously established target map may be updated according to newly recognized objects such as obstacles, carpets, etc. during the cleaning task performed by the cleaning robot. That is, the target map can be continuously updated as needed. Alternatively, the target map may be a map of the area to be cleaned specified by the user. In one embodiment, the target map may be generated based on a user selected area to be cleaned on the global map. For example, the global map may be a map of the entire home space, the region to be cleaned may include one or more rooms in the entire home space, and the user may determine a map portion corresponding to the one or more rooms on the global map as the target map. Alternatively, the user may select the area to be cleaned by selecting or inputting identification information of the area to be cleaned. For example, the global map may be divided into different areas in advance, for example, may be divided into different areas by rooms, i.e., each room is divided into one area. The user can select or input the label (i.e. the identification information) corresponding to any divided region through a mode of clicking a mouse and/or inputting through a keyboard. In response to a user operation, the area selected by the user may be determined as the area to be cleaned. Alternatively, the user may also select the area to be cleaned by marking the outline of the area to be cleaned on the map. For example, the user may outline any region in the global map by means of a mouse and/or a keyboard and/or a touch screen, etc., and the cleaning robot may take the region outlined by the user as the region to be cleaned. Of course, the above-described manner of determining the area to be cleaned is merely an example, and other suitable manners may be adopted to determine the area to be cleaned.

Alternatively, the cleaning robot may detect the floor material information in real time through the sensor during the process of performing the target task by the cleaning robot. The floor material information may include carpet signals and non-carpet signals. The above-mentioned sensor may be, for example, an ultrasonic sensor by means of which it is possible to detect whether the floor spot currently detected by the cleaning robot belongs to a carpet or a non-carpet. When the ground point belongs to the carpet, the ultrasonic sensor can output a carpet signal, and otherwise, the ultrasonic sensor outputs a non-carpet signal. In some embodiments, upon detecting a carpet signal, the location information corresponding to the carpet signal may be compared to the location information of known carpets in the target map to determine whether the carpet corresponding to the carpet signal is an unknown carpet.

Alternatively, the location information of the carpet may include any one or more of global coordinate information, contour information, center point coordinate information, and size information of the corresponding carpet in the target map. The overall coordinate information is the coordinate information of each point on the carpet. Preferably, when the location information includes size information of the corresponding carpet, the location information may further include center point coordinate information. For example, the target map or global map may be built based on a global world coordinate system, and the location information may be represented in terms of world coordinates of the carpet contour in the global world coordinate system or world coordinates of a carpet reference point (e.g., the geometric center of the carpet) in the global world coordinate system. Alternatively, the position information may be represented in coordinates in a robot coordinate system in which the cleaning robot reference point is located. The reference point of the cleaning robot may be the center of mass or gravity of a sensor on the cleaning robot for detecting carpets, the geometric center of the cleaning robot, or the like. For example, for a cleaning robot, a robot coordinate system may be established with the cleaning robot reference point as the origin.

Alternatively, after determining that the carpet corresponding to the carpet signal is an unknown carpet, the cleaning robot may be controlled to explore the position information of the unknown carpet. For example, an unknown carpet may be edgewise explored to determine where the contours of the unknown carpet are located to obtain location information for the unknown carpet. In some embodiments, the exploration mode may adopt an inner edge exploration mode. The inner edge search refers to the cleaning robot performing edge search on the carpet inside the carpet. During the edge-seeking process of the cleaning robot on the inner side, at least a part of the track formed by the orthographic projection of the geometric center of the cleaning robot falls into the orthographic projection area of the unknown carpet. Alternatively, the exploring manner may also adopt an outer edge exploring manner. The outer edge search refers to the cleaning robot performing edge search on the carpet outside the carpet. In the process that the cleaning robot performs edge-seeking on the outer side, the track formed by the orthographic projection of the geometric center of the cleaning robot does not fall into the orthographic projection area of the carpet. Compared with the inner edge exploration mode, the outer edge exploration mode is adopted, so that the movement range of the cleaning robot can be effectively controlled, and the cleaning robot is effectively prevented from polluting the carpet in the carpet exploration process.

An unknown carpet is a carpet that the cleaning robot identified during the execution of the target task and that does not belong to a known carpet. In one embodiment, the cleaning robot detects a carpet signal during the execution of the target task, and it may be determined that the cleaning robot recognizes the carpet. Then, the position information corresponding to when the cleaning robot detects the carpet signal may be compared with the position information of the known carpet in the target map, thereby determining whether the carpet corresponding to the carpet signal is an unknown carpet.

In some embodiments, after the location information for each unknown carpet is obtained, the location information for each unknown carpet may be compared. And the comparison result is the position relation among all unknown carpets. Alternatively, the positional relationship between each unknown carpet may refer to the positional relationship between every two unknown carpets. In this context, the positional relationship between any two carpets may include: the two carpets intersect each other and the two carpets do not intersect. Of course, the positional relationship may also include further relationships, and may include, for example: the area of the intersection of two carpets, and/or the ratio between the area of the intersection of two carpets and the area of either of the two carpets or the total area of the two carpets, etc. It may be determined whether the positional relationship between the unknown carpets meets the first target requirement. The first target requirement may include carpets intersecting each other and may include still other requirements. When there is an intersection of at least a portion of unknown carpets among the unknown carpets, the at least a portion of unknown carpets being a plurality of unknown carpets, if the intersecting unknown carpets meet the first target requirement, the above-described step S130 may be performed. The at least partially unknown carpet intersection refers to each unknown carpet in the at least partially unknown carpet having at least one unknown carpet intersecting it. In step S130, unknown carpets whose positional relationship satisfies the first target requirement may be merged, carpet information of at least one target merged unknown carpet obtained after merging, and the carpet information of at least one target merged unknown carpet may be added to the target map. In each unknown carpet, if any one or more unknown carpets exist, and the positional relationship between the other unknown carpets does not satisfy the first target requirement, the above-described step S140 may be performed. In step S140, for an unknown carpet whose positional relationship with other unknown carpets does not satisfy the first target requirement, carpet information of the unknown carpet may be added to the target map.

It will be appreciated that for unknown carpets whose positional relationship meets the first target requirement, each unknown carpet may be a single carpet. Only due to obstructions on the carpet, etc., the cleaning robot detects multiple carpets during the exploration, resulting in a carpet that is not fully drawn. In the technical scheme, the unknown carpets meeting the first target requirement are combined, so that a complete target combined unknown carpet can be obtained, the overall appearance of the whole carpet can be mastered, and the carpet information of the whole carpet can be determined accurately, so that the whole carpet can be accurately processed in the subsequent carpet cleaning process, and a good carpet cleaning effect is obtained.

Illustratively, when the detected current carpet is an unknown carpet, step S120 of determining a positional relationship between the unknown carpets based on the acquired positional information of the unknown carpets may include the steps of: when a previously unknown carpet exists in the target map, the positional relationship between the current carpet and the previously unknown carpet is determined based on the positional information of the current carpet and the positional information of the previously unknown carpet. Wherein the previously unknown carpet is an unknown carpet added to the target map before the current carpet is detected during the execution of the cleaning task.

It will be appreciated that the previously unknown carpet may be an unknown carpet detected by the cleaning robot, or may be an unknown carpet obtained by combining a plurality of unknown carpets. For example, there may be temporary incorporated unknown carpeting as shown below. As described above, in step S130, when there are unknown carpets whose positional relationship satisfies the first target requirement, these unknown carpets may be combined. In step S140, for an unknown carpet whose positional relationship with other unknown carpets does not satisfy the first target requirement, carpet information of the unknown carpet is directly added to the target map.

In one or some embodiments (this embodiment is referred to as embodiment a for convenience of the following description), steps S130 and S140 may be performed in real time, for example, each time any carpet is acquired, it is compared with the previously unknown carpets (including unknown carpets that cannot be merged with other unknown carpets and temporarily merged unknown carpets obtained by merging a plurality of unknown carpets) that have been previously added to the target map, to determine whether merging can be continued. That is, determining whether there is a prior unknown carpet whose positional relationship with the currently acquired unknown carpet meets the first target requirement, if there is one or more prior unknown carpets (referred to herein as target unknown carpets) whose positional relationship with the currently acquired unknown carpets meets the first target requirement, the currently acquired unknown carpets may be merged with the one or more target unknown carpets. This comparison and merging when there is an unknown carpet of interest may be iterated until either step S130 or S140 has been performed for the last unknown carpet detected by the cleaning robot during the execution of the target task. Of course, in one or some embodiments (this embodiment is referred to as embodiment B for convenience of the following description), steps S130 and S140 may also be performed for all unknown carpets after acquiring all unknown carpets detected. For example, all unknown carpets may be grouped to obtain one or more sets of unknown carpets, each of which satisfies the first target requirement in terms of their positional relationship to one another. For each set of unknown carpets, the unknown carpets in the set of unknown carpets may be consolidated in a unified manner to obtain a target consolidated unknown carpet corresponding to the set of unknown carpets.

As described above, the cleaning robot may detect the position information of the unknown carpet after detecting the carpet signal and determining that the carpet corresponding to the carpet signal is the unknown carpet. In other words, the cleaning robot may further detect the position information of the corresponding unknown carpet each time after detecting the carpet signal belonging to the unknown carpet. Thus, the cleaning robot can sequentially detect position information of a plurality of unknown carpets during the execution of one target task. It will be appreciated that the number of previously unknown carpets may be one or more. For any one of a plurality of unknown carpets, the unknown carpet added to the target map before the unknown carpet is detected is the prior unknown carpet corresponding to the unknown carpet. In some embodiments, when the detected current carpet is an unknown carpet, the carpet information of the current carpet may be compared to each previously unknown carpet to determine the positional relationship between the current carpet and each previously unknown carpet.

Illustratively, when the detected current carpet is an unknown carpet, the carpet information processing method 100 may further include the steps of: and judging whether a previously unknown carpet exists in the target map. When there is no previously unknown carpet in the target map, carpet information for the current carpet may be added to the target map. The above steps S120, S130 and S140 are performed when there is a previously unknown carpet in the target map.

It will be appreciated that when there is no previously unknown carpet in the target map and the current carpet is an unknown carpet, the current carpet is the first unknown carpet detected during the execution of the present cleaning task. At this time, it does not make sense to perform the above-described step S120, step S130, and step S140. Thus, the carpet information of the current carpet can be directly added to the target map. Thus, the processing efficiency of the carpet information can be improved.

According to the technical scheme, when the unknown carpet is detected each time, the position relation between the unknown carpet and the prior unknown carpet is determined, so that carpet information can be processed in real time. The scheme is beneficial to realizing the real-time updating of the carpet information in the target map.

Illustratively, in step S130, merging unknown carpets whose positional relationship satisfies the first target requirement, obtaining carpet information of at least one target merged unknown carpet after merging, and adding the carpet information of the at least one target merged unknown carpet to the target map, may include the following steps S131 and S132.

Step S131, when the target unknown carpet exists in the target map, combining the current carpet and the target unknown carpet to obtain carpet information of the temporary combined unknown carpet corresponding to the current carpet.

Step S132, adding the carpet information of the temporary incorporated unknown carpet to the target map and deleting the carpet information of the target unknown carpet in the target map.

Wherein the target unknown carpeting is a prior unknown carpeting whose positional relationship with the current carpeting satisfies a first target requirement, and the at least one target merge unknown carpeting comprises target merge unknown carpeting in one-to-one correspondence with one or more sets of unknown carpeting, the positional relationship between the unknown carpeting in each set of unknown carpeting satisfying the first target requirement, the target merge unknown carpeting corresponding to each set of unknown carpeting being a temporary merge unknown carpeting corresponding to the last detected unknown carpet in the set of unknown carpeting.

It will be appreciated that the cleaning robot may detect positional information of a plurality of unknown carpets in sequence during the execution of a target task. For an unknown carpet, multiple carpet merges may be involved in the process of the cleaning robot performing the target task. For example, the cleaning robot sequentially detects a first unknown carpet, a second unknown carpet, a third unknown carpet, and a fourth unknown carpet in the course of performing a target task. Upon detection of the second unknown carpet, the previously unknown carpet is the first unknown carpet. If the positional relationship between the first unknown carpet and the second unknown carpet satisfies the first target requirement, the first unknown carpet is the target unknown carpet for the second unknown carpet, and the first unknown carpet and the second unknown carpet may be combined to obtain a fifth unknown carpet. The cleaning robot continues to perform the target task, detecting a third unknown carpet. At this time, the previously unknown carpet is the fifth unknown carpet. If the positional relationship between the fifth unknown carpet and the third unknown carpet satisfies the first target requirement, the fifth unknown carpet is the target unknown carpet for the third unknown carpet, and the fifth unknown carpet and the third unknown carpet may be combined to obtain the sixth unknown carpet. The cleaning robot continues to perform the target task, detecting a fourth unknown carpet. At this time, the previously unknown carpet is the sixth unknown carpet. If the positional relationship between the sixth unknown carpet and the fourth unknown carpet satisfies the first target requirement, the sixth unknown carpet is the target unknown carpet for the fourth unknown carpet, and the sixth unknown carpet and the fourth unknown carpet may be combined to obtain the seventh unknown carpet. In this embodiment, the first unknown carpet actually participates in three carpet merges. If the fourth unknown carpet is the last unknown carpet detected by the cleaning robot during the execution of the current target task, the fifth unknown carpet, the sixth unknown carpet and the seventh unknown carpet are temporary merged unknown carpets for the current target task. Meanwhile, the seventh unknown carpet is targeted to merge unknown carpets. Wherein the fifth unknown carpet is obtained by combining the second unknown carpet with the previous unknown carpet (i.e., the first unknown carpet), the fifth unknown carpet may be considered as a temporary combined unknown carpet corresponding to the second unknown carpet. Similarly, the sixth unknown carpet is obtained by combining the third unknown carpet with the previous unknown carpet (i.e., the fifth unknown carpet), so the sixth unknown carpet can be considered as a temporary combined unknown carpet corresponding to the third unknown carpet. Similarly, the seventh unknown carpet is obtained by combining the fourth unknown carpet with the previous unknown carpet (i.e., the sixth unknown carpet), and thus the seventh unknown carpet can be regarded as a temporarily combined unknown carpet corresponding to the fourth unknown carpet. The fourth unknown carpet is the last detected unknown carpet, and thus the seventh unknown carpet is also the target unknown carpet. The set of unknown carpets corresponding to the target merged unknown carpet includes a first unknown carpet, a second unknown carpet, a third unknown carpet, and a fourth unknown carpet.

FIG. 2 illustrates a schematic of the location of each unknown carpet in a target map according to one embodiment of the present application. In this embodiment, carpet a, carpet B, and carpet C are unknown carpets, and carpet D is a known carpet. Each unknown carpet was B, A, C in sequence in the order of detected sequencing. It is assumed that the first target requirement only includes carpets intersecting each other. When A is detected, A and B can be combined first, as A and B intersect, to obtain a temporarily combined unknown carpet. When C is detected, as can be seen from the positional relationship of the carpets in fig. 2, C intersects a, and the temporarily combined unknown carpets obtained after C is combined with a and B also intersect. Thus, C can be combined with the temporary combined unknown carpet to yield the final target unknown combined carpet.

Illustratively, the step of merging the current carpet with the target unknown carpet may include the steps of: and carrying out convex combination on the area occupied by the current carpet and the area occupied by the target unknown carpet to obtain the area occupied by the temporary combined unknown carpet. The combination between any two or more carpets described herein may be achieved in such a raised combination, and will not be described in detail.

Alternatively, the way of the embossing merge may be any embossing method, existing or developed in the future. The convex merging may be: the circumscribed rectangle of the union of the areas occupied by two or more carpets participating in the consolidation is taken as the area occupied by the consolidated carpet. Fig. 3 shows a schematic diagram of merging unknown carpets according to one embodiment of the present application. In this example, unknown carpets are consolidated by way of a convex consolidation. As shown in fig. 3, carpet a, carpet B, and carpet C are embossed to combine to yield a target combined unknown carpet E. Of course, the above-described manner of embossed bonding is by way of example only and not by way of limitation, and other suitable bonding methods may be employed to bond carpets. For example, the union of the areas occupied by two or more carpets participating in the consolidation may be directly taken as the area occupied by the consolidated carpet. Fig. 4 shows a schematic diagram of combining an unknown carpet with a first known carpet according to another embodiment of the present application. In this embodiment, the unknown carpet and the first known carpet are combined in a direct combination.

According to the technical scheme, the area occupied by the current carpet and the area occupied by the target unknown carpet are subjected to convex combination, the obtained temporary combination unknown carpet can cover all carpets participating in combination completely and can automatically complement blank parts in the carpets, and therefore the determined temporary combination unknown carpet is relatively accurate.

In some embodiments, when the current carpet is an unknown carpet, the carpet information for the current carpet may be added to the target map first. When there is a previously unknown carpet whose positional relationship with the current carpet satisfies the first target requirement in the target map, the carpet information of the current carpet in the target map may be deleted after the carpet information of the temporarily incorporated unknown carpet corresponding to the current carpet is added to the target map. When there is no prior unknown carpet whose positional relationship with the current carpet satisfies the first target requirement in the target map, the carpet information of the current carpet added previously can be retained in the target map. In other embodiments, when the current carpet is an unknown carpet, the carpet information of the current carpet may not need to be added to the target map first. In this way, after the carpet information of the temporarily incorporated unknown carpet corresponding to the current carpet is added to the target map, it is also unnecessary to delete the carpet information of the current carpet in the target map. In such an embodiment, the carpet information of the current carpet may be added to the target map upon determining that there is no previously unknown carpet in the target map whose positional relationship with the current carpet satisfies the first target requirement.

According to the technical scheme, the carpet information of the temporary combined unknown carpet corresponding to the current carpet is obtained by combining the current carpet and the target unknown carpet, and the carpet information of the temporary combined unknown carpet is added to the target map after each time of obtaining the carpet information of the temporary combined unknown carpet, so that the carpet information in the target map can be updated in real time.

Illustratively, in step S140, for an unknown carpet whose positional relationship with other unknown carpets does not satisfy the first target requirement, adding carpet information of the unknown carpet to the target map may include the steps of: when there is no prior unknown carpet or there is a prior unknown carpet but no target unknown carpet in the target map, the carpet information of the current carpet is added to the target map.

It will be appreciated that where there is no prior unknown carpet in the target map or there is a prior unknown carpet but no target unknown carpet, the current carpet may be a separate full carpet or the first detected carpet portion of a full carpet. Thus, the carpet information of the current carpet can be directly added to the target map. The carpet information processing method and device are beneficial to guaranteeing accuracy of carpet information in the target map.

The target map is, for example, a map of at least two preset areas. The carpet information also includes attribution information for the corresponding carpet. The attribution information is used for indicating attribution areas corresponding to the corresponding carpets, and the attribution areas are one or more preset areas in at least two preset areas. The operation of the cleaning robot to clean any one of the carpets is performed in a case where the cleaning robot cleans a home area corresponding to the carpet. The at least one target-incorporated unknown carpet includes target-incorporated unknown carpets in one-to-one correspondence with one or more sets of unknown carpets, the positional relationship between the unknown carpets in each set of unknown carpets satisfying the first target requirement.

When the detected current carpet is an unknown carpet, the method 100 may further include the steps of: a home zone determination operation is performed on the current carpet to determine home information for the current carpet.

It is understood that the preset area may be any area in the target map. For example, when the area corresponding to the target map is a home space, the preset area may be each room of the home space, that is, how many rooms there are in the home space. Alternatively, the preset area may be a user-defined area. For example, the user may divide the region corresponding to the target map into a plurality of preset regions in the target map by means such as frame selection. When the region corresponding to the target map is a home space, a part of one room may be set as one preset region. It should be noted that any two preset areas may be the same type of area or different types of areas. For example, the two preset areas may be two different rooms, respectively, or may be one room, and one may be a partial area in the other room.

As described above, alternatively, the target map may be a global map, and the region corresponding to the target map may be an entire region including at least two preset regions. The area to be cleaned may be at least a partial area of the at least two preset areas. Alternatively, the target map may also be at least part of the global map, and the area corresponding to the target map may be the cleaning area itself. That is, the area to be cleaned may include at least two preset areas. In the process of cleaning the area to be cleaned, each preset area in the area to be cleaned can be cleaned one by one.

If the carpet exists in two or more preset areas at the same time, if the attribution area corresponding to the carpet is determined to be one of the preset areas, the carpet can be cleaned according to the cleaning mode corresponding to the carpet when the carpet is cleaned to the attribution area corresponding to the carpet. And cleaning the carpet until the carpet exists in a preset area which does not belong to the attribution area corresponding to the carpet. Thus, when one carpet exists in a plurality of preset areas at the same time, the cleaning robot can be prevented from repeatedly cleaning the carpet.

Optionally, after performing the home area determining operation on the current carpet, the carpet information of the temporary incorporated unknown carpet and/or the target incorporated unknown carpet corresponding to the current carpet may be determined according to the home areas of the current carpet and the target unknown carpet. Specific methods are described in detail below and are not repeated here for brevity.

According to the technical scheme, the attribution area determining operation is carried out on the unknown carpets after the unknown carpets are obtained each time, so that the attribution information of each unknown carpet can be accurately determined, reliable basis can be provided for subsequent operations (such as cleaning the carpets in the area to be cleaned), repeated cleaning is avoided, and the cleaning efficiency and the cleaning effect of the cleaning robot can be improved.

The target map is, for example, a map of at least two preset areas. The carpet information also includes attribution information for the corresponding carpet. The attribution information is used for indicating attribution areas corresponding to the corresponding carpets, and the attribution areas are one or more preset areas in at least two preset areas. The operation of the cleaning robot to clean any one of the carpets is performed in a case where the cleaning robot cleans a home area corresponding to the carpet.

The step of merging the current carpet and the target unknown carpet to obtain carpet information of the temporarily merged unknown carpet corresponding to the current carpet may specifically include the steps of:

and merging the area occupied by the current carpet and the area occupied by the target unknown carpet based on the position information of the current carpet and the position information of the target unknown carpet, and determining the position information of the temporary merged unknown carpet.

And executing a home area determining operation on the temporary merging unknown carpet to determine the home information of the temporary merging unknown carpet, or determining the home area corresponding to the current carpet and the home area corresponding to the target unknown carpet as the home area corresponding to the temporary merging unknown carpet to determine the home information of the temporary merging unknown carpet.

In some embodiments, after determining the location information of the temporary merge unknown carpet, the home area corresponding to the current carpet and the home area corresponding to the target unknown carpet may be determined as the home area of the temporary merge unknown carpet. For example, if the home area corresponding to the current carpet is a first area and the home area corresponding to the target unknown carpet is a second area, the home area of the temporary combined unknown carpet may be the first area and the second area. Alternatively, after determining the location information of the temporary consolidated unknown carpet, a home zone determination operation may be performed on the temporary consolidated unknown carpet to determine the home information of the temporary consolidated unknown carpet. Compared with the mode that the home area corresponding to the current carpet and the home area corresponding to the target unknown carpet are directly determined to be the home area of the temporary merging unknown carpet, the technical scheme can determine the home area of the temporary merging unknown carpet more accurately. Thus, the accuracy of the carpet information in the target map can be further improved.

Step S130, merging the unknown carpets whose positional relationship satisfies the first target requirement, to obtain carpet information of at least one target merged unknown carpet after merging, may include the following steps:

for any one of the one or more sets of unknown carpets, merging the areas occupied by each of the unknown carpets in the set of unknown carpets based on the location information of each of the unknown carpets in the set of unknown carpets, and determining the location information of the target merged unknown carpets corresponding to the set of unknown carpets.

A home zone determination operation is performed on the target consolidated unknown carpet corresponding to the set of unknown carpets to determine home information for the target consolidated unknown carpets corresponding to the set of unknown carpets.

The above describes embodiments for determining attribution information for temporarily incorporating unknown carpeting. Since the target merge unknown carpet is a temporary merge unknown carpet corresponding to the last detected unknown carpet in the set of unknown carpets, with the above-described embodiment, after determining the attribution information of the temporary merge unknown carpet corresponding to the last detected unknown carpet, the attribution information of the target merge unknown carpet is determined. However, such an embodiment is optional. For example, in the above embodiment a, the detected attribution information of each current unknown carpet (i.e., the current carpet) or the temporary-incorporated unknown carpet obtained by intermediate incorporation may not be determined, and the attribution area determining operation may be directly performed for the target-incorporated unknown carpet. In the above embodiment B, the home zone determination operation may be directly performed for the target merged unknown carpet without performing the home zone determination operation for each detected current unknown zone. That is, whether the above-described embodiment a or B is adopted, the home-area determining operation may be performed on the target-incorporated unknown carpet after the position information of the target-incorporated unknown carpet is obtained, to determine the home information of the target-incorporated unknown carpet.

In the above-described technical solution, the home-area determination operation may be performed after the target merged unknown carpet corresponding to the set of unknown carpets is obtained. Thus, a group of unknown carpets is allowed to determine the home information of the target merged unknown carpets by performing a home zone determination operation. This solution helps to improve the efficiency of carpet information processing.

The home zone determination operation may specifically include the following steps, for example. And determining a preset area corresponding to the carpet to be determined in the target map based on the position information of the carpet to be determined, wherein the preset area corresponding to the carpet to be determined is a preset area in which at least one part of the carpet to be determined exists. For example, when the number of preset areas corresponding to the carpet to be determined is at least two, for each preset area corresponding to the carpet to be determined, whether the area occupied by the carpet to be determined in the preset area is larger than a first area threshold is determined, and if the area occupied by the carpet to be determined in the preset area is larger than the first area threshold, the preset area is determined to be the attribution area corresponding to the carpet to be determined. In an exemplary embodiment, when the number of preset areas corresponding to the carpet to be determined is at least two, if the area occupied by the carpet to be determined in each corresponding preset area is not greater than the first area threshold, determining the preset area with the largest occupied area of the carpet to be determined as the attribution area corresponding to the carpet to be determined. Wherein the carpet to be determined is the carpet for which the home zone determination operation is directed.

The carpet to be determined may be the current carpet described above, a temporary merge unknown carpet, or a target merge unknown carpet.

Alternatively, the position information of the carpet to be determined may be compared with the position information of each preset area in the target map, thereby determining the preset area in which the carpet to be determined exists. Alternatively, when the carpet to be determined is a temporary-merging unknown carpet or a target-merging unknown carpet, the preset area corresponding to each of the plurality of unknown carpets for generating the carpet to be determined may be determined first, and the preset area corresponding to each of the plurality of unknown carpets is used as the preset area corresponding to the carpet to be determined obtained after merging. When the number of the preset areas corresponding to the carpet to be determined is at least two, the area occupied by the carpet to be determined in each preset area can be compared with a first area threshold value, and if the area occupied by the carpet to be determined in any preset area is larger than the first area threshold value, the preset area is determined to be the attribution area corresponding to the carpet to be determined.

Alternatively, the first area threshold may be set as desired. For example, the first area threshold may be at [0.4m ² ,1m ² ]Within a range of (2). In a specific embodiment, the first area threshold may be 0.6m ² 。

For example, assume that carpet a to be determined is present in two rooms at the same time, each room being a preset area. Assume that the portion of carpet a to be determined in room 1 is A1 and the portion in room 2 is A2. If the areas of A1 and A2 are both greater than 0.6m ² It can be determined that carpet a is simultaneously assigned to rooms 1, 2. If the area of A1 is greater than 0.6m ² The area of A2 is less than 0.6m ² It can be determined that carpet a belongs to room 1. If the areas of A1 and A2 are smaller than 0.6m ² And area of A1>The area of A2 then it can be determined that carpet a belongs to room 1.

The attribution of the carpet is divided to avoid repeated cleaning of the same carpet, and the cleaning times are preset times in the cleaning process of the carpet. For example, if the attribution of the carpet is not divided, the carpet a is cleaned a preset number of times when the room 1 is cleaned, and then the carpet a is recognized again when the room 2 is cleaned, and the carpet a is cleaned a preset number of times again. The preset number of times may be one or more times. A preset number of times for cleaning each carpet is generally set in the cleaning task, and if cleaning is performed in the above manner, the carpet a is finally cleaned 2 times the preset number of times, which is equivalent to repeating the cleaning for the carpet a. In the embodiment of the application, the carpet can be divided by judging the attribution area of the carpet, and the carpet can be cleaned only when the carpet is currently cleaned to the attribution area corresponding to the carpet. Thus, repeated cleaning of the carpet can be effectively avoided.

According to the technical scheme, the attribution information of the carpet to be determined is determined through the area of the carpet to be determined in each preset area, and the attribution area is used as a benchmark for dividing the attribution area in the mode, so that the attribution area is reasonably divided.

Illustratively, the carpet information also includes a cleaning mode. The cleaning mode is used to instruct the cleaning robot as to the manner in which the corresponding carpet is treated when performing the cleaning task. The method 100 may further include the following steps when the detected current carpet is an unknown carpet. Based on the positional information of the current carpet and the positional information of the known carpet in the target map, a positional relationship between the current carpet and the known carpet is determined. When at least one target known carpet exists in the target map, determining a current carpet cleaning mode based on the cleaning mode of the at least one target known carpet. Wherein the target known carpet represents a known carpet whose positional relationship with the current carpet in the target map satisfies the second target requirement. The second target requirement includes carpeting intersecting each other. The at least one target merge unknown carpet includes target merge unknown carpets that are in one-to-one correspondence with one or more sets of unknown carpets. The positional relationship between unknown carpets in each set of unknown carpets meets a first target requirement. The cleaning pattern of the current carpet is used to determine a cleaning pattern of a target merged unknown carpet corresponding to a set of unknown carpets on which the current carpet is located.

Alternatively, the cleaning mode may include one or more of a ignore carpet mode, an avoid carpet mode, a span carpet mode, and a clean carpet mode, among others. For any one carpet, the mode of the carpet can be set according to the needs of a user.

In some embodiments, for carpets that do not want to do any special treatment, the user may set the carpet cleaning mode to ignore the carpet mode, thereby causing the cleaning robot to do no special action on the carpet, such as treating the carpet as if it were a floor equivalent. For example, the cleaning robot cleans a carpet provided with a neglected carpet mode, and the action path and the area located in the action path are cleaned according to a planned action path (which belongs to the area to be cleaned) and a cleaning mode corresponding to the action path. For example, the cleaning robot is in a mopping mode aiming at the cleaning mode of the action path, and determines that a carpet exists in the action path, and determines that the cleaning mode corresponding to the carpet is in a neglect carpet mode according to the carpet information of the carpet, the cleaning robot does not trigger the action of lifting a mop because the carpet is identified, and still maintains the mopping action to process the carpet, namely, mopping action is carried out on the carpet.

In some embodiments, for carpets that are not intended to be cleaned or spanned by the cleaning robot, the user may set the cleaning mode of the carpet to the evasion carpet mode, thereby causing the cleaning robot to treat the carpeting set with the mode as a exclusion zone, including but not limited to setting the circumscribed rectangle of the carpet as the exclusion zone. In other words, the cleaning robot is prohibited from passing through the area where the carpet is located. For example, when the cleaning robot performs a cleaning task, if a carpet whose cleaning mode is an evasion carpet mode exists in a region to be cleaned, the cleaning robot does not travel onto the carpet, and does not clean the carpet. For another example, when planning the path of action of the cleaning robot according to the cleaning task, a carpet having a cleaning mode that is a carpet-avoidance mode is directly avoided. Therefore, when the cleaning robot executes the cleaning task according to the action path, the carpet can be avoided according to the planned action path.

In some embodiments, for carpets that do not want to be cleaned by the cleaning robot but that form a block to the navigation or travel path of the cleaning robot, the user may set the cleaning mode of the carpet to a cross carpet mode so that the cleaning robot may pass over the carpet without cleaning. In one embodiment, the planned path of the cleaning robot avoids the carpet set in a crossing carpet mode as much as possible, and when the navigation or action path is blocked by the carpet and an uncleanable area appears, the planned path of the cleaning robot passes through the carpet, so that the cleaning robot can cross the carpet to ensure the cleaning coverage rate of the cleaning robot. Meanwhile, the cleaning robot does not perform a cleaning operation while crossing the carpet. For example, for a cleaning robot that includes a roller brush and a squeegee, when cleaning a carpet in a cleaning mode that is a span carpet mode, the squeegee and the roller brush may be selectively lifted to prevent the squeegee and the roller brush from contaminating the carpet.

In some embodiments, for carpets that require a cleaning robot to clean, a user may set the cleaning mode of the carpet to a cleaning carpet mode. In one embodiment, the cleaning robot may first clean a non-carpet area each time a cleaning task is performed and it is determined that there is a carpet in a cleaning mode of a cleaning carpet mode in the area to be cleaned, and clean the carpet area after the cleaning of the non-carpet area is completed. Alternatively, the non-carpet area may be cleaned after the carpet provided with the carpet cleaning mode is cleaned. Of course, it is also possible to perform a carpet exploring action on the carpet before cleaning the carpet, explore the location of the carpet, and thus determine the carpet information of the carpet to ensure the accuracy of the carpet information. It will be appreciated that cleaning a carpet in which a cleaning carpet mode is set, that is, a cleaning robot performs a cleaning action according to preset parameters, such as selecting a cleaning actuator, an operation parameter of the cleaning actuator, the number of cleaning times, and the like. In some embodiments, for a cleaning robot including a rolling brush and a cleaning member, when cleaning a carpet in a carpet cleaning mode, the cleaning member can be lifted, the rolling brush rotating speed can be increased, the suction force of a fan can be increased, and the like, so that the cleaning effect on the carpet can be improved. Of course, the operating parameters of the roller brush and the blower may be the same as those of the cleaning non-carpet area, and are not limited herein.

It will be appreciated that "cleaning" in the cleaning carpet mode is different from "cleaning" in the ignore carpet mode. The cleaning in the carpet cleaning mode is the active action of the cleaning robot, that is, the cleaning robot aims to clean the carpet provided with the carpet cleaning mode, and the cleaning range corresponding to the action path of the cleaning robot (that is, the range which can be cleaned when the cleaning robot acts according to the action path) covers the whole carpet. The "cleaning" in the carpet mode is ignored, and the cleaning robot is passive, i.e. the cleaning robot is aimed at ensuring that the cleaning robot is not affected by the environment, and the cleaning of the area to be cleaned in the cleaning plan can be completed according to the planned path. Thus, when there is a carpet in the cleaning area in which the cleaning mode is the neglect carpet mode, the cleaning robot does not perform special treatment on the carpet, but chooses neglect and disregard to ensure that the cleaning robot can perform cleaning tasks according to a cleaning plan (e.g., the planned action path described above). In this case, the cleaning range corresponding to the movement path of the cleaning robot may pass through the carpet and may not necessarily cover the entire carpet, so that the cleaning of the carpet is not a real cleaning for the purpose of cleaning the carpet. Further, the "cleaning" performed by the cleaning robot for cleaning the carpet in the carpet mode is different from the "cleaning" performed for the carpet in the neglected carpet mode, both the action performed and the cleaning effect are different. Describing the cleaning robot comprising a rolling brush and a cleaning piece as an example, when the cleaning robot "cleans" a carpet in a carpet cleaning mode, the cleaning robot will lift the cleaning piece to reduce the possibility of wetting or contaminating the carpet by the cleaning piece, and at the same time, the cleaning robot will also increase the rolling brush rotation speed and/or increase the fan suction force to increase the cleaning effect on the carpet. How the cleaning robot "cleans" the carpet in the neglected carpet mode depends on the preset cleaning mode of the cleaning robot in the area to be cleaned, and if the preset cleaning mode of the cleaning robot is the floor mopping mode, the cleaning robot moves along the planned moving path and maintains the operation of the mopping piece to get on the carpet, so that the carpet is cleaned. However, the carpet is not cleaned, but is wet and even soiled. And if the cleaning robot recognizes that the preset cleaning mode before the carpet is a floor sweeping mode, the cleaning robot moves along the planned moving path and maintains the running of the rolling brush to go over the carpet, thereby realizing the cleaning of the carpet. It can be seen that the "cleaning" of carpets in the neglected carpet mode by the cleaning robot is not truly a cleaning, unlike the "cleaning" in the cleaning carpet mode.

In this embodiment, if any unknown carpet is detected, a target known carpet whose positional relationship with the unknown carpet satisfies the second target requirement may be first searched for from the target map. The second target requirement includes carpeting intersecting each other, that is, the target known carpet and the currently detected unknown carpet (i.e., the current carpet described above) at least intersect each other. Of course, the second target requirement may also include other requirements, such as requiring the area of intersection of the carpets to exceed a certain area threshold, or requiring the ratio of the area of intersection of the carpets to the area of the current carpet, the area of the target unknown carpet, or the area of the union between the current carpet and the target unknown carpet to exceed a certain ratio threshold, and so on. In the event that a target known carpet is found, the current carpet cleaning mode may be determined based on the target known carpet cleaning mode.

The cleaning pattern of the current carpet is used to determine a cleaning pattern of the target merged unknown carpet corresponding to the set of unknown carpets in which the current carpet is located. As will be appreciated from the above description, the target merged unknown carpet is obtained by merging a set of unknown carpets, and thus after determining the cleaning pattern of each unknown carpet, the cleaning patterns of the unknown carpets can be combined to determine the cleaning pattern of the target merged unknown carpet. In one embodiment, if the cleaning pattern of each unknown carpet in a set of unknown carpets is the same, determining the cleaning pattern of the corresponding target merged unknown carpet as the cleaning pattern of each unknown carpet; if the cleaning modes of all unknown carpets in a group of unknown carpets are different, outputting reminding information corresponding to the target combined unknown carpets and/or determining that the cleaning mode of the target combined unknown carpets is a fourth default cleaning mode. The fourth default cleaning mode may be the same or different from any of the first, second, and third default cleaning modes described below, and may be similar to any of the first, second, and third default cleaning modes described below, in particular, with reference to the following.

Of course, it will be understood that if, for the current carpet, there is no unknown carpet whose positional relationship with the current carpet satisfies the first target requirement among all unknown carpets detected during the execution of the target task, the cleaning mode of the current carpet can be directly used as a basis for cleaning the current carpet.

According to the technical scheme, the cleaning mode of the current carpet can be accurately determined by utilizing the cleaning mode of the target known carpet, so that the accuracy of carpet information of the current carpet or the target combined unknown carpet can be guaranteed. And then can guarantee good cleaning effect when follow-up based on carpet information to current carpet or target merge unknown carpet.

Illustratively, determining the current cleaning pattern of the carpet based on the at least one target known cleaning pattern of the carpet may specifically comprise the steps of: when the number of target known carpets is one, it is determined that the current cleaning mode of the carpet is the cleaning mode of the target known carpets. And when the number of the target known carpets is at least two, if the cleaning modes of the target known carpets are the same, determining that the cleaning mode of the current carpet is the cleaning mode of the target known carpets. If the cleaning modes of the carpets known by the targets are different, outputting reminding information corresponding to the current carpet and/or determining that the cleaning mode of the current carpet is a first default cleaning mode.

Take the embodiment shown in fig. 2 as an example. In this embodiment, carpet a, carpet B, and carpet C are unknown carpets, and carpet D is a known carpet. As shown in fig. 2, a intersects D. Thus, the cleaning mode of a can be determined from the cleaning mode of D. For example, if the cleaning mode of D is the ignore carpet mode, it may be determined that the cleaning mode of a is the ignore carpet mode. Alternatively, in one embodiment, a in fig. 2 is an unknown carpet and B, C, D are both known carpets. If the cleaning modes of B, C, D are all the same, then the cleaning mode of A is the same. For example, if the cleaning modes of B, C, D are all the evasive carpet modes, it may be determined that the cleaning mode of a is the evasive carpet mode. If the cleaning modes of B, C, D are not exactly the same, then the cleaning mode of A can be set to the first default cleaning mode. For example, if the cleaning mode of B is the evasion carpet mode and the cleaning mode of C, D is the span carpet mode, it may be determined that the cleaning mode of a is the first default cleaning mode.

Optionally, when the cleaning modes of the known carpets of the targets are different, reminding information corresponding to the current carpet can be directly output so as to remind the user to set the cleaning mode of the current carpet. Alternatively, when the cleaning modes of the respective target known carpets are different, the current cleaning mode of the carpet may be directly determined as the first default cleaning mode. Alternatively, when the cleaning modes of the known carpets of the targets are different, the cleaning mode of the current carpet can be determined to be the first default cleaning mode, and reminding information corresponding to the current carpet is output to remind the user to confirm the cleaning mode of the current carpet.

Alternatively, the first default cleaning mode may be a fixed cleaning mode set in advance, which may be set by a designer before shipment of the cleaning robot, or may be set by a user at any time while using the cleaning robot. For example, the first default cleaning mode may be a span carpet mode. That is, as long as the cleaning modes of the known carpets for the respective targets are different, the current carpet cleaning mode is directly determined to be the span carpet mode no matter what the cleaning mode of the known carpets for the respective targets is. Alternatively, the first default cleaning mode may be automatically adjusted based on the known carpet cleaning mode for each target. In some embodiments, the cleaning modes include a plurality of cleaning modes, and each cleaning mode has a different priority. The first default cleaning mode is the highest priority cleaning mode among the cleaning modes of the known carpets of each target. In embodiments where the cleaning modes of B, C, D are not exactly the same, priorities of the different cleaning modes may be set. For example, a priority from high to low may be a get around carpet mode, a span carpet mode, a clean carpet mode, a ignore carpet mode. In this embodiment, the cleaning mode with the highest priority among the cleaning modes B, C, D corresponding to each may be set as the first default cleaning mode according to the priority of each cleaning mode. In a specific embodiment, if the cleaning mode of at least one carpet in B, C, D is the avoid carpet mode, the first default cleaning mode may be the avoid carpet mode.

According to the technical scheme, the cleaning mode of the current carpet is determined by comprehensively considering the different modes of the cleaning modes of the known carpets of all targets, so that the accuracy of the cleaning mode of the current carpet is further guaranteed.

Illustratively, the method 100 may further include the steps of: and when the target known carpet does not exist in the target map, outputting reminding information corresponding to the current carpet and/or determining that the cleaning mode of the current carpet is a second default cleaning mode.

Alternatively, the second default cleaning mode may be set as actually needed. For example, the user may set the second default cleaning mode to any one of a neglect carpet mode, an avoidance carpet mode, a stride carpet mode, a cleaning carpet mode, and the like according to actual needs. In some embodiments, the second default cleaning mode may be different depending on the material of the current carpet. For example, for carpets made of wool, the corresponding second default cleaning mode may be the evade carpet mode. For carpets made of cotton, the corresponding second default cleaning mode may be a span carpet mode.

Optionally, when the target known carpet does not exist in the target map, reminding information corresponding to the current carpet can be directly output so as to remind the user to set the cleaning mode of the current carpet. Alternatively, when there is no target known carpet in the target map, the cleaning mode of the current carpet may be directly determined to be the second default cleaning mode. Alternatively, when the target known carpet does not exist in the target map, the cleaning mode of the current carpet can be determined to be the second default cleaning mode, and reminding information corresponding to the current carpet is output to remind the user to confirm the cleaning mode of the current carpet. In the embodiment, the user is reminded of confirming the cleaning mode of the current carpet by outputting reminding information, so that the accuracy of the current carpet cleaning mode is further guaranteed.

According to the technical scheme, when the target known carpet does not exist in the target map, the reminding information corresponding to the current carpet can be output and/or the cleaning mode of the current carpet is automatically set to be the second default cleaning mode according to the requirements, so that good cleaning effect can be ensured when the carpet is cleaned based on the carpet information.

Illustratively, combining the current carpet and the target unknown carpet to obtain carpet information of the temporary combined unknown carpet corresponding to the current carpet may specifically include the steps of:

and merging the area occupied by the current carpet and the area occupied by the target unknown carpet based on the position information of the current carpet and the position information of the target unknown carpet, and determining the position information of the temporary merged unknown carpet corresponding to the current carpet.

And when the cleaning mode of the current carpet is the same as the cleaning mode of the target unknown carpet, determining that the cleaning mode of the current carpet is the temporarily combined unknown carpet corresponding to the current carpet.

Outputting reminding information corresponding to the temporary merging unknown carpet and/or determining that the cleaning mode of the temporary merging unknown carpet corresponding to the current carpet is a third default cleaning mode when the cleaning mode of the current carpet is different from the cleaning mode of the target unknown carpet.

In example a above, the unknown carpets are iteratively combined, which results in temporarily combining the unknown carpets. The cleaning pattern of the temporary consolidated unknown carpet may be determined together each time the temporary consolidated unknown carpet is obtained. The cleaning pattern of the temporary merge unknown carpet may be determined based on the cleaning patterns of the current carpet and the target unknown carpet used to generate the temporary merge unknown carpet. Similar to the above-described scheme of determining the cleaning pattern of the current carpet by taking into account the dissimilarity of the cleaning patterns of the respective target known carpets, the cleaning pattern of the temporarily incorporated unknown carpets may also be determined by taking into account the dissimilarity of the cleaning pattern of the current carpet and the cleaning pattern of the target unknown carpets in the present embodiment. That is, when the cleaning modes of the current carpet and the target unknown carpet are the same, determining that the cleaning mode of the temporary merging unknown carpet is the same as the cleaning mode of the current carpet and the target unknown carpet, otherwise, directly setting the cleaning mode of the temporary merging unknown carpet to be a third default cleaning mode and/or outputting reminding information corresponding to the temporary merging unknown carpet.

Alternatively, the third default cleaning mode may be a fixed cleaning mode set in advance, or may be automatically adjusted according to the current carpet cleaning mode and the target unknown carpet cleaning mode, similar to the first default cleaning mode. The specific arrangement is described in detail above. For brevity, no further description is provided herein. In addition, the scheme of outputting the reminding information corresponding to the temporary combined unknown carpet is similar to the implementation mode and the function of outputting the reminding information corresponding to the current carpet, and is not repeated.

In the above technical solution, according to the cleaning mode of the current carpet and the cleaning mode of the target unknown carpet, the cleaning mode of the temporary combined unknown carpet corresponding to the current carpet is determined. This solution is advantageous for improving the accuracy of the cleaning pattern of temporarily incorporating unknown carpets.

Fig. 5 illustrates an exemplary flow chart of a carpet information processing method according to one specific embodiment of the present application. As shown in fig. 5, the method of this embodiment includes the steps of:

in step S510, when the detected current carpet is an unknown carpet, position information of the unknown carpet is acquired.

Step S520, a home zone determination operation is performed on the current carpet.

In step S530, carpet information of the current carpet is added to the target map. In performing step S530, carpet information of the current carpet may be added to a target map such as a global map, and/or an obstacle map, and/or a planning map.

Step S540, determining the positional relationship between the current carpet and the previously unknown carpet.

Step S550, judging whether the position relation between the current carpet and the previously unknown carpet meets the second target requirement. When there is a target known carpet whose positional relationship satisfies the second target requirement, step S570, step S580, and step S590 are performed. Otherwise, step S560 is performed.

Step S560, outputting reminding information corresponding to the current carpet. The reminder information may be reminder information as described above that reminds the user to set or confirm the current cleaning mode of the carpet.

Step S570, determining the current carpet cleaning mode. In this step, the current carpet cleaning mode may be determined based on the target known carpet cleaning mode.

Step S580, merging the current carpet and the target unknown carpet. In this step, a temporary consolidated unknown carpet can be obtained. If the current carpet is the last detected unknown carpet, the temporary unknown carpet is the target unknown carpet.

Step S590, deleting the current carpet and the target unknown carpet. In this step, the carpet information of the current carpet and the target unknown carpet is deleted from the target map. In addition, in step S590, the carpet information of the temporary merge unknown carpet or the target merge unknown carpet may be further added to the target map.

It will be appreciated that the specific implementation of the steps in fig. 5 has been described in detail above. For brevity, no further description is provided herein.

Illustratively, the target task is a cleaning task, and the method 100 may further include the steps of: the area identification information of the area to be cleaned is acquired before the cleaning task is performed. A global map is acquired. And generating a target map corresponding to the cleaning task based on the region identification information of the region to be cleaned and the global map. And preloading the position information of at least part of carpets meeting preset conditions in the global map into the target map. Determining attribution information of the carpet to be cleaned in at least part of the carpets based on the area identification information of the area to be cleaned, and adding the attribution information of the carpet to be cleaned to the target map. Wherein the global map is a map of one or more preset areas. The one or more predetermined areas include an area to be cleaned. The attribution information is used for indicating an attribution area corresponding to the corresponding carpet. The home zone is at least one of the one or more preset zones. The operation of the cleaning robot to clean any one of the carpets is performed in a case where the cleaning robot cleans a home area corresponding to the carpet.

Alternatively, the area identification information may include one or more of the following: coordinate information of a plurality of representative points in the region to be cleaned, geometric center coordinates in the region to be cleaned, contour information, labels, size information of the region to be cleaned, and the like. The representative point may be, for example, a vertex in the area to be cleaned, or the like. The label may be, for example, an area number or the like. Preferably, when the region identification information includes geometric center coordinates in the region to be cleaned, the region identification information may further include size information. For example, the region to be cleaned may be a rectangular region, and the region identification information may be coordinate information of the region to be cleaned in a coordinate system corresponding to the global map.

Alternatively, the area to be cleaned may be one or more of all preset areas in the global map. In one embodiment, the region to which the global map corresponds may be a home space. The area to be cleaned may be one or more rooms in the home space. Alternatively, the area to be cleaned may be a part of the preset area. In one embodiment, the region to which the global map corresponds may be a home space. The area to be cleaned may be a partial area in one room in the home space. For example, a desk may be provided in a room. The area to be cleaned may be an area near a desk.

In some embodiments, the area to be cleaned may be determined in response to a user input instruction in the global map. For example, the user may click on any one of the preset areas in the global map to determine the preset area as an area to be cleaned. Alternatively, the user may outline a partial region in the global map to determine the region as the region to be cleaned. Of course, the user may also input the labels of one or more preset areas by means of a mouse click and/or a keyboard input to select these preset areas as the area to be cleaned, for example, input a text message such as "room 1" to select room 1 as the area to be cleaned. In response to a user operation, corresponding region identification information may be acquired. Based on the area identification information of the area to be cleaned and the global map, a target map corresponding to the cleaning task may be generated, and the target map may be the planning map and/or the obstacle map.

Alternatively, at least part of the carpets may be all carpets satisfying the preset condition in the global map, or may be part of the carpets satisfying the preset condition in the global map. For example, at least a portion of the carpeting may be carpeting in the global map that is located within the area corresponding to the target map.

In some embodiments, the attribution information of unknown carpets that are ultimately obtained in the current cleaning task (including the unknown carpets obtained by the initial detection and/or the target merge unknown carpets obtained by the merge) may not be determined. When the cleaning task is executed next time, if an unknown carpet in the previous cleaning task (known carpet in the cleaning task) is related to the target map of the cleaning task, determining attribution information of the unknown carpet before the cleaning task is executed. In this embodiment, the home information of the corresponding carpet is confirmed only before it is required to be acquired, thereby contributing to improvement in the processing efficiency of the carpet information. Of course, this solution is optional, and the attribution information of each unknown carpet that is finally obtained may be determined in each cleaning task, so that if any unknown carpet with the determined attribution information needs to be cleaned when the cleaning task is performed next time, it is unnecessary to determine the attribution information again.

Illustratively, before the start of a cleaning task (which may specifically be, for example, a first cleaning subtask), a reset planning map (reset planning map) service may be invoked by a program (application) in the cleaning robot to preload the position information of at least part of the carpets meeting the preset conditions into the planning map, which is then the target map. Furthermore, cleaning tasks may be invoked by programs. After invoking the cleaning task, the cleaning robot may navigate to the area to be cleaned. The preloading of the carpet location information may be accomplished before navigating to the area to be cleaned, and the carpet attribution information may be further determined.

According to the technical scheme, before the cleaning task is executed, carpets in the global map are loaded into the target map in advance, so that when the known carpets are detected, the carpets do not need to be explored. The carpet information processing amount of the cleaning robot in the cleaning task executing process is reduced, and meanwhile the efficiency of the cleaning robot in executing the cleaning task is improved.

Illustratively, the preset conditions include: the area of the carpet is greater than the second area threshold. Hereinafter, this condition is simply referred to as a first preset condition.

Alternatively, the second area threshold may be set as desired. For example, the second area threshold may be at [0.4m ² ,1m ² ]Within a range of (2). In a specific embodiment, the second area threshold may be 0.6m ² 。

It will be appreciated that the carpet may be a larger area carpet or a smaller area carpet such as a door mat. Carpets of smaller area are more susceptible to displacement by external factors than carpets of larger area. In this embodiment, only carpets with a large area need to be loaded. On the one hand, this is advantageous in reducing carpet information data loading. On the other hand, a carpet with a smaller area can be repositioned each time a cleaning task is performed, which is beneficial to improving the accuracy of the location information of the carpet in the target map.

Illustratively, the preset conditions include: the carpet cleaning mode is a carpet avoidance mode, and the carpet avoidance mode is used for indicating that a cleaning robot avoids the position of a corresponding carpet in the running process when performing a cleaning task. Hereinafter, this condition is simply referred to as a second preset condition.

It will be appreciated that the cleaning mode of the carpet is a evasive carpet mode, meaning that the cleaning robot is not allowed to clean or ride over. I.e. the carpet is the forbidden zone of the cleaning robot. In this embodiment, before the cleaning robot performs the cleaning task, a carpet whose cleaning mode is the evasion carpet mode is loaded in advance into the target map. So that the cleaning robot can avoid the carpet by the action path when planning the action path based on the cleaning area. Therefore, the technical scheme is beneficial to improving the use experience of the user.

Alternatively, the preset condition employed when preloading the positional information of the carpet may include a first preset condition. That is, the preset conditions may include: the area of the carpet is greater than the second area threshold. Thus, if the area of the carpet is greater than the second area threshold, the carpet may be preloaded into the target map.

Alternatively, the preset conditions employed when preloading the positional information of the carpet may include a second preset condition. That is, the preset conditions may include: the carpet cleaning mode is a evasion carpet mode. In this way, if the cleaning mode of the carpet is the evasion carpet mode, the carpet may be preloaded into the target map.

Alternatively, the preset conditions employed when preloading the positional information of the carpet may include a first preset condition or a second preset condition. That is, the preset conditions may include: the area of the carpet is greater than the second area threshold, or the cleaning mode of the carpet is an evasion carpet mode. In this embodiment, a carpet in the global map may be preloaded into the target map as long as the carpet satisfies any one of the first preset condition and the second preset condition.

Alternatively, the preset conditions used when preloading the positional information of the carpet may include a first preset condition and a second preset condition. That is, the preset conditions may include: the area of the carpet is greater than the second area threshold and the cleaning mode of the carpet is an evasive carpet mode. In this embodiment, the carpet in the global map is required to satisfy both the first preset condition and the second preset condition in order to be preloaded into the target map.

According to the technical scheme, the carpet meeting the preset conditions in the global map is loaded into the target map, so that the processing amount of carpet information data can be reduced, and the processing efficiency of the carpet information and the execution efficiency of cleaning tasks are improved.

Illustratively, preloading carpet information of at least a portion of carpets in the global map meeting preset requirements into the target map may include the steps of: carpet information of carpets which meet preset conditions in the global map and intersect with a movement path when the cleaning robot performs a cleaning task is preloaded into the target map.

It will be appreciated that a carpet intersecting a path of action when the cleaning robot performs a cleaning task represents a carpet located on the path of action corresponding to the cleaning task. Optionally, the action path may include: a path of the cleaning robot when cleaning in the cleaning area, a path from a base station corresponding to the cleaning robot to the cleaning area, and a path from the cleaning area to the base station corresponding to the cleaning robot. In this embodiment, only carpet information of carpets in the global map, which satisfy the preset conditions and intersect with the action path when the cleaning robot performs the cleaning task, is loaded into the target map, which is beneficial to reducing the occupation of computing resources. Meanwhile, the carpet information processing method and device are beneficial to improving the carpet information processing efficiency.

Illustratively, the method 100 may further include the steps of:

map point type information detected for each of at least some of the map points in the target map during execution of the target task is acquired.

For each known carpet in the target map, determining whether the known carpet is shifted based on map point type information corresponding to map points at the location of the known carpet.

When any one of the known carpets is shifted, the carpet information of the known carpet is deleted from the target map. Wherein the map point type information is used to indicate whether the corresponding map point belongs to a carpet.

It will be appreciated that the above-described displacement of the known carpet includes not only a change in the position of the known carpet in the narrow sense, but also the disappearance of the known carpet.

In some embodiments, during the process of the cleaning robot performing the target task, a sensor of the cleaning robot may detect map point type information. The target task may be, for example, a first cleaning subtask for a non-carpeted area. The map point type information may be, for example, the above-described ground material information. For example, a sensor such as an ultrasonic sensor may be employed to detect map point type information, and determine whether each map point belongs to a carpet.

It will be appreciated that the known carpet shift may be determined when no carpet signal is detected where the known carpet was originally located. Optionally, determining whether the known carpet is shifted based on map point type information corresponding to map points at the location of the known carpet may include the steps of:

And determining that the known carpet is shifted when the map point type information corresponding to at least a first number of map points belonging to the location of the known carpet is non-carpet. For example, from the target map, the location where each known carpet should originally be can be determined. Assuming that the location where any known carpet originally resides occupies 100 map points, the 100 map points may be detected during execution of the target task, and if the map point type information corresponding to the map points where the first number of map points exists is found to be non-carpet, the known carpet shift may be determined.

Alternatively, the first number may be set as desired. For example, the first number may be 1. Alternatively, in order to avoid that the acquired map point type information is generated due to erroneous detection of the cleaning robot, the first number may be at least 2. According to the scheme, when the map point type information is that the number of the map points which are not carpets reaches the first number, the corresponding known carpets are determined to be shifted, and therefore accuracy of judging results can be ensured.

According to the technical scheme, the corresponding carpet information in the target map can be deleted in time after the carpet is shifted, so that the accuracy of the carpet information in the target map is guaranteed.

Illustratively, determining whether the known carpet is shifted based on map point type information corresponding to map points at the location of the known carpet may specifically include the steps of:

calculating the ratio between the occupied area of the non-carpet map points at the position of the known carpet and the total area of the known carpet based on the map point type information corresponding to the map points at the position of the known carpet;

judging whether the ratio is larger than a ratio threshold;

when the ratio is greater than the ratio threshold, the known carpet is determined to be shifted.

Alternatively, the ratio threshold may be set as desired. For example, the ratio threshold may be in the range of [5%,40% ]. In a specific embodiment, the ratio threshold may be 20%. I.e., the known carpet is determined to have shifted when the ratio between the area occupied by the non-carpet map points at the location of the known carpet and the total area of the known carpet is greater than 20%. For example, from the target map, the location where each known carpet should originally be can be determined. Assuming that the location where any known carpet is originally located occupies 100 map points, the 100 map points can be detected in the process of executing the target task, and if the map point type information corresponding to at least 20% map points (i.e., at least 20 map points) are found to be non-carpeted, the known carpet shift can be determined.

According to the technical scheme, when the ratio of the occupied area of the non-carpet map points at the position of the known carpet to the total area of the known carpet is larger than the proportional threshold, the known carpet is determined to shift, so that the map point type information of a single map point is prevented from affecting the final judging result in an error manner. The scheme has good fault tolerance.

According to another aspect of the present application, a cleaning method is provided. Fig. 6 shows a schematic flow chart of a cleaning method according to one embodiment of the present application. As shown in fig. 6, the cleaning method 600 may include the following steps S610 and S620.

In step S610, the carpet information processing method 100 is performed during the execution of the first cleaning subtask for the non-carpet area. Wherein the non-carpet area is an area outside the carpet area where the carpet is located.

In step S620, a carpet cleaning operation is performed using the target map during execution of the second cleaning subtask for the carpet area. The cleaning tasks comprise a first cleaning subtask and a second cleaning subtask, and the target task is the first cleaning subtask.

Alternatively, the cleaning task may be performed for the non-carpet area first and then for the carpet area separately. This separate cleaning scheme facilitates improved cleaning efficiency and cleaning effectiveness, as non-carpet areas and carpet areas are typically adapted for different cleaning modes. While performing the first cleaning subtask, the carpet may be explored while cleaning, so that up-to-date carpet information may be obtained. Subsequently, while the second cleaning subtask is being performed, a carpet cleaning operation may be performed based on previously determined carpet information. Illustratively, the cleaning method 600 may further include, prior to performing the second cleaning subtask: and controlling the cleaning robot to perform self-cleaning. In some embodiments, the cleaning robot may include a sweeping robot and a base station corresponding to the sweeping robot. Before the second cleaning subtask is executed, the sweeping robot can be controlled to return to the base station for self cleaning, so that the carpet area is prevented from being polluted by dirt possibly existing on the sweeping robot.

It can be understood that the target map in step S620 is an updated target map obtained after the cleaning robot performs the carpet information processing method 100 in the first cleaning subtask. According to the technical scheme, the carpet area is cleaned based on the carpet information in the target map, so that the cleaning effect of the carpet area is improved. In addition, the separate cleaning manner also helps to improve the cleaning efficiency and cleaning effect.

According to yet another aspect of the present application, a cleaning robot is provided, fig. 7 shows a schematic block diagram of the cleaning robot according to an embodiment of the present application. As shown in fig. 7, the cleaning robot 700 includes a processor 710 and a memory 720, wherein the memory 720 stores computer program instructions for executing the map updating method as described above or the cleaning method as described above when the computer program instructions are executed by the processor 710.

Illustratively, the cleaning robot includes a carpet sensor for detecting a floor material. Alternatively, the carpet sensor may be any sensor that can detect the texture of the floor surface, either existing or developed in the future. For example, an ultrasonic sensor may be used.

According to yet another aspect of embodiments of the present application, there is also provided a computer-readable storage medium. The storage medium has stored therein a computer program/instruction which, when executed by a processor, implements the map updating method as described above or the cleaning method as described above. The storage medium may include, for example, read-only memory (ROM), erasable programmable read-only memory (EPROM), portable compact disc read-only memory (CD-ROM), USB memory, or any combination of the preceding. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

The realization structure, working principle and advantageous effects of the cleaning method, the cleaning robot and the computer-readable storage medium are easily understood by those of ordinary skill in the art by reading the above carpet information processing method. For brevity, the description is omitted here.

Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the above illustrative embodiments are merely illustrative and are not intended to limit the scope of the present invention thereto. Various changes and modifications may be made therein by one of ordinary skill in the art without departing from the scope and spirit of the invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, e.g., the division of elements is merely a logical function division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another device, or some features may be omitted, or not performed.

In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in order to streamline the invention and aid in understanding one or more of the various inventive aspects, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of the invention. However, the method of the present invention should not be construed as reflecting the following intent: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be combined in any combination, except combinations where the features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functions of some modules in a cleaning robot according to embodiments of the present invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.

The foregoing description is merely illustrative of specific embodiments of the present invention and the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the scope of the present invention. The protection scope of the invention is subject to the protection scope of the claims.

Claims

1. A carpet information processing method applied to a cleaning robot, comprising:

acquiring position information of each unknown carpet detected in the execution process of a target task;

determining a positional relationship between the unknown carpets based on the acquired positional information of the unknown carpets;

merging unknown carpets with the position relationship meeting the first target requirement to obtain carpet information of at least one target merged unknown carpet after merging, and adding the carpet information of the at least one target merged unknown carpet into a target map;

for an unknown carpet whose positional relationship with other unknown carpets does not meet the first target requirement, adding carpet information of the unknown carpet to the target map;

the target task is at least a task for detecting unknown carpets, the target map is a map according to which the cleaning robot executes a cleaning task, the first target requirement comprises that the carpets intersect each other, and the carpet information comprises position information.

2. The carpet information processing method according to claim 1, wherein when the detected current carpet is an unknown carpet,

The determining the position relation among the unknown carpets based on the acquired position information of the unknown carpets comprises the following steps:

determining a positional relationship between the current carpet and the previously unknown carpet based on the positional information of the current carpet and the positional information of the previously unknown carpet when the previously unknown carpet exists in the target map;

wherein the prior unknown carpet is an unknown carpet added on the target map before the current carpet is detected in the execution process of the target task.

3. The carpet information processing method according to claim 2, wherein the merging unknown carpets whose positional relationship satisfies a first target requirement, obtaining carpet information of at least one target merged unknown carpet after merging, and adding the carpet information of the at least one target merged unknown carpet to a target map, comprises:

when a target unknown carpet exists in the target map, merging the current carpet and the target unknown carpet to obtain carpet information of a temporary merged unknown carpet corresponding to the current carpet;

adding the carpet information of the temporary merge unknown carpet to the target map and deleting the carpet information of the target unknown carpet in the target map;

Wherein the target unknown carpeting is a prior unknown carpeting whose positional relationship with the current carpeting satisfies the first target requirement, the at least one target merge unknown carpeting includes target merge unknown carpeting in one-to-one correspondence with one or more sets of unknown carpeting, the positional relationship between unknown carpeting in each set of unknown carpeting satisfies the first target requirement, and the target merge unknown carpeting corresponding to each set of unknown carpeting is a temporary merge unknown carpeting corresponding to the last detected unknown carpet in the set of unknown carpeting.

4. The carpet information processing method according to claim 3, wherein the adding of the carpet information of the unknown carpet to the target map for an unknown carpet whose positional relationship with other unknown carpets does not satisfy the first target requirement includes:

the carpet information of the current carpet is added to the target map when there is no prior unknown carpet or there is a prior unknown carpet but no target unknown carpet in the target map.

5. The carpet information processing method according to claim 1, wherein the target map is a map of at least two preset areas; the carpet information also comprises attribution information of the corresponding carpet; the attribution information is used for indicating attribution areas corresponding to the corresponding carpets, the attribution areas are one or more preset areas in the at least two preset areas, and the operation of cleaning any carpet by the cleaning robot is executed under the condition that the cleaning robot cleans the attribution area corresponding to the carpet; the at least one target merging unknown carpet comprises target merging unknown carpets which are in one-to-one correspondence with one or more groups of unknown carpets, and the position relationship between the unknown carpets in each group of unknown carpets meets the first target requirement;

Combining the unknown carpets with the position relationship meeting the first target requirement to obtain carpet information of at least one target combined unknown carpet after combination, wherein the method comprises the following steps:

for any one of the one or more unknown carpet sets,

merging the areas occupied by the unknown carpets in the unknown carpets based on the position information of the unknown carpets in the unknown carpets, and determining the position information of the target merged unknown carpets corresponding to the unknown carpets;

6. The carpet information processing method according to claim 1, wherein the target map is a map of at least two preset areas; the carpet information also comprises attribution information of the corresponding carpet; the attribution information is used for indicating attribution areas corresponding to the corresponding carpets, the attribution areas are one or more preset areas in the at least two preset areas, and the operation of cleaning any carpet by the cleaning robot is executed under the condition that the cleaning robot cleans the attribution area corresponding to the carpet; the at least one target merging unknown carpet comprises target merging unknown carpets which are in one-to-one correspondence with one or more groups of unknown carpets, and the position relationship between the unknown carpets in each group of unknown carpets meets the first target requirement;

When the detected current carpet is an unknown carpet, the method further comprises:

and executing a home area determining operation on the current carpet to determine home information of the current carpet.

7. The carpet information processing method according to claim 2, wherein the target map is a map of at least two preset areas; the carpet information also comprises attribution information of the corresponding carpet; the attribution information is used for indicating attribution areas corresponding to the corresponding carpets, the attribution areas are one or more preset areas in the at least two preset areas, and the operation of cleaning any carpet by the cleaning robot is executed under the condition that the cleaning robot cleans the attribution area corresponding to the carpet;

combining the current carpet and the target unknown carpet to obtain carpet information of a temporary combined unknown carpet corresponding to the current carpet, wherein the carpet information comprises:

combining the area occupied by the current carpet and the area occupied by the target unknown carpet based on the position information of the current carpet and the position information of the target unknown carpet, and determining the position information of the temporary combined unknown carpet;

8. The carpet information processing method according to any one of claims 5 to 7, wherein the home zone determination operation includes:

determining a preset area corresponding to the carpet to be determined in the target map based on the position information of the carpet to be determined, wherein the preset area corresponding to the carpet to be determined is a preset area in which at least one part of the carpet to be determined exists;

when the number of preset areas corresponding to the carpet to be determined is at least two,

judging whether the area occupied by the carpet to be determined in the preset area is larger than a first area threshold value or not for each preset area corresponding to the carpet to be determined, and if the area occupied by the carpet to be determined in the preset area is larger than the first area threshold value, determining the preset area as the attribution area corresponding to the carpet to be determined; and/or the number of the groups of groups,

If the occupied area of the carpet to be determined in each corresponding preset area is not larger than the first area threshold value, determining that the preset area with the largest occupied area of the carpet to be determined is the attribution area corresponding to the carpet to be determined;

wherein the carpet to be determined is the carpet for which the home zone determination operation is directed.

9. The carpet information processing method according to any one of claims 1 to 7, wherein the carpet information further includes a cleaning mode for instructing the cleaning robot to perform the cleaning task in a treatment manner for a corresponding carpet, and when the detected current carpet is an unknown carpet, the method further includes:

determining a positional relationship between the current carpet and the known carpet based on the positional information of the current carpet and the positional information of the known carpet in the target map;

determining a cleaning mode of the current carpet based on a cleaning mode of at least one target known carpet when the at least one target known carpet is present in the target map;

wherein the target known carpet represents a known carpet in which a positional relationship with the current carpet in the target map satisfies a second target requirement including carpets intersecting each other;

The at least one target merging unknown carpet comprises target merging unknown carpets which are in one-to-one correspondence with one or more groups of unknown carpets, the position relation among the unknown carpets in each group of unknown carpets meets the first target requirement, and the cleaning mode of the current carpet is used for determining the cleaning mode of the target merging unknown carpets corresponding to the group of unknown carpets where the current carpet is located.

10. The carpet information processing method of claim 9, wherein the determining the cleaning mode of the current carpet based on the cleaning mode of the at least one target known carpet comprises:

determining that the cleaning mode of the current carpet is the cleaning mode of the target known carpet when the number of the target known carpets is one;

where the number of target known carpets is at least two,

if the cleaning modes of all the target known carpets are the same, determining that the current cleaning mode of the carpets is the cleaning mode of all the target known carpets;

if the cleaning modes of the carpets known by the targets are different, outputting reminding information corresponding to the current carpets and/or determining that the cleaning mode of the current carpets is a first default cleaning mode.

11. The carpet information processing method according to claim 9, characterized in that the method further comprises:

and when the target known carpet does not exist in the target map, outputting reminding information corresponding to the current carpet and/or determining that the cleaning mode of the current carpet is a second default cleaning mode.

12. A carpet information processing method according to claim 5 when dependent on claim 3, wherein said merging the current carpet and the target unknown carpet to obtain carpet information of a temporarily merged unknown carpet corresponding to the current carpet comprises:

combining the area occupied by the current carpet and the area occupied by the target unknown carpet based on the position information of the current carpet and the position information of the target unknown carpet, and determining the position information of the temporary combined unknown carpet corresponding to the current carpet;

determining that the cleaning mode of the current carpet is the cleaning mode of the temporary combined unknown carpet corresponding to the current carpet when the cleaning mode of the current carpet is the same as the cleaning mode of the target unknown carpet;

13. The carpet information processing method according to any one of claims 1 to 7, wherein the target task is the cleaning task, the method further comprising:

before the execution of the cleaning task in question,

acquiring area identification information of an area to be cleaned;

acquiring a global map;

generating the target map corresponding to the cleaning task based on the region identification information of the region to be cleaned and the global map;

preloading the position information of at least part of carpets meeting preset conditions in the global map into the target map;

determining attribution information of a carpet to be cleaned in the at least part of carpets based on the area identification information of the area to be cleaned, and adding the attribution information of the carpet to be cleaned into the target map;

the global map is a map of one or more preset areas, the one or more preset areas comprise the areas to be cleaned, the attribution information is used for indicating attribution areas corresponding to the corresponding carpets, the attribution areas are at least one preset area in the one or more preset areas, and the operation of cleaning any carpet by the cleaning robot is executed under the condition that the cleaning robot cleans the attribution areas corresponding to the carpets.

14. The carpet information processing method according to claim 13, wherein,

the preset conditions include: the carpet has an area greater than a second area threshold;

the preset conditions include: the carpet cleaning mode is a carpet evasion mode;

the preset conditions include: the area of the carpet is greater than a second area threshold, and/or the cleaning mode of the carpet is an evasion carpet mode;

the carpet avoidance mode is used for indicating the cleaning robot to avoid the position of the corresponding carpet in the running process when the cleaning robot executes the cleaning task.

15. The carpet information processing method according to claim 13, wherein preloading the carpet information of at least part of the carpets satisfying a preset requirement in the global map into the target map includes:

and preloading carpet information of carpets which meet the preset conditions in the global map and intersect with a movement path when the cleaning robot executes the cleaning task into the target map.

16. The carpet information processing method according to any one of claims 1 to 7, further comprising:

acquiring map point type information detected for each map point in at least part of map points in the target map in the execution process of the target task;

For each known carpet in the target map, judging whether the known carpet is shifted or not based on map point type information corresponding to map points at the position of the known carpet;

deleting carpet information of any known carpet from the target map when the known carpet is shifted;

wherein the map point type information is used for indicating whether the corresponding map point belongs to a carpet.

17. The carpet information processing method according to claim 16, wherein the determining whether the known carpet is shifted based on map point type information corresponding to map points at the location of the known carpet comprises:

judging whether the ratio is larger than a ratio threshold;

when the ratio is greater than a ratio threshold, the known carpet is determined to be shifted.

18. A cleaning method, wherein the cleaning task includes a first cleaning sub-task that cleans a non-carpet area, which is an area outside of a carpet area where a carpet is located, and a second cleaning sub-task that cleans a carpet area, wherein the cleaning method includes:

The carpet information handling method according to any one of claims 1 to 17, wherein the non-carpet area is an area located outside the carpet area where the carpet is located, during execution of the first cleaning subtask;

in the execution process of the second cleaning subtask, performing carpet cleaning operation by utilizing the target map;

the cleaning tasks comprise the first cleaning subtask and the second cleaning subtask, and the target task is the first cleaning subtask.

19. A cleaning robot, comprising: a processor and a memory in which a computer program is stored, the processor executing the computer program to implement the carpet information handling method of any one of claims 1 to 17 or the cleaning method of claim 18.

20. A computer-readable storage medium, characterized in that a computer program/instruction is stored, which, when being executed by a processor, implements the carpet information processing method according to any one of claims 1 to 17 or the cleaning method according to claim 18.