CN116250765A

CN116250765A - Dirty cleaning method

Info

Publication number: CN116250765A
Application number: CN202310208746.0A
Authority: CN
Inventors: 朱泽春; 孙安临; 赵霄汉
Original assignee: Joyoung Co Ltd
Current assignee: Joyoung Co Ltd
Priority date: 2023-03-01
Filing date: 2023-03-01
Publication date: 2023-06-13

Abstract

The application provides a dirty cleaning method, is applied to cleaning robot, dirty cleaning method includes: acquiring an area to be cleaned, and controlling the cleaning robot to execute a cleaning strategy of a first path mode to clean the area to be cleaned; if dirt exists in the to-be-cleaned area in the cleaning process, controlling the cleaning robot to execute a cleaning strategy of a second path mode to clean the dirt; judging whether the area to be cleaned is clean or not when the dirt is clean; and if the area to be cleaned is not cleaned, controlling the cleaning robot to continuously execute the cleaning strategy of the first path mode to clean the area to be cleaned. The special cleaning strategy is adopted in the application to clean the dirt, so that the cleaning effect on the dirt is improved, the dirt residue phenomenon after the dirt is cleaned is avoided, and the cleaning cleanliness of the cleaning robot and the use experience of a user are improved.

Description

Dirty cleaning method

Technical Field

The application relates to the technical field of robots, in particular to a dirt cleaning method.

Background

With the improvement of living standard of people, more and more cleaning robots are applied to daily life of people. The cleaning robot can replace a user to finish the cleaning work of the ground in the home, and the cleaning burden of the user is reduced. Illustratively, the cleaning robot may include a floor sweeping robot, a mopping robot, a sweeping and mopping robot, and the like.

However, in the prior art, when the cleaning robot cleans dirt such as dust and liquid on the ground, a corresponding cleaning strategy is not formulated, so that the conditions of incomplete cleaning and residual dirt are often caused, the cleaning effect is poor, and the use experience of a user is greatly influenced.

Disclosure of Invention

An object of the embodiment of the application is to provide a dirty cleaning method, adopt specific cleaning strategy to clean dirty in this application, promoted the clean effect to dirty, avoided appearing dirty residual phenomenon behind clean dirty, promoted cleaning robot's clean cleanliness factor and user's use experience.

The application provides a dirty cleaning method, is applied to cleaning robot, dirty cleaning method includes:

acquiring an area to be cleaned, and controlling the cleaning robot to execute a cleaning strategy of a first path mode to clean the area to be cleaned;

if dirt exists in the to-be-cleaned area in the cleaning process, controlling the cleaning robot to execute a cleaning strategy of a second path mode to clean the dirt;

judging whether the area to be cleaned is clean or not when the dirt is clean;

and if the area to be cleaned is not cleaned, controlling the cleaning robot to continuously execute the cleaning strategy of the first path mode to clean the area to be cleaned.

In an embodiment, before the cleaning robot is controlled to perform the cleaning strategy of the second path mode to clean the dirt, the dirt cleaning method further comprises:

determining a size parameter of the dirt, and determining a cleaning strategy of the second path mode according to the size parameter; the size parameter indicates a dirty area that is positively correlated with the cleaning intensity indicated by the cleaning strategy of the second path mode.

judging whether a target distance between the dirt and the cleaning robot is within a preset range;

if the target distance is within the preset range, controlling the cleaning robot to execute a cleaning strategy of a second path mode;

and if the target distance is not in the preset range, controlling the cleaning robot to execute the cleaning strategy of the first path mode.

In one embodiment, the cleaning robot is provided with an image pickup device, and the image pickup device is used for picking up images around the cleaning robot;

determining a dimensional parameter of the soil, comprising:

determining the number of pixels of a dirty region in a target image shot by an imaging device; wherein the dirty region is a region covered by dirt in the region to be cleaned;

And determining the size parameter of the dirt according to the pixel number of the dirt area and the total pixel number of the target image.

In one embodiment, determining the number of pixels of a dirty region in a target image captured by an imaging device includes:

determining position information of a dirty region in a target image;

acquiring edge information of a dirty area according to the position information;

based on the edge information, the number of pixels of the dirty region in the target image is calculated.

In one embodiment, determining a cleaning strategy for the second path mode based on the dimension parameter comprises:

if the size parameter is smaller than the first threshold value, determining that the cleaning strategy of the second path mode is a linear cleaning strategy;

if the size parameter is greater than the first threshold value, determining that the cleaning strategy of the second path mode is a zigzag cleaning strategy or a spiral cleaning strategy _。

In an embodiment, when the cleaning strategy of the second path mode is a linear cleaning strategy, controlling the cleaning robot to execute the cleaning strategy of the second path mode to clean the dirt includes:

generating a linear cleaning path, and controlling the cleaning robot to reciprocate according to the linear cleaning path to clean dirt;

when the cleaning strategy of the second path mode is a zigzag cleaning strategy, controlling the cleaning robot to execute the cleaning strategy of the second path mode to clean dirt, comprising:

Generating a back-shaped cleaning path, and controlling the cleaning robot to sequentially travel from outside to inside according to the mouth-shaped cleaning path to clean dirt;

when the cleaning strategy of the second path mode is a spiral cleaning strategy, controlling the cleaning robot to execute the cleaning strategy of the second path mode to clean dirt, comprising:

a spiral cleaning path is generated, and the cleaning robot is controlled to sequentially travel along the circular cleaning path from outside to inside to clean dirt.

In one embodiment, the method of cleaning soil further comprises:

when the dirt is cleaned, the size parameter of the dirt is calculated, and whether the dirt is cleaned or not is determined according to the calculation result.

In one embodiment, the cleaning robot is provided with a cleaning device, and the cleaning device is used for cleaning an area to be cleaned;

the soil cleaning method further comprises:

when the dirt is cleaned, if the triggering condition is met, returning to the base station to clean the cleaning device;

when the base station finishes cleaning the cleaning device, controlling the cleaning robot to return to the dirty area; wherein the dirty region is a region covered by dirt in the region to be cleaned;

judging whether the dirt is cleaned;

if the dirt is cleaned, judging whether the area to be cleaned is clean;

If the dirt is not cleaned, continuing to clean the dirt area.

In one embodiment, the cleaning robot is provided with a laser emitting device and a Raman light receiving device, wherein the laser emitting device is used for emitting laser signals, and the Raman light receiving device is used for receiving the laser signals reflected by the obstacle;

the method for cleaning the dirt before detecting the dirt in the area to be cleaned in the cleaning process further comprises the following steps:

and processing the laser signal received by the Raman light receiving device to generate a Raman spectrum, and judging whether the area to be cleaned is polluted or not according to the Raman spectrum.

In the scheme, the cleaning robot executes the cleaning strategy of the first path mode to clean the area to be cleaned, detects whether dirt exists in the area to be cleaned in the execution process, and if the dirt exists in the area to be cleaned, the cleaning robot executes the cleaning strategy of the second path mode to clean the dirt. From this, adopt specific cleaning strategy to clean the dirty in this application, promoted the clean effect to the dirty, avoided appearing dirty residual phenomenon after cleaning the dirty, promoted cleaning robot's clean cleanliness factor and user's use experience.

In an embodiment, the cleaning robot in the application may further select a cleaning strategy according to the size of the dirty area; if the dirt area is large, a cleaning strategy with large cleaning strength is selected to clean the dirt; if the dirt area is smaller, a cleaning strategy with smaller cleaning strength can be selected to clean the dirt, and the cleaning efficiency of the dirt is improved while the cleaning effect is ensured.

In addition, the cleaning strategy can be selected according to the shape of the dirt, so that the best cleaning effect is achieved by utilizing the shortest cleaning path, and the cleaning efficiency of the cleaning robot is greatly improved while the cleaning effect is ensured.

In the prior art, the dirt can be identified by adopting a visual navigation mode, however, under the influence of light, the identification accuracy of the visual navigation mode on the dirt and other ground-attached obstacles is lower, and the identification effect is poor. Therefore, in an embodiment, the raman spectrum is adopted to identify the dirt, so that the accuracy of identifying the dirt is improved, and the effect of identifying the dirt is ensured; the condition of incomplete dirt cleaning is fully avoided.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly explain the drawings that are required to be used in the embodiments of the present application.

Fig. 1 is a schematic structural view of a cleaning robot according to an embodiment of the present application;

FIG. 2 is a schematic flow chart of a method for cleaning dirt according to a first embodiment of the present application;

fig. 3 is a schematic structural view of a cleaning robot according to another embodiment of the present application;

FIG. 4 is a schematic flow chart of determining a size parameter of a dirt according to an embodiment of the present application;

FIG. 5 is a schematic diagram of a cleaning robot according to an embodiment of the present application for cleaning dirt according to a linear cleaning strategy;

FIG. 6 is a schematic diagram of a cleaning robot according to an embodiment of the present application for cleaning dirt according to a zigzag cleaning strategy;

fig. 7 is a schematic flow chart of a method for cleaning dirt according to a second embodiment of the present application;

fig. 8 is a schematic view of a cleaning robot according to an embodiment of the present application for cleaning an area to be cleaned.

Reference numerals:

1-a control module; 10-buses; 11-a processor; 12-memory; 2-a camera device; 3-a laser emitting device; a 4-Raman light receiving device; 100-cleaning robot.

Detailed Description

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

Like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.

Referring to fig. 1, a schematic structural diagram of a cleaning robot 100 according to an embodiment of the disclosure is shown. As shown in fig. 1, the cleaning robot 100 includes a control module 1; wherein, the control module 1 in the present application includes: at least one processor 11 and a memory 12, one processor 11 being exemplified in fig. 2. The processor 11 and the memory 12 are connected by a bus 10, and the memory 12 stores instructions executable by the processor 11, which are executed by the processor 11, so that the control module 1 can execute all or part of the flow of the method in the embodiments described below. Illustratively, the cleaning robot 100 in the present application may be a sweeping robot, a mopping robot, or a sweeping and mopping robot, etc. The cleaning robot 100 may be provided with a cleaning device such as a mop and a brush for cleaning the cleaning area.

The Memory 12 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as static random access Memory (Static Random Access Memory, SRAM), electrically erasable Programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), erasable Programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), programmable Read-Only Memory (PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.

The present application also provides a computer readable storage medium storing a computer program executable by the processor 11 to perform the soil cleaning method provided herein.

Fig. 2 is a schematic flow chart of a method for cleaning dirt according to an embodiment of the disclosure. As shown in fig. 2, the soil cleaning method in the present application includes the following steps S210 to S230.

Step S210: and acquiring the area to be cleaned, and controlling the cleaning robot to execute a cleaning strategy of a first path mode to clean the area to be cleaned.

Wherein the area to be cleaned is an area where the cleaning robot 100 performs a cleaning task. Specifically, the area to be cleaned may be a floor area in the user's home. Illustratively, the area to be cleaned may be a combination of one or more of a living room floor, a kitchen floor, a study room floor, a restroom floor, and a bedroom floor. The cleaning strategy of the first path mode refers to a cleaning logic in which the cleaning robot cleans the area to be cleaned.

In the step, when the cleaning condition is met, the control module can acquire the area to be cleaned, and control the cleaning robot to clean the area to be cleaned according to the cleaning strategy of the first path mode according to the acquisition result. Specifically, when the control module controls the cleaning robot to clean the area to be cleaned according to the cleaning strategy of the first path mode, the first cleaning path can be generated first, and then the cleaning robot is controlled to travel according to the first cleaning path after the first cleaning path is generated to clean the area to be cleaned. Illustratively, the first cleaning path may be an arcuate cleaning path or the like.

On the one hand, an application program for controlling the cleaning robot 100 may be installed on an application terminal such as a mobile phone, and when the cleaning robot 100 is required to clean an area to be cleaned, a user may send a cleaning instruction to the cleaning robot 100 through the application program, and when the control module 1 receives the cleaning instruction, the cleaning robot 100 is controlled to clean the area to be cleaned. In this case, the cleaning condition is that the control module 1 receives the above-described cleaning instruction, and at the same time, the control module acquires the area information of the area to be cleaned from the cleaning instruction. On the other hand, the user may set a timed cleaning task for the cleaning robot 100, and when the time reaches the set time of the timed cleaning task, the control module 1 controls the cleaning robot 100 to clean the area to be cleaned. In this case, the cleaning condition is a set time when the time reaches the cleaning task, and the control module acquires the area information of the area to be cleaned from the timed cleaning task.

Step S220: and if the dirt exists in the area to be cleaned in the cleaning process, controlling the cleaning robot to execute a cleaning strategy of a second path mode to clean the dirt.

Wherein, the dirt can be liquid dirt such as greasy dirt; the dirt can also be solid dirt such as food residues; the dirt may also be semisolid dirt such as porridge. The second path mode cleaning strategy refers to the cleaning logic that the cleaning robot is actually cleaning the soil.

In the step, when the control module cleans the area to be cleaned according to the cleaning strategy of the first path mode, whether dirt exists in the area to be cleaned is detected in real time. If the control module detects that the dirt exists in the area to be cleaned, the cleaning robot is controlled to switch from the cleaning strategy of the first path mode to the cleaning strategy of the second path mode, and after the switching is successful, the cleaning robot is controlled to clean the dirt according to the cleaning strategy of the second path mode. Specifically, when the control module controls the cleaning robot to clean the dirt according to the cleaning strategy of the second path mode, the second cleaning path can be generated first, and then the cleaning robot is controlled to travel according to the second cleaning path after the second cleaning path is generated to clean the dirt. Wherein the second cleaning path is different from the first cleaning path described above.

Step S230: judging whether the area to be cleaned is clean or not when the dirt is clean.

In the step, when the cleaning robot cleans the dirt, if the control module detects that the dirt is cleaned, whether the area to be cleaned is clean is judged in real time. If the judging result indicates that the area to be cleaned is cleaned, the control module can send out warning information to prompt a user that the cleaning robot has completed the cleaning work of the area to be cleaned; meanwhile, the control module can control the cleaning robot to return to the base station, and the base station charges, washes, adds water and the like to the cleaning robot. The warning information may be vibration, voice broadcast, text display, etc.

Step S240: and if the area to be cleaned is not cleaned, controlling the cleaning robot to continuously execute the cleaning strategy of the first path mode to clean the area to be cleaned.

In the step, when the cleaning robot finishes cleaning the dirt, if the control module detects that the area to be cleaned is not cleaned, the cleaning robot is controlled to switch from the cleaning strategy of the second path mode to the cleaning strategy of the first path mode, and after the switching is successful, the cleaning robot is controlled to continuously clean the area to be cleaned according to the cleaning strategy of the first path mode. The cleaning robot cleans an area which is not cleaned by the cleaning robot in the area to be cleaned after the cleaning strategy is switched.

Through the above-mentioned content can see, adopt specific cleaning strategy to clean the dirty in this application, promoted the clean effect to the dirty, avoid appearing dirty residual phenomenon after clean the dirty, promoted cleaning robot's clean cleanliness factor and user's use experience.

In one embodiment, the control module further performs the following steps when detecting the presence of dirt in the area to be cleaned: and determining a size parameter of the dirt, and determining a cleaning strategy of the second path mode according to the size parameter.

Wherein the size parameter of the soil can reflect the area size of the soil area; if the area of the dirty area is large, the corresponding dirty size parameter is larger; if the area of the dirty region is small, the corresponding dirty size parameter will also be smaller. The cleaning robot is provided with a plurality of cleaning strategies, and the cleaning strength of each cleaning strategy is different; the cleaning strength can be reflected by factors such as cleaning time, cleaning speed, cleaning frequency, downward pressure of a cleaning device, cleaning turning radius and the like; a cleaning strategy with stronger cleaning strength, longer cleaning time, slower cleaning speed, faster cleaning frequency, greater downforce of the cleaning device, and greater cleaning radius of gyration. The size parameter of the soil indicates a soil area that is positively correlated with the cleaning intensity indicated by the cleaning strategy of the second path mode.

In this embodiment, when the control module detects that the dirt exists in the area to be cleaned, the control module may first determine a size parameter of the dirt, then select a cleaning policy corresponding to the cleaning strength according to the size parameter of the dirt as a cleaning policy of the second path mode, and after the selection is successful, the control module controls the cleaning robot to clean the dirt according to the cleaning policy of the second path mode. Specifically, after determining the size parameter of the dirt, the area size of the dirt area is correspondingly determined; at this time, the control module 1 may select a cleaning strategy of the second path mode corresponding to the cleaning intensity according to the area size of the dirty region. Specifically, if the area of the dirty region is relatively large, a cleaning strategy with stronger cleaning strength can be selected to clean the dirty; if the area of the dirty region is smaller, a cleaning strategy with common cleaning strength can be selected to clean the dirty.

In this embodiment, a plurality of cleaning strategies with different cleaning intensities are formulated for the cleaning robot, and the cleaning robot 100 can select the cleaning strategy with the corresponding cleaning intensity according to the area of the dirty region to clean the dirty; if the area is larger, a cleaning strategy with larger cleaning strength is selected to clean the dirt; if the area is smaller, a cleaning strategy with smaller cleaning strength can be selected to clean the dirt, so that the cleaning effect on the dirt is fully ensured, and the phenomenon of dirt remaining in the area to be cleaned after cleaning is avoided. Meanwhile, in the application, when the area is smaller, a cleaning strategy with smaller cleaning strength is adopted, so that the cleaning time for dirt is reduced while the cleaning effect is ensured, and the cleaning efficiency for the dirt is improved.

It is noted that the dirty area may be a two-point connecting line with the largest distance between the identified dirty outer edges, and the area covered by a circle with the diameter formed by the two-point connecting line; or the two points can be used as the areas covered by the rectangle formed by the diagonal points; or may be the area actually covered by the soil identified in the area to be cleaned; wherein the first two cases are equivalent models of the dirty region.

Fig. 3 is a schematic structural diagram of a cleaning robot 100 according to another embodiment of the disclosure. As shown in fig. 3, the cleaning robot 100 in the present application further includes an image pickup device 2, a laser emitting device 3, and a raman light receiving device; as shown in fig. 3, the image pickup device 2, the laser emitting device 3 and the raman light receiving device 4 are connected to the control module 1, and the image pickup device 2 is used for picking up an image around the cleaning robot 100 and transmitting the image to the control module 1; the control module 1 is configured to determine a size parameter of the dirt based on the image captured by the image capturing device 2. The image pickup apparatus 2 may be, for example, a grayscale camera, an HLS camera, an RGB camera, or the like. The laser emitting device 3 is used for emitting laser signals under the control of the control module 1, and the Raman light receiving device 4 is used for receiving the laser signals reflected by the obstacle and sending the laser signals reflected by the obstacle to the control module 1; the control module 1 is configured to process the laser signal received by the raman light receiving device 4 to generate a raman spectrum, and determine whether there is dirt in the area to be cleaned according to the raman spectrum.

In one embodiment, the control module 1 may determine whether there is soil in the area to be cleaned by performing the following steps: the laser signal received by the raman light receiving device 4 is processed to generate a raman spectrum, and whether or not contamination exists in the cleaning region is judged according to the raman spectrum.

In the present embodiment, the control module 1 controls the laser emitting device 3 to emit a laser signal into the surrounding environment of the cleaning robot 100 when the cleaning robot 100 cleans an area to be cleaned. Then, an obstacle located in the surrounding of the cleaning robot 100 reflects the laser signal to the raman light receiving device 4. Further, the raman light receiving device 4 sends the received laser signal reflected by the obstacle to the control module 1, and the control module 1 processes the laser signal reflected by the obstacle to generate a raman spectrum, and determines whether there is dirt in the area to be cleaned according to the raman spectrum.

In the prior art, the cleaning robot 100 detects the obstacle in the following two ways, namely, in the laser navigation way, but in the way, the layout of the laser sensor is limited, the cleaning robot 100 easily generates a detection blind area, and the acquired surrounding environment information is less, so that the detection information of the obstacle cannot be accurately acquired. The other is to adopt a visual navigation mode, namely simulating human vision, collect environmental information by carrying the camera device 2, and further obtain the position, the direction and other information of the cleaning robot 100 in space according to the environmental information, so as to realize the identification and navigation of the surrounding environment. In terms of working principle, visual navigation can acquire massive and rich texture information, and has strong scene recognition capability. The visual navigation processes the two-dimensional environment information acquired by the camera device 2 through an algorithm to generate a three-dimensional environment map; the three-dimensional environment map has rich semantic information, so that the distance between the cleaning robot 100 and the obstacle can be calculated, the volume and attribute information of the obstacle can be calculated, and sufficient preconditions are provided for realizing intelligent obstacle avoidance and interaction. However, the light has a large influence on the visual navigation system, and the visual navigation system has low recognition accuracy and poor recognition effect on the ground-adhering obstacles such as dirt and the like under the influence of the light. It can be seen that the recognition accuracy of the dirt is low in the prior art, the recognition effect is poor, and thus the cleaning robot 100 cannot thoroughly clean the dirt.

However, each substance emits unique Raman light, and the spectral lines of the Raman spectra of different substances are greatly different, so that dirt such as liquid, dust and the like can be accurately identified according to the fluctuation condition of the spectral lines in the Raman spectra. Therefore, it can be seen that when the raman spectrum is adopted to identify the dirt in the embodiment, the accuracy of identifying the dirt is improved and the effect of identifying the dirt is ensured; the occurrence of incomplete cleaning of dirt by the cleaning robot 100 is sufficiently avoided. In addition, in the present embodiment, the raman light receiving device 4 and the image pickup device 2 recognize dirt at the same time, but only when the raman light receiving device 4 detects that there is liquid or dust dirt in front, the result of detection by the image pickup device 2 is valid; therefore, it can be seen that when the raman spectrum mode is adopted to perform the dirt identification in this embodiment, the false detection of the dirt caused by the interference of the light of the image pickup device 2 is eliminated, the identification defect of the image pickup device 2 is made up, and the accuracy and the effect of the dirt identification are fully ensured.

As shown in fig. 4, a flow chart for determining a size parameter of the dirt is provided in an embodiment of the present application. Specifically, the control module 1 may determine the size parameter of the soil by performing the following steps S310 to S320.

Step S310: the number of pixels of the dirty region in the target image captured by the image capturing apparatus 2 is determined.

Wherein the camera device 2 is mounted on the cleaning robot 100 at a certain angle; the target image is obtained by shooting the image pickup device 2 under the condition of a certain horizontal distance from the dirty region and a certain height from the dirty region; the target image is an image with a dirty region captured by the imaging device 2.

In this step, when determining that there is dirt in the area to be cleaned according to raman spectrum, the control module 1 may calculate a size parameter of the dirt according to the target image. Specifically, the control module 1 may determine the number of pixels of the dirty region in the target image first, and then determine the size parameter of the dirty according to the number of pixels of the dirty region in the target image. Specifically, the control module 1 may determine the number of pixels of the dirty region in the target image in the following manner.

(1) And preprocessing the target image.

In this step, the target image may be preprocessed before determining the number of pixels of the dirty region in the target image. Specifically, the control module 1 performs brightness processing on each frame of image captured by the image capturing device 2; and then, adopting a mean shift algorithm to perform noise reduction processing on the multi-frame image shot by the camera device 2.

By the measures, the image shot by the image pickup device 2 is preprocessed, so that the influence of interference factors on the calculation accuracy of the dirt size parameters is reduced, and the calculation accuracy of the dirt size parameters is ensured.

(2) Position information of the dirty region in the target image is determined.

In this step, the control module 1 may detect the position of the dirty region in the target image using a Canny edge detection algorithm. Specifically, the method of detecting the position of the dirty region in the target image is to extract edge information in the target image and roughly determine the position of the dirty region in the target image based on the result of the extraction of the edge information. In this case, since there may be other obstacles in the target image in addition to the dirt, the position of the dirt region in the target image can only be roughly determined.

(3) And acquiring edge information of the dirty region according to the position information.

The dirty area is a closed-loop connected area, and the edge information of the dirty area is a closed-loop connected curve graph. In this step, the control module may extract edge information of the dirty region from the target image according to the above-mentioned features of the dirty region. Specifically, the control module 1 can accurately lock the position information of the dirty region from the target image by detecting the connected region. And then after the position of the dirty region is determined, extracting a curve graph connected in a closed loop from the target image, and completing the operation of acquiring the edge information of the dirty region after the extraction is finished. Specifically, the control module 1 may extract edge information of the dirty region using an edge detection function. The edge detection function may be, for example, a FindContours edge detection function.

(4) Based on the edge information, the number of pixels of the dirty region in the target image is calculated.

The number of pixels of the dirty region refers to the number of pixels occupied by the dirty region in the target image.

In this step, the control module 1 extracts edge information of the dirty region from the target image by using the edge detection function, and then calculates the number of pixels of the dirty region in the target image according to the extraction result of the edge information. For example, the control module 1 may calculate the number of pixels occupied by the dirty region in the target image using a Regionprop function.

Step S320: and determining the size parameter of the dirt according to the pixel number of the dirt area and the total pixel number of the target image.

Wherein the size parameter of the smudge refers to the ratio of the number of pixels of the smudge area to the total number of pixels of the target image. The size parameter of the dirt can reflect the area size of the dirt area, and the larger the size parameter of the dirt is, the larger the area of the dirt area is; the smaller the size parameter of the soil, the smaller the area of the soil area.

In this step, after the control module 1 calculates the number of pixels occupied by the dirty region in the target image, the ratio operation can be performed on the number of pixels of the dirty region and the total number of pixels of the target image, and the ratio result is the size parameter of the dirty. Wherein the total number of pixels of the further target image is stored in advance in the control module 1. For example, assuming that the number of pixels of the stained area is 5 and the total number of pixels of the target image is 40, the size parameter of the stain calculated by the control module 1 should be 5/40=0.125=12.5%.

By the measures, the size parameters of the dirt are calculated based on the target image shot by the image pickup device 2, and the calculation mode of the dirt size parameters is simplified while the calculation accuracy of the dirt size parameters is ensured.

In an embodiment, the control module 1 further performs the following steps in case it detects that there is dirt in the area to be cleaned: judging whether a target distance between the dirt and the cleaning robot 100 is within a preset range; if the target distance is within the preset range, controlling the cleaning robot to execute a cleaning strategy of a second path mode; and if the target distance is not in the preset range, controlling the cleaning robot to execute the cleaning strategy of the first path mode. The preset range may be, for example, 10 to 20cm.

In this embodiment, when the cleaning robot cleans the area to be cleaned, the control module 1 determines whether there is dirt in the area to be cleaned in real time according to the raman spectrum transmitted by the raman light receiving device 4. If the control module 1 detects that dirt exists in the area to be cleaned, the distance between the dirt and the cleaning robot 100 is calculated, and whether the distance is within a preset range is judged after the calculation is successful. If the distance is within the preset range, determining a size parameter of the dirt, selecting a cleaning strategy of a second path cleaning mode with corresponding strength according to the size parameter of the dirt, and controlling the cleaning robot to clean the dirt according to the cleaning strategy of the selected second path cleaning mode by the control module after the selection is finished. If the distance is not within the preset range and is greater than the maximum value of the preset range, the cleaning robot 100 is controlled to continuously clean the area to be cleaned according to the cleaning strategy of the first path mode; when the cleaning robot 100 travels to a distance between the cleaning robot 100 and the dirt within the above-mentioned preset range, the cleaning robot 100 is controlled to clean the dirt.

It should be noted that, since the image capturing device 2 is mounted on the cleaning robot 100 at a certain angle, the vertical height and the included angle between the image capturing device 2 and the floor are certain, the distance between the cleaning robot 100 and the dirt can be calculated by means of triangulation, that is, the distance between the cleaning robot 100 and the dirt can be calculated by means of the operation relationship of trigonometric functions.

When calculating the size parameter of the dirt, the number of pixels of the dirt area needs to be calculated from the target image, however, when the cleaning robot 100 is far away from the dirt, there may be a large deformation of the dirt area in the target image captured by the image capturing device 2, in this case, the control module 1 may not accurately calculate the number of pixels of the dirt area, and the accuracy of calculating the dirt size parameter is reduced. Further, when the calculated size parameter precision of the dirt is low, the size of the area of the dirt cannot be accurately determined according to the size parameter of the dirt, so that the selection of a cleaning strategy is inaccurate, the cleaning effect on the dirt is reduced, and the condition that the dirt is not thoroughly cleaned easily occurs. For this reason, in the present embodiment, the size parameter of the dirt is calculated only when the distance between the dirt and the cleaning robot 100 is determined to be within the preset range, and the calculation accuracy of the dirt size parameter is sufficiently ensured. Further, the size of the dirt area can be determined accurately according to the size parameters of the dirt, and the dirt can be cleaned by accurately selecting a corresponding cleaning strategy, so that the cleaning effect of the dirt is improved, and the condition that the dirt is not thoroughly cleaned is fully avoided.

In an embodiment, after calculating the size parameter of the dirt, the control module 1 may determine the cleaning strategy of the second path mode by: if the size parameter of the dirt is smaller than the first threshold value, the control module 1 can use the linear cleaning strategy as the cleaning strategy of the second path mode; if the size parameter of the dirt is greater than the first threshold, the control module 1 may use the back-shaped cleaning strategy or the spiral cleaning strategy as the cleaning strategy of the second path mode. Wherein, the linear cleaning strategy refers to controlling the cleaning robot 100 to travel according to a linear motion path to clean dirt; the back-shaped cleaning strategy refers to controlling the cleaning robot 100 to travel according to a back-shaped motion path so as to clean dirt; the spiral cleaning strategy refers to controlling the cleaning robot 100 to travel along a circular cleaning path with sequentially decreasing radius to clean the dirt. Illustratively, the first threshold may be 7% to 9%.

In this embodiment, after calculating the size parameter of the dirt, the control module 1 may compare the size parameter of the dirt with the first threshold stored therein, and determine a cleaning strategy of the second path mode for actually cleaning the dirt according to the comparison result. Specifically, if the comparison result shows that the size parameter of the dirt is smaller than the first threshold value, which indicates that the detected dirt is a small-area dirt, the linear cleaning strategy is taken as the cleaning strategy of the second path mode. If the comparison result shows that the size parameter of the dirt is larger than the first threshold value, which indicates that the dirt detected by the control module 1 is large-area dirt at the moment, the back-shaped cleaning strategy or the spiral cleaning strategy is used as the cleaning strategy of the second path mode.

In the first aspect, when the comparison result shows that the size parameter of the dirt is greater than the first threshold, the control module 1 may randomly select one cleaning strategy from the zigzag cleaning strategy and the spiral cleaning strategy as the cleaning strategy of the second path mode. In a second aspect, when the comparison result shows that the size parameter of the soil is greater than the first threshold, the control module 1 may determine the cleaning strategy according to the shape of the soil; if the shape of the dirt is close to a circle, taking the spiral cleaning strategy as a cleaning strategy of a second path mode; and if the shape of the dirt is close to a rectangle, taking the back character shape cleaning strategy as the cleaning strategy of the second path mode. In a third aspect, when the comparison result shows that the size parameter of the dirt is greater than the first threshold, the cleaning strategy of the second path mode may be further determined according to the size of the area of the dirt. In this case, the control module 1 also stores a second threshold value, and may further compare the size parameter of the dirt with the second threshold value. If the size parameter of the dirt is found to be larger than the first threshold value and smaller than the second threshold value after comparison, the size of the dirt area is moderate, and the spiral cleaning strategy is used as the cleaning strategy of the second path mode; and if the size parameter of the dirt is larger than the second threshold value after comparison, indicating that the dirt area is larger, taking the back-shaped cleaning strategy as the cleaning strategy of the second path mode.

Through the measures, when the optimal cleaning strategy is selected according to the characteristic parameters to clean the dirt, the best cleaning effect can be achieved by utilizing the shortest cleaning path, and the cleaning efficiency of the cleaning robot 100 is greatly improved while the cleaning effect is ensured. The characteristic parameter may be the size of the area of the dirt, the shape of the dirt, and the like.

The principle of the cleaning robot 100 cleaning dirt according to the cleaning strategy of the second path mode is explained in detail as follows:

(1) When the cleaning strategy of the second path mode is a linear cleaning strategy.

In this embodiment, when the cleaning robot 100 cleans the dirt according to the linear cleaning strategy, the control module 1 may generate the linear cleaning path first, and control the cleaning robot 100 to reciprocate according to the linear cleaning path after generating the linear cleaning path to clean the dirt. Wherein the linear cleaning path passes through the dirty region. For example, as shown in fig. 5, when the control module 1 detects the dirt, the cleaning robot 100 is located at a in the figure, and the control module 1 may plan a cleaning path extending from a to B as shown in fig. 5; and controls the cleaning robot 100 to travel back and forth according to the cleaning path to clean the dirt after the planning is successful. Wherein circles in the figure represent dirt. Specifically, when the cleaning robot 100 travels along the straight cleaning path, the cleaning robot 100 first starts to travel from the starting point a, and during the traveling process, the cleaning robot 100 gradually approaches the dirt, passes through the dirt after a period of time, gradually moves away after passing through the dirt, turns 180 ° away from the cleaning robot 100 when moving away to the point B in fig. 5, and repeats the above procedure with the point B as the starting point after turning around to continue cleaning the dirt. In this way, when the number of reciprocations reaches the set number, it is determined that the dirt is cleaned, and the cleaning robot 100 is controlled to stop executing the linear cleaning strategy. For example, the number of reciprocating movements of the cleaning robot 100 may be 3 to 5.

In another embodiment, the control module 1 calculates the size parameter of the dirt again from the target image photographed by the photographing device 2 every time the cleaning robot 100 reciprocates; if the calculation result shows that the size parameter of the dirt is greater than the third threshold value, which indicates that the dirt is not cleaned, the control module 1 can control the cleaning robot 100 to continue to reciprocate at this time; if the calculation result shows that the size parameter of the dirt is smaller than the third threshold, and the dirt is basically cleaned, the control module 1 may control the cleaning robot 100 to stop executing the linear cleaning strategy. Illustratively, the third threshold may be 0.2% to 0.8%. As shown in fig. 5, the cleaning robot 100 reciprocates once, which means that the cleaning robot 100 travels from point a to point B in fig. 5, then from point B to point a, after which the cleaning robot 100 recalculates the size parameter of the contamination after traveling to point a, and controls the movement of the cleaning robot 100 according to the calculation result.

(2) When the cleaning strategy of the second path mode is a back-font cleaning strategy.

In this embodiment, when the cleaning robot 100 cleans the dirt according to the zigzag cleaning strategy, the control module 1 may generate the zigzag cleaning path; the back-font cleaning path consists of a plurality of mouth-font cleaning paths with sequentially reduced radiuses; and then controls the cleaning robot 100 to sequentially travel the cleaning dirt along the mouth-shaped cleaning path from outside to inside after the cleaning path is generated. Wherein the number of the mouth-shaped cleaning paths is determined by the size of the dirt area and the radius of the cleaning device for cleaning the floor. For example, as shown in fig. 6, a circle represents dirt, when the dirt is cleaned by adopting the back-shaped cleaning strategy, the cleaning robot 100 may generate 3 sequentially smaller-radius mouth-shaped cleaning paths, and after the generation is successful, the cleaning robot 100 is controlled to travel according to the mouth-shaped cleaning paths corresponding to C in fig. 6 to clean the dirt. When the travel of the mouth-shaped cleaning path is completed, the cleaning robot 100 is controlled to move inwards to move on the mouth-shaped cleaning path corresponding to D in fig. 6, and after the movement is successful, the cleaning robot 100 is controlled to travel according to the mouth-shaped cleaning path corresponding to D in fig. 6, so that the dirt is cleaned. After the traveling, the cleaning robot 100 is controlled to travel along the cleaning path corresponding to E in fig. 6. After the traveling is completed, it is determined that the dirt is cleaned, and the cleaning robot 100 is controlled to stop executing the zigzag cleaning strategy.

In another embodiment, the control module 1 calculates the size parameter of the dirt again according to the target image captured by the image capturing device 2 every time the cleaning robot 100 completes one of the mouth-shaped cleaning paths; if the calculation result shows that the size parameter of the dirt is greater than the third threshold value, which indicates that the dirt is not cleaned, the control module 1 may control the cleaning robot 100 to continuously execute the next mouth-shaped cleaning path at this time; if the calculation result shows that the size parameter of the dirt is smaller than the third threshold, and the specification dirt is basically clean, the control module 1 may control the cleaning robot 100 to stop executing the back-shaped cleaning strategy. Illustratively, the third threshold may be 0.2% to 0.8%.

(3) When the target cleaning strategy is a spiral cleaning strategy.

In this embodiment, when the cleaning robot 100 cleans the dirt according to the spiral cleaning strategy, the control module 1 may generate the spiral cleaning path first; the spiral cleaning path consists of a plurality of circular cleaning paths with sequentially reduced radiuses; and then controls the cleaning robot 100 to sequentially travel the cleaning dirt along the circular cleaning path from the outside to the inside after the cleaning path is generated. Wherein the number of circular cleaning paths is determined by the size of the dirty area and the radius of the cleaning device for cleaning the floor.

It is noted that the difference between the spiral cleaning strategy and the zigzag cleaning strategy is that the path expression form is different, and the cleaning path in the spiral cleaning strategy is composed of a plurality of circular cleaning paths with sequentially reduced radii, and whether the cleaning path in the zigzag cleaning strategy is composed of a plurality of square cleaning paths with sequentially reduced radii. Except the above differences, the cleaning logic of the two is basically the same, so that the specific principle of the spiral cleaning strategy is not described in detail in this embodiment, and the detailed principle is explained in the back-shaped cleaning strategy.

In an embodiment, when the dirt is cleaned, the control module 1 may determine whether the area to be cleaned is cleaned; if the judging result shows that the area to be cleaned is not cleaned, the cleaning robot can be controlled to switch from the cleaning strategy of the second path mode to the cleaning strategy of the first path mode, and after the switching is successful, the cleaning robot is controlled to continuously clean the area to be cleaned according to the cleaning strategy of the first path mode. Specifically, after the dirt is cleaned, if the control module detects that the area to be cleaned is not cleaned, the cleaning robot 100 may be controlled to travel to a position where the cleaning strategy of the first path mode is interrupted when the dirt is encountered, and then the cleaning robot 100 is controlled to continue cleaning the area to be cleaned according to the cleaning strategy of the first path mode after the travel is successful.

Note that when the cleaning robot 100 encounters dirt, it stops executing the original cleaning strategy of the first path mode, and instead adopts the cleaning strategy of the second path mode to clean the dirt; therefore, in this embodiment, after the dirt is cleaned, the cleaning robot 100 is controlled to return to the position where the cleaning strategy of the first path mode is interrupted, and the cleaning area is continuously cleaned according to the cleaning strategy of the first path mode after the return.

In an embodiment, as shown in fig. 7, when the control module 1 performs the dirt cleaning method, the following steps S410-S432 are further performed.

Step S410: when the dirt is cleaned, if the triggering condition is met, returning to the base station to clean the cleaning device.

The triggering condition is that the size parameter of the dirt reaches a third threshold when the cleaning robot 100 cleans the dirt with a larger area, or that the cleaning duration of the cleaning robot 100 reaches a preset duration when the cleaning robot 100 cleans the dirt with a larger area. By larger area of fouling is meant that the size parameter of the fouling is larger than the first threshold mentioned above. Specifically, the calculation method of the size parameter of the dirt is the same as that of the foregoing embodiment, and will not be described herein. Illustratively, the third threshold may be 0.2% to 0.8%; the preset duration may be 4-10 s.

In this step, when the cleaning robot 100 cleans the dirt, if the control module 1 detects that the size parameter of the dirt reaches the third threshold value, or when the cleaning duration of the cleaning robot 100 reaches the preset duration, the control module 1 may control the cleaning robot 100 to return to the base station, and then the base station cleans the cleaning device. Specifically, the cleaning device is disposed on the cleaning robot 100 in a liftable manner, in this embodiment, before the cleaning robot 100 returns to the base station, the control module 1 may lift the cleaning device first, plan a shortest travel path from the current position of the cleaning robot 100 to the base station after the cleaning robot is lifted, and control the cleaning robot 100 to travel back to the base station according to the shortest travel path after the planning is successful.

Step S420: when the cleaning device is completely cleaned by the base station, the cleaning robot 100 is controlled to return to the dirty region.

The dirty area is an area where target dirt is located; the target dirt is a dirt that the cleaning robot 100 cleans when performing the above-described step S210 to step S240.

In this step, after the cleaning device is cleaned by the base station, the control module 1 controls the cleaning robot 100 to return to the dirty region. Specifically, the control module 1 may control the cleaning robot 100 to travel back to the dirty region according to the shortest travel path planned in the above step S410, and control the cleaning robot 100 to stop traveling when the distance between the cleaning robot 100 and the dirty is within the preset range. The preset range may be, for example, 10 to 20cm.

Step S430: and judging whether the dirty area is cleaned.

In this step, when the control module 1 detects that the cleaning robot 100 stops traveling, the control module 1 may secondarily detect whether the dirt in the dirt area is cleaned. Specifically, the control module 1 may determine whether the dirt is cleaned by calculating a size parameter of the dirt. The calculation method of the dirt size parameter is detailed in the above embodiments, and is not repeated here. If the size parameter of the dirt is larger than the third threshold value, the dirt is not cleaned; if the size parameter of the soil is less than the third threshold, it is indicated that the soil has been cleaned.

Step S431: if the dirt is cleaned, judging whether the area to be cleaned is cleaned.

In this embodiment, if the control module 1 detects that the dirt is cleaned, it can determine whether the cleaning area is cleaned. And if the control module detects that the area to be cleaned is cleaned, controlling the cleaning robot to return to the base station. And if the control module detects that the area to be cleaned is not cleaned, the cleaning robot is controlled to continuously clean the area to be cleaned according to the cleaning strategy of the first path mode.

Note that, in this embodiment, if the cleaning of the area to be cleaned needs to be continued after the secondary detection of the dirt, the control module 1 may control the cleaning robot 100 to return to the position where the cleaning policy of the first path mode is interrupted, and continue to clean the area to be cleaned according to the cleaning policy of the first path mode after the return, so as to form the closed loop control logic.

Step S432: if the dirt is not cleaned, continuing to clean the dirt area.

In this step, if the control module 1 finds that the dirt is not cleaned after the second detection, the cleaning robot 100 can be controlled to continue cleaning the dirt area. Specifically, when it is detected that the dirt is not cleaned, the control module 1 may calculate a size parameter of the dirt, select a corresponding cleaning policy of the second path mode according to a calculation result of the size parameter, and then control the cleaning robot 100 to clean the dirt for the second time according to the cleaning policy of the second path mode after the selection is successful, and details of a cleaning principle of the dirt are described in the foregoing embodiments, which are not described herein again. After the dirty area is cleaned, judging whether the area to be cleaned is cleaned, and executing corresponding cleaning logic according to the judging result, wherein the specific cleaning logic is the same as that described above, and the detailed description is omitted.

If the dirt area is relatively large, the cleaning robot 100 may adhere more dirt to the cleaning device after cleaning for a period of time, and in this case, the cleaning device may not ensure a good cleaning effect. Therefore, in this embodiment, when the control module 1 detects that the cleaning duration of the cleaning robot 100 reaches the preset duration, or when the control module 1 detects that the size parameter of the dirty region reaches the third threshold, the cleaning robot 100 is controlled to return to the base station, and the base station cleans the cleaning device, so that the cleaning effect of the cleaning robot 100 on the region to be cleaned in the subsequent cleaning is fully ensured, and the dirty of the cleaning device is prevented from polluting other regions of the region to be cleaned. In addition, after returning to the base station, the control module 1 controls the cleaning robot 100 to return to the dirty region, and secondarily recognizes whether the dirty is cleaned after the return. If the dirt is detected to be not cleaned, the dirt is cleaned for the second time, so that the phenomenon of dirt residue in the area to be cleaned after cleaning is fully avoided, and the cleaning effect of the dirt is fully ensured.

The following describes in detail the method of cleaning dirt in the present application, taking fig. 8 as an example:

the control module firstly acquires an area to be cleaned, and controls the cleaning robot to clean the area to be cleaned according to a cleaning strategy of a first path mode after the area to be cleaned is acquired successfully. Specifically, as shown in fig. 8, before the cleaning robot 100 cleans the area to be cleaned, the control module 1 generates an arcuate cleaning path as shown in fig. 8, and the control module 1 controls the cleaning robot 100 to travel along the arcuate cleaning path with the point F as the starting point to clean the area to be cleaned. Wherein the arrow in fig. 8 indicates the movement direction of the cleaning robot 100. During cleaning, the control module 1 determines whether the cleaning area is dirty or not according to the reflected light signal transmitted by the raman light receiving device 4. When the cleaning robot 100 requests to go to the point M, the control module 1 detects that the dirt K exists in the area to be cleaned. And then calculating the distance between the dirt K and the cleaning robot 100, and after calculation, controlling the cleaning robot 100 to continue to travel according to the arcuate cleaning path by the control module 1 when detecting that the distance between the cleaning robot 100 and the dirt is not in the preset range. When traveling to the point G, the distance between the cleaning robot 100 and the contamination K is within a preset range, and at this time, the cleaning robot 100 determines a size parameter of the contamination from the target image captured by the image capturing device 2. Further, after the size parameter of the dirt is determined, the dirt K is determined to be a small-area dirt according to the size parameter of the dirt, and the cleaning robot 100 is controlled to clean the dirt K according to the linear cleaning strategy. Judging whether the to-be-cleaned area is cleaned or not when the dirt is cleaned, detecting that the to-be-cleaned area is not cleaned, and controlling the cleaning robot to switch to a cleaning strategy of a first path mode to continuously clean the to-be-cleaned area. Specifically, at the time of cleaning, the cleaning robot 100 is controlled to return to the point G, and after the return, the cleaning robot 100 is controlled to continue to travel along the arcuate cleaning path to clean the cleaning region.

As the cleaning process proceeds, when the cleaning robot 100 travels to the point V, the control module 1 detects the presence of the dirt J in the area to be cleaned. And then calculating the distance between the dirt J and the cleaning robot 100, and after calculation, controlling the cleaning robot 100 to continuously clean the area to be cleaned according to a cleaning strategy of a first path mode by the control module 1 when detecting that the distance between the cleaning robot 100 and the dirt is not in a preset range. When traveling to the point O, the distance between the cleaning robot 100 and the dirt is within a preset range, and at this time, the cleaning robot 100 determines a size parameter of the dirt from the target image captured by the image capturing device 2. Further, after the size parameter of the dirt is determined, the cleaning robot 100 is controlled to clean the dirt J according to the zigzag cleaning strategy according to the size parameter of the dirt. If the size parameter of the dirty region is smaller than the third threshold value in the cleaning process, or the cleaning duration of the cleaning robot 100 on the dirty J reaches the preset duration, the control module 1 controls the cleaning device to lift, and controls the cleaning robot 100 to return to the base station after lifting, and the base station cleans the cleaning device. After the cleaning, the control module 1 controls the cleaning robot 100 to return to the dirty region, and detects whether the dirty J is cleaned after the return. If the control module 1 detects that the dirt J is not cleaned, the cleaning robot 100 is controlled to continue cleaning the dirt J. If the control module 1 detects that the dirt J is cleaned, judging whether the area to be cleaned is cleaned; if the detection finds that the area to be cleaned is not cleaned, the cleaning robot is controlled to switch to a cleaning strategy of a first path mode to continuously clean the area to be cleaned; specifically, during cleaning, the cleaning robot 100 is controlled to move to the O point first, and after the movement is successful, the cleaning robot 100 is controlled to continue to travel along the arcuate cleaning path to clean the area to be cleaned. And if the detection finds that the area to be cleaned is cleaned, controlling the cleaning robot to return to the base station. And cleaning the area to be cleaned and the dirt in the area to be cleaned according to the cleaning logic until the cleaning work of the area to be cleaned is completed.

In the several embodiments provided in the present application, the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative, for example, flow diagrams and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, the functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored on a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Claims

1. A method of cleaning soil applied to a cleaning robot, the method comprising:

judging whether the area to be cleaned is clean or not when the dirt is clean;

2. The method of claim 1, wherein prior to the controlling the cleaning robot to perform a second path mode cleaning strategy to clean the soil, the method further comprises:

determining a size parameter of the dirt, and determining a cleaning strategy of the second path mode according to the size parameter; the size parameter indicates a dirty area that is positively correlated with a cleaning intensity indicated by the cleaning strategy of the second path mode.

3. The method of claim 1, wherein prior to the controlling the cleaning robot to perform a second path mode cleaning strategy to clean the soil, the method further comprises:

and if the target distance is not within the preset range, controlling the cleaning robot to execute a cleaning strategy of a first path mode.

4. The method according to claim 2, wherein the cleaning robot is mounted with an image pickup device for picking up an image of the surroundings of the cleaning robot;

the determining the size parameter of the dirt comprises:

determining the number of pixels of a dirty region in a target image shot by the shooting device; wherein the dirty region is a region covered by the dirty in the region to be cleaned;

5. The method according to claim 4, wherein determining the number of pixels of the dirty region in the target image captured by the image capturing device includes:

determining position information of the dirty region in the target image;

Acquiring edge information of the dirty area according to the position information;

and calculating the pixel number of the dirt region in the target image based on the edge information.

6. The method of claim 2, wherein determining the cleaning strategy of the second path pattern based on the dimensional parameter comprises:

if the size parameter is smaller than a first threshold value, determining that the cleaning strategy of the second path mode is a linear cleaning strategy;

if the size parameter is greater than the first thresholdValue, determining the cleaning strategy of the second path mode as a back-shape cleaning strategy or a spiral cleaning strategy _。

7. The method according to claim 1, wherein when the cleaning strategy of the second path mode is a linear cleaning strategy, the controlling the cleaning robot to perform the cleaning strategy of the second path mode cleans the dirt, comprising:

generating a linear cleaning path, and controlling the cleaning robot to reciprocate according to the linear cleaning path to clean the dirt;

when the cleaning strategy of the second path mode is a zigzag cleaning strategy, the controlling the cleaning robot to execute the cleaning strategy of the second path mode to clean the dirt comprises the following steps:

Generating a back-shaped cleaning path, and controlling the cleaning robot to sequentially travel from outside to inside according to the mouth-shaped cleaning path to clean the dirt;

when the cleaning strategy of the second path mode is a spiral cleaning strategy, controlling the cleaning robot to execute the cleaning strategy of the second path mode to clean the dirt, including:

generating a spiral cleaning path, and controlling the cleaning robot to sequentially travel from outside to inside according to the circular cleaning path to clean the dirt.

8. The method of claim 1, further comprising:

and when the dirt is cleaned, calculating the size parameter of the dirt, and determining whether the dirt is cleaned or not according to the calculation result.

9. The method according to claim 1, wherein the cleaning robot is provided with a cleaning device for cleaning the area to be cleaned;

the method further comprises the steps of:

when the base station finishes cleaning the cleaning device, controlling the cleaning robot to return to a dirty area; wherein the dirty region is a region covered by the dirty in the region to be cleaned;

Judging whether the dirt is cleaned;

if the dirt is cleaned, judging whether the area to be cleaned is clean;

and if the dirt is not cleaned, continuing to clean the dirt area.

10. The method according to claim 1, wherein the cleaning robot is mounted with a laser emitting device for emitting a laser signal and a raman light receiving device for receiving the laser signal reflected by the obstacle;

before detecting that the cleaning area is stained during the cleaning process, the method further comprises:

and processing the laser signal received by the Raman light receiving device to generate a Raman spectrum, and judging whether dirt exists in the area to be cleaned according to the Raman spectrum.