A cleaning method, readable medium, and electronic device

Abstract

The application discloses a cleaning method applied to a cleaning device, and the method comprises the following steps: acquiring a temperature distribution image of a cleaning area of the cleaning device; dividing the temperature distribution image into a plurality of temperature areas based on temperature; and selecting a temperature area meeting a preset condition from the plurality of temperature areas as a to-be-cleaned area. The cleaning method acquires a plurality of temperature areas with different temperatures in the cleaning area, judges whether each temperature area contains an object needing cleaning based on the preset condition, and determines whether the temperature area is the to-be-cleaned area, so that the cleaning device automatically judges the area where the object needing cleaning is located, and further automatically cleans the object needing cleaning, thereby improving the cleaning efficiency of the cleaning device. If the object is water stains, manual inspection and manual treatment of the ground water stains are avoided, and the cleaning efficiency of the cleaning device is improved. The application also discloses a program product, a readable medium and an electronic device.

Description

[0001] This application is a divisional application filed pursuant to Article 42 of the Implementing Regulations of the Patent Law. Its parent application is Chinese Invention Application No. 202111134448.9, filed on September 27, 2021, by Tangen Intelligent Technology (Shanghai) Co., Ltd., entitled "A Cleaning Method, Program Product, Readable Medium, and Electronic Device." The entire contents of the parent application are incorporated herein by reference. Technical Field

[0002] This application relates to the field of cleaning equipment technology, and more particularly to a cleaning method, a readable medium, and an electronic device. Background Technology

[0003] With the improvement of urbanization, the demand for floor cleaning in various places is increasing day by day. At present, the mainstream floor cleaning method is to use automatic or semi-automatic cleaning equipment to clean the floor, replacing the traditional manual mopping method. During the cleaning process, the cleaning equipment actively sprays clean water onto the work surface, uses a brush to clean the work surface, and then uses a vacuum suction device installed behind the brush to suck the wastewater into the wastewater tank, thereby achieving the purpose of cleaning the floor.

[0004] With the continuous development of science and technology, cleaning equipment is becoming increasingly widespread and rapidly evolving towards intelligent operation. However, in actual use, issues such as improper water volume settings and inefficient automatic cleaning paths often result in wastewater residue on the floor. Furthermore, the large number of people in shopping malls increases the likelihood of water spills, further contributing to wastewater residue. In public places, this wastewater residue can pose a significant public safety hazard. Current technologies often rely on manual inspection and treatment of wastewater residue, which is inefficient and labor-intensive. Summary of the Invention

[0005] Therefore, it is necessary to provide a cleaning method, program product, readable medium, and electronic device to address the problem of cleaning water stains (i.e., the aforementioned wastewater) using cleaning equipment.

[0006] To address the aforementioned technical problems, in a first aspect, embodiments of this application provide a cleaning method applied to a cleaning device. The method includes: acquiring a temperature distribution image of a cleaning area of ​​the cleaning device; the temperature distribution image is an infrared image, and each pixel in the infrared image has a corresponding temperature value; based on the temperature values ​​corresponding to each pixel in the infrared image, performing cluster analysis on each pixel to segment the infrared image into multiple temperature regions; and selecting a temperature region that meets preset conditions from the multiple temperature regions as the area to be cleaned.

[0007] The above cleaning method obtains multiple temperature zones with different temperatures within the cleaning area, and determines whether each temperature zone contains an object that needs to be cleaned based on preset conditions. This determines whether the temperature zone is the area to be cleaned, allowing the cleaning equipment to automatically determine the area where the object to be cleaned is located. This further enables the cleaning equipment to automatically clean the object, improving the cleaning efficiency of the cleaning equipment. If the object is a water stain, it avoids manual inspection and manual handling of water stains on the ground, further improving the cleaning efficiency of the cleaning equipment.

[0008] In one possible implementation of the first aspect described above, the preset condition includes the temperature of the temperature region reaching a temperature threshold.

[0009] Because of temperature differences between objects, the type of object is determined by the temperature values ​​corresponding to temperature zones. The temperature threshold is either the maximum or minimum value. For example, in a shopping mall, the temperature value of a water-containing area on the floor (20℃) is significantly lower than the temperature value of a non-water-containing area (25℃). When the temperature threshold is at its maximum (e.g., 23℃), the temperature of the affected area is less than 23℃. The same logic applies when the temperature threshold is at its minimum, and will not be elaborated further here.

[0010] In one possible implementation of the first aspect above, the aforementioned preset condition further includes at least one of the following: the area of ​​the temperature region reaches an area threshold; there is no object with a three-dimensional structure on the clean plane in which the temperature region is located.

[0011] By further limiting the area and three-dimensional structure of the temperature region containing the object that needs to be cleaned, it is possible to avoid excluding objects with three-dimensional structures and objects that are too small to need cleaning, thereby improving the accuracy of detecting objects that need to be cleaned and thus improving the accuracy of the cleaning equipment in cleaning objects.

[0012] In some embodiments, if the cleaning plane where the temperature region is located is tilted at a certain angle relative to other cleaning planes, the temperature region is judged to contain a three-dimensional structure based on the cleaning plane where the temperature region is located, so as to avoid misjudging that the temperature region contains an object with a three-dimensional structure because the cleaning plane where the temperature region is located contains a three-dimensional structure relative to other cleaning planes.

[0013] In one possible implementation of the first aspect described above, the method further includes: determining, by means of a three-dimensional image of the temperature region, whether there is an object with a three-dimensional structure relative to the clean plane in which the temperature region is located.

[0014] In one possible implementation of the first aspect described above, a three-dimensional depth camera is used to acquire the three-dimensional image.

[0015] In one possible implementation of the first aspect above, the temperature threshold is obtained based on the temperature difference between an object in the area to be cleaned and other objects in the clean area.

[0016] In one possible implementation of the first aspect above, before selecting a temperature region that meets preset conditions from multiple temperature regions as the region to be cleaned, the method includes: determining a temperature threshold based on the median of the temperature distribution in a temperature distribution image.

[0017] In one possible implementation of the first aspect described above, the temperature threshold may be one or more.

[0018] In one possible implementation of the first aspect described above, an infrared camera is used to acquire the infrared image.

[0019] In one possible implementation of the first aspect above, the area to be cleaned includes water stains.

[0020] Secondly, embodiments of this application provide a computer program product, which includes instructions for implementing the above-described method for cleaning water stains.

[0021] Thirdly, embodiments of this application provide a computer-readable medium storing instructions that, when executed on an electronic device, cause the electronic device to perform the aforementioned cleaning method.

[0022] Fourthly, embodiments of this application provide an electronic device, which includes: a memory for storing instructions executed by one or more processors of the electronic device, and a processor, one of the processors of the electronic device, for performing the cleaning method described above. Attached Figure Description

[0023] The specific features involved in this application are shown in the appended claims. A better understanding of the features and advantages of the invention can be achieved by referring to the exemplary embodiments and accompanying drawings described in detail below. A brief description of the drawings is as follows:

[0024] Figure 1 This is a scenario diagram illustrating the application of a cleaning device 100 according to some embodiments of this application;

[0025] Figure 2 This is a flowchart illustrating a method for detecting water stains 200 using a cleaning device 100 according to some embodiments of this application;

[0026] Figure 3A An infrared thermal distribution map of a colorless water stain 200 region according to some embodiments of this application;

[0027] Figure 3BAn infrared thermal distribution map of a colored water stain 200 region according to some embodiments of this application;

[0028] Figure 4 This is a flowchart of a method for detecting water stains 200 using another cleaning device 100 according to some embodiments of this application;

[0029] Figure 5 An infrared thermal distribution map of a colorless water stain 200 region containing debris 400 according to some embodiments of this application;

[0030] Figure 6 This is a schematic diagram of the structure of an electronic device 600 according to some embodiments of this application;

[0031] Figure 7 This is a block diagram of an electronic device according to some embodiments of this application. Detailed Implementation

[0032] The illustrative embodiments of this application include, but are not limited to, a cleaning method, a program product, a readable medium, and an electronic device.

[0033] The cleaning method described below uses water stains (the area to be cleaned mentioned above) as an example. It should be noted that the scope of protection of this application is not limited to the description of the following embodiments.

[0034] Figure 1 This is a scenario illustration of a cleaning device 100 applied according to some embodiments of this application. The cleaning device 100 typically operates in public environments, such as shopping malls and transportation waiting areas. Figure 1 As shown, in the working area of ​​the cleaning equipment 100 (i.e., the cleaning area mentioned above), water stains 200 remain on the floor due to cleaning residue and human factors, thus posing a public safety hazard. In addition, detecting water stains 200 using images captured by ordinary cameras is difficult, has low accuracy, and is easily affected by factors such as ambient light and floor texture, especially for colorless and transparent liquids such as water.

[0035] To improve the cleaning efficiency of the cleaning equipment 100, quickly and automatically detect water stains 200, and save manpower, this application proposes a cleaning method that improves the cleaning efficiency of the cleaning equipment 100 by automatically detecting water stains 200. Specifically, this application acquires a temperature distribution map of objects in the work area, divides the temperature distribution map into multiple regions through image segmentation, and identifies regions where the temperature (which can be a representative value of the region, such as the maximum, minimum, or average temperature) is lower than a preset value as areas with water stains 200. Areas with water stains 200 larger than a preset area are identified as areas requiring cleaning. This allows for rapid detection of water stains 200 in the work area, enabling the cleaning equipment to clean them promptly and prevent safety accidents caused by water stains 200. In some implementations, after determining that the temperature of a certain region in the temperature distribution map is lower than the preset value, a 3D camera can be used to detect whether the region has a 3D structure. If the region does not have a 3D structure, it is then identified as an area with water stains 200, further improving the accuracy of water stain detection and thus enhancing the cleaning effectiveness of the cleaning equipment 100.

[0036] The steps for detecting water stains 200 in the above cleaning method are described below. Figure 2 This is a flowchart illustrating a method for detecting water stains 200 using a cleaning device 100 according to some embodiments of this application; Figure 3A An infrared thermal distribution map (i.e., an infrared image) including a colorless water stain 200 region according to some embodiments of this application; Figure 3B This is an infrared thermal distribution map of a region including a colored water stain 200, according to some embodiments of this application. The following is in conjunction with… Figure 2 , Figure 3A and Figure 3B The detection method is described in detail, and the main body executing this method is the cleaning equipment 100, such as... Figure 2 As shown, the method includes the following steps.

[0037] Step S102: Based on the temperature distribution of the working area of ​​the cleaning equipment 100, determine a temperature threshold and an area threshold. The temperature threshold is used to determine whether the working area contains water stains 200, and the area threshold is used to determine whether the water stains 200 need to be cleaned. Since the temperature of different objects in the same working area is different, a temperature threshold is set based on the temperature distribution of water stains 200 and other objects. When the temperature threshold is at its maximum value, the temperature of an object is lower than the temperature threshold, and the object is then determined to be a water stain 200. In addition, because the area of ​​water stains 200 is too small, targeted cleaning is not required, so the area threshold is used to determine whether water stains 200 need to be cleaned.

[0038] Based on the principles of heat conduction and specific heat capacity, objects within the same working area will have different temperatures. Typically, the temperature of water stain 200 is lower than that of other objects (such as the floor), and water stain 200 absorbs heat during natural evaporation, resulting in a maximum surface temperature of water stain 200 that is lower than the minimum temperature of the surrounding floor. In some embodiments of this application, when the temperature of an object within the same working area (this temperature can be a representative value of the area, such as the maximum, minimum, or average temperature) is less than a temperature threshold, the object is identified as water stain 200, meaning the working area contains water stain 200.

[0039] When there are significant temperature differences between different areas of the work area, using the overall work area temperature threshold can easily lead to a decrease in the accuracy of identifying water stain 200. For example, a cleaning device 100 with mapping and positioning functions divides the work area into five test areas: area A, area B, area C, area D, and area E. When the work area temperature is 22℃, the room temperature in area A is 20℃, and the room temperature in area B is 23℃. The overall work area temperature threshold is set at 21℃. At a room temperature of 22℃, the temperature of water stain 200 in area A is 19℃, and the temperature of water stain 200 in area B is 22℃. Therefore, water stain 200 cannot be identified in area B.

[0040] For the reasons stated above, in some embodiments of this application, the temperature threshold includes a regional temperature threshold. That is, different regional temperature thresholds are set for multiple test areas within the working area to determine whether the test areas corresponding to different regional temperature thresholds contain water stains 200. This reduces the impact of temperature changes in the working area on the detection accuracy, thereby improving the accuracy of detecting water stains 200.

[0041] In some embodiments of this application, an infrared image of the work area is acquired based on the temperature distribution of the work area, and the median of all temperature values ​​in the infrared image is set as the base temperature value; the aforementioned temperature threshold is then set based on the base temperature value. For example, if the temperature characteristic values ​​(temperature characteristic values ​​represent the overall temperature distribution of the area, such as the average indoor air temperature) of each area of ​​the work area are uniformly distributed, and the base temperature value of the work area is 28.9℃, the temperature threshold is set to 28℃, so that water stains in each area can be identified by the temperature threshold.

[0042] In some embodiments of this application, based on the temperature distribution of the area to be measured, a regional infrared image of the area to be measured is obtained, and the median of all temperature values ​​in the regional infrared image is set as the regional temperature baseline value; the aforementioned regional temperature threshold is set based on the regional temperature baseline value. For example, if the regional temperature baseline value A of area A is 19.5℃, the regional temperature threshold A is set to 19.5℃; if the regional temperature baseline value B of area B is 22.5℃, the regional temperature threshold B is set to 22℃; and the regional temperature thresholds for each area are all set to their maximum values.

[0043] In some embodiments of this application, one or more temperature thresholds are set to improve the effectiveness of water stain 200 detection. For example, based on the working area of ​​the cleaning device 100, Figure 3A The temperature range of the water stain 200 shown is 26.0℃-27.0℃. Figure 3B The water stain 200 shown is for cold drinks with a temperature less than 10℃, and for hot drinks with a temperature greater than 40℃. Therefore, the temperature thresholds are 27℃ (maximum) and 40℃ (minimum). Objects with temperatures less than 27℃ and greater than 40℃ are classified as water stain 200. Detection of high-temperature water stain 200 can effectively improve the validity of water stain 200 identification.

[0044] Step S104: Acquire an infrared thermal image of the working area. In some embodiments of this application, the cleaning device 100 uses an infrared camera to generate an infrared image containing object temperature information.

[0045] In some embodiments of this application, the infrared images may include multiple infrared images of different areas within the work area. For example, an infrared camera mounted on cleaning equipment 100 can capture multiple infrared images of the ground in different areas of a shopping mall, and the temperature distribution of the mall obtained based on multiple infrared images of different shopping mall areas is more accurate.

[0046] Step S106: Perform image segmentation on the infrared image based on temperature to obtain temperature regions. Specifically, perform image segmentation on the infrared image to obtain one or more temperature regions. For example, Figure 3A and Figure 3B The area shown (a) contains water stain 200 and luminescent body 300, targeting Figure 3A and Figure 3B After image segmentation of the thermal infrared distribution map of region (a) shown in Figure (b), the temperature region below 27°C is identified as region 200 (water stain 200), indicated by arrow M, and the temperature region above 28°C is identified as region 300 (emitter 300), indicated by arrow P. Image segmentation includes various methods, such as using cluster analysis based on temperature to segment the image and obtain one or more temperature regions. It is understood that in some embodiments, regions with similar temperatures in the infrared image will be segmented into the same region.

[0047] Step S108: Determine whether the temperature of the temperature zone has reached the temperature threshold.

[0048] If the temperature in the above temperature zone does not reach the temperature threshold, it means that the zone does not include water stain 200. Proceed to step S104, where the infrared camera continues to acquire infrared images of other areas in the working area to detect other areas.

[0049] If the temperature in the above temperature zone reaches the temperature threshold, it means that the zone includes water stains 200, and proceed to step S110.

[0050] Step S110: Determine whether the area of ​​the temperature region has reached the area threshold.

[0051] If the area of ​​the aforementioned temperature zone does not reach the area threshold, then proceed to step S104 to acquire infrared images of other areas within the working area. For example, if the area threshold is set to 3 square centimeters, then when the target area is 1 square centimeter, the infrared thermal camera acquires infrared images of other areas. By ignoring smaller areas and less dangerous water stains 200, the effectiveness of the cleaning device 100 in cleaning water stains 200 is improved.

[0052] If the area of ​​the temperature region reaches the area threshold, proceed to step S112.

[0053] S112: Determine the temperature zone as the location of the water stain 200 to be cleaned.

[0054] Understandable. Figure 2 The described method for the cleaning device 100 to detect water stains 200 is only an example. In other embodiments, the execution order of each step may also be different. For example, steps S108 and S110 may be performed simultaneously, or step S110 may precede step S108. This is not limited here.

[0055] After determining the temperature zone as the location of the water stain 200 to be cleaned in step S112, the control center of the cleaning equipment 100 obtains the location of the temperature zone and moves to the location of the temperature zone to clean the water stain 200.

[0056] In the above embodiment, if the temperature of some debris on the ground in the work area also reaches the aforementioned temperature threshold, the debris may be misidentified as water stains 200, leading to a misjudgment and reducing the working efficiency of the cleaning equipment 100. For example... Figure 5 The area (a) shown includes water stains 200, a luminous object 300, and debris 400. Figure 5 In the thermal infrared distribution map (b) of region (a) shown, the temperature difference between the temperature region of the impurity 400 (indicated by arrow O) and the temperature region of the luminescent body 300 (indicated by arrow P) is significant (approximately 3°C), and is close to the temperature region of the water stain 200 (indicated by arrow M). Simultaneously, the temperature reaches the temperature threshold of the water stain 200 (e.g., 28°C). Therefore, step S114 is performed... Figure 5 When judging whether there is water stain 200 in the area (a) shown, the debris 400 will be mistakenly identified as water stain 200.

[0057] To address this issue, this application provides another method for detecting water stains 200 using a cleaning device 100. This method detects the three-dimensional structure of the work area to avoid misidentifying non-water stain 200 objects (i.e., debris) with three-dimensional structures as water stains 200. Figure 4 This is a flowchart illustrating a method for detecting water stains 200 using another cleaning device 100 according to some embodiments of this application. (See also:) Figure 4 The method includes steps S102 to S110, S1111, S1112, and S112. Steps S102 to S110 and S112 can be referred to the aforementioned method. Figure 2 The description of steps S1111 and S1112 will not be repeated here.

[0058] After step S110, that is, after confirming that the temperature and area of ​​the above-mentioned temperature region have reached the above-mentioned temperature threshold and area threshold respectively, proceed to step S1111.

[0059] Step S1111: Acquire a three-dimensional structural image of the temperature region. For example, the cleaning device 100 can acquire a three-dimensional structural image of the temperature region using a three-dimensional depth camera to detect whether the temperature region has a three-dimensional structure.

[0060] It's understandable that a 3D depth camera cannot detect the 3D structure of water stain 200. Specifically, current 3D depth cameras are generally divided into three categories: binocular depth, structured light, and time-of-flight. Binocular depth requires both cameras to see the same texture features, which water stain 200 typically lacks, making measurement impossible. Structured light projects a laser speckle onto the surface of the object being measured and calculates the depth based on the observation angle of the speckle from another camera. However, since the laser passes through water stain 200, it also cannot be measured. Time-of-flight works for a similar reason; the light penetrates the interior of water stain 200, making it impossible to accurately calculate its surface 3D structure. In other words, when a temperature region lacks a 3D structure, it is considered a water stain 200.

[0061] Step S1112: Determine whether a three-dimensional structure exists in the temperature region. Based on the three-dimensional structure image obtained in step S1111, determine whether a three-dimensional structure exists in the temperature region.

[0062] If the aforementioned temperature area does not have a three-dimensional structure, proceed to step S112 to confirm that the temperature area is the location of the water stain 200 to be cleaned. If the aforementioned temperature area has a three-dimensional structure, proceed to step S104 to acquire infrared images of other areas in the working area.

[0063] exist Figure 4The method shown further eliminates the possibility of the temperature region being filled with debris by determining whether the temperature region has a three-dimensional structure, thus improving the accuracy of detecting water stains 200.

[0064] Steps S1111 and S1112 can be performed in any step prior to step S112. For example, before proceeding to step S108, three-dimensional structural regions contained within the temperature region are excluded, and the temperature and area of ​​non-three-dimensional structural regions within the temperature region are determined to identify the water stain 200 to be cleaned.

[0065] Figure 6 This is a schematic diagram of the structure of an electronic device 600 according to some embodiments of this application. The electronic device 600 is used to detect water stains 200, such as... Figure 6 As shown, the electronic device includes a preset module 601, an acquisition module 602, an image processing module 603, and a determination module 604.

[0066] The preset module 601 is used to determine a temperature threshold based on the temperature distribution of the working area of ​​the cleaning device 100. The temperature threshold is used to identify water stains 200, and an area threshold is used to determine whether water stains 200 are water stains that need to be cleaned. The acquisition module 602 is used to acquire infrared images within the working area. The image processing module 603 is used to perform image segmentation on the infrared images based on temperature to obtain temperature regions. The determination module 607 is used to determine the location of the temperature region as the water stain 200 that needs to be cleaned when the temperature of the temperature region reaches the temperature threshold and the area of ​​the temperature region reaches the area threshold.

[0067] In some embodiments of this application, an automatic water stain cleaning system 200 is provided, comprising the aforementioned electronic device 600 and a cleaning device 100. The cleaning device 100 includes a navigation device; the cleaning device 100 uses the navigation device to obtain the location of the water stain 200 that needs to be cleaned; the cleaning device 100 moves to the location of the water stain 200 that needs to be cleaned and cleans the water stain 200. Thus, the cleaning device 100 can automatically detect the water stain 200 and automatically navigate to clean it, improving the efficiency of water stain detection, saving manpower, further making the cleaning device 100 intelligent, and improving the user experience.

[0068] Figure 7 This is a schematic diagram of the hardware structure of a cleaning device 100 according to some embodiments of this application.

[0069] Specifically, such as Figure 7 As shown, the cleaning device 100 includes a processor 710, a display 720, a camera 730, a sensor module 740, a memory 750, and a power supply 760.

[0070] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the cleaning device 100. In other embodiments of this application, the cleaning device 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0071] The processor 710 may include one or more processing units, such as an application processor (AP), a modem processor, a central processing unit (CPU), a graphics processing unit (GPU), an image signal processor (ISP), a control unit, a video codec, a digital signal processor (DSP), a data processing unit (DPU), a baseband processor, and / or a neural network processing unit (NPU). These different processing units may be independent devices or integrated into one or more processors.

[0072] The processor 710 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 710 is a cache memory. This memory can store instructions or data that the processor 710 has just used or that are used repeatedly. If the processor 710 needs to use the instruction or data again, it can retrieve it directly from the memory. This avoids repeated accesses, reduces the waiting time of the processor 710, and thus improves the efficiency of the system.

[0073] In some embodiments, the processor 710 may include one or more interfaces. Interfaces may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0074] It is understood that the interface connection relationships between the modules illustrated in the embodiments of this application are merely illustrative and do not constitute a structural limitation on the cleaning device 100. In other embodiments of this application, the cleaning device 100 may also employ different interface connection methods or combinations of multiple interface connection methods as described in the above embodiments.

[0075] The display 720 can be a liquid crystal display (LCD), an organic light-emitting diode (OLED) display, an active-matrix organic light-emitting diode (AMOLED) display, a flexible light-emitting diode (FLED) display, a quantum dot light-emitting diode (QLED) display, etc. In some embodiments of this application, the display 720 may also include a touch screen, through which a user can interact with the cleaning device 100, for example, by inputting ambient temperature, temperature threshold, area threshold, etc.

[0076] Camera 730 is used to acquire still images or videos. An image of an object is projected onto a photosensitive element through the lens. The photosensitive element converts the light signal into an electrical signal, which is then transmitted to an image signal processor (ISP) to be converted into a digital image signal. The ISP outputs the digital image signal to the ISP for further processing. The DSP converts the digital image signal into image signals in standard RGB, YUV, or other formats. In some embodiments, the cleaning device 100 may include one or N cameras 730, where N is a positive integer greater than 1. In some embodiments of this application, camera 730 includes an infrared camera and a three-dimensional depth camera. The infrared camera works by emitting infrared light from an infrared lamp to illuminate the object; the infrared light is diffusely reflected and received by a monitoring infrared thermal camera to form a video image. The three-dimensional depth camera can detect the depth of field in the shooting space. For example, multiple infrared cameras and multiple three-dimensional depth cameras are installed on the top or side of the cleaning device 100. The infrared cameras and three-dimensional depth cameras acquire images of the cleaned area. The processor 710 can determine whether there are water stains 200 in the cleaned area based on the infrared images captured by the infrared cameras and the three-dimensional images captured by the three-dimensional depth cameras.

[0077] The cleaning device 100 also includes a sensor module 740, which may include pressure sensors, gyroscope sensors, barometric pressure sensors, magnetic sensors, accelerometers, distance sensors, proximity sensors, temperature sensors, touch sensors, ambient light sensors, etc. For example, in some embodiments, the aforementioned laser sensor is used for obstacle detection on the road surface.

[0078] The memory 750 is used to store software programs and data. The processor 710 executes various functional applications and data processing of the cleaning device 100 by running the software programs and data stored in the memory 750. For example, in some embodiments of this application, the memory 750 can store infrared thermal image data acquired by an infrared camera and three-dimensional images captured by a three-dimensional depth camera.

[0079] The cleaning device 100 also includes a power supply 760 (such as a battery) to power various components. Preferably, the power supply can be logically connected to the processor 710 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 760 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0080] This application also provides a computer program product including instructions for implementing the above-described method for detecting water stains 200.

[0081] This application also provides a readable medium storing instructions that, when executed on an electronic device, cause the electronic device to perform the method for detecting water stains 200 as described above.

[0082] This application also provides an electronic device, which includes a memory for storing instructions executed by one or more processors of the electronic device, and a processor, one of the processors of the electronic device, for performing the method of detecting water stains 200 as described above.

[0083] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0084] Similarly, it should be understood that, in order to streamline this application and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of this application, various features of this application are sometimes grouped together into a single embodiment, figure, or description thereof. However, this method of disclosure should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0085] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature serving the same, equivalent, or similar purpose.

[0086] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

Claims

1. A cleaning method applied to cleaning equipment, characterized in that, The method includes: Acquire a temperature distribution image of the cleaning area of ​​the cleaning equipment; the temperature distribution image is an infrared image, and each pixel in the infrared image has a corresponding temperature value; the cleaning area includes multiple areas to be measured with different ambient temperatures; Based on the temperature value corresponding to each pixel in the infrared image, cluster analysis is performed on each pixel to divide the infrared image into multiple temperature regions. Select a temperature region that meets preset conditions from the plurality of temperature regions as the region to be cleaned; wherein, the region to be cleaned includes water stains, and the preset conditions include: the temperature of the temperature region reaches a region temperature threshold set for the region to be tested where the temperature region is located, and the area of ​​the temperature region reaches an area threshold.

2. The method according to claim 1, characterized in that, The preset conditions also include: The temperature region does not contain any three-dimensional objects relative to the clean plane in which it is located.

3. The method according to claim 2, characterized in that, Also includes: The presence of a three-dimensional object relative to the clean plane in which the temperature region is located is determined by a three-dimensional image of the temperature region.

4. The method according to claim 3, characterized in that, The three-dimensional image is acquired using a three-dimensional depth camera.

5. The method according to any one of claims 1 to 3, characterized in that, The regional temperature threshold is obtained based on the temperature difference between an object in the region to be tested and other objects in the region to be tested.

6. The method according to any one of claims 1 to 3, characterized in that, Before selecting a temperature region that meets preset conditions from the plurality of temperature regions as the region to be cleaned, the method includes: determining a temperature threshold for the region based on the median of the temperature distribution in the temperature distribution image of the region to be tested.

7. The method according to any one of claims 1 to 3, characterized in that, The temperature threshold for the region can be one or more.

8. The method according to claim 1, characterized in that, The infrared image is acquired using an infrared camera.

9. A readable medium, characterized in that, The readable medium stores instructions that, when executed on an electronic device, cause the electronic device to perform the cleaning method as described in any one of claims 1 to 8.

10. An electronic device, characterized in that, include: A memory for storing instructions executed by one or more processors of the electronic device, and The processor is one of the processors of the electronic device, used to perform the cleaning method as described in any one of claims 1 to 8.

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