Method and system for planning shoe washing path according to stain degree

Abstract

The invention discloses a method and system for planning a shoe washing path according to the stain degree. The method for planning the shoe washing path according to the stain degree comprises the steps that an acquired shoe surface image is preprocessed; carrying out stain detection on the preprocessed image by adopting an image recognition algorithm to generate stain quantitative data; and generating a cleaning scheme and a moving path of the shoe cleaning brush head based on the stain quantitative data and the feature data of the shoes. Stain information is obtained in real time through an image processing technology, and light and heavy areas are distinguished; the cleaning sequence, time and strength are adjusted according to the stain grade and position distribution; a brush head cleaning scheme is set by calculating a cleaning force coefficient and a cleaning time coefficient, a proper amount of resources are used in necessary areas, waste is reduced, and shoe materials are protected; a mathematical model is constructed through quantitative data to plan an optimal moving path of the brush head, so that a high-stain area is processed preferentially, repeated cleaning is avoided, and the overall time is shortened.

Description

Technical Field

[0001] The present application relates to the technical field of automated shoe washing, and in particular to a method and system for planning a shoe washing path according to the degree of stains. Background Art

[0002] In the shoe-washing field, automated shoe-washing equipment must simulate the delicate operations of manual shoe-washing to achieve optimal cleaning results. These devices typically have a pre-set, fixed cleaning process, such as starting with the upper, then cleaning the sole, and so on. Regardless of the severity of the shoe's stains, the cleaning process follows this fixed sequence and method. However, the severity and distribution of stains vary significantly from shoe to shoe, and accurately planning the cleaning process to address these differences has become a key challenge in improving automated shoe-washing effectiveness. Summary of the Invention

[0003] The embodiments of the present application provide a method and system for planning a shoe washing route according to the degree of stains, so as to solve the problems of poor cleaning targeting, waste of resources and low efficiency caused by traditional fixed shoe washing procedures.

[0004] In a first aspect, an embodiment of the present application provides a method for planning a shoe washing path according to the degree of stains, comprising:

[0005] Preprocessing the collected shoe surface images;

[0006] Using an image recognition algorithm to detect stains on the pre-processed image, and generating stain quantification data, the stain quantification data includes: a quantified value of the stain degree, a stain area ratio, and a stain location coordinate value;

[0007] A cleaning scheme and a moving path of the shoe brush head are generated based on the stain quantification data and the characteristic data of the shoe, wherein the characteristic data of the shoe includes the shape and material of the shoe.

[0008] In a possible embodiment, preprocessing the collected shoe surface image includes:

[0009] Map the pixel values ​​of the image to the range of [0,1] to obtain the normalized image pixel values;

[0010] The pixels in the image area are weighted averaged using a Gaussian function to obtain a noise-removed image.

[0011] In a possible embodiment, the step of performing stain detection on the preprocessed image using an image recognition algorithm to generate stain quantification data includes:

[0012] The degree of stain and the type of stain are obtained according to the color information in the pre-processed image;

[0013] Generate a quantitative value of the degree of stain and the proportion of the stain area according to the set quantitative evaluation standards based on the degree of stain and the type of stain;

[0014] According to the shape of the shoe and the preprocessed image, the specific position coordinates of the stain on the shoe are determined to generate the stain position coordinate value.

[0015] In a possible embodiment, generating a cleaning scheme and a movement path of the shoe brush head based on the stain quantification data and the shoe characteristic data includes:

[0016] Calculating the cleaning force coefficient and cleaning time coefficient at different positions on the shoe surface according to the stain quantification data;

[0017] A cleaning scheme and a moving path of the shoe brush head are generated according to the cleaning force coefficient, the cleaning time coefficient and the stain position coordinate value.

[0018] In a possible embodiment, calculating the cleaning force coefficient and the cleaning time coefficient at different locations on the shoe surface according to the stain quantification data includes:

[0019] Constructing a relationship between the degree of stain and the cleaning intensity based on the quantified value of the degree of stain, and calculating the cleaning intensity coefficient of the stain at different positions on the shoe surface;

[0020] A relationship between the degree of stain and the cleaning time is constructed according to the quantified value of the degree of stain and the proportion of the stain area, and the stain cleaning time coefficients at different positions on the shoe surface are calculated.

[0021] In a possible embodiment, generating a cleaning scheme and a moving path of the shoe brush head according to the cleaning force coefficient, the cleaning time coefficient, and the stain location coordinate value includes:

[0022] Setting the scrubbing force of the brush head at different locations on the shoe surface according to the scrubbing force coefficient, wherein the scrubbing force includes the amount of cleaning liquid sprayed and the water flow pressure at the brush head;

[0023] The residence time of the brush head at different positions on the shoe surface is set according to the cleaning time coefficient.

[0024] In a possible embodiment, generating a cleaning solution and a movement path of the shoe brush head based on the stain quantification data and the shoe characteristic data further includes:

[0025] The starting and ending positions of the brush head for washing shoes are set in descending order according to the quantitative values ​​of the degree of stains;

[0026] A heuristic search algorithm is used to generate an optimal path for the brush head to wash shoes, wherein the optimal path is a path in which the brush head starts brushing at the starting position and moves to the ending position with the shortest distance.

[0027] In a second aspect, an embodiment of the present application provides a system for planning a shoe washing path according to the degree of stains, including:

[0028] An image processing module, used for preprocessing the collected shoe surface images;

[0029] A stain detection module is used to detect stains on the pre-processed image using an image recognition algorithm to generate stain quantification data, which includes: a quantified value of the stain degree, a stain area ratio, and a stain location coordinate value;

[0030] The path planning module is used to generate a cleaning plan and a moving path for the shoe brush head based on the stain quantification data and the characteristic data of the shoes, wherein the characteristic data of the shoes include the shape and material of the shoes.

[0031] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory, wherein the memory stores program code. When the program code is executed by the processor, the processor executes the method of planning a shoe washing path according to the degree of stains as described in the first aspect above.

[0032] In a fourth aspect, the present application provides a computer-readable storage medium, which includes a program code. When the storage medium is run on an electronic device, the program code is used to enable the electronic device to execute the method of planning a shoe washing path according to the degree of stains described in the first aspect above.

[0033] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes computer instructions, and the computer instructions are stored in a computer-readable storage medium; when a processor of an electronic device reads the computer instructions from the computer-readable storage medium, the processor executes the computer instructions, so that the electronic device executes the method of planning a shoe washing path according to the degree of stains as described in the first aspect above.

[0034] The beneficial effects of this application are as follows:

[0035] The embodiment of the present application provides a method and system for planning a shoe washing path according to the degree of stains. Among them, the method for planning a shoe washing path according to the degree of stains includes: first, pre-processing the collected shoe surface image; second, using an image recognition algorithm to detect stains on the pre-processed image, and generating stain quantification data, the stain quantification data including: a quantified value of the stain degree, a percentage of the stain area, and a coordinate value of the stain position; finally, based on the stain quantification data and the characteristic data of the shoe, generating a cleaning scheme and a moving path for the shoe washing brush head, the characteristic data of the shoe including the shape and material of the shoe. The present invention generates stain quantification data after stain detection on the shoe surface image, which solves the problems of poor cleaning targeting, serious waste of resources, and low efficiency caused by the traditional method of fixing the shoe washing program. Its technical effects include: obtaining stain information in real time through image processing technology to distinguish between light and heavy areas; adjusting the cleaning order, time and intensity according to the stain level and location distribution; setting the brush head cleaning plan by calculating the cleaning intensity coefficient and cleaning time coefficient, using appropriate resources in necessary areas, reducing waste and protecting shoe materials; constructing a mathematical model through quantitative data to plan the optimal movement path of the brush head, giving priority to high-stained areas, avoiding repeated cleaning, and shortening the overall time.

[0036] Other features and advantages of the present application will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present application. The purposes and other advantages of the present application can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0038] Figure 1 This is a schematic diagram of a method for planning a shoe washing path according to the degree of stains in an embodiment of the present application;

[0039] Figure 2 This is a schematic diagram of a system framework for planning a shoe washing path according to the degree of stains in an embodiment of the present application;

[0040] Figure 3 This is a schematic diagram of the hardware structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other in any way. In addition, although a logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.

[0042] The following is a brief introduction to the design concept of the embodiment of this application:

[0043] Existing automated shoe-washing equipment relies on a fixed program for path planning, failing to adjust the path based on the actual level of soiling and distribution. Shoes vary widely in soiling. Some shoes may only have minor stains on the upper, while the sole is mostly clean; others may have heavily stained soles, while the upper is relatively clean. Fixed shoe-washing programs lack the flexibility to address these differences, making it difficult to guarantee effective cleaning. Because uniform cleaning time and intensity are applied regardless of the severity of the soiling, over-cleaning lightly soiled areas consumes excessive amounts of water and detergent. Furthermore, excessive cleaning can cause unnecessary damage to the shoe material, shortening its lifespan. For example, excessive scrubbing of softer uppers can lead to wear and discoloration. For heavily soiled areas, a fixed cleaning schedule and method often fail to completely clean them, requiring secondary or even multiple washes. This significantly increases overall cleaning time and reduces efficiency. Even shoes requiring minimal cleaning are washed according to complex, fixed programs, wasting time and resources. Based on this, the present application provides a method and system for planning a shoe-washing path according to the degree of stains. By setting the system for planning a shoe-washing path according to the degree of stains in the present application in an automated shoe-washing device, the system can implement a method for planning a shoe-washing path according to the degree of stains. The method first pre-processes the collected shoe surface image; then, an image recognition algorithm is used to detect stains on the pre-processed image to generate stain quantification data; finally, based on the stain quantification data and the characteristic data of the shoe, a cleaning plan and a moving path for the shoe-washing brush head are generated. The characteristic data of the shoe includes the shape and material of the shoe. The purpose is to plan a personalized shoe-washing path by accurately detecting the degree of stains on the shoe. For areas with severe stains, the cleaning time and intensity are increased; for areas with lighter stains, the cleaning time and intensity are reduced, thereby achieving precise cleaning and greatly improving the cleaning effect.

[0044] The application scenario of the present application is in an automated shoe washing device. Specifically, the system for planning the shoe washing path according to the degree of stains is configured on the server of the automated shoe washing device, communicates with the automated shoe washing device through a network connection, and then controls the brush head on the automated shoe washing device to work according to the brush head cleaning plan and moving path generated by the method for planning the shoe washing path according to the degree of stains in the present application.

[0045] The preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application. In addition, the embodiments and features in the embodiments of the present application can be combined with each other if there is no conflict.

[0046] like Figure 1 As shown in FIG, it is an implementation flow chart of a method for planning a shoe washing path according to the degree of stains provided in an embodiment of the present application. Here, the server is used as the execution subject for introduction. The specific implementation process of the method is as follows:

[0047] S101. Preprocess the collected shoe surface image.

[0048] In this embodiment, shoe surface images include images of the upper, sole, and shoe body captured by a camera installed in the automated cleaning equipment, as well as images of designated shoe locations based on cleaning requirements. In practice, using a color camera with high resolution and excellent color reproduction to capture shoe surface images facilitates providing high-quality metadata for stain detection. The camera's location in the corner of the shoe compartment within the automated cleaning equipment results in a fan-shaped field of view, allowing for maximum shoe information to be captured in a single image, facilitating identification of the preceding and following frames. Inside the shoe washer, the color camera is mounted at the bottom, providing a full field of view covering the entire area of ​​the shoe being cleaned. The camera lens features a special design, such as a nano-waterproof coating on the camera's imaging area, ensuring stable operation in humid environments and preventing splashes from affecting the lens during cleaning. Images captured by the camera are transmitted via data to a system that plans the shoe cleaning route based on the severity of the stain. Upon receiving the image information, the system performs pre-processing to remove noise.

[0049] In some implementations, the specific implementation of step S101 includes:

[0050] First, the pixel values ​​of the image are mapped to the range of [0,1] to obtain the normalized image pixel values;

[0051] Then, the pixels in the image area are weighted averaged by the Gaussian function to obtain the noise-removed image.

[0052] This embodiment maps the pixel values ​​of the image to [0,1], which can speed up the convergence of the model and help reduce the impact caused by the large difference in pixel value ranges between different images; at the same time, the pixels in the neighborhood are weighted averaged according to the Gaussian function, which can better retain the edge information of the image while removing noise. The Gaussian function, also known as the normal distribution function, is an important continuous probability distribution function in mathematics and statistics. Its core characteristic is that it is a bell-shaped curve, symmetrical about the mean position, and the width and height of the curve are controlled by the standard deviation. By substituting the pixel values ​​of the image into the Gaussian function, the weight of the Gaussian kernel is generated, and then the image is smoothed by the Gaussian kernel to remove noise and enhance image clarity, so as to improve the accuracy of subsequent stain detection on the image.

[0053] S102. Use an image recognition algorithm to perform stain detection on the pre-processed image to generate stain quantification data, wherein the stain quantification data includes: a stain degree quantification value, a stain area ratio, and a stain position coordinate value.

[0054] In practice, image recognition algorithms are used to detect stains in preprocessed images. Specifically, the color information in the image is analyzed to determine the severity and type of the stain. Image recognition technology is also used to determine the specific location of the stain on the shoe, providing data support for subsequent shoe cleaning path planning. The quantified stain severity value is defined according to pre-set stain assessment criteria, based on the severity of the stain, or the difficulty and type of cleaning. The stain area ratio is the ratio of the stain area to the overall surface area of ​​the shoe. The stain location coordinates are generated by constructing a spatial coordinate system on the shoe surface to determine the coordinates of the stain's location.

[0055] In some implementations, step S102 is implemented as follows:

[0056] The degree of stain and the type of stain are obtained according to the color information in the pre-processed image;

[0057] Generate a quantitative value of the degree of stain and the proportion of the stain area according to the set quantitative evaluation standards based on the degree of stain and the type of stain;

[0058] According to the shape of the shoe and the preprocessed image, the specific position coordinates of the stain on the shoe are determined to generate the stain position coordinate value.

[0059] In practice, the set quantitative evaluation standard can be the system default standard or a customized quantitative evaluation standard based on factors such as shoe shape, material, and surface pattern. For example, in one application scenario, the stain quantization value range is [1, 10]. For a stain detected on the shoe upper, based on its color, shape, and other characteristics such as the upper material and color, if it is assessed as a severe stain, the stain degree is quantitatively assessed as 8; for moderate stains, the stain degree is quantitatively assessed as 4; for light stains, the stain degree is quantitatively assessed as 2. The total area of ​​the shoe is defined as 1, and the stain area ratio is calculated based on the detected stain area and the total shoe area.

[0060] This embodiment quantifies the degree, type, and location of stains to generate specific numerical values, converting abstract image recognition and analysis into specific data information, providing an accurate data basis for shoe washing path planning, and ensuring the effectiveness and rationality of shoe washing path planning.

[0061] S103. Generate a cleaning plan and a moving path for the shoe brush head based on the stain quantification data and the characteristic data of the shoe, wherein the characteristic data of the shoe includes the shape and material of the shoe.

[0062] Among them, the cleaning plan of the shoe brush head includes but is not limited to: the rotation speed of the brush head, the selection of the softness and hardness of the bristles, the amount of cleaning liquid sprayed, the water flow pressure and other brush head settings that affect the cleaning effect of shoe stains; the movement path of the brush head includes but is not limited to: the position of the brush head on the shoe when it starts working, and the route of moving to the next stain after cleaning each stain and the order of stain cleaning, etc.

[0063] In some implementations, the specific implementation method of step S103 includes:

[0064] Calculating the cleaning force coefficient and cleaning time coefficient at different positions on the shoe surface according to the stain quantification data;

[0065] A cleaning scheme and a moving path of the shoe brush head are generated according to the cleaning force coefficient, the cleaning time coefficient and the stain position coordinate value.

[0066] In practice, when an automatic shoe-washing device is operating, the cleaning force and cleaning time of the brush head are set according to the shoe-washing scenario. In the prior art, it is mainly up to the operator to set a fixed cleaning force and cleaning time based on the observed stains to complete the entire shoe cleaning process. This application sets the cleaning force coefficient and the cleaning time coefficient, so that the system can map the corresponding cleaning plan through the coefficients, allowing the shoe-washing device to flexibly adjust the shoe-washing plan and the brush head movement path according to the actual shoe-washing needs, thereby improving the working efficiency of the automated equipment.

[0067] In some embodiments, the above-mentioned calculation of the cleaning force coefficient and the cleaning time coefficient at different positions on the shoe surface based on the stain quantification data includes:

[0068] Constructing a relationship between the degree of stain and the cleaning intensity based on the quantified value of the degree of stain, and calculating the cleaning intensity coefficient of the stain at different positions on the shoe surface;

[0069] A relationship between the degree of stain and the cleaning time is constructed according to the quantified value of the degree of stain and the proportion of the stain area, and the stain cleaning time coefficients at different positions on the shoe surface are calculated.

[0070] In actual application scenarios, assuming that the shoes to be cleaned require cleaning of the upper, sole, and upper, the image data of these three parts are focused on and the stain detection data is quantified to obtain the stain degree quantification value and stain area ratio data as follows:

[0071] Assume that the pre-set soiling evaluation criteria based on the cleaning scenario are: the soiling degree quantification value range is [1, 10], the quantification value range for light soiling is [1, 3], the quantification value range for moderate soiling is [4, 6], and the quantification value range for severe soiling is [7, 10]. For ease of calculation, the total area of ​​the shoe is set to 1. The quantification process is as follows:

[0072] Upper: The quantitative assessment value of the stain degree is 8 (severe stains), and the area ratio is 0.3;

[0073] Sole: The quantitative assessment of the degree of stain is 2 (light stain), and the area ratio is 0.4;

[0074] Upper: The quantitative assessment of the degree of stains is 4 (moderate stains), and the area accounts for 0.3.

[0075] An embodiment of calculating the cleaning force coefficient and the cleaning time coefficient at different positions on the shoe surface based on the above-mentioned stain quantification data may be:

[0076] Based on the quantified value of the degree of stain, a relationship between the degree of stain and the intensity of cleaning is constructed. The cleaning intensity coefficient k is set, which is proportional to the quantified value of the degree of stain. The constructed relationship is k = n / 10, where n is the quantified evaluation value of the degree of stain. Based on the quantified value of the degree of stain and the percentage of the stain area, a relationship between the degree of stain and the cleaning time is constructed. The cleaning time coefficient t is set, which is directly proportional to the product of the quantified value of the degree of stain and the percentage of the stain area. The constructed relationship is t = α × n × s, where α is a proportional constant. In practice, the value of α is set according to the shoe washing scenario. Here, α is assumed to be 1; s is the percentage of the stain area. The cleaning intensity coefficient and cleaning time coefficient of the upper, sole, and shoe upper are calculated as follows:

[0077] Cleaning intensity coefficient k of shoe upper face =8 / 10=0.8; cleaning time coefficient t face =1×8×0.3=2.4.

[0078] Cleaning intensity coefficient k of the sole face =2 / 10=0.2; cleaning time coefficient t face =1×2×0.4=0.8.

[0079] Cleaning intensity coefficient k of shoe upper face =4 / 10=0.4; cleaning time coefficient t face =1×4×0.3=1.2.

[0080] In this embodiment, a relationship between the degree of stain and the cleaning intensity is constructed, and a relationship between the degree of stain and the cleaning time is constructed using the quantitative value of the degree of stain and the proportion of the stain area. The shoe washing plan design is converted into a specific mathematical calculation problem, providing accurate data preparation for generating the optimal shoe washing planning path.

[0081] In some embodiments, the above-mentioned method of generating the cleaning scheme and movement path of the shoe brush head according to the cleaning force coefficient, the cleaning time coefficient, and the stain position coordinate value includes:

[0082] Setting the scrubbing force of the brush head at different locations on the shoe surface according to the scrubbing force coefficient, wherein the scrubbing force includes the amount of cleaning liquid sprayed and the water flow pressure at the brush head;

[0083] The residence time of the brush head at different positions on the shoe surface is set according to the cleaning time coefficient.

[0084] For example, using the above actual example, based on the above calculation results, a specific scenario of generating a cleaning plan and a moving path for a shoe brush head according to the cleaning force coefficient, the cleaning time coefficient, and the stain location coordinate value can be as follows:

[0085] According to the quantitative results of the above data, since the shoe surface has the highest degree of stains (n=8), according to the principle of "prioritizing cleaning of the heavily stained areas and increasing the brush head's residence time and scrubbing intensity", the brush head is planned to prioritize cleaning the shoe surface. Therefore, the residence time of the brush head on the shoe surface is t face = 2.4 time units. The actual time of a time unit can be set to 1 minute or 5 minutes according to the specific scenario. Here, it is assumed that a time unit is 1 minute; the scrubbing force is k face =0.8. In practice, each brushing force value or interval can correspond to a brushing plan. Assume that 1 is the maximum force, the brush head speed is the highest, the cleaning liquid injection dosage is the largest, and the water flow pressure is the largest.

[0086] After cleaning the upper, the upper is considered next, because the degree of stain on the upper (n=4) is higher than that on the sole (n=2). The brush head cleans the upper for a dwell time of t face = 1.2 time units, the scrubbing force is k face =0.4.

[0087] Finally, clean the soles of the shoes and the brush head stays there for t face = 0.8 time units, scrubbing force is k face =0.2.

[0088] This embodiment can map different shoe washing schemes according to the degree of stains at various locations on the shoes, so that during the operation of the shoe washing equipment, the brush head execution parameters are dynamically adjusted according to the cleaning force coefficient and cleaning time coefficient of each location, ensuring that the heavily stained areas are fully cleaned, while avoiding excessive cleaning of the lightly stained areas, saving resources and protecting shoe materials.

[0089] In some implementations, the specific implementation method of step S103 further includes:

[0090] The starting and ending positions of the brush head for washing shoes are set in descending order according to the quantitative values ​​of the degree of stains;

[0091] A heuristic search algorithm is used to generate an optimal path for the brush head to wash shoes, wherein the optimal path is a path in which the brush head starts brushing at the starting position and moves to the ending position with the shortest distance.

[0092] In practice, when the automatic shoe washing device is turned on, the brush head must first determine its starting and ending positions, and then plan the optimal path for the brush head to move, reducing ineffective movement paths and improving cleaning efficiency. Preferably, this embodiment sets the starting and ending positions of the brush head for shoe washing in descending order of the quantified values ​​of the degree of stain. In practice, other settings can also be used according to the needs of the scene, such as in ascending order of the quantified values ​​of the degree of stain or in order of the length of cleaning time.

[0093] This embodiment uses a heuristic search algorithm to generate the optimal path for the brush head to wash shoes, and tries to make the brush head pass through the upper, upper and sole of the shoes and other locations where different stains are located in the shoes in the shortest path, avoiding repeated and invalid movements, and reducing the distance the brush head moves between different parts of the shoes, thereby improving cleaning efficiency.

[0094] Based on the same inventive concept, the embodiment of the present application also provides a system for planning a shoe washing path according to the degree of stains. Figure 2 As shown, it is a schematic diagram of the framework of a system 200 for planning a shoe washing path according to the degree of stains, which may include:

[0095] An image processing module 201 is used to pre-process the collected shoe surface image;

[0096] The stain detection module 202 is used to detect stains on the pre-processed image using an image recognition algorithm to generate stain quantification data, which includes a stain degree quantification value, a stain area ratio, and a stain location coordinate value;

[0097] The path planning module 203 is used to generate a cleaning plan and a moving path for the shoe brush head based on the stain quantification data and the characteristic data of the shoe, wherein the characteristic data of the shoe includes the shape and material of the shoe.

[0098] The system provided in the present application plans a shoe-washing route based on the degree of stains. An image processing module preprocesses captured shoe surface images. A stain detection module then performs stain detection on the preprocessed images to generate stain quantification data. Finally, a path planning module generates a cleaning plan and movement path for the shoe-washing brush head based on the stain quantification data and shoe feature data, including the shoe's shape and material. This allows for a personalized shoe-washing route to be planned based on the degree and location of stains. This increases cleaning time and intensity for heavily stained areas and reduces cleaning effort for lightly stained areas, significantly improving cleaning effectiveness and meeting the diverse cleaning needs of different shoes. Furthermore, by intelligently planning the brush head's path, the amount of cleaning fluid sprayed and the water pressure are precisely controlled, ensuring that only the necessary areas and levels of cleaning are cleaned. For example, this reduces the use of cleaning fluid in lightly stained areas, avoiding unnecessary wear on the shoe's upper material and reducing resource consumption and shoe-washing costs in multiple ways. This allows for a single, centralized cleaning of heavily stained areas while employing a faster route for minor stains. If a small, serious stain is found on the shoe surface, focus on cleaning that area first, and then clean the shoe surface normally. This will greatly shorten the shoe washing time and better meet the efficiency requirements of large-scale shoe washing.

[0099] In some possible implementations, the system for planning a shoe washing route according to the degree of stains of the present application may include at least a processor and a memory. The memory stores program code, and when the program code is executed by the processor, the processor executes the steps of the method for planning a shoe washing route according to the degree of stains according to various exemplary embodiments of the present application described in this specification. For example, the processor may execute the following steps: Figure 1 Follow the steps shown in .

[0100] Based on the same inventive concept, an electronic device is also provided in the embodiment of the present application. The electronic device can realize the functions of the method and system for planning the shoe washing path according to the degree of stains. Figure 3A schematic diagram of the structure of an electronic device in one embodiment shows that, at the hardware level, the electronic device includes a processor 301, and optionally also includes an internal bus 300, a network interface 303, and a memory 302. The memory 302 may include internal memory, such as high-speed random-access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device. Of course, the electronic device may also include hardware required for other services.

[0101] The processor 301, the network interface 303, and the memory 302 can be interconnected via an internal bus 300. The internal bus 300 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0102] The memory 302 is used to store programs. Specifically, the programs may include program codes, which include computer operating instructions. The memory may include internal memory and non-volatile memory, and provides instructions and data to the processor.

[0103] In one possible implementation, a processor reads a corresponding computer program from non-volatile memory into internal memory and then executes it. Alternatively, the processor may obtain the corresponding computer program from another device to form a data monitoring and acceptance device at a logical level. Processor 301 executes the program stored in memory 302 to implement the data monitoring and acceptance method provided in any embodiment of the present application through the executed program.

[0104] The present invention Figure 2The method for planning a shoe washing path according to the degree of stains provided in the illustrated embodiment can be applied to the processor 301, or implemented by the processor 301. The processor 301 may be an integrated circuit chip with signal processing capabilities. During implementation, the various steps of the above method can be completed by hardware integrated logic circuits in the processor 301 or instructions in software form. The above-mentioned processor 301 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The various methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0105] The steps of the method disclosed in the embodiments of this application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0106] Based on the same inventive concept, an embodiment of the present application also provides a storage medium, which computer-readable storage medium stores one or more programs, and the one or more programs include instructions. When the instructions are executed by an electronic device including multiple applications, the electronic device can execute the method of planning a shoe washing path according to the degree of stains provided in any embodiment of the present application.

[0107] The systems and modules described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0108] For the convenience of description, the above device is described as being divided into various units or modules according to their functions. Of course, when implementing the present invention, the functions of each unit or module can be implemented in the same or multiple software and / or hardware.

[0109] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0110] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0111] The various embodiments in this application are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiment is generally similar to the method embodiment, so the description is relatively simple. For relevant parts, refer to the partial description of the method embodiment.

[0112] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for planning a shoe washing route according to the degree of stains, characterized in that: include: Preprocessing the collected shoe surface images; Using an image recognition algorithm to detect stains on the pre-processed image, and generating stain quantification data, the stain quantification data includes: a quantified value of the stain degree, a stain area ratio, and a stain location coordinate value; A cleaning scheme and a moving path of the shoe brush head are generated based on the stain quantification data and the characteristic data of the shoe, wherein the characteristic data of the shoe includes the shape and material of the shoe.

2. The method according to claim 1, wherein: The preprocessing of the collected shoe surface image includes: Map the pixel values ​​of the image to the range of [0,1] to obtain the normalized image pixel values; The pixels in the image area are weighted averaged using a Gaussian function to obtain a noise-removed image.

3. The method according to claim 1, wherein: The method of using an image recognition algorithm to detect stains on the pre-processed image and generate stain quantification data includes: The degree of stain and the type of stain are obtained according to the color information in the pre-processed image; Generate a quantitative value of the degree of stain and the proportion of the stain area according to the set quantitative evaluation standards based on the degree of stain and the type of stain; According to the shape of the shoe and the preprocessed image, the specific position coordinates of the stain on the shoe are determined to generate the stain position coordinate value.

4. The method according to claim 1, wherein: Generating a cleaning scheme and a moving path of the shoe brush head based on the stain quantification data and the shoe characteristic data includes: Calculating the cleaning force coefficient and cleaning time coefficient at different positions on the shoe surface according to the stain quantification data; A cleaning scheme and a moving path of the shoe brush head are generated according to the cleaning force coefficient, the cleaning time coefficient and the stain position coordinate value.

5. The method according to claim 4, wherein: The step of calculating the cleaning force coefficient and the cleaning time coefficient at different positions on the shoe surface according to the stain quantification data includes: Constructing a relationship between the degree of stain and the cleaning intensity based on the quantified value of the degree of stain, and calculating the cleaning intensity coefficient of the stain at different positions on the shoe surface; A relationship between the degree of stain and the cleaning time is constructed according to the quantified value of the degree of stain and the proportion of the stain area, and the stain cleaning time coefficients at different positions on the shoe surface are calculated.

6. The method according to claim 4, wherein: The step of generating a cleaning scheme and a moving path of the shoe brush head according to the cleaning force coefficient, the cleaning time coefficient, and the stain position coordinate value includes: Setting the scrubbing force of the brush head at different locations on the shoe surface according to the scrubbing force coefficient, wherein the scrubbing force includes the amount of cleaning liquid sprayed and the water flow pressure at the brush head; The residence time of the brush head at different positions on the shoe surface is set according to the cleaning time coefficient.

7. The method according to claim 1, wherein: The step of generating a cleaning scheme and a moving path of the shoe brush head based on the stain quantification data and the shoe characteristic data further includes: The starting and ending positions of the brush head for washing shoes are set in descending order according to the quantitative values ​​of the degree of stains; A heuristic search algorithm is used to generate an optimal path for the brush head to wash shoes, wherein the optimal path is a path in which the brush head starts brushing at the starting position and moves to the ending position with the shortest distance.

8. A system for planning shoe washing routes according to the degree of stains, characterized in that: include: An image processing module, used for preprocessing the collected shoe surface images; A stain detection module is used to detect stains on the pre-processed image using an image recognition algorithm to generate stain quantification data, which includes: a quantified value of the stain degree, a stain area ratio, and a stain location coordinate value; The path planning module is used to generate a cleaning plan and a moving path for the shoe brush head based on the stain quantification data and the characteristic data of the shoes, wherein the characteristic data of the shoes include the shape and material of the shoes.

9. An electronic device, characterized in that: The device comprises a processor and a memory, wherein the memory stores program codes, and when the program codes are executed by the processor, the processor executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The storage medium comprises a program code, and when the storage medium is run on an electronic device, the program code is used to enable the electronic device to execute any one of the methods according to claims 1 to 7.

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