A method and system for planning ceiling sites of spraying and polishing robots

Abstract

The present invention provides a method and system for planning ceiling sites of a spraying and polishing robot, which belongs to the field of image processing technology. The method includes: obtaining a ceiling image; using image processing technology to segment the ceiling image, determine the robot's working surface and movable area; loading the robot's process parameters; sliding the window on the working surface according to the robot's minimum working surface to determine the starting position of the operation; based on the starting position of the operation, using sliding window processing to determine the position of each site; obtaining the robot's maximum sub-working surface at each site; calculating the robot's maximum workable surface on each maximum sub-working surface, and adding each maximum workable surface to the site result map; selecting the unworked area; determining the maximum sub-working surface that includes the current unworked area, and recording the corresponding site location; saving the site location and the corresponding working area, marking the current unworked area as a worked state, and updating it to the site result map.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and system for planning ceiling sites of a spraying and polishing robot. Background Art

[0002] With the rapid development of robot technology, spraying and polishing robots have been widely used in the industrial and construction fields, especially in the operation of complex surfaces such as ceilings. In order to ensure that the robot can efficiently and accurately complete the spraying or polishing tasks of the ceiling, reasonable work surface planning becomes the key. The goal of work surface planning is to reduce repeated operations and uncovered areas by optimizing the robot path, station distribution and work area, and improve overall work efficiency.

[0003] At present, the common method for planning the ceiling work surface of spraying and polishing robots is to use rectangular segmentation technology. Specifically, the robot work surface is first divided into multiple rectangular areas, and then these rectangles are further planned and arranged for work. This method simplifies the complex ceiling surface into several regular rectangular areas for planning, making it easier for the robot to complete the spraying or polishing work in each area in turn.

[0004] However, existing methods have high requirements for image segmentation algorithms. Especially when dealing with irregular ceiling surfaces, the segmentation process may not accurately reflect the actual work surface, resulting in a mismatch between the segmentation results and actual needs. At the same time, due to the inaccuracy of segmentation, some robot stations may be located in overlapping or invalid areas, resulting in reduced work efficiency and waste of resources. Summary of the invention

[0005] The main purpose of the present invention is to provide a method and system for planning ceiling sites of spraying and polishing robots, so as to solve the problem that the existing methods have high requirements for image segmentation algorithms, especially when processing irregular ceiling surfaces, the segmentation process may not accurately reflect the actual working surface, resulting in the mismatch between the segmentation results and the actual needs. At the same time, due to the inaccuracy of segmentation, some robot sites may be located in overlapping or invalid areas, resulting in technical problems such as reduced work efficiency and waste of resources.

[0006] In order to achieve the above object, according to one aspect of the present invention, a method for planning a ceiling site of a spraying and polishing robot is provided, comprising:

[0007] S1: Acquire ceiling image;

[0008] S2: using image processing technology to segment the ceiling image and determine the robot's working surface and movable area;

[0009] S3: Load the process parameters of the robot;

[0010] S4: Using image processing technology, sliding window processing is performed on the working surface according to the minimum working surface of the robot, and the first feasible position is used as the working starting position of the robot;

[0011] S5: Based on the operation start position, determine the position of each site using a sliding window processing method;

[0012] S6: Obtain the maximum sub-operation surface of the robot at each site;

[0013] S7: Calculate the maximum workable surface of the robot on each of the maximum sub-work surfaces according to the process parameters and the movable area, and add each of the maximum workable surfaces to the site result map;

[0014] S8: traverse the site result map and select unoperated areas;

[0015] S9: According to the process parameters of the robot and the maximum working surface, determine the maximum sub-working surface including the current non-working area, and record the corresponding station position;

[0016] S10: Save the site location and the corresponding operation area, mark the current unoperated area as an operated state, and update the site result map.

[0017] Furthermore, the determining of the working surface of the robot is specifically as follows:

[0018] The ceiling image is segmented by using image processing technology, and the pixel value of the robot working surface is marked as 255, and the pixel value of the first remaining area is marked as 0.

[0019] Furthermore, the determination of the movable area of ​​the robot is specifically as follows:

[0020] The ceiling image is segmented by using image processing technology, and the pixel value of the robot movable area is marked as 255, and the pixel value of the second remaining area is marked as 0.

[0021] Furthermore, the process parameters include the length, width, minimum working surface, maximum working surface, position of the center point on the maximum working surface, and the minimum distance from the movable area of ​​the robot.

[0022] Furthermore, the maximum working surface is divided into a plurality of areas according to the minimum working surface, and the state of each area is marked by binary.

[0023] Further, the S9 specifically includes:

[0024] S901: Analyze the result graph to determine multiple feasible sites for completing the unoperated area;

[0025] S902: Calculate the coverage rate of the unoperated area by the maximum sub-operation face of each feasible site;

[0026] S903: Calculate the movement cost of the robot from the current working position to the maximum sub-operation surface of each feasible site;

[0027] S904: constructing a comprehensive evaluation function according to the coverage rate and the mobility cost;

[0028] S905: Determine the maximum sub-operation surface corresponding to the maximum value of the comprehensive evaluation function as the maximum sub-operation surface including the current non-operation area, and record the corresponding site location.

[0029] Furthermore, the calculation formula of the coverage is:

[0030]

[0031] Among them, C i represents the coverage of the largest sub-operation surface of the i-th feasible site, A u Indicates the area of ​​the unoperated area, S i represents the maximum sub-operation area of ​​the i-th feasible site, Represents the total area of ​​unworked areas.

[0032] Furthermore, the calculation formula of the movement cost is:

[0033]

[0034] Among them, D i represents the movement cost of the robot from the current working position to the largest sub-operation area of ​​the i-th feasible site, d( ) represents the distance function, R current Indicates the current working position, S i Represents the maximum sub-operation area of ​​the i-th feasible site.

[0035] Furthermore, the comprehensive evaluation function is specifically:

[0036]

[0037] Among them, F i represents the comprehensive evaluation value of the largest sub-operation surface of the i-th feasible site, C i represents the coverage of the largest sub-operation surface of the i-th feasible site, D i represents the movement cost of the robot from the current working position to the i-th sub-operation surface area, α represents the weight coefficient of the coverage rate, and β represents the weight coefficient of the movement cost.

[0038] According to one aspect of the present invention, a spraying and polishing robot ceiling site planning system is provided, comprising:

[0039] processor;

[0040] A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the above-mentioned spraying and polishing robot ceiling site planning method is implemented.

[0041] By applying the technical solution of the present invention, the robot's working surface and movable area are determined by using flexible image processing and sliding window technology, avoiding the limitations of the traditional rectangular segmentation method in processing irregular ceiling surfaces, reducing the high requirements for image segmentation algorithms, and ensuring that the segmentation results can accurately reflect actual work needs. By accurately calculating the maximum working surface of each station, dynamically traversing the result map, and updating the working status in real time, it is ensured that each station covers the unoperated area, avoiding repeated operations and station overlap, thereby improving work efficiency and reducing resource waste.

[0042] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0044] Figure 1 A schematic diagram of a process flow of a ceiling site planning method for a spraying and polishing robot provided in an embodiment of the present invention is shown;

[0045] Figure 2 A structural schematic diagram of a spraying and polishing robot ceiling site planning system provided in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0046] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0047] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0048] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so as to describe the embodiments of the present invention described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0049] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0050] Reference Manual Attached Figure 1 , showing a flow chart of a spraying and polishing robot ceiling site planning method provided in an embodiment of the present invention.

[0051] An embodiment of the present invention provides a method for planning a ceiling site of a spraying and polishing robot, comprising:

[0052] S1: Acquire ceiling image;

[0053] S2: Use image processing technology to segment the ceiling image and determine the robot's working surface and movable area.

[0054] Image processing technology refers to the technology of analyzing, processing and converting digital images to extract useful information or improve image quality. It involves processing, optimizing, extracting features and other operations for specific tasks from image data, and is widely used in many fields (such as computer vision, medical imaging, autonomous driving, etc.).

[0055] The work surface refers to the specific area where the robot needs to perform the task. This area is where the robot performs operations (such as spraying, grinding, cleaning, etc.). The work surface can vary depending on the nature of the specific task, but it represents the target area where the robot actually completes the task.

[0056] The movable area refers to the range within which the robot can move freely during operation. It defines the area that the robot can physically reach and is determined based on the robot structure, environmental restrictions, and safety requirements.

[0057] In a possible implementation, determining the working surface of the robot is specifically as follows:

[0058] The ceiling image is segmented using image processing technology, and the pixel value of the robot working surface is marked as 255, and the pixel value of the first remaining area is marked as 0.

[0059] In a possible implementation, determining the movable area of ​​the robot is specifically as follows:

[0060] The ceiling image is segmented using image processing technology, and the pixel value of the robot's movable area is marked as 255, and the pixel value of the second remaining area is marked as 0.

[0061] In the present invention, the image segmentation technology can accurately identify the area where the robot actually needs to operate (the working surface) and the range within which the robot can move (the movable area), thereby avoiding blind operation on the entire ceiling. At the same time, by clearly dividing the working surface and the movable area, the robot is prevented from performing repeated operations in invalid areas or entering areas where it cannot operate, thereby reducing resource waste.

[0062] Furthermore, through image segmentation and labeling, it not only ensures that the robot can operate accurately in complex environments, but also greatly improves the degree of automation, efficiency and accuracy of the operation.

[0063] S3: Load the process parameters of the robot.

[0064] In a possible implementation, the process parameters include the length, width, minimum working surface, maximum working surface, the position of the center point on the maximum working surface, and the minimum distance from the movable area of ​​the robot.

[0065] In a possible implementation, the maximum working surface is divided into multiple areas according to the minimum working surface, and the state of each area is marked by binary.

[0066] In the present invention, the maximum working surface is divided into multiple sub-areas according to the minimum working surface, and each sub-area represents the minimum working unit that the robot can handle at one time. This division method can ensure that the working area is accurately allocated, reducing or avoiding the overlap or omission of work. At the same time, the maximum working surface is divided into multiple areas and the status of each area is marked by binary, which simplifies the management of the working area. The robot can judge the working status based on a simple binary and quickly decide the next action without complicated calculations and checks.

[0067] Furthermore, by dividing the maximum working surface and marking the status of each area, the robot can reasonably allocate resources and time to avoid ineffective operations. Each operation will select the area that has not been processed to ensure that all areas are effectively covered and reduce duplication or omissions in the operation.

[0068] S4: Using image processing technology, a sliding window is processed on the working surface according to the robot's minimum working surface, and the first feasible position is used as the robot's working starting position.

[0069] Among them, Sliding Window Algorithm is a commonly used algorithmic technique that traverses subsets of a data set and performs calculations or operations at each position of the moving window. This technique is often used in image processing, signal processing, time series analysis and other fields, and is particularly effective when local areas of a data set need to be processed step by step.

[0070] In the present invention, the sliding window processing avoids global scanning of the entire working surface by gradually calculating the local area of ​​the working surface. This method significantly reduces the complexity of calculation and is particularly suitable for large-area or complex-shaped ceiling working surfaces. At the same time, through the sliding window processing, the first feasible position can be dynamically found as the starting point of the operation. In this way, the robot can quickly determine where to start working and avoid unnecessary delays.

[0071] Furthermore, the sliding window processing is highly adaptable and can perform well when handling irregular or complex ceiling work surfaces. Even when the work surface is complex in shape, the sliding window can flexibly adjust the window size and step length to find a suitable starting position, avoiding errors in global planning. At the same time, the sliding window processing can scan and analyze each local area of ​​the work surface in real time. When encountering an infeasible area, the sliding window can continue to slide to find the next feasible area. This real-time decision-making and adjustment capability enables the robot to quickly adapt to changes in the work environment.

[0072] S5: Based on the job start position, the position of each site is determined using a sliding window processing method.

[0073] The core of sliding window processing is a fixed-size window that slides gradually over the data set, one step at a time, and operates on the area covered by the window.

[0074] Optionally, the step length of the robot's sliding window is determined according to the robot's minimum working surface.

[0075] In the present invention, by matching the sliding window step length with the minimum working surface of the robot, it can be ensured that the window can completely cover a minimum working surface each time it slides. In this way, the robot can accurately process the entire minimum working area in each sliding step, avoid missing or overlapping operations, and ensure that the working surface can be completely covered. At the same time, by matching the minimum working surface to determine the sliding window step length, it can ensure the coverage accuracy of the operation and reduce the number of window sliding times. This balance allows the robot to complete tasks more efficiently when performing path planning without the need for overly fine or rough sliding.

[0076] Furthermore, since the step length corresponds to the minimum working surface, the robot can reduce unnecessary sliding times and operate directly on the minimum working unit. This greatly improves the working efficiency, and the robot can cover the entire working surface with the shortest path. At the same time, the minimum working surface is used as the sliding window step length, and the window can be adjusted to match the edge, reducing the problem of uncovered or repeated coverage of the working edge area.

[0077] S6: Obtain the maximum sub-operation surface of the robot at each site.

[0078] The maximum sub-operation surface refers to the maximum physical area that the robot can cover at a certain site. This is based on the maximum operating range of the robot during operation, which usually depends on the robot's physical size, operating capabilities (such as spraying range, grinding radius) and process parameters. The maximum sub-operation surface is a local operating area that reflects the maximum amount of work that the robot can complete in one operation at a specific location.

[0079] In the present invention, determining the maximum sub-operation surface of the robot at each station can ensure that the robot covers as much of the operation area as possible in one operation. This can reduce the frequent movement of the robot and improve the efficiency of a single operation. At the same time, by obtaining the maximum sub-operation surface of each station, the system can reasonably plan the robot path according to the division of the operation surface to ensure that the movement distance of the robot between different stations is minimized.

[0080] Furthermore, the maximum sub-operation surface can be dynamically adjusted according to the robot's operating capabilities and environmental conditions. For example, the ceiling operation area may have different heights, angles or shapes. By calculating the maximum sub-operation surface, it can ensure that the robot can flexibly adapt to different operating environments at each station. At the same time, the maximum sub-operation surface can be dynamically adjusted according to specific operation requirements, such as adjusting the operating range according to the accuracy requirements of the operation, the load conditions of the equipment, etc., to ensure optimal performance under various operating conditions.

[0081] S7: Calculate the maximum workable surface of the robot on each maximum sub-work surface according to the process parameters and the movable area, and add each maximum workable surface to the site result diagram.

[0082] The site result map is an image or data structure used to record and display the operation status and progress of each site during the robot operation. It visualizes the work completed by the robot at each operation site, the processed areas, the unprocessed areas, and related operation information in a graphical or data-based way. The site result map is an important tool for operation planning, progress tracking, and path optimization, and can help the system or operator monitor and adjust the operation tasks in real time.

[0083] In the present invention, adding the maximum workable surface to the site result map can provide a detailed reference for subsequent planning, ensuring that the robot works efficiently at each position. This can reduce unnecessary energy consumption, time waste, and waste of process materials. At the same time, by adding the maximum workable surface to the site result map, the system can obtain a clear work progress map, thereby optimizing the robot's path planning. The robot can give priority to unworked areas or areas that have not been fully worked when planning the path, avoiding repeated processing of completed areas, saving movement time and path length.

[0084] Furthermore, each sub-operation surface may have different physical constraints in different operating environments. By calculating the maximum operable surface, the system can dynamically adapt to various complex environmental conditions.

[0085] S8: Traverse the site result map and select the unoperated areas.

[0086] S9: According to the process parameters of the robot and the maximum working surface, determine the maximum sub-working surface including the current non-working area, and record the corresponding site position.

[0087] In a possible implementation, S9 specifically includes:

[0088] S901: Analyze the result graph to determine multiple feasible sites for completing the unoperated area;

[0089] S902: Calculate the coverage rate of the maximum sub-operation surface of each feasible site to the non-operation area.

[0090] In a possible implementation, the calculation formula for coverage is:

[0091]

[0092] Among them, C i represents the coverage of the largest sub-operation surface of the i-th feasible site, A u Indicates the area of ​​the unoperated area, S i represents the maximum sub-operation area of ​​the i-th feasible site, Represents the total area of ​​unworked areas.

[0093] In the present invention, by calculating the coverage rate, the sub-operation surfaces with the highest coverage rate of the unoperated area can be preferentially selected. In this way, the robot can cover a larger area of ​​the unoperated area at one time, reduce the number of frequent switching between different areas, and thus improve the overall operation efficiency.

[0094] S903: Calculate the movement cost of the robot from the current working position to the maximum sub-operation surface of each feasible site.

[0095] In a possible implementation, the calculation formula of the moving cost is:

[0096]

[0097] Among them, D i represents the movement cost of the robot from the current working position to the largest sub-operation area of ​​the i-th feasible site, d( ) represents the distance function, R current Indicates the current working position, S i Represents the maximum sub-operation area of ​​the i-th feasible site.

[0098] In the present invention, the cost of moving the robot from the current working position to each sub-working surface is calculated, and the sub-working surface with a shorter distance can be preferentially selected to reduce the moving distance of the robot. This not only saves time, but also reduces energy consumption and equipment wear, and prolongs the service life of the robot.

[0099] S904: Construct a comprehensive evaluation function according to the coverage rate and the mobility cost.

[0100] In a possible implementation, the comprehensive evaluation function is specifically:

[0101]

[0102] Among them, F i represents the comprehensive evaluation value of the largest sub-operation surface of the i-th feasible site, C i represents the coverage of the largest sub-operation surface of the i-th feasible site, D i It represents the moving cost of the robot from the current working position to the largest sub-operation area of ​​the i-th feasible site, α represents the weight coefficient of the coverage rate, and β represents the weight coefficient of the moving cost.

[0103] In the present invention, by calculating the coverage and movement cost of each sub-operation surface in real time and constructing a comprehensive evaluation function, the robot can make the best decision in each operation cycle. This enables the system to have real-time optimization capabilities and can continuously and efficiently operate without relying on manual intervention or fixed paths.

[0104] S905: Determine the maximum sub-operation surface corresponding to the maximum value of the comprehensive evaluation function as the maximum sub-operation surface including the current non-operation area, and record the corresponding site location.

[0105] In the present invention, by selecting the sub-operation surface corresponding to the maximum value of the comprehensive evaluation function, the robot can be prevented from repeatedly entering the same area to operate, thereby reducing the occurrence of repeated operations. This not only improves the overall coverage of the operation, but also ensures the uniformity of the operation quality. At the same time, through the comprehensive evaluation function, the system only needs to calculate and compare the comprehensive value of each sub-operation surface, rather than evaluating multiple complex factors separately. This simplifies the calculation process and enables the system to maintain efficient operation when processing large-scale operation surfaces.

[0106] S10: Save the site location and the corresponding operation area, mark the currently unoperated area as an operated state, and update the site result map.

[0107] In the present invention, by saving the completed site locations and work areas, and marking the corresponding areas as "worked", the system can understand the progress of the work in real time. This can prevent the robot from re-entering the worked area, thereby reducing repeated work and saving time and resources. At the same time, saving the location and work area of ​​each site allows the system or operator to view the work progress at any time. The site result map will be dynamically updated to clearly show which areas have been worked and which areas still need to be processed, which is helpful for managing and optimizing the work process.

[0108] Furthermore, the real-time update of the site result map can help the robot determine which areas have not been processed, ensuring that there are no omissions or blind spots on the work surface. This ensures complete coverage of the entire work surface and avoids omissions.

[0109] From the above description, it can be seen that the ceiling site planning method for spraying and polishing robots provided by the present invention can determine the robot's working surface and movable area by utilizing flexible image processing and sliding window technology, avoiding the limitations of the traditional rectangular segmentation method in processing irregular ceiling surfaces, reducing the high requirements for image segmentation algorithms, and ensuring that the segmentation results can accurately reflect actual work requirements. By accurately calculating the maximum working surface of each site, dynamically traversing the result graph, and updating the working status in real time, it is ensured that each site covers the unoperated area, avoiding repeated operations and site overlap, thereby improving work efficiency and reducing resource waste.

[0110] Reference Manual Attached Figure 2 , showing a structural schematic diagram of a spraying and polishing robot ceiling site planning system provided in an embodiment of the present invention.

[0111] The embodiment of the present invention provides a spraying and polishing robot ceiling site planning system 20, comprising:

[0112] Processor 201;

[0113] The memory 202 stores computer-readable instructions, and when the computer-readable instructions are executed by the processor 201, the above-mentioned spraying and polishing robot ceiling site planning method is implemented.

[0114] From the above description, it can be seen that the ceiling site planning system for spraying and polishing robots provided by the present invention can determine the robot's working surface and movable area by utilizing flexible image processing and sliding window technology, avoiding the limitations of the traditional rectangular segmentation method in processing irregular ceiling surfaces, reducing the high requirements for image segmentation algorithms, and ensuring that the segmentation results can accurately reflect actual work requirements. By accurately calculating the maximum working surface of each site, dynamically traversing the result graph, and updating the working status in real time, it is ensured that each site covers the unoperated area, avoiding repeated operations and site overlap, thereby improving work efficiency and reducing resource waste.

[0115] Unless otherwise specifically stated, the relative arrangement of the parts and steps described in these embodiments, numerical expressions and numerical values ​​do not limit the scope of the present invention. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to the actual proportional relationship. The technology, method and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but in appropriate cases, the technology, method and equipment should be regarded as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0116] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0117] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the devices or elements referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention. The directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for planning ceiling sites of a spraying and polishing robot, characterized in that: include: S1: Acquire ceiling image; S2: using image processing technology to segment the ceiling image and determine the robot's working surface and movable area; S3: Load the process parameters of the robot; S4: Using image processing technology, sliding window processing is performed on the working surface according to the minimum working surface of the robot, and the first feasible position is used as the working starting position of the robot; S5: Based on the operation start position, determine the position of each site using a sliding window processing method; S6: Obtain the maximum sub-operation surface of the robot at each site; S7: Calculate the maximum workable surface of the robot on each of the maximum sub-work surfaces according to the process parameters and the movable area, and add each of the maximum workable surfaces to the site result map; S8: traverse the site result map and select unoperated areas; S9: According to the process parameters of the robot and the maximum working surface, determine the maximum sub-working surface including the current non-working area, and record the corresponding station position; S10: saving the site location and the corresponding operation area, marking the currently unoperated area as an operated state, and updating the site result map; The S9 specifically includes: S901: Analyze the result graph to determine multiple feasible sites for completing the unoperated area; S902: Calculate the coverage rate of the unoperated area by the maximum sub-operation face of each feasible site; S903: Calculate the movement cost of the robot from the current working position to the maximum sub-operation surface of each feasible site; S904: constructing a comprehensive evaluation function according to the coverage rate and the mobility cost; S905: Determine the maximum sub-operation surface corresponding to the maximum value of the comprehensive evaluation function as the maximum sub-operation surface including the current non-operation area, and record the corresponding site location; The calculation formula of the coverage is: ； in, C i Indicates i The coverage rate of the largest sub-operation surface of a feasible site, A u Indicates the area of ​​unused area. S i Indicates i The maximum sub-operation area of ​​a feasible site, Indicates the total area of ​​the unworked area; The calculation formula of the moving cost is: ； in, D i Indicates the robot moves from the current working position to the i The moving cost of the largest sub-operation area of ​​a feasible site, d ( ) represents the distance function, R current Indicates the current working position. S i Indicates i The maximum sub-operation area of ​​a feasible site; The comprehensive evaluation function is specifically: ； in, F i Indicates i The comprehensive evaluation value of the largest sub-operation surface of a feasible site, C i Indicates i The coverage rate of the largest sub-operation surface of a feasible site, α represents the weight coefficient of coverage, β The weight coefficient representing the movement cost.

2. The method for planning ceiling sites of a spraying and polishing robot according to claim 1, characterized in that: The specific method for determining the robot's working surface is as follows: The ceiling image is segmented by using image processing technology, and the pixel value of the robot working surface is marked as 255, and the pixel value of the first remaining area is marked as 0.

3. The method for planning ceiling sites of a spraying and polishing robot according to claim 1, characterized in that: The specific determination of the movable area of ​​the robot is: The ceiling image is segmented by using image processing technology, and the pixel value of the robot movable area is marked as 255, and the pixel value of the second remaining area is marked as 0.

4. The method for planning ceiling sites of a spraying and polishing robot according to claim 1, characterized in that: The process parameters include the length, width, minimum working surface, maximum working surface, the position of the center point on the maximum working surface, and the minimum distance from the movable area of ​​the robot.

5. The method for planning ceiling sites of a spraying and polishing robot according to claim 3, characterized in that: The maximum working surface is divided into a plurality of areas according to the minimum working surface, and the state of each area is marked by binary.

6. A spraying and polishing robot ceiling site planning system, characterized in that: include: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method for planning a ceiling site of a spraying and polishing robot as described in any one of claims 1 to 5 is implemented.

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