Building surface treatment intelligent robot construction technology and system

Abstract

The invention discloses an intelligent robot construction technology and system for building surface treatment, and relates to the technical field of building construction.The technology comprises the following specific processes that three-dimensional contour data collection is conducted, specifically, a building surface is comprehensively scanned through high-precision three-dimensional laser scanning equipment, and space coordinate information of all points on the surface of the building surface is obtained; by integrating three-dimensional laser scanning, image processing and spray gun and polishing control, full-process automatic operation from putty spraying, polishing to paint spraying is achieved, the construction period is greatly shortened, the efficiency advantage is particularly remarkable for large-area or complex-shape building surface treatment, and meanwhile, the construction efficiency is greatly improved. Due to the fact that the robot can work strictly according to the preset program and path and conduct accurate adjustment in combination with real-time feedback data, high consistency and uniformity of construction quality are ensured, and the problems of spraying omission, repeated spraying or uneven grinding and the like possibly occurring in manual construction are effectively avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of building construction, and in particular to an intelligent robot construction process and system for building surface treatment. Background Art

[0002] In the field of construction technology, with the rapid development of science and technology and the continuous improvement of modern construction needs, the treatment of building surfaces has gradually become a critical and complex task. Building surface treatment not only involves multiple processes such as putty spraying, polishing and paint spraying, but also requires efficient construction and stable quality. In recent years, with the rapid development of artificial intelligence, machine vision and automatic control technology, the application of intelligent robots in construction has become possible and gradually demonstrated its huge potential.

[0003] Traditional building surface treatment technology mainly relies on manual operation, which has many disadvantages. First, manual construction is inefficient and difficult to adapt to the needs of large-scale and high-efficiency construction. Second, manual construction is difficult to ensure the consistency and uniformity of construction quality, and often there will be problems such as uneven spraying and uneven grinding, which will affect the overall appearance and service life of the building. In addition, for high or complex-shaped building surfaces, manual construction has great safety risks, such as falling from heights, working in dangerous areas, etc., which pose a serious threat to the life safety of construction workers. At the same time, manual construction also needs to consider factors such as the health status and work intensity of construction workers, which further increases construction costs and management difficulties.

[0004] In view of the shortcomings of traditional building surface treatment technology, the present invention proposes a construction process and system for building surface treatment by an intelligent robot. The system uses three-dimensional laser scanning technology to obtain three-dimensional contour information of the building surface, identifies key features through image processing algorithms, and plans the optimal movement path of the spray gun. At the same time, the movement and spraying parameters of the spray gun are accurately controlled by an intelligent control system to realize the automation of processes such as putty spraying, polishing and paint spraying. Compared with traditional manual construction methods, the present invention has the advantages of high construction efficiency, stable construction quality and low safety risks. Therefore, it is of great significance to develop a construction process and system for building surface treatment by an intelligent robot that can comprehensively realize the above characteristics. Summary of the invention

[0005] The purpose of the present invention is to make up for the deficiencies of the prior art and to provide an intelligent robot construction process and system for building surface treatment, which can realize the automation and intelligence of building surface treatment by integrating multiple processes such as three-dimensional laser scanning, image acquisition and processing, spray gun control, real-time feedback, polishing and paint spraying. It uses a three-dimensional laser scanning module to obtain accurate three-dimensional contour information of the building surface, combines image processing algorithms to identify key features, plans the best movement path of the spray gun, and accurately controls the movement and spraying parameters of the spray gun through an intelligent control system to ensure uniform distribution of paint, smooth polishing, and uniform and beautiful paint spraying. At the same time, the system also has a real-time feedback function, which can monitor and adjust spray parameters in real time to ensure construction quality. In addition, the application of intelligent robots has greatly reduced construction safety risks, improved construction efficiency and quality, and provided new solutions for the intelligent development of the construction industry.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: On the one hand, a construction process of an intelligent robot for building surface treatment includes the following specific processes:

[0007] 3D contour data acquisition: Use high-precision 3D laser scanning equipment to comprehensively scan the building surface and obtain the spatial coordinate information of each point on its surface. The collected coordinate data is sent to the intelligent robot control system in real time via the transmission line. The data is processed using the data fusion algorithm to filter and denoise the data, remove abnormal data, and splice and fuse the scattered data into a complete 3D contour model of the building surface based on the geometric features of the building surface and the distribution law of the scanning points.

[0008] Image recognition of key surface features: The intelligent robot is equipped with a high-resolution camera, and its installation position ensures that it can clearly and comprehensively capture the image of the building surface. During construction, the camera is started to collect images according to the preset shooting frequency and timing, and the collected original images are transmitted to the image processing unit for image preprocessing, feature analysis and recognition, and preliminary path planning operations. For image preprocessing, the original image is converted into a format to be analyzed, and denoising and contrast enhancement operations are performed. For feature analysis and recognition, image recognition technology is used to extract edge, texture and color feature information in the image, and it is compared and matched with the pre-stored building surface feature database to identify key features such as corners, edges, protrusions and depressions. For preliminary path planning, the path planning algorithm is used to plan the initial movement path of the spray gun based on the identified key features and combined with the geometric shape and size information of the building surface;

[0009] Optimal path planning for spray guns: The key feature information identified by the image processing algorithm and the generated preliminary movement path data of the spray gun are integrated with the acquired three-dimensional contour information of the building surface in the intelligent robot control system. The integrated movement path of the spray gun is optimized using the path optimization algorithm based on mathematical optimization theory. Through continuous iterative calculation, the coordinates of the movement path points of the spray gun are adjusted until the optimal movement path that meets the optimization goal is found. The optimized path data is stored in the control system and controls the movement of the spray gun in real time.

[0010] Precise control of spray gun operation: precisely control the movement of the spray gun, receive, store and transmit the optimal movement path data of the spray gun, and generate corresponding motion instructions accordingly. The spray control subunit is responsible for adjusting the spray pressure and speed parameters of the spray gun. The motion control subunit converts the coordinates of each point on the path into the displacement, speed and acceleration motion parameters that the spray gun actually needs to move. By controlling the drive motor or other drive device of the spray gun, the spray gun moves strictly according to the planned path.

[0011] Real-time parameter feedback adjustment: A variety of sensors are installed on and around the spray gun of the intelligent robot, including but not limited to flow sensors, distance sensors and thickness sensors. The flow sensor monitors the flow rate of paint sprayed from the spray gun, the distance sensor monitors the distance between the spray gun and the building surface, and the thickness sensor monitors the thickness of the paint sprayed on the building surface. During the spraying process, each sensor collects corresponding parameter data in real time and transmits these data to the control system of the intelligent robot in real time through the data transmission line. After receiving the real-time data transmitted by the sensor, the control system analyzes it. If any deviation is found, the parameters of the spray gun, including injection pressure, speed and paint flow, are adjusted in real time;

[0012] Automatic grinding process execution: According to the three-dimensional contour information of the building surface and the grinding requirements, the path planning algorithm is used to plan the movement path of the grinding tool. The driving device drives the grinding tool to move at a predetermined speed and direction according to the planned grinding path data. During the grinding process, according to the material and grinding requirements of the building surface, the power and speed of the driving device and the contact pressure parameters of the grinding tool are adjusted to control the grinding depth and accuracy, so that the building surface can achieve a flat and smooth effect;

[0013] Automatic paint spraying operation: According to the 3D contour information, key features and paint spraying requirements of the building surface, the path planning algorithm is used to plan the movement path of the paint spray gun, control the paint spray gun to move according to the planned movement path, and adjust the spray pressure and speed of the paint spray gun according to the type of paint, the material of the building surface and construction requirements to ensure that the paint can be evenly adhered to the building surface. During the spraying process, the spraying parameters can also be monitored through a real-time feedback mechanism, and the parameters of the paint spray gun can be adjusted according to the monitoring results.

[0014] Furthermore, in the three-dimensional contour data acquisition process, according to the geometric features of the building surface and the distribution law of the scanning points, the scattered data are spliced ​​and fused into a complete three-dimensional contour model of the building surface, and the algorithm formula is: Among them, M(x, y, z) represents the final coordinate value of a point (x, y, z) on the building surface in three-dimensional space after fusion, n represents the total number of scan points involved in the fusion of a specific point (x, y, z), i is the index variable, and w i is called the weight coefficient, θ i represents the angle between the scanning light of the i-th scanning point and the normal direction of the building surface at the target point (x, y, z), S i (x, y, z) represents the spatial coordinate value of the original measurement of the i-th scanning point itself, is a distance-based decay function, G(θ i is an adjustment function based on the scan angle.

[0015] Furthermore, in the surface key feature image recognition process, for feature analysis and recognition, image recognition technology is used to extract edge, texture and color feature information in the image, and then the information is compared and matched with the pre-stored building surface feature database to identify key features such as corners, edges, protrusions and depressions. The algorithm formula is: Among them, P(C k ) represents a key feature C on the building surface k The probability value of being identified, m represents the key feature C used to identify k The total number of image feature types considered, j is the index variable used to traverse the key features involved in identifying C k Each image feature, w kj It is called the dynamic weight coefficient, F j (C k ) represents the jth image feature for identifying the key feature C k The characteristic function value of is a decay function based on feature distance, which is used to calculate the distance between the jth image feature and the key feature C. k The distance in the image adjusts the value of its characteristic function.

[0016] Furthermore, in the surface key feature image recognition process, for the preliminary path planning, the path planning algorithm is used to plan the preliminary movement path of the spray gun based on the identified key features and combined with the building surface geometry and size information. The algorithm formula is: Among them, L pαth(i) represents the cost function value of the initial moving path of the spray gun at a certain point i on the building surface, K represents the total number of key features identified in the building surface image, L represents the total number of regions into which the building surface is divided, l: is an index variable, α k It is called the key feature importance weight coefficient, which represents the relative importance weight of the kth key feature in path planning, β k It is called the key feature coverage influence coefficient, E(C k ,i) represents the spray gun at point i for the kth key feature C k The coverage evaluation function value, F(C k ,i) is the key feature direction matching function value, γ l It is called the area coverage weight coefficient, which represents the relative importance weight of the lth divided area in path planning. i , i) represents the spray gun at point i for the lth divided area R ι The coverage evaluation function value of .

[0017] Furthermore, in the spray gun optimal path planning process, the integrated spray gun movement path is optimized using a path optimization algorithm based on mathematical optimization theory, and the calculation formula is: Among them, O path (p) represents the optimal path planning objective function value of the spray gun at the path point p. path (p) value is optimized to determine an optimal spray gun movement path that meets multiple target requirements. T represents the total number of target factors related to spray gun movement and spraying effect considered in the path planning process, t is the index variable, ω t is the weight coefficient of the target factor importance, H t (p) represents the basic evaluation function value of the spray gun at the path point p for the tth target factor, λ t is the dynamic adjustment coefficient of the target factor, I t (p is the dynamic influence function value of the target factor, μ t is the target factor collaborative adjustment coefficient, which is used to adjust the influence of the mutual influence relationship between different target factors on the optimal path planning. t (p) is the value of the synergistic influence function of the target factors, which is used to measure the specific influence of the mutual influence relationship between different target factors on the tth target factor at point p. S represents the total number of fixed constraints on the building surface considered in the path planning process. s is an index variable. is the fixed constraint weight coefficient, K s(p) represents the evaluation function value of the satisfaction degree of the spray gun at the path point p for the sth fixed constraint condition, Q represents the total number of dynamic constraints of the spray gun considered in the path planning process, q is the index variable, θ q is the dynamic constraint weight coefficient, which represents the relative importance weight of the qth dynamic constraint in the optimal path planning. q (p) represents the evaluation function value of the degree of satisfaction of the spray gun at the path point p for the qth dynamic constraint condition.

[0018] Furthermore, in the real-time parameter feedback adjustment process, after the control system receives the real-time data transmitted by the sensor, it analyzes the data. Specifically, the collected flow data is compared with the preset flow standard value. If a deviation occurs, the spray control subunit adjusts the spray pressure or speed of the spray gun according to the deviation size to restore the flow to the standard value. The distance data is compared with the preset optimal distance value. If a deviation occurs, the motion control subunit adjusts the position of the spray gun to maintain an optimal distance between the spray gun and the building surface. The thickness data is compared with the preset spray thickness standard value. If a deviation occurs, the spray control subunit adjusts the spray pressure and speed of the spray gun according to the deviation size, or the motion control subunit adjusts the moving speed of the spray gun to ensure that the spray thickness meets the standard value. Through this real-time feedback and adjustment mechanism, it is guaranteed that the spraying quality always meets the construction requirements.

[0019] Furthermore, in the automatic grinding process, according to the material of the building surface and the grinding requirements, the power and speed of the driving device and the contact pressure parameters of the grinding tool are adjusted to control the grinding depth and accuracy. The power and speed are calculated as follows: Among them, P adj Indicates the adjusted grinding power value, P ref represents the reference value of grinding power obtained from the above grinding parameter database, k P is the grinding power adjustment coefficient, ΔS represents the adjustment amount related to the grinding requirements, R adj Indicates the adjusted grinding speed value, R ref represents the grinding speed reference value obtained from the above grinding parameter database, k R is the grinding speed adjustment coefficient, and the contact pressure parameter calculation formula of the grinding tool is: D = k D ×F c ×t, where D represents the grinding depth, k D is the grinding depth factor, F c It represents the contact pressure between the grinding tool and the building surface, and t represents the duration of grinding.

[0020] Furthermore, in the automatic paint spraying process, the spray pressure and speed of the paint spray gun are adjusted according to the type of paint, the material of the building surface and the construction requirements, and the adjustment formula is: Among them, P adj Indicates the adjusted injection pressure, P ref Indicates the injection pressure reference value queried, k P is the injection pressure adjustment coefficient, ΔT represents the adjustment amount related to the construction progress and specific requirements, V adj Indicates the adjusted injection velocity, V ref Indicates the queried injection speed reference value, k V For the spray speed adjustment coefficient, during the spraying process, the spraying parameters are monitored through a real-time feedback mechanism, and the parameters of the paint spray gun are adjusted according to the monitoring results.

[0021] On the other hand, an intelligent robot construction system for building surface treatment includes the following components:

[0022] 3D laser scanning module: used to obtain the 3D contour information of the construction object and generate a 3D model of the construction object through data fusion algorithm;

[0023] Image acquisition and processing module: including a camera and an image processing algorithm unit. The camera is used to capture the surface image of the spraying object, and the image processing algorithm unit is used to analyze and process the collected image. It includes three sub-steps: image acquisition, image analysis, and path planning. By identifying the key features of the building surface, the movement path of the spray gun is preliminarily planned;

[0024] Spray gun control module: It consists of two parts: motion control and spray control. The motion control part is responsible for accurately controlling the movement of the spray gun along the planned path, while the spray control part is used to adjust the spray gun's spray pressure and speed parameters, thereby improving construction efficiency and quality by optimizing the control strategy;

[0025] Real-time feedback module: Utilize various sensors, including flow sensor, distance sensor and thickness sensor, to monitor various parameters in the spraying process in real time, and feed back the parameters to the control system. The control system adjusts the spray gun parameters in time according to the feedback data to ensure the spraying quality;

[0026] Polishing module: used to automatically polish the building surface. The module is equipped with polishing tools and corresponding drive devices, and can perform polishing according to preset polishing paths and parameters to make the building surface flat and smooth.

[0027] Paint spraying module: used for automatic paint spraying operation. According to the three-dimensional contour information, key features and planned movement path of the spray gun, the paint spray gun is controlled to spray paint evenly.

[0028] Human-computer interaction interface: By designing a human-computer interaction interface, operators can view the real-time progress of construction and various parameter settings through the interface, thereby adjusting the construction process.

[0029] Compared with the prior art, this building surface treatment intelligent robot construction process and system has the following beneficial effects:

[0030] 1. The present invention realizes the full automation of the process from putty spraying, grinding to paint spraying by integrating three-dimensional laser scanning, image processing, spray gun and grinding control, which not only greatly shortens the construction period, but also has a significant efficiency advantage, especially for the surface treatment of large-area or complex-shaped buildings. At the same time, since the robot can operate strictly according to the preset procedures and paths, and make precise adjustments based on real-time feedback data, it ensures the high consistency and uniformity of the construction quality, effectively avoiding the problems of spraying omissions, repeated spraying or uneven grinding that may occur in manual construction, thereby improving the overall quality of the building surface treatment.

[0031] 2. The present invention can replace manual labor in construction of these high-risk areas by adopting intelligent robots, thereby greatly reducing the safety risks in the construction process. In addition, the friendly human-computer interaction interface equipped with the system enables operators to monitor the construction process in real time, including the real-time progress of the construction, various parameter settings, and possible problems, etc., which is convenient for operators to discover problems in time and make adjustments to ensure that the construction process always meets the predetermined quality and safety requirements.

[0032] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 This is a process operation diagram of an intelligent robot construction system for building surface treatment.

[0035] Figure 2 The present invention is a flow chart of a construction process of an intelligent robot for building surface treatment. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] Embodiment 1

[0038] This embodiment describes in detail the specific application of an intelligent robot construction process and system for building surface treatment in the surface treatment of exterior walls of residential buildings. Through close cooperation and collaborative work of all links, the advantages of the intelligent robot construction process and system are fully utilized, effectively improving the construction quality, efficiency and accuracy.

[0039] Move the building surface treatment intelligent robot to the exterior wall construction site of a building in a residential area, and ensure that it is in a stable working state. For example, by adjusting the supporting feet or fixing devices to make it firmly placed on the outdoor ground or on a constructed work platform, check each module of the robot to ensure that the accuracy setting of the 3D laser scanner meets the exterior wall size and accuracy requirements, the camera is clean and focused, the circuit connections of each control unit are normal, and the grinding tools and paint spray guns are not blocked or damaged. According to the characteristics of the exterior walls of the residential area buildings (such as the wall material is mainly concrete, the design style requires a medium degree of surface flatness and smoothness, the paint color is the common off-white, etc.) and construction requirements, set relevant parameters on the human-computer interaction interface.

[0040] The 3D laser scanning unit is started to conduct a comprehensive scan of the building's exterior wall surface. The scanning accuracy is set to the millimeter level. The scanning range covers the entire building's exterior wall area to be processed to avoid scanning blind spots. The scanner emits a laser beam at a fixed frequency and receives the reflected laser signal. The spatial coordinates of each point are calculated based on the principle of laser beam flight time or phase change. The large amount of collected coordinate data is sent to the intelligent robot control system in real time via the transmission line. In the control system, the data fusion algorithm is used to process these raw data. After filtering, denoising, splicing, fusion and other operations, a 3D contour model of the building's exterior wall is generated. The algorithm formula is: Among them, M(x, y, z) represents the final coordinate value of a point (x, y, z) on the building surface in three-dimensional space after fusion, n: represents the total number of scanning points involved in the fusion of a specific point (x, y, z) data, i is the index variable, w i is called the weight coefficient, θ irepresents the angle between the scanning light of the i-th scanning point and the normal direction of the building surface at the target point (x, y, z), S i (x, y, z) represents the spatial coordinate value of the original measurement of the i-th scanning point itself, is a distance-based decay function, G(θ i ) is an adjustment function based on the scanning angle to accurately describe the shape and size of the exterior wall as well as the geometric features of protruding and recessed parts such as balconies and window edges, providing basic data for subsequent construction.

[0041] The camera in the image acquisition and processing unit is turned on, and the image of the exterior wall surface is acquired at the preset shooting frequency. The camera lens parameters are reasonably adjusted according to the distance between the exterior wall and the camera and the required shooting range to ensure that the acquired image has sufficient resolution and color reproduction, and can clearly reflect the actual situation of the exterior wall surface. The acquired original image is transmitted to the image processing algorithm unit and processed according to the three sub-steps of image preprocessing, feature analysis and recognition, and preliminary path planning. In the image preprocessing stage, the image is format converted, denoised, and contrast enhanced to improve the image quality. In the feature analysis and recognition stage, the image recognition technology is used to extract feature information such as edges, textures, and colors in the image, and the image is compared and matched with the pre-stored building exterior wall surface feature database to identify key features such as wall corners, window frame edges, and wall convexities or concave. The algorithm formula is as follows: Among them, P(C k ) represents a key feature C on the building surface k The probability value of being identified, m represents the key feature C used to identify k The total number of image feature types considered, j: is an index variable used to traverse the key features involved in identifying C k Each image feature, w kj It is called the dynamic weight coefficient, F j (C k ) represents the jth image feature for identifying the key feature C k The characteristic function value of is a decay function based on feature distance, which is used to calculate the distance between the jth image feature and the key feature C. k The distance in the image is used to adjust the characteristic function value. In the preliminary path planning stage, the path planning algorithm is used to plan the initial movement path of the spray gun based on the identified key features and the geometric shape and size information of the building's exterior wall. The algorithm formula is: Among them, L path (i) represents the cost function value of the initial moving path of the spray gun at a certain point i on the building surface, K represents the total number of key features identified in the building surface image, L represents the total number of regions into which the building surface is divided, l: is an index variable, αk It is called the key feature importance weight coefficient, which represents the relative importance weight of the kth key feature in path planning, β k It is called the key feature coverage influence coefficient, E(C k ,i) represents the spray gun at point i for the kth key feature C k The coverage evaluation function value, F(C k ,i) is the key feature direction matching function value, γ l It is called the area coverage weight coefficient, which represents the relative importance weight of the lth divided area in path planning. i , i) represents the spray gun at point i for the lth divided area R ι The coverage evaluation function value is used to ensure that the spray gun can reasonably cover the key feature areas and other exterior wall areas to avoid omissions or repeated spraying.

[0042] The key feature information identified by the image processing algorithm and the generated preliminary movement path data of the spray gun are integrated with the three-dimensional contour information of the building exterior wall obtained by the three-dimensional contour data collection in the intelligent robot control system to ensure that the data is processed in the same format and coordinate system for subsequent path optimization operations. The integrated movement path of the spray gun is optimized using the path optimization algorithm based on mathematical optimization theory. The objective function is that the spray gun can evenly and efficiently cover the entire building exterior wall and meet the construction quality requirements. At the same time, the kinematic characteristics of the spray gun, the spray characteristics of the paint, and the actual situation of the building exterior wall are considered. Through continuous iterative calculation, the coordinates of the movement path points of the spray gun are adjusted until the optimal movement path that meets the optimization goal is found, and it is stored in the control system and transmitted to the spray gun control unit in real time. The calculation formula is: Among them, O path (p) represents the optimal path planning objective function value of the spray gun at the path point p. path (p) value is optimized to determine an optimal spray gun movement path that meets multiple target requirements. T represents the total number of target factors related to spray gun movement and spraying effect considered in the path planning process. t: is the index variable, ω t is the weight coefficient of the target factor importance, H t (p) represents the basic evaluation function value of the spray gun at the path point p for the tth target factor, λ t is the dynamic adjustment coefficient of the target factor, I t (p is the dynamic influence function value of the target factor, μ t is the target factor collaborative adjustment coefficient, which is used to adjust the influence of the mutual influence relationship between different target factors on the optimal path planning. t(p) is the value of the synergistic influence function of the target factors, which is used to measure the specific influence of the mutual influence relationship between different target factors on the tth target factor at point p. S represents the total number of fixed constraints on the building surface considered in the path planning process. s is an index variable. is the fixed constraint weight coefficient, K s (p) represents the evaluation function value of the satisfaction degree of the spray gun at the path point p for the sth fixed constraint condition, Q represents the total number of dynamic constraints of the spray gun considered in the path planning process, q is the index variable, θ q is the dynamic constraint weight coefficient, which represents the relative importance weight of the qth dynamic constraint in the optimal path planning. q (p) represents the evaluation function value of the degree of satisfaction of the spray gun at the path point p for the qth dynamic constraint condition.

[0043] After the spray gun control unit of the intelligent robot receives the optimal movement path data of the spray gun, the motion control subunit and the spray control subunit start working. The motion control subunit converts the coordinates of each point on the path into the displacement, speed, acceleration and other motion parameters that the spray gun actually needs to move. By controlling the drive motor or other drive device of the spray gun, the movement of the spray gun is accurately controlled according to these motion parameters to ensure that the spray gun moves strictly along the planned path and the error is controlled within the allowable range. During the movement, the kinematic characteristics of the spray gun are considered to avoid excessive acceleration and deceleration to prevent uneven spraying or splashing of the paint. The spray control subunit adjusts the spray gun according to the type of paint (exterior wall putty and latex The spray pressure and speed of the spray gun are adjusted according to factors such as the type of paint and the material of the building's exterior wall preset before construction. First, the corresponding spray pressure and speed reference values ​​are queried from the pre-stored paint parameter database. Then, based on the current construction progress and specific requirements, the queried reference values ​​are fine-tuned to ensure that the paint can be evenly adhered to the surface of the building's exterior wall. During the adjustment process, the pressure sensor and speed sensor installed on the spray gun monitor the actual values ​​of the spray pressure and speed in real time, and feed them back to the spray control subunit for real-time adjustment to ensure the stability and accuracy of the spray pressure and speed.

[0044] A variety of sensors are installed on and around the spray gun of the intelligent robot, including flow sensors, distance sensors, thickness sensors, etc. The flow sensor monitors the flow rate of paint sprayed from the spray gun, the distance sensor monitors the distance between the spray gun and the surface of the building's exterior wall, and the thickness sensor monitors the thickness of the paint sprayed on the surface of the building's exterior wall. These sensors have sufficient accuracy and reliability to accurately obtain relevant parameter information. During the spraying process, each sensor collects corresponding parameter data in real time and transmits this data to the control system of the intelligent robot in real time through the data transmission line. The transmitted data should be kept complete and accurate to avoid data loss or distortion. After receiving the real-time data transmitted by the sensor, the control system analyzes it, for example, the collected flow rate The data is compared with the preset flow rate standard value. If there is a deviation, the spray control subunit adjusts the spray gun's spray pressure or speed according to the deviation to restore the flow rate to the standard value. Similarly, the distance data is compared with the preset optimal distance value. If there is a deviation, the motion control subunit adjusts the position of the spray gun to keep the spray gun at the optimal distance from the building's exterior wall surface. The thickness data is compared with the preset spray thickness standard value. If there is a deviation, the spray control subunit adjusts the spray gun's spray pressure and speed according to the deviation, or the motion control subunit adjusts the spray gun's moving speed to ensure that the spray thickness meets the standard value. Through this real-time feedback and adjustment mechanism, the spraying quality is guaranteed to always meet the construction requirements.

[0045] After the putty is sprayed, wait for it to dry to a certain extent, and then start the grinding unit. The grinding tool of the grinding unit selects a grinding wheel of appropriate particle size according to the material of the building's exterior wall. The driving device should have sufficient power and speed adjustment range. According to the three-dimensional contour information of the building's exterior wall and the grinding requirements, the path planning algorithm is used to plan the moving path of the grinding tool to ensure that the grinding tool can evenly and efficiently cover the entire building's exterior wall to avoid omissions or repeated grinding. Start the grinding module, and the driving device drives the grinding tool to move at a predetermined speed and direction according to the planned grinding path data. During the grinding process, according to the material and grinding requirements of the building's exterior wall, the power and speed of the driving device and the contact pressure parameters of the grinding tool are adjusted to control the grinding depth and accuracy, so that the surface of the building's exterior wall achieves a smooth effect. The calculation formula for its power and speed is, Among them, P adj Indicates the adjusted grinding power value, P ref represents the reference value of grinding power obtained from the above grinding parameter database, k P is the grinding power adjustment coefficient, ΔS represents the adjustment amount related to the grinding requirements, R adj Indicates the adjusted grinding speed value, R ref represents the grinding speed reference value obtained from the above grinding parameter database, kR is the grinding speed adjustment coefficient, and the contact pressure parameter calculation formula of the grinding tool is: D = k D ×F c ×t, where D represents the grinding depth, k D is the grinding depth factor, F c It represents the contact pressure between the grinding tool and the building surface, and t represents the duration of grinding.

[0046] After polishing, the paint spraying unit is started. According to the three-dimensional contour information, key features and paint spraying requirements of the building's exterior wall (such as evenly and beautifully covering the exterior wall surface, achieving the color and gloss required by the design, etc.), the path planning algorithm is used to plan the movement path of the paint spray gun to ensure that the paint spray gun can evenly and efficiently cover the entire building's exterior wall to avoid omissions or repeated spraying. The paint spray gun is started and controlled to move along the planned movement path. According to factors such as the type of paint (exterior wall special latex paint), the material of the building's exterior wall (concrete) and construction requirements, the spray pressure and speed of the paint spray gun are adjusted to ensure that the paint can be evenly attached to the surface of the building's exterior wall. During the spraying process, the adjustment formula is: Among them, P adj Indicates the adjusted injection pressure, P ref Indicates the injection pressure reference value queried, k P is the injection pressure adjustment coefficient, ΔT represents the adjustment amount related to the construction progress and specific requirements, V adj Indicates the adjusted injection velocity, V ref Indicates the queried injection speed reference value, k V It is the injection speed adjustment coefficient. During the spraying process, the spraying parameters are monitored through the real-time feedback mechanism, and the parameters of the paint spray gun are adjusted according to the monitoring results. At the same time, the spraying parameters are monitored through the real-time feedback mechanism, and the parameters of the paint spray gun are adjusted according to the monitoring results to ensure the paint spraying quality.

[0047] To sum up, in the application of exterior wall surface treatment of residential buildings, the present invention realizes the automation, precision and efficiency of exterior wall surface treatment of buildings through close cooperation of various links, rational use of algorithm formulas and parameters, effectively improves the construction quality and efficiency, and meets the diverse needs of residential buildings for exterior wall surface treatment.

[0048] Embodiment 2

[0049] This embodiment describes in detail a specific application of an intelligent robot construction process and system for building surface treatment in the surface treatment of interior walls and ceilings of large commercial buildings. By applying the present invention, the quality and efficiency of interior decoration of commercial buildings are improved.

[0050] During the construction preparation stage, the intelligent robot is first properly placed in the indoor area to be constructed in a large commercial building to ensure that it is in a stable working state. Subsequently, a comprehensive and detailed inspection is carried out on each key module of the robot to ensure that each component functions normally and that the parameter settings meet the requirements of the size, precision and decoration style of the indoor walls and ceilings. At the same time, based on the interior characteristics of the commercial building, such as the walls are mainly made of gypsum boards, the ceilings may be metal gussets or gypsum board ceilings, and there are various paint color requirements, the relevant construction parameters are accurately set in the human-computer interaction interface, including paint type, spray thickness, grinding accuracy and paint colors corresponding to different areas, etc., providing clear operating instructions and basic settings for subsequent construction processes.

[0051] In the 3D contour data collection stage, the 3D laser scanning unit is started to conduct a comprehensive scan of the indoor wall and ceiling surfaces. The scanning accuracy reaches the millimeter level, and the coverage range covers the entire floor of the area to be processed, eliminating scanning blind spots. After obtaining the spatial coordinates of each point based on the laser beam flight time or phase change principle, the creative data fusion algorithm formula is used to process the large amount of collected coordinate data.

[0052] In the stage of surface key feature image recognition, with the help of the camera in the image acquisition and processing unit, images of the indoor wall and ceiling surfaces are collected according to the preset shooting frequency. During the acquisition process, the camera lens parameters are reasonably adjusted according to the characteristics of the indoor environment to ensure that the acquired images have sufficient resolution and color reproduction. The collected original images then enter the image processing algorithm unit, and go through three sub-steps: image preprocessing, feature analysis and recognition, and preliminary path planning. In the preliminary path planning link, a specially designed preliminary path planning algorithm formula is used to comprehensively consider the importance of key features, coverage, and regional coverage after dividing the indoor wall and ceiling surfaces into regions. Factors such as the area coverage situation, scientifically plan the initial movement path of the spray gun, and reasonably set the weight coefficient of each key feature, the coverage influence coefficient, and the coverage weight coefficient of each divided area, and combine the corresponding coverage evaluation function and direction matching function to ensure that the spray gun can comprehensively and reasonably cover the key feature areas and other areas of the indoor walls and ceilings, effectively avoiding omissions or duplications in spraying, and significantly improving construction efficiency and quality.

[0053] For the optimal path planning process of the spray gun, the key feature information identified by the image processing algorithm and the generated preliminary movement path data of the spray gun are integrated with the three-dimensional contour information of the indoor wall and ceiling obtained by the three-dimensional contour data acquisition, so that they are in the same format and coordinate system for subsequent path optimization operations. Then, the integrated movement path of the spray gun is optimized using the optimal path planning algorithm formula of the spray gun based on multi-objective optimization and dynamic constraint adjustment. By considering multiple target factors related to the spray gun movement and the spraying effect, such as spraying uniformity, path length, and avoiding collision with indoor obstacles (such as lamps, air conditioners, etc.), the optimal path planning algorithm formula of the spray gun is optimized. At the same time, the actual conditions of the building's interior walls and ceilings (such as shape, size, surface roughness, etc.) and the kinematic characteristics of the spray gun (such as speed, acceleration limits, etc.) and the spray characteristics of the paint (such as spray range, the relationship between spray pressure and speed, etc.) are fully considered. By scientifically and reasonably setting the importance weight coefficient, dynamic adjustment coefficient, synergistic adjustment coefficient and other parameters of each target factor, as well as the corresponding basic evaluation function, dynamic influence function and synergistic influence function, etc., after continuous iterative calculation, the optimal spray gun movement path that meets multiple requirements is accurately determined, further improving the accuracy and efficiency of construction.

[0054] In terms of precise control of spray gun operations, when the spray gun control unit of the intelligent robot receives the optimal movement path data of the spray gun, the motion control subunit and the spray control subunit work together. The motion control subunit accurately converts the coordinates of each point on the path into the displacement, speed, acceleration and other motion parameters that the spray gun actually needs to move based on the path point coordinate conversion formula, and combines the speed adjustment formula that considers the kinematic characteristics of the spray gun to ensure that the spray gun moves smoothly during the movement process, strictly follows the planned path, and the error is controlled within the allowable range (such as millimeter level). The spray control subunit first adjusts the speed according to the type of paint (such as indoor special putty and latex paint), the material of the building's interior walls and ceilings (such as gypsum The corresponding spray pressure and speed reference values ​​are queried from the pre-stored paint parameter database based on factors such as the current construction progress and specific requirements (such as spray thickness, uniformity requirements, etc.). Subsequently, the queried reference values ​​are fine-tuned through a specific fine-tuning formula to ensure that the paint can be evenly adhered to the interior walls and ceiling surfaces of the building. During the adjustment process, the actual values ​​of the spray pressure and speed are monitored in real time with the help of the pressure sensor and speed sensor installed on the spray gun, and the spray pressure and speed are adjusted in real time according to the sensor feedback based on the real-time adjustment formula, thereby ensuring that the spray pressure and speed of the spray gun are stable and accurate, and achieving precise spraying operation control.

[0055] For the real-time parameter feedback adjustment mechanism, a variety of high-precision sensors are installed on and around the spray gun of the intelligent robot, including flow sensors, distance sensors, thickness sensors, etc., which are used to collect parameter data such as the flow rate of paint sprayed from the spray gun, the distance between the spray gun and the indoor wall and ceiling surface, and the thickness of the paint sprayed on the surface in real time. These sensors transmit the collected data to the control system of the intelligent robot in real time. After receiving the data, the control system analyzes and compares it according to the preset standard value. Once it is found that the collected parameter data deviates from the preset standard value, the position, injection pressure and speed of the spray gun are adjusted in time according to the specific situation of the deviation through the corresponding adjustment formula. For example, if the flow sensor detects a flow deviation, the injection pressure or speed of the spray gun is adjusted through the spray control subunit; if the distance sensor detects a distance deviation, the position of the spray gun is adjusted through the motion control subunit; if the thickness sensor shows a thickness deviation, the injection pressure and speed of the spray gun are adjusted through the spray control subunit according to the deviation size, or the moving speed of the spray gun is adjusted through the motion control subunit. Through this real-time feedback and adjustment mechanism, it is ensured that the spraying quality always meets the construction requirements, and the stability of the construction quality is effectively guaranteed.

[0056] In the automatic grinding process execution stage, after the putty is sprayed, the waiting time is determined according to the drying characteristics of the indoor special putty and the environmental conditions at that time. After it is dried to a certain degree, the grinding unit is started. According to the different materials of the indoor walls and ceilings, such as gypsum board walls, finer sandpaper is used, and metal gusset ceilings use special flexible grinding sheets. Select the appropriate grinding tool. According to the three-dimensional contour information of the building's indoor walls and ceilings and the grinding requirements (such as making the surface roughness of the walls and ceilings reach a specific value, ensuring that the surface is flat and smooth to meet the standards of high-end decoration of commercial buildings), the path planning algorithm formula is used again to plan the moving path of the grinding tool. During the grinding process, by adjusting the power and speed of the drive device and the contact pressure of the grinding tool and other parameters, according to the relevant formulas for controlling the grinding depth and accuracy, the grinding depth and accuracy are effectively controlled, so that the surface of the building's indoor walls and ceilings can achieve a smooth effect, meeting the high standards for surface quality of large commercial building interior decoration.

[0057] After polishing is completed, the paint spraying unit is started. According to the three-dimensional contour information, key features and paint spraying requirements of the building's interior walls and ceilings, the path planning algorithm is used to plan the movement path of the paint spray gun to ensure that the paint spray gun can evenly and efficiently cover the entire interior walls and ceilings to avoid omissions or repeated spraying. The paint spray gun is started and controlled to move along the planned movement path. The spray pressure and speed of the paint spray gun are adjusted according to factors such as the type of paint, the material of the building's interior walls and ceilings, and construction requirements to ensure that the paint can be evenly attached to the surface of the building's interior walls and ceilings. During the spraying process, the spraying parameters can also be monitored through a real-time feedback mechanism, and the parameters of the paint spray gun can be adjusted according to the monitoring results to ensure the quality of paint spraying.

[0058] In summary, in the entire process of surface treatment of interior walls and ceilings of large commercial buildings, the present invention closely cooperates with each link to achieve efficient and accurate execution of a series of operations from data collection, path planning to precise operation control and polishing processing, which greatly improves the quality and efficiency of interior decoration of commercial buildings and fully demonstrates its excellent application value in the field of interior decoration of commercial buildings.

[0059] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A construction process for building surface treatment by an intelligent robot, characterized in that: The process includes the following specific steps: 3D contour data acquisition: Use high-precision 3D laser scanning equipment to comprehensively scan the building surface and obtain the spatial coordinate information of each point on its surface. The collected coordinate data is sent to the intelligent robot control system in real time via the transmission line. The data is processed using the data fusion algorithm to filter and denoise the data, remove abnormal data, and splice and fuse the scattered data into a complete 3D contour model of the building surface based on the geometric features of the building surface and the distribution law of the scanning points. Image recognition of key surface features: The intelligent robot is equipped with a high-resolution camera, and its installation position ensures that it can clearly and comprehensively capture the image of the building surface. During construction, the camera is started to collect images according to the preset shooting frequency and timing, and the collected original images are transmitted to the image processing unit for image preprocessing, feature analysis and recognition, and preliminary path planning operations. For image preprocessing, the original image is converted into a format to be analyzed, and denoising and contrast enhancement operations are performed. For feature analysis and recognition, image recognition technology is used to extract edge, texture and color feature information in the image, and it is compared and matched with the pre-stored building surface feature database to identify key features such as corners, edges, protrusions and depressions. For preliminary path planning, the path planning algorithm is used to plan the initial movement path of the spray gun based on the identified key features and combined with the geometric shape and size information of the building surface; Optimal path planning for spray guns: The key feature information identified by the image processing algorithm and the generated preliminary movement path data of the spray gun are integrated with the acquired three-dimensional contour information of the building surface in the intelligent robot control system. The integrated movement path of the spray gun is optimized using the path optimization algorithm based on mathematical optimization theory. Through continuous iterative calculation, the coordinates of the movement path points of the spray gun are adjusted until the optimal movement path that meets the optimization goal is found. The optimized path data is stored in the control system and controls the movement of the spray gun in real time. Precise control of spray gun operation: precisely control the movement of the spray gun, receive, store and transmit the optimal movement path data of the spray gun, and generate corresponding motion instructions accordingly. The spray control subunit is responsible for adjusting the spray pressure and speed parameters of the spray gun. The motion control subunit converts the coordinates of each point on the path into the displacement, speed and acceleration motion parameters that the spray gun actually needs to move. By controlling the drive motor or other drive device of the spray gun, the spray gun moves strictly according to the planned path. Real-time parameter feedback adjustment: A variety of sensors are installed on and around the spray gun of the intelligent robot, including but not limited to flow sensors, distance sensors and thickness sensors. The flow sensor monitors the flow rate of paint sprayed from the spray gun, the distance sensor monitors the distance between the spray gun and the building surface, and the thickness sensor monitors the thickness of the paint sprayed on the building surface. During the spraying process, each sensor collects corresponding parameter data in real time and transmits these data to the control system of the intelligent robot in real time through the data transmission line. After receiving the real-time data transmitted by the sensor, the control system analyzes it. If any deviation is found, the parameters of the spray gun, including injection pressure, speed and paint flow, are adjusted in real time; Automatic grinding process execution: According to the three-dimensional contour information of the building surface and the grinding requirements, the path planning algorithm is used to plan the movement path of the grinding tool. The driving device drives the grinding tool to move at a predetermined speed and direction according to the planned grinding path data. During the grinding process, according to the material and grinding requirements of the building surface, the power and speed of the driving device and the contact pressure parameters of the grinding tool are adjusted to control the grinding depth and accuracy, so that the building surface can achieve a flat and smooth effect; Automatic paint spraying operation: According to the 3D contour information, key features and paint spraying requirements of the building surface, the path planning algorithm is used to plan the movement path of the paint spray gun, control the paint spray gun to move according to the planned movement path, and adjust the spray pressure and speed of the paint spray gun according to the type of paint, the material of the building surface and construction requirements to ensure that the paint can be evenly adhered to the building surface. During the spraying process, the spraying parameters can also be monitored through a real-time feedback mechanism, and the parameters of the paint spray gun can be adjusted according to the monitoring results.

2. The intelligent robot construction process for building surface treatment according to claim 1 is characterized in that: In the three-dimensional contour data acquisition process, according to the geometric features of the building surface and the distribution law of the scanning points, the scattered data are spliced ​​and fused into a complete three-dimensional contour model of the building surface. The algorithm formula is: Among them, M(x, y, z) represents the final coordinate value of a point (x, y, z) on the building surface in three-dimensional space after fusion, n represents the total number of scanning points involved in the fusion of a specific point (x, y, z), i is the index variable, and w i is called the weight coefficient, θ i represents the angle between the scanning light of the i-th scanning point and the normal direction of the building surface at the target point (x, y, z), S i (x, y, z) represents the spatial coordinate value of the original measurement of the i-th scanning point itself, is a distance-based decay function, G(θ i is an adjustment function based on the scan angle.

3. The intelligent robot construction process for building surface treatment according to claim 1 is characterized in that: In the surface key feature image recognition process, for feature analysis and recognition, image recognition technology is used to extract edge, texture and color feature information in the image, and then the information is compared and matched with the pre-stored building surface feature database to identify key features such as corners, edges, protrusions and depressions. The algorithm formula is: Among them, P(C k ) represents a key feature C on the building surface k The probability value of being identified, m represents the key feature C used to identify k The total number of image feature types considered, j is the index variable used to traverse the key features involved in identifying C k Each image feature, w kj It is called the dynamic weight coefficient, F j (C k ) represents the jth image feature for identifying the key feature C k The characteristic function value of is a decay function based on feature distance, which is used to calculate the distance between the jth image feature and the key feature C. k The distance in the image adjusts the value of its characteristic function.

4. The intelligent robot construction process for building surface treatment according to claim 1 is characterized in that: In the surface key feature image recognition process, for the preliminary path planning, the path planning algorithm is used to plan the preliminary movement path of the spray gun based on the identified key features and combined with the building surface geometry and size information. The algorithm formula is: Among them, L path (i) represents the cost function value of the initial moving path of the spray gun at a certain point i on the building surface, K represents the total number of key features identified in the building surface image, L represents the total number of regions into which the building surface is divided, l is an index variable, and α k It is called the key feature importance weight coefficient, which represents the relative importance weight of the kth key feature in path planning, β k It is called the key feature coverage influence coefficient, E(C k ,i) represents the spray gun at point i for the kth key feature C k The coverage evaluation function value, F(C k ,i) is the key feature direction matching function value, γ l It is called the area coverage weight coefficient, which represents the relative importance weight of the lth divided area in path planning. i , i) represents the spray gun at point i for the lth divided area R ι The coverage evaluation function value of .

5. The intelligent robot construction process for building surface treatment according to claim 1 is characterized in that: In the spray gun optimal path planning process, the integrated spray gun movement path is optimized using a path optimization algorithm based on mathematical optimization theory, and the calculation formula is: Among them, O path (p) represents the optimal path planning objective function value of the spray gun at the path point p. path (p) value is optimized to determine an optimal spray gun movement path that meets multiple target requirements. T represents the total number of target factors related to spray gun movement and spraying effect considered in the path planning process, t is the index variable, ω t is the weight coefficient of the target factor importance, H t (p) represents the basic evaluation function value of the spray gun at the path point p for the tth target factor, λ t is the dynamic adjustment coefficient of the target factor, I t (p) is the dynamic influence function value of the target factor, μ t is the target factor collaborative adjustment coefficient, which is used to adjust the influence of the mutual influence relationship between different target factors on the optimal path planning. t (p) is the value of the synergistic influence function of the target factors, which is used to measure the specific influence of the mutual influence relationship between different target factors on the tth target factor at point p. S represents the total number of fixed constraints on the building surface considered in the path planning process. s is an index variable. is the fixed constraint weight coefficient, K s (p) represents the evaluation function value of the satisfaction degree of the spray gun at the path point p for the sth fixed constraint condition, Q represents the total number of dynamic constraints of the spray gun considered in the path planning process, q is the index variable, θ q is the dynamic constraint weight coefficient, which represents the relative importance weight of the qth dynamic constraint in the optimal path planning. q (p) represents the evaluation function value of the degree of satisfaction of the spray gun at the path point p for the qth dynamic constraint condition.

6. The intelligent robot construction process for building surface treatment according to claim 1 is characterized in that: In the real-time parameter feedback adjustment process, after the control system receives the real-time data transmitted by the sensor, it analyzes the data. Specifically, the collected flow data is compared with the preset flow standard value. If a deviation occurs, the spray pressure or speed of the spray gun is adjusted by the spray control subunit according to the deviation size to restore the flow to the standard value. The distance data is compared with the preset optimal distance value. If a deviation occurs, the position of the spray gun is adjusted by the motion control subunit to keep the spray gun at an optimal distance from the building surface. The thickness data is compared with the preset spray thickness standard value. If a deviation occurs, the spray pressure and speed of the spray gun are adjusted by the spray control subunit according to the deviation size, or the movement speed of the spray gun is adjusted by the motion control subunit to ensure that the spray thickness meets the standard value. Through this real-time feedback and adjustment mechanism, it is guaranteed that the spraying quality always meets the construction requirements.

7. The intelligent robot construction process for building surface treatment according to claim 1 is characterized in that: In the automatic grinding process, according to the material and grinding requirements of the building surface, the power and speed of the driving device and the contact pressure parameters of the grinding tool are adjusted to control the grinding depth and accuracy. The power and speed are calculated as follows: Among them, P adj Indicates the adjusted grinding power value, P ref represents the reference value of grinding power obtained from the above grinding parameter database, k P is the grinding power adjustment coefficient, ΔS represents the adjustment amount related to the grinding requirements, R adj Indicates the adjusted grinding speed value, R ref represents the grinding speed reference value obtained from the above grinding parameter database, k R is the grinding speed adjustment coefficient, and the contact pressure parameter calculation formula of the grinding tool is: D = k D ×F c ×t, where D represents the grinding depth, k D is the grinding depth factor, F c It represents the contact pressure between the grinding tool and the building surface, and t represents the duration of grinding.

8. The intelligent robot construction process for building surface treatment according to claim 1 is characterized in that: In the automatic paint spraying process, the spray pressure and speed of the paint spray gun are adjusted according to the type of paint, the material of the building surface and the construction requirements. The adjustment formula is: Among them, P adj Indicates the adjusted injection pressure, P ref Indicates the injection pressure reference value queried, k P is the injection pressure adjustment coefficient, ΔT represents the adjustment amount related to the construction progress and specific requirements, V adj Indicates the adjusted injection velocity, V ref Indicates the queried injection speed reference value, k V For the spray speed adjustment coefficient, during the spraying process, the spraying parameters are monitored through a real-time feedback mechanism, and the parameters of the paint spray gun are adjusted according to the monitoring results.

9. An intelligent robot construction system for building surface treatment, applicable to an intelligent robot construction process for building surface treatment as claimed in any one of claims 1 to 8, characterized in that: The system comprises the following components: 3D laser scanning module: used to obtain the 3D contour information of the construction object and generate a 3D model of the construction object through data fusion algorithm; Image acquisition and processing module: including a camera and an image processing algorithm unit. The camera is used to capture the surface image of the spraying object, and the image processing algorithm unit is used to analyze and process the collected image. It includes three sub-steps: image acquisition, image analysis, and path planning. By identifying the key features of the building surface, the movement path of the spray gun is preliminarily planned; Spray gun control module: It consists of two parts: motion control and spray control. The motion control part is responsible for accurately controlling the movement of the spray gun along the planned path, while the spray control part is used to adjust the spray gun's spray pressure and speed parameters, thereby improving construction efficiency and quality by optimizing the control strategy; Real-time feedback module: Utilize various sensors, including flow sensor, distance sensor and thickness sensor, to monitor various parameters in the spraying process in real time, and feed back the parameters to the control system. The control system adjusts the spray gun parameters in time according to the feedback data to ensure the spraying quality; Polishing module: used to automatically polish the building surface. The module is equipped with polishing tools and corresponding drive devices, and can perform polishing according to preset polishing paths and parameters to make the building surface flat and smooth. Paint spraying module: used for automatic paint spraying operation. According to the three-dimensional contour information, key features and planned movement path of the spray gun, the paint spray gun is controlled to spray paint evenly. Human-computer interaction interface: By designing a human-computer interaction interface, operators can view the real-time progress of construction and various parameter settings through the interface, thereby adjusting the construction process.

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