Coating preparation system and method

Abstract

The invention relates to the technical field of coating preparation, and provides a coating preparation system and method.The coating preparation system comprises an operation platform, a mobile robot, a main cooperative mechanical arm and a control unit; wherein the operating platform is provided with a container storage area and a coating preparation area; the mobile robot is arranged on the operation platform, the mobile robot can move between the container storage area and the coating preparation area, and a grabbing structure used for grabbing the container is arranged on the mobile robot; the main cooperative mechanical arm is arranged on the operation platform and corresponds to the coating preparation area, and the main cooperative mechanical arm is provided with a clamping device used for clamping a base material; the control unit is in communication connection with the mobile robot and the main cooperative mechanical arm. The mobile robot in the system can grab and move the container, and the main cooperative mechanical arm is arranged, so that a base material to be coated is conveniently clamped and moved for coating. According to the system, high efficiency, accuracy and consistency of the coating preparation process are realized, and the development of a coating technology can be promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of coating preparation, and in particular to a coating preparation system and method. Background Art

[0002] Among various coating technologies, the layer-by-layer self-assembly method has become a prominent method due to its versatility, simplicity and cost-effectiveness. The layer-by-layer self-assembly method was first proposed by Decher et al. in 1990. Through the control of material properties and assembly conditions, precise control and optimization of coating assembly can be achieved. Recently, an innovative coating preparation method uses the self-healing effect of damaged coatings through biomineralization by Shewanella putrefaciens. This innovative method not only repairs the damage of the coating, but also enhances its corrosion resistance, providing a new avenue for the development of antimicrobial coatings. By exploring the use of this advanced method to prepare antimicrobial coatings, it aims to slow the spread of pathogens and enhance public health safety.

[0003] At present, coating preparation is mainly carried out through manual experiments, which has low precision and heavy workload, limiting the rapid development of coating technology. Summary of the invention

[0004] In order to solve the technical problems of low precision and large workload in the prior art, which restrict the rapid development of coating technology, the embodiment of the present invention provides a coating preparation system and method. The technical solution is as follows:

[0005] In one aspect, a coating preparation system is provided, the system comprising: an operating platform, a mobile robot, a main collaborative robot arm and a control unit;

[0006] Wherein, the operating platform has a container storage area and a coating preparation area;

[0007] The mobile robot is arranged on the operating platform, and the mobile robot can move between the container storage area and the coating preparation area, and the mobile robot is provided with a grasping structure for grasping a container;

[0008] The main collaborative robot arm is arranged on the operating platform and corresponds to the coating preparation area, and the main collaborative robot arm is provided with a clamp for clamping the substrate;

[0009] The control unit is communicatively connected with the mobile robot and the main collaborative robot arm.

[0010] Optionally, a visual recognition unit is provided on the main collaborative robot arm, and the visual recognition unit is communicatively connected with the control unit for identifying the substrate and the liquid level in the container.

[0011] Optionally, a contact detection device is provided on the main collaborative robot arm, and the contact detection device is communicatively connected to the control unit for detecting whether there is contact between the main collaborative robot arm and the container.

[0012] Optionally, the system further comprises:

[0013] A water drop angle detection device, wherein the water drop angle detection device is arranged on the operating platform;

[0014] A secondary collaborative robotic arm, the secondary collaborative robotic arm is arranged on the operating platform and corresponds to the water drop angle detection device, and the secondary collaborative robotic arm is provided with a pipette gun.

[0015] Optionally, the system further includes: a display unit and an input unit, and both the display unit and the input unit are communicatively connected to the control unit.

[0016] In another aspect, a method for preparing a coating is provided, the method comprising:

[0017] Controlling the mobile robot to move a plurality of containers from the container storage area to the coating preparation area, wherein the plurality of containers are respectively filled with a preset polyanion solution, a first deionized water, a polycation solution, and a second deionized water;

[0018] Control the main collaborative robot arm to grab the substrate;

[0019] The main collaborative robot arm is controlled to drive the substrate to repeatedly prepare the coating, wherein each coating preparation includes: sequentially immersing the substrate in a polyanion solution, a first deionized water, a polycation solution, and a second deionized water for corresponding preset time periods.

[0020] Optionally, controlling the main collaborative robot arm to grasp the substrate comprises:

[0021] Determine substrate location;

[0022] The main collaborative robot arm is controlled to move to the substrate position and the substrate is grasped by a gripper.

[0023] Optionally, the sequentially immersing the substrate in the polyanion solution, the first deionized water, the polycation solution and the second deionized water for corresponding preset time periods all include:

[0024] Determine the container location;

[0025] According to the position of the container, controlling the main collaborative robot arm to move above the container;

[0026] Determining the liquid level in the container based on the visual recognition unit;

[0027] Determine the descending distance according to the liquid level in the container;

[0028] Based on the descending distance, controlling the main collaborative robot arm to drive the substrate to descend so that the substrate is immersed in the solution in the container;

[0029] After soaking for a preset time, the main collaborative robot arm is controlled to drive the substrate to rise.

[0030] Optionally, the method further comprises:

[0031] Control the main collaborative robot arm to clamp the substrate and place it at a preset position of the water drop angle detection device;

[0032] Controlling the pipette held by the secondary cooperative robot arm to absorb water and drop water drops on the substrate;

[0033] The water drop angle of the substrate is detected based on the water drop angle detection device.

[0034] Optionally, the method further comprises:

[0035] Based on the received input information, the virtual simulation model is run and simulation data is obtained;

[0036] comparing the water drop angles of the plurality of substrates with the simulation data;

[0037] According to the comparison results, the coating preparation parameters are optimized.

[0038] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0039] The coating preparation system provided by the embodiment of the present invention can grab and move containers by setting a mobile robot, thereby improving work efficiency and reducing the complexity and risk of manual operation. By setting a main collaborative robot arm, it is convenient to clamp and move the substrate to be coated so that it can be accurately placed in a predetermined position for coating. Through highly automated equipment and precise control systems, the workload of manual labor is reduced, and the efficiency, precision and consistency of the coating preparation process are achieved, which can promote the development of coating technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1is a structural schematic diagram of a coating preparation system provided by an embodiment of the present invention;

[0042] Figure 2 This is one of the flow charts of a coating preparation method provided by an embodiment of the present invention;

[0043] Figure 3 This is the second flow chart of a coating preparation method provided by an embodiment of the present invention;

[0044] Figure 4 This is a third flow chart of a coating preparation method provided by an embodiment of the present invention;

[0045] Figure 5 This is a fourth flow chart of a coating preparation method provided by an embodiment of the present invention;

[0046] Figure 6 This is a fifth flow chart of a coating preparation method provided by an embodiment of the present invention;

[0047] Figure 7 It is one of the display schematic diagrams of a virtual simulation model provided by an embodiment of the present invention;

[0048] Figure 8 This is the second display schematic diagram of a virtual simulation model provided by an embodiment of the present invention.

[0049] Reference numerals:

[0050] 100. Operation platform; 110. Container storage area; 120. Coating preparation area;

[0051] 200. Mobile robots;

[0052] 300, main collaborative robot arm; 310, gripper;

[0053] 400, control unit; 410, virtual simulation model;

[0054] 500. Water drop angle detection device;

[0055] 600, auxiliary collaborative robot arm; 610, pipette gun;

[0056] 700, display unit;

[0057] 800. Input unit. DETAILED DESCRIPTION

[0058] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0059] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0060] In recent years, artificial intelligence has become an important tool to assist scientific research in many fields such as biology, medicine and chemistry. In chemical laboratories, automation systems and robots have become an indispensable part of the experimental process, and the robots are controlled by programs written by researchers to perform specific operations.

[0061] Many advanced laboratories around the world are gradually using intelligent robots to perform tasks such as prediction, analysis, screening, and synthesis in the field of chemistry and materials, helping researchers reduce repetitive experimental operations and simplify operations in chemical and material research, thereby improving experimental efficiency and making the preparation process of new drugs and new materials more intelligent. The existing robotic systems cannot completely liberate researchers from tedious and fixed experimental processes, and there is still a lack of robots that can be tailored for material coatings through layer-by-layer self-assembly and hydrophobic detection.

[0062] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0063] The embodiment of the present invention provides a coating preparation system. Figure 1 is a schematic diagram of a coating preparation system provided by an embodiment of the present invention, see Figure 1 The system includes: an operating platform 100 , a mobile robot 200 , a main collaborative robot arm 300 and a control unit 400 .

[0064] The operating platform 100 provides a stable working environment, and has a container storage area 110 and a coating preparation area 120. The container storage area 110 is used to store paint or other required chemicals, while the coating preparation area 120 is the main place for coating process.

[0065] The mobile robot 200 is disposed on the operating platform 100 , and the mobile robot 200 can move between the container storage area 110 and the coating preparation area 120 . The mobile robot 200 is provided with a grasping structure for grasping a container.

[0066] The mobile robot 200 can move freely on the operating platform 100 based on the built-in navigation system, and can shuttle between the container storage area 110 and the coating preparation area 120. The mobile robot 200 is equipped with a grasping structure, which can grasp and move containers, such as beakers or other containers. This design greatly improves work efficiency and reduces the complexity and risk of manual operation.

[0067] The main collaborative robot arm 300 is disposed on the operating platform 100 and corresponds to the coating preparation area 120. The main collaborative robot arm 300 is provided with a clamp 310 for clamping the substrate, which is used to clamp the substrate and alternately deposit polyanion and polycation electrolytes on it to complete the coating preparation. This method is more accurate and efficient than traditional manual operation.

[0068] The control unit 400 is in communication connection with the mobile robot 200 and the main collaborative robot arm 300. Through the control unit 400, each action of the mobile robot 200 and the main collaborative robot arm 300 can be accurately controlled to ensure the accuracy and consistency of the coating process. In addition, the control unit 400 can also automatically adjust various parameters according to the preset program to adapt to different coating requirements. Through highly automated equipment and precise control systems, the workload of manual labor is reduced, and the efficiency, accuracy and consistency of the coating preparation process are achieved, which can promote the development of coating technology.

[0069] The coating preparation system provided by the embodiment of the present invention can grab and move the container by setting the mobile robot 200, thereby improving the work efficiency and reducing the complexity and risk of manual operation. By setting the main collaborative robot arm 300, it is convenient to clamp and move the substrate to be coated so that it can be accurately placed in a predetermined position for coating. Through highly automated equipment and precise control systems, the workload of manual labor is reduced, and the efficiency, precision and consistency of the coating preparation process are achieved, which can promote the development of coating technology.

[0070] This system can not only greatly improve production efficiency and reduce production costs, but also significantly improve the quality and stability of the coating. At the same time, since the manual operation links are reduced, the operation risks and the possibility of personal injury are also greatly reduced.

[0071] The above-mentioned coating can be of different types, for example, it can be an antibacterial coating, and the system can realize a fully automated experimental process for preparing the antibacterial coating.

[0072] Among them, a drying box is provided on the container storage area 110. The drying box can quickly dry the container, reduce the time waiting for natural air drying, and improve the turnover rate of container use. Moreover, the drying process helps to remove moisture that may remain on the container, keep the container dry and clean, and avoid bacteria breeding due to moisture or affecting subsequent use. This makes the container storage area 110 not only have a simple storage function, but also has the ability to process the container, which increases the functionality of the overall system and enables the container storage area 110 to adapt to a variety of needs, such as some containers that need to be dried immediately before use, or situations where there are high requirements for the degree of dryness of the container. In actual applications, the specific parameters of the drying box such as temperature range, drying time, etc. can be reasonably set and adjusted according to different types of containers and usage scenarios to achieve good drying effects and work efficiency.

[0073] The main collaborative robot arm 300 usually has multiple joints and degrees of freedom to achieve flexible movement. The main collaborative robot arm 300 is responsible for performing various operations, including but not limited to grasping, moving and placing items.

[0074] The main collaborative robot arm 300 is provided with a visual recognition unit, which is in communication with the control unit 400 and is used to recognize the height of the substrate and the liquid level in the container.

[0075] The visual recognition unit has the ability to collect and analyze images. The visual recognition unit can capture images in the working area. The captured images are processed using image processing technology to extract the characteristic information of the substrate. The substrate in the image is identified through a preset algorithm or template matching. The recognition result determines the specific position of the substrate in the working area. It can also accurately identify the height of the liquid level in the container by capturing the image of the container and applying specific algorithms and technologies.

[0076] Moreover, the visual recognition unit establishes a communication connection with the control unit 400, which means that it can transmit the recognized liquid level information to the control unit 400 in real time. After receiving this information, the control unit 400 can make corresponding decisions and control operations according to specific needs, such as adjusting the distance that the main collaborative robot arm 300 moves downward so as to immerse the substrate in the solution in the container to an appropriate depth. This design makes the entire system more efficient, accurate and reliable when handling tasks related to liquid level height. At the same time, it can be determined whether to perform a solution replenishment operation based on the liquid level information returned by the visual recognition unit. If the liquid level is lower than the specified value, the end converter of the main collaborative robot arm 300 is started and adjusted to the pipetting mode to inject a certain amount of solution into the corresponding beaker.

[0077] Furthermore, the visual recognition unit includes a high-resolution camera and an image processor. Furthermore, the visual recognition unit also includes an auxiliary lighting device.

[0078] Based on the above structure, the visual recognition unit captures the image of the container through a camera. The image data is then transmitted to the image processor, which uses an image processing algorithm to identify and locate the liquid level. Further, the liquid level position can be accurately identified by edge detection, color analysis or machine learning technology. After the liquid level position is determined, the visual recognition unit transmits the relevant data to the control unit 400. This can be achieved by wired or wireless means, depending on the design and requirements of the system.

[0079] After receiving the liquid level data, the control unit 400 analyzes it to determine whether action is required. For example, if the liquid level is lower than a preset threshold, the control unit 400 may generate an instruction to control the main collaborative robot arm 300 to move downward; if the liquid level is lower than a preset threshold, the control unit 400 may generate an instruction to start the liquid filling process.

[0080] Based on the instructions of the control unit 400, the main collaborative robot arm 300 performs corresponding actions.

[0081] Furthermore, the entire system also includes feedback and monitoring mechanisms to ensure the accuracy and safety of the action. For example, the control unit 400 may continuously receive updated data from the visual recognition unit to monitor the liquid level changes and adjust the action of the robot arm.

[0082] In one embodiment provided by the present invention, a contact detection device is provided on the main collaborative robot arm 300, and the contact detection device is in communication with the control unit 400, and is used to detect whether the main collaborative robot arm 300 is in contact with the container, so as to ensure that the robot arm avoids collision during automated operation and improves work efficiency. Then, based on the visual feedback results and contact detection results of the visual recognition unit, the movement of the main collaborative robot arm 300 is fine-tuned to accurately position the end tool at the mouth of the container and maintain stable contact. Once the end tool of the main collaborative robot arm 300 is accurately positioned at the mouth of the container and maintains stable contact, the main collaborative robot arm 300 can perform the action of reaching into the container, gradually enter the container, and finally complete the specified pipetting operation.

[0083] For example, the contact detection device may be a pressure sensor, a proximity sensor, etc., to accurately determine whether contact has occurred, which is not limited in this embodiment.

[0084] In an embodiment provided by the present invention, the system further includes: a water drop angle detection device 500 and a secondary collaborative robot arm 600.

[0085] Among them, the water drop angle refers to the angle between the gas-liquid interface and the solid-liquid interface at the junction of gas, liquid and solid when a drop of liquid reaches equilibrium on the solid surface. For example, the liquid can be water. The size of the water drop angle directly reflects the interaction force between the liquid and the solid surface. According to the surface tension theory, when the interaction force between the droplet and the solid is strong, the water drop angle is smaller, indicating that the liquid is easier to spread on the solid surface; conversely, when the interaction force is weak, the water drop angle is larger, indicating that the liquid has poorer spreading ability on the solid surface. The above-mentioned water drop angle detection device 500 is arranged on the operating platform 100, and the main collaborative robot arm 300 can easily move the substrate to the water drop angle detection device 500.

[0086] The above-mentioned sub-cooperative robot arm 600 is arranged on the operating platform 100 and corresponds to the water drop angle detection device 500, which facilitates its coordinated work with the water drop angle detection device 500. Moreover, a pipette gun 610 is provided on the sub-cooperative robot arm 600, which can perform precise liquid suction and distribution operations. The cooperation between the sub-cooperative robot arm 600 and the water drop angle detection device 500 can realize an automated detection process and improve work efficiency and accuracy. The above-mentioned coating can be of different types, for example, it can be an antibacterial coating. The system can realize a fully automated experimental process for the preparation of antibacterial coatings and the characterization of hydrophilic / hydrophobic properties.

[0087] Furthermore, the water drop angle detection device 500 includes: a liftable platform, a light source and a camera unit.

[0088] The lifting platform is horizontally arranged to support the substrate. The relative position between the substrate and the camera unit can be adjusted through lifting operations, thereby ensuring the accuracy and convenience of detection.

[0089] The light source is arranged toward the liftable platform to ensure that sufficient light is provided to the camera unit during the detection process, so that the captured image is clear and accurate. The camera unit is arranged toward the liftable platform to capture the image of the droplet on the surface of the substrate, and the camera unit is connected to the control unit 400 in communication so as to transmit the captured image to the control unit 400 in real time for analysis and processing. Among them, the light source can be an LED (light emitting diode), and the camera unit can include a CCD (charge coupled device) camera. The water drop angle detection device 500 is based on an industrial macro camera, a high-definition CCD camera, a brightness-adjustable LED fill light, and a liftable level adjustment table. It can solve the problems of small and transparent droplets and the need to adjust the level of the platform. Considering the irregular shape of the pipette gun 610 and the need for pressing, releasing, and other operations, a new type of pipette gun 610 mechanical arm end clamp 310 is designed.

[0090] In any of the above embodiments provided by the present invention, the system further includes: a display unit 700 and an input unit 800 , and the display unit 700 and the input unit 800 are both communicatively connected to the control unit 400 .

[0091] Among them, the display unit 700 is used to display the results of the water drop angle detection, including the image of the drop, the value of the contact angle, etc. It can display various parameters and states in the detection process in real time to help users understand the operation of the system. The display unit 700 usually adopts technologies such as liquid crystal display (LCD) or touch screen (Touch Screen), which can present clear and intuitive images and text information. Through the communication connection with the control unit 400, the display unit 700 can update the display content in real time to ensure that the user can understand the detection results in a timely manner.

[0092] The input unit 800 is used to receive the user's operation instructions and parameter settings. The user can select a detection mode, set detection parameters, start or stop detection, etc. through the input unit 800.

[0093] The input unit 800 may include various input devices, such as a keyboard, a mouse, a touch screen, etc., to meet the needs and habits of different users. Through the communication connection with the control unit 400, the input unit 800 can transmit the user's operation instructions and parameter settings to the control unit 400 in real time, ensuring that the system can work according to the user's requirements.

[0094] The communication connection between the above-mentioned units and the control unit 400 can be carried out by wired or wireless means. Wired connection usually uses interfaces such as USB and RS-232, and the transmission is stable and reliable; wireless connection can use technologies such as Wi-Fi and Bluetooth, which is convenient and flexible.

[0095] The coating preparation system provided by the embodiment of the present invention can grab and move the container by setting the mobile robot 200, thereby improving the work efficiency and reducing the complexity and risk of manual operation. By setting the main collaborative robot arm 300, it is convenient to clamp and move the substrate to be coated so that it can be accurately placed in a predetermined position for coating. Through highly automated equipment and precise control systems, the workload of manual labor is reduced, and the efficiency, precision and consistency of the coating preparation process are achieved, which can promote the development of coating technology.

[0096] Specifically, the mobile robot 200 can ensure the safe flow of materials, and use the main collaborative robot arm 300 and the auxiliary collaborative robot arm 600 to efficiently and alternately deposit polyanions and polycation electrolytes on the substrate. The pipette 610 and the clamp 310 at the end of the main collaborative robot arm 300 and the auxiliary collaborative robot arm 600 assist in completing the coating preparation and water drop angle detection. The matching visualization interface can display the system data in real time, which is convenient for users to grasp the system status and issue instructions. The present invention provides a material experiment robot intelligent system that can autonomously realize high-throughput preparation of antibacterial coatings. The system platform improves the level of informatization of the experiment, avoids the tedious and repetitive experimental steps of the experimenter, reduces the burden, and improves the efficiency of scientific research.

[0097] This embodiment uses a layer-by-layer self-assembly method for coating preparation and water drop angle detection, thereby realizing full-process automated material preparation and achieving interdisciplinary communication and comprehensive project management.

[0098] The present invention also provides a coating preparation method. Figure 2 This is one of the flow charts of a coating preparation method provided in an embodiment of the present invention, see Figure 2 The method comprises:

[0099] 910 . Control the mobile robot 200 to move the plurality of containers from the container storage area 110 to the coating preparation area 120 .

[0100] Wherein, a plurality of containers are respectively filled with a preset polyanion solution, a first deionized water, a polycation solution and a second deionized water.

[0101] In this step, the mobile robot 200 and the main collaborative robot arm 300 system need to be initialized. Specifically, ensure that the power of the mobile robot 200 and the main collaborative robot arm 300 is connected and turned on. Check the communication connection between the mobile robot 200 and the main collaborative robot arm 300 to ensure that instructions can be received and executed. Calibrate the position and posture of the mobile robot 200 and the main collaborative robot arm 300 to ensure accurate execution of subsequent tasks.

[0102] The mobile robot 200 is controlled to move to the container storage area 110. Specifically, a command is sent to the mobile robot 200 to move to a designated position of the container storage area 110. The mobile robot 200 uses its navigation and positioning system to reach the target position.

[0103] The mobile robot 200 is controlled to grab and move the container to the coating preparation area 120. Specifically, the mobile robot 200 identifies each container in the container storage area 110, including the polyanion solution, the first deionized water, the polycation solution, and the second deionized water. The mobile robot 200 grabs each container in turn and moves it to a designated position in the coating preparation area 120. During the movement, the stability and safety of the container are ensured to avoid leakage of the solution or damage to the container.

[0104] Specifically, the container can be a beaker or other container. After the container is detected, the detected pixel coordinates of the container need to be converted into the coordinates required by the main collaborative robot arm 300. There are mainly three conversions. First, the pixel coordinates are converted into camera coordinates. The pixel coordinates on the image are converted into camera coordinates by using the internal and external parameter matrices of the camera, that is, the relationship between the pixel coordinate system UV and the image coordinate system XY. After obtaining the pixel coordinates (u, v), first restore the (x, y) in the image coordinates, and use the proportional relationship between different coordinates to obtain the projection process of the pixel coordinates to the camera coordinates. The pixel coordinates can be converted into world coordinates through the Euler angles obtained by hand-eye calibration and the relationship between the Euler angles and the transformation matrix R.

[0105] The conversion relationship is

[0106]

[0107] Among them, u, v represent pixel coordinates, X W , Y W , Z W Represents the world coordinates, which can be used to obtain the camera coordinate position of the identified object.

[0108] Secondly, the camera coordinates are converted into the coordinates of the main collaborative robot 300. The main collaborative robot 300 clamps the substrate and uses the camera to identify the three-dimensional coordinates of the substrate, that is, the position of the camera relative to the substrate. Then, according to the built-in parameters of the main collaborative robot 300, the position change from the end to the main collaborative robot 300 coordinate system. From the above two parts, the conversion matrix between the camera coordinate system and the main collaborative robot 300 coordinate system can be obtained, and the conversion of the camera coordinates to the main collaborative robot 300 coordinates can be realized.

[0109] Finally, the coordinates of the container are obtained. The coordinates of the camera detected by YOLOv8 (a model used for classification, detection and segmentation tasks in the field of computer vision) are multiplied by the inverse of the transformation matrix to obtain the coordinates of the container in the coordinate system of the main collaborative robot 300. After three coordinate transformations, the main collaborative robot 300 can be accurately controlled to move to the position of the container.

[0110] In order to accurately control the main collaborative robot arm 300 to reach the specified container position and prevent the container from being overturned, a strategy is adopted to control the main collaborative robot arm 300 to reach the container mouth first, and then extend into the container to contact the liquid. When the device is just started, the main collaborative robot arm 300 is at the initial position. After the target detection recognizes the container, the coordinate conversion is performed to obtain the actual coordinate position. The motion planning algorithm of the main collaborative robot arm 300 is used to plan the trajectory of the main collaborative robot arm 300 according to the path between the initial position and the target position to reach the container.

[0111] The main collaborative robot arm 300 performs a partial approach according to the motion plan, moving the end tool near the container but still maintaining a certain distance. Use a visual recognition unit, such as a camera or sensor, to monitor the position and posture of the container in real time. Use a force sensor or other contact detection device to detect whether the main collaborative robot arm 300 has contacted the container. Then, based on the visual feedback results and contact detection results of the visual recognition unit, the movement of the main collaborative robot arm 300 is fine-tuned to accurately position the end tool at the mouth of the container and maintain stable contact. Once the end tool of the main collaborative robot arm 300 is accurately positioned at the mouth of the container and maintains stable contact, the main collaborative robot arm 300 can execute the action of reaching into the container, gradually entering the container, and finally completing the specified pipetting operation.

[0112] 920. Control the main collaborative robot arm 300 to grab the substrate.

[0113] In this step, the main collaborative robot arm 300 grabs the substrate using the gripper 310 at its end, ensuring that the substrate is stably and firmly grasped for subsequent coating preparation.

[0114] In this step, the timing sequence between step 920 and step 910 is not limited. Step 910 may be performed first and step 920 may be performed later; step 920 may be performed first and step 910 may be performed later; or step 910 and step 920 may be performed simultaneously.

[0115] 930. Control the main collaborative robot arm 300 to drive the substrate to repeatedly prepare the coating.

[0116] Each coating preparation includes: sequentially immersing the substrate in a polyanion solution, a first deionized water, a polycation solution, and a second deionized water for corresponding preset time periods.

[0117] In this step, the main collaborative robot arm 300 moves the substrate to a designated position in the coating preparation area 120. According to the preset coating preparation process, the main collaborative robot arm 300 sequentially immerses the substrate in a polyanion solution, a first deionized water, a polycation solution, and a second deionized water for coating treatment. In each treatment step, the main collaborative robot arm 300 needs to accurately control the immersion depth, speed, and dwell time of the substrate to ensure the quality and uniformity of the coating. After completing all coating preparation steps, the main collaborative robot arm 300 moves the substrate to a designated position for subsequent processing or storage.

[0118] Specifically, the immersion time in the polyanion solution can be 15-30 minutes, the immersion time in the first deionized water for cleaning can be 2 minutes, the immersion time in the polycation solution can be 15-30 minutes, and the immersion time in the second deionized water for cleaning can be 2 minutes. Repeat the above alternating deposition steps 20-50 times to complete the coating preparation. The first deionized water and the second deionized water can be the same solution or different solutions.

[0119] The coating preparation method provided by the embodiment of the present invention can grab and move the container by setting the mobile robot 200, thereby improving work efficiency and reducing the complexity and risk of manual operation. By setting the main collaborative robot arm 300, it is convenient to clamp and move the substrate to be coated so that it can be accurately placed in a predetermined position for coating. Through highly automated equipment and precise control systems, the workload of manual labor is reduced, and the efficiency, precision and consistency of the coating preparation process are achieved, which can promote the development of coating technology.

[0120] Furthermore, Figure 3 This is a second flow chart of a coating preparation method provided by an embodiment of the present invention, see Figure 3 In one embodiment provided by the present invention, step 920 includes:

[0121] 921. Determine the substrate position.

[0122] In this step, it is necessary to ensure that the visual recognition unit of the main collaborative robot arm 300 has been calibrated and can accurately identify the substrate in the working environment. The working area is scanned by a visual system or other sensors to identify the specific position of the substrate. A positioning algorithm (such as image recognition, mark recognition, etc.) is used to accurately determine the position of the substrate in the working environment. The identified substrate position information is recorded in the system for subsequent operations.

[0123] 922. Control the main collaborative robot arm 300 to move to the substrate position and grasp the substrate through the clamper 310.

[0124] The visual recognition unit sends the recognized position information of the substrate to the control unit 400. The control unit 400 plans the optimal path for the main collaborative robot arm 300 to move to the substrate position according to the received position information.

[0125] The control unit 400 converts the result of path planning into an instruction that the main collaborative robot arm 300 can understand, and sends it to the main collaborative robot arm 300. The main collaborative robot arm 300 moves according to the received instruction through its built-in motor and control system. During the movement, the position and state of the main collaborative robot arm 300 are fed back in real time through sensors to ensure accurate movement along the predetermined path.

[0126] When the main collaborative robot arm 300 moves to the vicinity of the substrate, the position and posture of the main collaborative robot arm 300 are finely adjusted to ensure that the gripper 310 can accurately align with the substrate. A command is sent to the gripper 310 to open and clamp the substrate. The clamping force is ensured to be moderate to avoid damaging the substrate. The substrate is confirmed to be firmly clamped by the gripper 310 through sensors or other detection means.

[0127] Figure 4 This is a flowchart of a coating preparation method provided by an embodiment of the present invention. Figure 4 In one embodiment provided by the present invention, the substrate is sequentially immersed in the polyanion solution, the first deionized water, the polycation solution and the second deionized water for corresponding preset time periods, each of which includes:

[0128] 931. Determine the container location.

[0129] In this step, the visual recognition unit or other sensors on the main collaborative robot arm 300 are used to identify the containers storing the polyanion solution, the first deionized water, the polycation solution, and the second deionized water. Based on the recognition results, the specific location of each container is determined.

[0130] 932. According to the position of the container, control the main collaborative robot arm 300 to move above the container.

[0131] Based on the position information of the container, the control unit 400 plans the optimal path from the current position of the main collaborative robot arm 300 to the top of the container. According to the planned path, the main collaborative robot arm 300 is controlled to move to the top of the container.

[0132] 933. Determine the liquid level in the container based on the visual recognition unit.

[0133] The visual recognition unit captures the image inside the container and uses image processing technology to identify the position of the liquid surface and thus determine the height of the liquid surface.

[0134] 934. Determine the descent distance based on the liquid level in the container.

[0135] According to the height of the liquid level and the size of the substrate, the distance that the main collaborative robot arm 300 needs to descend is calculated to ensure that the substrate can be completely immersed in the solution.

[0136] 935. Based on the descending distance, control the main collaborative robot arm 300 to drive the substrate to descend so that the substrate is immersed in the solution in the container.

[0137] The control unit 400 sends an instruction to the main collaborative robot arm 300, informing it of the distance it needs to descend. The main collaborative robot arm 300 drives the substrate to descend according to the instruction until the substrate is completely immersed in the solution.

[0138] 936. After soaking for a preset time, control the main collaborative robot arm 300 to drive the substrate to rise.

[0139] The control unit 400 monitors the immersion time, and when the preset time is reached, sends a command to the main collaborative robot arm 300. After receiving the command, the main collaborative robot arm 300 drives the substrate to rise and leave the solution.

[0140] Figure 5 This is a fourth flow chart of a coating preparation method provided by an embodiment of the present invention, see Figure 5 In any of the above embodiments provided by the present invention, the method further includes:

[0141] 940 . Control the main collaborative robot arm 300 to clamp the substrate and place it at a preset position of the water drop angle detection device 500 .

[0142] The main collaborative robot arm 300 is controlled to use the gripper 310 to grip the substrate and accurately move it to a preset position of the water drop angle detection device 500 .

[0143] 950. Control the pipette gun 610 held by the secondary collaborative robot arm 600 to absorb water and drop water drops onto the substrate.

[0144] The secondary collaborative robot arm 600 is controlled to immerse the tip of the pipette gun 610 into water to absorb a certain amount of water. The pipette gun 610 is moved above the substrate and controlled to release water so that the water droplets accurately fall on the surface of the substrate. This process requires precise control of the height and release speed of the pipette gun 610 to ensure that the size and shape of the water droplets meet the measurement requirements.

[0145] 960. Based on the water drop angle detection device 500, detect the water drop angle of the substrate.

[0146] The water drop angle detection device 500 captures the image formed by the water drop on the substrate surface. Using image processing technology, the system can automatically analyze the image and calculate the contact angle between the water drop and the substrate surface, that is, the water drop angle.

[0147] Furthermore, the calculated water drop angle results can be displayed for user reference and analysis. This result can be used to evaluate the wettability, surface tension and other properties of the substrate.

[0148] Figure 6 This is a flowchart of a coating preparation method provided by an embodiment of the present invention, see Figure 6 After performing coating preparation according to preset coating preparation parameters and obtaining the water drop angles of multiple substrates, in a further embodiment provided by the present invention, the method further includes:

[0149] 970. Based on the received input information, run the virtual simulation model 410 and obtain simulation data.

[0150] The input information may include the material of the substrate, surface properties, properties of the coating material, preparation parameters, etc.

[0151] Figure 7 It is one of the display schematic diagrams of a virtual simulation model provided by an embodiment of the present invention; Figure 8 This is a second display schematic diagram of a virtual simulation model provided by an embodiment of the present invention. Figures 7 and 8 The virtual simulation model 410 is a tool for simulating the actual coating preparation and detection process on a computer, and can also be referred to as the virtual simulation model 410. It can simulate the behavior of water droplets on the surface of the substrate according to the input parameters and conditions, including the shape, size, angle of the water droplets, etc. By running the virtual simulation model 410, a series of simulation data related to coating preparation and detection can be obtained. These data can be used as a benchmark for comparison with actual measurement data.

[0152] Furthermore, the material experiment robot intelligent system for coating preparation uses model-based systems engineering to build a platform integrating hardware systems and software systems. The virtual simulation model 410 is based on Gazebo (an open source 3D robot simulator) to build a simulated real laboratory. The entire model includes three-dimensional models of objects such as the operating platform 100, the mobile robot 200, the main collaborative robot arm 300, the water drop angle detection device 500 and the auxiliary collaborative robot arm 600. The virtual simulation model 410 will help to conduct experimental verification in a virtual environment. In addition, the system realizes the interaction between virtual and reality by constructing a simulation environment, providing effective verification and guidance for the operation of the robot arm.

[0153] Specifically, the virtual simulation model 410 is based on Gazebo to build a simulated real laboratory, using UR3 and UR3e robotic arms for dual-arm collaborative operation. UR3 officially provides the URDF file of the UR3 collaborative robotic arm, converts the URDF file into an XML file, and adds other object models to finally build a model platform.

[0154] The virtual platform was developed to provide technicians with limited IT skills with the ability to operate the system. In the early stages of experimentation, it is safer and more convenient for users to operate in a simulated environment than in the real world. The platform will also help verify experiments in a virtual environment without having to worry about the safety of the actual equipment.

[0155] In view of the experimental needs, in order to better realize the operation status of the experimental process and the visualization of experimental data, an intuitive user interface (UI) and voice input system for coating preparation and hydrophilic and hydrophobic performance testing are designed. Including the monitoring display of the coating preparation process, water drop angle detection and other states, the experimental process data can be displayed in real time. For example, the display pages can be home page display, coating preparation, water drop angle detection and data analysis respectively. The initial page is displayed as the home page, and when the platform starts running, it will switch to the page of each link for display. In the water drop angle measurement link, the current measurement image and results are recorded, and historical data are presented. By recording the operation data in real time, it is more conducive to problem solving. The software not only has a user-friendly design that is easy for researchers to use, but also shows a clear and efficient logical process that can seamlessly guide and manage the operation of the robot system. The simplicity and effectiveness of the software system greatly improve the automation and intelligence level of the laboratory environment.

[0156] The visual digital interface is used to record various operating data in real time during the experiment, which is convenient for the experimenter to observe the experimental data and experimental status in real time. The complete experimental process software architecture process is system initialization, input of experimental parameters, experimental preparation, experimental operation, virtual simulation and optimization, result evaluation, and generation of experimental report. The visual surface analysis technology used for hydrophilicity and hydrophobicity detection provides practitioners with instant feedback on coating performance.

[0157] 980. Compare the water drop angles of multiple substrates with simulation data.

[0158] In actual operation, the water drop angles of multiple substrates have been measured in step 960. These data reflect the actual wetting performance of the coating on the substrate. The actual measured water drop angle data is compared with the simulation data to analyze the difference between the two. This comparison can help identify possible problems or deficiencies in the coating preparation process.

[0159] 990. Based on the comparison results, optimize the coating preparation parameters.

[0160] By comparing the actual measurement data with the simulation data, possible problems in the coating preparation process can be identified, such as the properties of the coating material, preparation process parameters, etc. Based on the results of the comparative analysis, the coating preparation parameters are optimized. For example, this may include adjusting the ratio of the coating material or changing the preparation process parameters, such as temperature, pressure, time, etc.

[0161] Furthermore, after optimizing the parameters, the virtual simulation model 410 can be run again to obtain new simulation data. Then, the new simulation data is compared with the actual measurement data to evaluate the optimization effect. If necessary, iterative improvements can be continued until satisfactory results are obtained.

[0162] In other words, the material experiment robot system includes two parts: the hardware system and the software system. The hardware system mainly includes the operating platform 100 and the mobile robot 200, the main collaborative robot arm 300 and the auxiliary collaborative robot arm 600, and the water drop angle detection device 500; the software system mainly includes the virtual simulation model 410 and the visual digital interface display. The software system mainly includes the virtual simulation model 410, the intuitive user interface (UI), the voice input system, and a corresponding complete experimental process software architecture.

[0163] Please continue to see Figures 7 and 8 , wherein the operating platform 100 and the mobile robot 200 (AGV, Automated Guided Vehicle) are used to realize the material transfer. The mobile robot 200 has a built-in navigation system or sensor, which can perform autonomous navigation and obstacle avoidance, and transfer the container from the solution storage area to the coating preparation area 120 for experiment; the main collaborative robot 300 is a UR3 robot, and its end is equipped with a specially designed gripper 310 two-finger gripper for gripping the substrate, and alternately depositing polyanion and polycation electrolytes on it to complete the coating preparation. After the preparation is completed, the substrate is clamped and placed at an appropriate position on the water drop angle detection platform; the auxiliary collaborative robot 600 is a UR3e robot, and its end clamps a pipette 610, which can absorb water and drop water drops on the substrate; the water drop angle detection device 500 is composed of a liftable platform, an LED light source, and a CCD camera, and can be combined with the main collaborative robot 300 and the auxiliary collaborative robot 600 to realize water drop angle detection.

[0164] The overall experimental process architecture of the Materials Experiment Department is described as follows:

[0165] The system first performs initialization to perform a hardware platform self-check and establishes a connection with the virtual simulation model 410; secondly, input the parameters required for the experiment, and input the relevant experimental conditions of the experimental scheme and the required materials, experimental personnel, and running time of each link through the visual interface; then prepare the experiment, and prepare the corresponding experimental materials and tools according to the input experimental parameters, and move the required materials and tools to the coating preparation area 120. At the same time, the virtual simulation model 410 loads the corresponding simulation model and waits for access to the experimental data; then the experimental operation is performed, and the platform performs coating preparation and water drop angle experiments according to the set program; after the experiment is completed, the virtual simulation model 410 simulates according to the experimental data, optimizes the experimental parameters according to the simulation results, and then performs experimental verification and improvement; the experimental performance is evaluated by comparing the experimental results with the simulation results. If the results do not achieve the ideal effect, continue to input the optimized experimental parameters for the experiment until the ideal effect is achieved; finally, the system experimental report is output according to the experimental results, showing various operating data, operating status, and operating data results of the experimental process, such as the remaining amount of preparation materials, the actual static time of the coating preparation process, the experimental detection history data and error results, and whether there are abnormalities in the operating status.

[0166] The coating preparation method provided by the embodiment of the present invention can grab and move the container by setting the mobile robot 200, thereby improving work efficiency and reducing the complexity and risk of manual operation. By setting the main collaborative robot arm 300, it is convenient to clamp and move the substrate to be coated so that it can be accurately placed in a predetermined position for coating. Through highly automated equipment and precise control systems, the workload of manual labor is reduced, and the efficiency, precision and consistency of the coating preparation process are achieved, which can promote the development of coating technology.

[0167] Furthermore, by comparing the actual measurement data with the simulation data, possible problems in the coating preparation process can be identified, such as the properties of the coating material, preparation process parameters, etc. Based on the results of the comparative analysis, the coating preparation parameters are optimized. For example, this may include adjusting the ratio of the coating material or changing the preparation process parameters, such as temperature, pressure, time, etc.

[0168] Furthermore, after optimizing the parameters, the virtual simulation model 410 can be run again to obtain new simulation data. Then, the new simulation data is compared with the actual measurement data to evaluate the optimization effect. If necessary, iterative improvements can be continued until satisfactory results are obtained.

[0169] The intelligent material preparation robot system for coating preparation realizes the automation of the whole process of material preparation by programming the process of antibacterial coating preparation and water drop angle detection. In order to achieve effective collaboration between different teams, a systematic approach was adopted. Through the design process of MBSE (Model-Based Systems Engineering), a unified platform was built to promote effective communication and collaboration between expert teams from different fields such as materials science, robotics, computer science and systems engineering. In the material experiment robot system for coating preparation, this process ensures the programmatic design of the process of antibacterial coating preparation and water drop angle detection, and realizes the automation of the whole process of material preparation. This method not only improves scientific research efficiency and saves time and cost, but also lays a solid foundation for the use of advanced robot systems for research in other fields in the future.

[0170] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0171] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0172] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0173] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A coating preparation system, characterized in that: The system comprises: an operating platform, a mobile robot, a main collaborative mechanical arm and a control unit; Wherein, the operating platform has a container storage area and a coating preparation area; The mobile robot is arranged on the operating platform, and the mobile robot can move between the container storage area and the coating preparation area, and the mobile robot is provided with a grasping structure for grasping a container; The main collaborative robot arm is arranged on the operating platform and corresponds to the coating preparation area, and the main collaborative robot arm is provided with a clamp for clamping the substrate; The control unit is communicatively connected with the mobile robot and the main collaborative robot arm.

2. The coating preparation system according to claim 1, characterized in that: The main collaborative robot arm is provided with a visual recognition unit, which is communicatively connected with the control unit and is used for identifying the substrate and the liquid level in the container.

3. The coating preparation system according to claim 1, characterized in that: The main collaborative robot arm is provided with a contact detection device, which is communicatively connected with the control unit and is used for detecting whether the main collaborative robot arm is in contact with the container.

4. The coating preparation system according to claim 1, characterized in that: The system further comprises: A water drop angle detection device, wherein the water drop angle detection device is arranged on the operating platform; A secondary collaborative robotic arm, the secondary collaborative robotic arm is arranged on the operating platform and corresponds to the water drop angle detection device, and the secondary collaborative robotic arm is provided with a pipette gun.

5. The coating preparation system according to any one of claims 1 to 4, characterized in that: The system further includes: a display unit and an input unit, wherein both the display unit and the input unit are communicatively connected with the control unit.

6. A coating preparation method, characterized in that: The method comprises: Controlling the mobile robot to move a plurality of containers from the container storage area to the coating preparation area, wherein the plurality of containers are respectively filled with a preset polyanion solution, a first deionized water, a polycation solution, and a second deionized water; Control the main collaborative robot arm to grab the substrate; The main collaborative robot arm is controlled to drive the substrate to repeatedly prepare the coating, wherein each coating preparation includes: sequentially immersing the substrate in a polyanion solution, a first deionized water, a polycation solution, and a second deionized water for corresponding preset time periods.

7. The coating preparation method according to claim 6, characterized in that: The controlling the main collaborative robot arm to grasp the substrate comprises: Determine substrate location; The main collaborative robot arm is controlled to move to the substrate position and the substrate is grasped by a gripper.

8. The coating preparation method according to claim 6, characterized in that: The step of sequentially immersing the substrate in the polyanion solution, the first deionized water, the polycation solution, and the second deionized water for corresponding preset time periods includes: Determine the container location; According to the position of the container, controlling the main collaborative robot arm to move above the container; Determining the liquid level in the container based on the visual recognition unit; Determine the descending distance according to the liquid level in the container; Based on the descending distance, controlling the main collaborative robot arm to drive the substrate to descend so that the substrate is immersed in the solution in the container; After soaking for a preset time, the main collaborative robot arm is controlled to drive the substrate to rise.

9. The coating preparation method according to any one of claims 6 to 8, characterized in that: The method further comprises: Control the main collaborative robot arm to clamp the substrate and place it at a preset position of the water drop angle detection device; Controlling the pipette held by the secondary cooperative robot arm to absorb water and drop water drops on the substrate; The water drop angle of the substrate is detected based on the water drop angle detection device.

10. The coating preparation method according to claim 9, characterized in that: The method further comprises: Based on the received input information, the virtual simulation model is run and simulation data is obtained; comparing the water drop angles of the plurality of substrates with the simulation data; According to the comparison results, the coating preparation parameters are optimized.

Images