A method and apparatus for laser cleaning of vacuum coating chambers based on a mobile robot

Abstract

This invention relates to a method and apparatus for laser cleaning of a vacuum coating chamber based on a mobile robot. The method includes the following steps: deploying a structured light camera, a laser, and a dust removal device at the end of the robot's manipulator arm; establishing a first mapping relationship between the vacuum chamber coordinate system and the robot's base coordinate system using a dry crucible inside the vacuum coating chamber as a calibration object; fitting the inner wall of the vacuum chamber into multiple cylindrical surface models with different radii and planning the acquisition path of the structured light camera; controlling the structured light camera to take pictures along the acquisition path, identifying the surface to be cleaned on the inner wall of the vacuum chamber and updating it on the cylindrical surface model; planning the cleaning path and pose of the laser to ensure that the unit energy of the laser reaching the surface to be cleaned remains constant; moving the robot along the transformed cleaning path and driving the manipulator arm to control the laser to perform the operation with the transformed pose. This invention enables remote automated operation of laser cleaning in a vacuum coating chamber and can be quickly adapted to different coating machines.

Description

Technical Field

[0001] This invention relates to the field of vacuum coating equipment maintenance technology, and in particular to a laser cleaning method and apparatus for vacuum coating chambers based on a mobile robot. Background Technology

[0002] After long-term operation, metal oxides, deposits, and rust can easily form on the inner walls, baffles, and crucible surfaces of a vacuum coating machine, affecting the vacuum level and film quality. These contaminants can generate gases and vapors during later machine startups, preventing the vacuum system from reaching the required vacuum level. They can also affect the strength and sealing performance of vacuum component connections, as well as the bonding between the target material and the substrate, thus impacting product quality and resulting in substandard coatings. Therefore, the vacuum chamber must be cleaned before starting the equipment.

[0003] Generally, vacuum coating equipment should be cleaned once after each number of coating processes. The current method involves repeatedly scrubbing the inner wall of the vacuum chamber with a saturated sodium hydroxide (NaOH) solution. The purpose is to cause the aluminum (Al) coating material to react with the NaOH, resulting in the film layer peeling off and releasing hydrogen gas. The vacuum chamber is then rinsed with water, and the inside of the suction valve is cleaned with a cloth dampened with gasoline. This cleaning method may corrode the substrate, requires environmentally friendly waste treatment, and is difficult to use for complex structures or small areas. Furthermore, personnel entering the chamber may cause secondary pollution, operators need to work in confined spaces, and there is the presence of metal dust, resulting in poor working conditions.

[0004] Document CN221854736U discloses a coating apparatus with laser cleaning, wherein the laser cleaning mechanism is mounted on a frame for cleaning the cooling rollers. This laser cleaning mechanism can only clean specific areas in a set manner, resulting in poor versatility, low automation, and the inability to monitor the operation status in real time. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and apparatus for laser cleaning of vacuum coating chamber based on a mobile robot, which can realize remote automated operation of laser cleaning of vacuum coating chamber and can be quickly adapted to different coating machines.

[0006] The technical solution adopted by this invention to solve its technical problem is: to provide a laser cleaning method for a vacuum coating chamber based on a mobile robot, comprising the following steps:

[0007] A tool system is deployed at the end of the robot's manipulator arm, the tool system including a structured light camera and a laser;

[0008] A vacuum chamber coordinate system is established with the rotation center of the dry crucible inside the vacuum coating chamber as the origin;

[0009] Multiple corner points on the upper surface of the dry pot are selected as feature points, and the coordinates of these feature points in the vacuum chamber coordinate system are obtained to obtain the first feature pose of the dry pot.

[0010] The robot is moved to the vicinity of the vacuum coating chamber, and the second feature pose of the dry pot in the camera coordinate system is obtained using a structured light camera.

[0011] Based on the first feature pose and the second feature pose, the first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system is determined.

[0012] The inner wall of the vacuum chamber is fitted as multiple cylindrical surface models with different radii in the vacuum chamber coordinate system. The acquisition path of the structured light camera is planned for each cylindrical surface model and transformed to the robot base coordinate system based on the first mapping relationship.

[0013] The structured light camera is controlled to take pictures along the converted acquisition path. Based on the acquired data, the surface to be cleaned on the inner wall of the vacuum chamber is identified and updated onto the cylindrical model.

[0014] The cleaning path and pose of the laser are planned based on the updated cylindrical surface model so that the unit energy of the laser emitted by the laser when it reaches the surface to be cleaned remains unchanged.

[0015] Based on the first mapping relationship, the planned cleaning path and pose are transformed into the robot's base coordinate system, allowing the robot to move along the transformed cleaning path and drive the manipulator to control the laser to carry out the operation in the transformed pose.

[0016] Furthermore, determining the first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system based on the first feature pose and the second feature pose includes:

[0017] Establish a second mapping relationship between the camera coordinate system and the tool system coordinate system, and a third mapping relationship between the tool system coordinate system and the robot base coordinate system when the structured light camera is shooting the dry pot;

[0018] Based on the second and third mapping relationships, the second feature pose is transformed into the robot base coordinate system;

[0019] Based on the second feature pose in the robot base coordinate system and the first feature pose in the vacuum chamber coordinate system, a first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system is established.

[0020] Furthermore, the planned acquisition path of the structured light camera includes:

[0021] Unfold each cylindrical model into a rectangular unfolded diagram;

[0022] Based on the positional relationship of each cylindrical surface model in three-dimensional space, draw the two-dimensional spatial distribution of the corresponding rectangular unfolded diagram;

[0023] The acquisition path of the structured light camera is planned based on the two-dimensional spatial distribution sequence of the rectangular unfolded diagram.

[0024] Furthermore, the step of identifying the surface to be cleaned on the inner wall of the vacuum chamber based on the collected data and updating it on the cylindrical surface model includes:

[0025] Based on the collected data, the surface to be cleaned on the inner wall of the vacuum chamber is identified, and the corresponding rectangular cleaning frame in the camera coordinate system is obtained;

[0026] Based on the second mapping relationship, the cleaning box in the camera coordinate system is transformed to the robot base coordinate system;

[0027] Based on the first mapping relationship, the cleaning frame in the robot base coordinate system is transformed to the vacuum chamber coordinate system, and then the rectangular cleaning frame is marked on the rectangular unfolded diagram of the corresponding cylindrical model.

[0028] Furthermore, based on the updated cylindrical surface model, the cleaning path and pose of the laser are planned to ensure that the unit energy of the laser emitted by the laser remains constant when it reaches the surface to be cleaned, including:

[0029] Set the distance between the laser and the surface to be cleaned;

[0030] When the length of the short side of the surface to be cleaned is less than the length of the laser beam, the laser is planned to perform a one-time cleaning along the central axis of the short side of the surface to be cleaned, while maintaining a constant distance from the surface to be cleaned during the cleaning process.

[0031] When the length of the short side of the surface to be cleaned is greater than the length of the laser beam, the laser is planned to clean along a serpentine path covering the entire surface to be cleaned, while maintaining a constant distance from the surface to be cleaned during the cleaning process.

[0032] Furthermore, before planning the cleaning path and pose of the laser based on the updated cylindrical surface model, the method further includes the step of expanding the four sides of the rectangular cleaning frame outward by a set length.

[0033] Furthermore, the step of identifying the surface to be cleaned on the inner wall of the vacuum chamber based on the collected data and obtaining the corresponding rectangular cleaning frame in the camera coordinate system includes:

[0034] The surface to be cleaned on the inner wall of the vacuum chamber is selected based on the collected data.

[0035] The selected surface to be cleaned is binarized and segmented before contour extraction is performed to form a rectangular cleaning frame in the camera coordinate system.

[0036] Furthermore, it also includes:

[0037] The degree of pollution is determined based on data collected by a structured light camera.

[0038] The laser's moving speed is adjusted according to the degree of contamination, so that the emitted laser irradiates the heavily contaminated surface for a longer time and the lightly contaminated surface for a shorter time.

[0039] Furthermore, the second feature pose of the dry pot in the camera coordinate system is obtained by using a structured light camera to photograph the dry pot and identify the coordinates of the feature points in the camera coordinate system.

[0040] Furthermore, the tool system also includes a dust removal device. While the robot controls the laser to carry out the cleaning operation, it turns on the dust removal device to suck in the smoke and dust generated during the cleaning process.

[0041] The present invention also provides a vacuum coating chamber laser cleaning device based on a mobile robot, comprising:

[0042] A mobile robot having a tool system deployed at the end of its manipulator arm, the tool system including a structured light camera and a laser;

[0043] The visual calibration module is used to establish a vacuum chamber coordinate system with the rotation center of the dry pot in the vacuum coating chamber as the origin, select multiple corner points on the upper surface of the dry pot as feature points, obtain the coordinates of these feature points in the vacuum chamber coordinate system to obtain the first feature pose of the dry pot, move the robot to the vicinity of the vacuum coating chamber, and use a structured light camera to obtain the second feature pose of the dry pot in the camera coordinate system. Based on the first feature pose and the second feature pose, the first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system is determined.

[0044] The model processing module is used to fit the inner wall of the vacuum chamber into multiple cylindrical surface models with different radii in the vacuum chamber coordinate system.

[0045] The image path planning module is used to plan the acquisition path of the structured light camera for each cylindrical surface model and transform it to the robot base coordinate system based on the first mapping relationship.

[0046] The cleaning path planning module is used to identify the surface to be cleaned on the inner wall of the vacuum chamber based on the data collected by the structured light camera along the acquisition path and update it on the cylindrical surface model. Based on the updated cylindrical surface model, the cleaning path and pose of the laser are planned so that the unit energy of the laser emitted by the laser when it reaches the surface to be cleaned remains unchanged. Based on the first mapping relationship, the planned cleaning path and pose are converted to the robot base coordinate system.

[0047] The control system is used to control the structured light camera to take pictures along the converted acquisition path, to make the robot move along the converted cleaning path, and to drive the manipulator to control the laser to carry out the operation in the converted pose.

[0048] Furthermore, it also includes a human-machine interface system deployed on the terminal device; the visual calibration module, model processing module, photo path planning module, cleaning path planning module and control system are deployed on the edge computer, and the vacuum chamber model, cleaning progress and alarm information are sent to the human-machine interface system through a wireless network.

[0049] Beneficial effects

[0050] By adopting the above-mentioned technical solutions, this invention has the following advantages and positive effects compared with the prior art: This invention uses a dry pot inside a vacuum chamber as a calibration object. By operating a mobile robot to photograph the evaporation dry pot, the mapping relationship between the vacuum chamber coordinate system and the robot's base coordinate system is calibrated, omitting a complex calibration process and enabling quick and easy determination of the coordinate transformation between the robot and the vacuum chamber. Based on the cylindrical surface model of the vacuum chamber, this invention plans the corresponding route and then transforms it to the robot's base coordinate system. The robot is then controlled to move along the planned path for data acquisition and laser cleaning, achieving high-precision spatial coordinate mapping and dynamic path planning. This allows for rapid adaptation to different coating machines and supports remote control. Through laser pose planning and real-time control, this invention ensures that the unit energy of the laser emitted by the laser remains constant when it reaches the surface to be cleaned, ensuring balanced energy distribution and improving cleaning consistency. Furthermore, since the unit energy during laser cleaning is constant, the laser's moving speed can be adjusted according to the degree of contamination, thereby adjusting the laser irradiation time to ensure the cleaning effect. Attached Figure Description

[0051] Figure 1 This is a flowchart of the first embodiment of the present invention;

[0052] Figure 2 This is a structural diagram of the vacuum coating chamber according to the first embodiment of the present invention;

[0053] Figure 3 These are structural diagrams of the mobile robot in the first and second embodiments of the present invention;

[0054] Figure 4 This is a schematic diagram of the shooting path planning for the first embodiment of the present invention;

[0055] Figure 5 This is a schematic diagram of the cleaning path planning for the first implementation method of the present invention;

[0056] Figure 6 This is a schematic diagram of the system control architecture of the second embodiment of the present invention. Detailed Implementation

[0057] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0058] The first embodiment of the present invention relates to a laser cleaning method for a vacuum coating chamber based on a mobile robot, such as... Figure 1 As shown, it includes the following steps:

[0059] A tool system is deployed at the end of the robot's manipulator arm, which includes a structured light camera and a laser;

[0060] A vacuum chamber coordinate system is established with the rotation center of the dry crucible inside the vacuum coating chamber as the origin;

[0061] Multiple corner points on the upper surface of the dry pot are selected as feature points, and the coordinates of these feature points in the vacuum chamber coordinate system are obtained to obtain the first feature pose of the dry pot.

[0062] The robot is moved to the vicinity of the vacuum coating chamber, and the second feature pose of the dry pot in the camera coordinate system is obtained using a structured light camera.

[0063] Based on the first feature pose and the second feature pose, the first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system is determined.

[0064] The inner wall of the vacuum chamber is fitted as multiple cylindrical surface models with different radii in the vacuum chamber coordinate system. The acquisition path of the structured light camera is planned for each cylindrical surface model and transformed to the robot base coordinate system based on the first mapping relationship.

[0065] The structured light camera is controlled to take pictures along the converted acquisition path. Based on the acquired data, the surface to be cleaned on the inner wall of the vacuum chamber is identified and updated onto the cylindrical model.

[0066] The cleaning path and pose of the laser are planned based on the updated cylindrical surface model so that the unit energy of the laser emitted by the laser when it reaches the surface to be cleaned remains unchanged.

[0067] Based on the first mapping relationship, the planned cleaning path and pose are transformed into the robot's base coordinate system, allowing the robot to move along the transformed cleaning path and drive the manipulator to control the laser to carry out the operation in the transformed pose.

[0068] The first mapping relationship is obtained by using the corner points of the upper surface of the dry crucible in the vacuum coating chamber as feature points for calibration, specifically including:

[0069] Establish a second mapping relationship between the camera coordinate system and the tool system coordinate system, and a third mapping relationship between the tool system coordinate system and the robot base coordinate system when the structured light camera is shooting the dry pot;

[0070] Based on the second and third mapping relationships, the second feature pose is transformed into the robot base coordinate system;

[0071] Based on the second feature pose in the robot base coordinate system and the first feature pose in the vacuum chamber coordinate system, a first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system is established.

[0072] Because the constructed digital model of the vacuum chamber is in the vacuum chamber coordinate system, the paths planned based on this model are also in the vacuum chamber coordinate system. By utilizing the mapping relationship between the various coordinate systems, the planned paths in the vacuum chamber coordinate system can be transformed into those in the robot's base coordinate system.

[0073] like Figure 2 As shown, multiple corner points 103 are distributed on the upper surface of the dry crucible 102 inside the vacuum coating chamber 101. Preferably, four corner points at different positions are used as feature points for calibration. For example, two pairs of corner points that are symmetrically distributed relative to the rotation center of the dry crucible can be selected.

[0074] The inner wall of the vacuum coating chamber is a cylindrical structure, and its internal components are mainly composed of various pipes and cylindrical shells. Therefore, it can be abstracted as a three-dimensional digital model composed of multiple cylindrical surfaces. During route planning, the three-dimensional digital space can be converted into a two-dimensional planar distribution, specifically including:

[0075] Unfold each cylindrical model into a rectangular unfolded diagram;

[0076] Based on the positional relationship of each cylindrical surface model in three-dimensional space, draw the two-dimensional spatial distribution of the corresponding rectangular unfolded diagram;

[0077] The acquisition path of the structured light camera is planned based on the two-dimensional spatial distribution sequence of the rectangular unfolded diagram.

[0078] Data acquired using a structured light camera can be mapped onto a 3D digital model, allowing for route planning of cleaning operations based on its 2D planar distribution. Furthermore, to ensure that the unit energy of the laser beam reaching the surface to be cleaned remains constant, the laser's pose can be adjusted to be equidistant from the surface. This ensures consistent energy attenuation of the emitted light in the air, resulting in a constant unit energy upon reaching the cleaning surface.

[0079] In some preferred embodiments, the degree of contamination can be determined based on the data collected by the structured light camera, and then the moving speed of the laser can be adjusted according to the degree of contamination, so that the laser emitted by the laser irradiates the surface to be cleaned for a longer time when the degree of contamination is high, and irradiates the surface to be cleaned for a shorter time when the degree of contamination is low, thereby achieving a better cleaning effect.

[0080] A preferred embodiment 1 of the present invention is a mobile laser cleaning system and path planning method applicable to multiple coating machines of different models and locations. It relates to the fields of visual recognition, equipment maintenance, laser application and automation. It includes using a structured light camera to identify the calibration objects and parameters of the vacuum chamber of the coating machine involved, identifying the cleaning area and selecting the laser intensity, cleaning process and dust removal, and remote control of human-machine collaborative robot execution.

[0081] The components of a mobile robot are as follows Figure 3 As shown, it includes a mobile platform 201, a laser 202, a 3D camera 203, a dust collector 204, a robotic arm 205, and a robotic arm base 206.

[0082] Before cleaning, the vacuum chamber of the coating machine needs to be calibrated in terms of spatial coordinates. During operation, the laser's position within the vacuum chamber is obtained using the calibration data. The vacuum chamber is then scanned according to a pre-planned path. The area requiring cleaning is identified based on the obtained point cloud data. A segmented cleaning path is generated, and instructions are transmitted to the robot controller. The vacuum chamber wall diagram and cleaning path are displayed on the user interface, allowing for manual or remote control of the cleaning process. This method enhances the intelligence, flexibility, and automation of the operation, improves work efficiency and operator health and safety, and provides an efficient and intuitive solution for remote control of the human-robot collaborative arm. Specifically, the following steps are included:

[0083] (a) The tool system consisting of a structured light camera, a laser, and a dust hood is mounted on the end flange of the collaborative robot, and the coordinate transformation matrix T between the camera coordinate system, the laser coordinate system, and the robot tool coordinate system is obtained. 相机 T 激光 Transformation from robot tool coordinate system to robot base coordinate system (T) 基 (T) 基 (Calculations need to be performed in real time based on the robot's forward kinematics).

[0084] (b) Select the dry pot at the evaporation position as the calibration object, and establish the vacuum chamber coordinate system O with its rotation center. 真空 A three-dimensional model of the vacuum chamber was established using this coordinate system, yielding a digital model of its walls and other surfaces requiring cleaning and rust removal. Using the four corner points of the dry pot as feature points, the characteristic pose of the dry pot was obtained.

[0085] P 干锅-真空=(P1,P2,P3,P4)

[0086] (c) Establish the transformation matrix between the robot base coordinate system and the vacuum chamber coordinate system: Move the mobile platform to the vicinity of the coating machine, and obtain the pose P of the dry pot in the camera coordinate system through the structured light camera. 干锅-相机 This allows us to determine the transformation matrix T between the robot's base coordinates and the vacuum chamber coordinate system. 变 ;

[0087] (d) Based on the three-dimensional model of the vacuum chamber wall, an approximate fitting is performed using a cylindrical surface to obtain its position in the vacuum chamber coordinate system O. 真空 The digital model below is used to plan the movement path and shooting points of the 3D camera. For example, the shooting point W on the planned shooting path is located in coordinate system O. 真空 Below is W 真空 This requires controlling the collaborative robot's movement (in the robot's base coordinate system): W 基 =T 变 W 真空 Take a picture to obtain S in the camera coordinate system 相机 Transform camera coordinates into robot base coordinates: S 基 =T 基 T 相机 S 相机 Transforming the base coordinates to vacuum chamber coordinates: S 真空 =T -1 变 S 基 The cleaning area M was identified using a visual recognition method. 真空 and the required laser intensity;

[0088] (e) Based on the distance M of the laser from the cleaning surface 真空 The optimal distance d yields the laser pose P. 真空 The system plans the cleaning path for the laser, transmits the generated task path information to the robot controller, and plans the path P in the vacuum coordinate system. 真空 Transform to robot base coordinate system: P 基 =T 变 P 真空 The robotic arm moves the laser to this position and controls the laser beam to be parallel to the generatrix of the cylindrical surface. This ensures that the laser is equidistant from the surface being cleaned, achieving a better cleaning effect. It moves along the planned cleaning path, and while working, it activates the dust removal device to draw in fumes and dust.

[0089] (f) After all cleaning is completed, if manual cleaning is still required after manual confirmation, the operator can remotely operate the PAD to perform manual cleaning; after all cleaning is completed, the robot will automatically retract and leave the vacuum chamber of the coating machine, and the operator will move the platform to the next coating machine.

[0090] The origin of the vacuum chamber coordinate system can be chosen at the center point of the dry pot's rotation, thus establishing the vacuum chamber coordinate system O. 真空 Based on the CAD drawing of the vacuum chamber, and using an approximate fit through a cylindrical surface, assuming the cylinder axis is parallel to vector d=(a,b,c) and passes through point p0=(x0,y0,z0), the distance from a point on the cylindrical surface to the axis is r, and the height is h, its mathematical equation is:

[0091]

[0092]

[0093] Based on the imaging principle, we have the following transformation formula from the camera coordinate system to the robot's base coordinate system:

[0094] P 基 =T 基 T 相机 P 相机 (1)

[0095] Since the camera and laser are mounted on the same tool, the transformation of the camera and laser coordinates is a fixed transformation:

[0096] P 激光 = T 激光 相机 P 相机 (2)

[0097] The four corner points on the upper surface of the dry pot are selected as the recognition coordinate system O. 真空 Feature points, these four points in coordinate system O 真空 The middle is fixed, P 干锅-真空 = (P1, P2, P3, P4). The coordinates of the four corner points are identified by photographing the dry pot at the evaporation point using a 3D camera on the robot. According to equation (1), their coordinates in the robot's base coordinate system are obtained:

[0098] P 干锅-基 = T 基 T 相机 P 干锅-相机 ;

[0099] Because the dry pot is in the vacuum chamber coordinate system O 真空 The mid-coordinate is determined to be P. 干锅-真空 = (P1, P2, P3, P4), therefore we can obtain:

[0100] P 干锅-真空 = T 变 P 干锅-基 ; (3)

[0101] Therefore, the transformation matrix T between the robot's base coordinates and the vacuum chamber coordinate system can be determined.变 .

[0102] Step (d) involves fitting the vacuum chamber wall to cylindrical surfaces of different radii using cylindrical surface fitting. This allows the camera's image path to be planned by unfolding the wall into a rectangle. The overlap of each image is set to 10mm, and n images are planned sequentially. For example... Figure 4 As shown: The robotic arm controls the camera to move along the path, takes a picture at shooting point i, and then continues to move along the path to the next shooting point.

[0103] Step (e) Based on the identified cleaning area, the position and orientation of the laser are controlled according to the generatrix and normal direction of the surface, so that the light beam is parallel to the generatrix and the laser energy reaching the wall is the same, thus achieving green (energy-saving) manufacturing and optimizing the cleaning effect.

[0104] The robot moves along the path at a speed of 30 mm / s, and the pose of the laser and its distance from the cleaning surface are controlled in real time to ensure optimal cleaning results. Assume the area to be cleaned is a rectangle with sides of length a * b, the laser line length is c, and the initial distance d between the laser line and the cleaning area is (alternatively, area expansion can be performed first, expanding each side by a distance d, and then trajectory planning can be performed within the rectangular area):

[0105] (1) When the laser beam length c is greater than the width a+2d, the midpoint of the beam is directly cleaned in one go, such as Figure 5 (1);

[0106] (2) Follow the edge along the broken line, with the light edge extending beyond the cleaning edge d, and cover the entire cleaning area through the broken line, such as... Figure 5 (2).

[0107] A second embodiment of the present invention relates to a vacuum coating chamber laser device based on a mobile robot, used to implement the method described above. Specifically, it includes:

[0108] A mobile robot with a tool system deployed at the end of its manipulator arm, the tool system including a structured light camera and a laser;

[0109] The visual calibration module is used to establish a vacuum chamber coordinate system with the rotation center of the dry pot in the vacuum coating chamber as the origin, select multiple corner points on the upper surface of the dry pot as feature points, obtain the coordinates of these feature points in the vacuum chamber coordinate system to obtain the first feature pose of the dry pot, move the robot to the vicinity of the vacuum coating chamber, and use a structured light camera to obtain the second feature pose of the dry pot in the camera coordinate system. Based on the first feature pose and the second feature pose, the first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system is determined.

[0110] The model processing module is used to fit the inner wall of the vacuum chamber into multiple cylindrical surface models with different radii in the vacuum chamber coordinate system.

[0111] The image path planning module is used to plan the acquisition path of the structured light camera for each cylindrical surface model and transform it to the robot base coordinate system based on the first mapping relationship.

[0112] The cleaning path planning module is used to identify the surface to be cleaned on the inner wall of the vacuum chamber based on the data collected by the structured light camera along the acquisition path and update it on the cylindrical surface model. Based on the updated cylindrical surface model, the cleaning path and pose of the laser are planned so that the unit energy of the laser emitted by the laser when it reaches the surface to be cleaned remains unchanged. Based on the first mapping relationship, the planned cleaning path and pose are converted to the robot base coordinate system.

[0113] The control system is used to control the structured light camera to take pictures along the converted acquisition path, to make the robot move along the converted cleaning path, and to drive the manipulator to control the laser to carry out the operation in the converted pose.

[0114] In some preferred embodiments, the device also includes a human-machine interface system deployed on a terminal device. The visual calibration module, model processing module, image path planning module, cleaning path planning module, and control system are deployed on an edge computer, which transmits the vacuum chamber model, cleaning progress, and alarm information to the human-machine interface system via a wireless network.

[0115] like Figure 6 As shown, this is a preferred embodiment 2 of the present implementation.

[0116] like Figure 1 As shown, the mobile robot includes:

[0117] Mobile platform 201: Transports the robot from the standby position to the door of the vacuum chamber of the coating machine;

[0118] Laser 202: Employs a pulsed fiber laser with a power of 500–1000W and a wavelength of 1064 nm, featuring a coaxial red light indicator;

[0119] 3D Camera 203: Employs a structured light high-definition camera with a resolution of 2448 × 2048;

[0120] Dust collector 204: adopts a dust collection / smoke exhaust integrated head, negative pressure 20 kPa, built-in HEPA + activated carbon filter;

[0121] Robotic arm 205: It adopts a six-axis force-controlled collaborative robotic arm with a load capacity of 10 kg, a repeatability of ±0.05 mm, and an end flange integrated with a quick-change disc;

[0122] Robotic arm base 206: Fixes the robot manipulator 205 onto the mobile platform 201;

[0123] Communication and Interaction: The PAD app supports multi-touch, gesture selection, and real-time video.

[0124] Control system: Deployed on an edge computer, including the following modules:

[0125] Model processing module: A fitting model of the vacuum chamber based on the cylindrical model will be established in the vacuum chamber coordinate system;

[0126] Visual calibration module: Acquires 3D point cloud data of the vacuum chamber dry pot through a structured light camera, identifies four corner points and establishes the transformation relationship between the robot's base coordinates and the vacuum chamber coordinate system;

[0127] The module for planning shooting paths and shooting points: A digital model of each coating machine is pre-built, and the shooting points and movement paths are planned.

[0128] Cleaning path planning module: Based on point cloud segmentation and feature recognition, it generates segmented cleaning paths;

[0129] Control and Interaction System: The edge calculator transmits the path and process parameters generated by the cleaning path planning module to the robot controller as a robot control program, thereby starting the robot to execute the task;

[0130] Robot controller execution: Executes the control program, the robotic arm drives the laser to move, and adjusts the laser pose and power in real time (or turns it on and off) according to the cleaning path.

[0131] Human-Machine Interface (HMI): The PAD connects to the edge calculator via Wi-Fi. The PAD displays the vacuum chamber model, cleaning progress, and alarm information, and supports switching between manual and automatic modes.

[0132] Follow these steps to carry out the cleaning operation:

[0133] Step 1: Pre-model processing and shooting point path planning: Based on the CAD model of the vacuum chamber of each coating machine, a fitted digital model of the vacuum chamber based on a cylindrical model is established in the vacuum chamber coordinate system, and the shooting points and paths are planned; the distance from a point on the cylindrical surface to the axis is r, and the height is h, and its mathematical equation is:

[0134]

[0135]

[0136] Models of the walls in different regions are created separately, so that their generatrices and normal vectors can be obtained. The generatrices vector is the axis vector, and the normal vector is perpendicular to the generatrices and points towards the axis.

[0137] Step 2: Movable Calibration and Spatial Mapping: Move the robot to the vicinity of the vacuum chamber of the target coating machine, and scan the dry pot in the vacuum chamber with a structured light camera to obtain high-precision point cloud data. Combined with the calibration algorithm to identify four points, use a 3D camera to identify the dry pot at the evaporation position, and obtain the coordinates P of the four corner points on its upper surface in the robot coordinate system. R The coordinates of points P1, P2, P3, and P4 in the coordinate system of the vacuum chamber are P_1, P_2, P_3, and P_4. K K1, K2, K3, K4, thus the robot's position in the vacuum chamber coordinate system can be determined using these four corner points. P K =R K P R Since the camera is fixed at the robot's end effector, the transformation relationship T between the robot's base coordinate system and the vacuum chamber coordinate system can be determined using PK. 变 This is equivalent to establishing a mapping relationship between the base coordinate system of the pot robot and the coordinate system of the vacuum chamber through registration with the dry pot. This registration error is ≤0.5 mm.

[0138] Step 3: Cleaning Area Recognition and Path Planning: The camera transmits images to the PAD in real time. The operator selects the rusted ROI on the touchscreen. The system binarizes and extracts the contour of the ROI, forming a rectangular cleaning area. The controller determines the laser's pose based on the surface generatrix and normal information, maintaining the parallelism of the laser beam with the generatrix and the distance from the surface. It automatically generates the cleaning path and displays a preview on the PAD. After operator confirmation, the task is issued with a single click, and the robot enters automatic cleaning mode. A level system is established based on the degree of contamination. By changing the speed, the laser irradiation time on the surface varies, resulting in four levels: normal speed (V), heavy contamination (0.5V), medium contamination (0.75V), ordinary contamination (V), and light contamination (1.2V).

[0139] Step 4: Transfer the processing program to the robot controller: The main task of the system is completed in the edge processor. The edge processor transfers the generated robot control program to the robot controller via TCP / IP or OPC UA. The robot executes the program by controlling the command, ensuring that the distance between the laser head and the wall is constant, and controlling the light beam formed by the laser head to be parallel to the generatrix of the cleaning surface to ensure uniform energy distribution.

[0140] Step 5: Multi-mode cleaning execution:

[0141] Automatic mode: The robot autonomously completes the cleaning process according to the planned path;

[0142] Remote collaboration mode: Operators monitor and intervene in cleaning parameters (such as laser power and movement speed) in real time through HMI.

[0143] Manual mode: Manually control the robot to move in a vacuum coordinate system, browse video streams, and manipulate the laser. Based on the image transmitted from the 3D camera to the PAD, the operator manually determines the area to be cleaned and the cleaning intensity (laser strength), using the 3D coordinates identified by the camera and the optimal distance between the laser and the surface to be cleaned. The laser machine's red light is activated to identify the laser beam's position, positioning the laser at the beginning of the cleaning area, setting the laser's movement range, and then initiating the robot controller to execute the commands.

[0144] Step 6: Dust Removal and Quality Verification: An integrated negative pressure dust collection device collects particles generated during cleaning in real time. The cleaning effect is verified through secondary visual scanning analysis; unqualified areas are marked for automatic rework. A cleaning completion PDF report is automatically generated upon completion. After cleaning, the camera re-captures the ROI and calculates the percentage of rust pixels (ρ). If ρ > 5%, automatic re-scanning is performed; otherwise, a cleaning report (including before-and-after comparison images, time consumed, and energy consumption) is generated, and manual finishing is performed.

[0145] Step 7: Retract the robot to clean the next machine: After all are completed, set a one-key retraction on the HMI. The robot will automatically retract its arm, exit the vacuum chamber, and then be moved by the operator (or automatically by the AGV chassis) to the next coating machine.

Claims

1. A laser cleaning method for a vacuum coating chamber based on a mobile robot, characterized in that, Includes the following steps: A tool system is deployed at the end of the robot's manipulator arm, the tool system including a structured light camera and a laser; A vacuum chamber coordinate system is established with the rotation center of the crucible inside the vacuum coating chamber as the origin; Multiple corner points on the upper surface of the crucible are selected as feature points, and the coordinates of these feature points in the vacuum chamber coordinate system are obtained to obtain the first feature pose of the crucible. The robot is moved to the vicinity of the vacuum coating chamber, and the second feature pose of the crucible in the camera coordinate system is obtained using a structured light camera. Based on the first feature pose and the second feature pose, the first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system is determined. The inner wall of the vacuum chamber is fitted as multiple cylindrical surface models with different radii in the vacuum chamber coordinate system. The acquisition path of the structured light camera is planned for each cylindrical surface model and transformed to the robot base coordinate system based on the first mapping relationship. The structured light camera is controlled to take pictures along the converted acquisition path. Based on the acquired data, the surface to be cleaned on the inner wall of the vacuum chamber is identified and updated onto the cylindrical model. The cleaning path and pose of the laser are planned based on the updated cylindrical surface model so that the unit energy of the laser emitted by the laser when it reaches the surface to be cleaned remains unchanged. Based on the first mapping relationship, the planned cleaning path and pose are transformed into the robot's base coordinate system, allowing the robot to move along the transformed cleaning path and drive the manipulator to control the laser to carry out the operation in the transformed pose.

2. The method according to claim 1, characterized in that, The determination of the first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system based on the first feature pose and the second feature pose includes: Establish a second mapping relationship between the camera coordinate system and the tool system coordinate system, and a third mapping relationship between the tool system coordinate system and the robot base coordinate system when the structured light camera photographs the crucible; Based on the second and third mapping relationships, the second feature pose is transformed into the robot base coordinate system; Based on the second feature pose in the robot base coordinate system and the first feature pose in the vacuum chamber coordinate system, a first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system is established.

3. The method according to claim 2, characterized in that, The planned acquisition path of the structured light camera includes: Unfold each cylindrical model into a rectangular unfolded diagram; Based on the positional relationship of each cylindrical surface model in three-dimensional space, draw the two-dimensional spatial distribution of the corresponding rectangular unfolded diagram; The acquisition path of the structured light camera is planned based on the two-dimensional spatial distribution sequence of the rectangular unfolded diagram.

4. The method according to claim 3, characterized in that, The step of identifying the surface to be cleaned on the inner wall of the vacuum chamber based on the collected data and updating it on the cylindrical surface model includes: Based on the collected data, the surface to be cleaned on the inner wall of the vacuum chamber is identified, and the corresponding rectangular cleaning frame in the camera coordinate system is obtained; Based on the second mapping relationship, the cleaning box in the camera coordinate system is transformed to the robot base coordinate system; Based on the first mapping relationship, the cleaning frame in the robot base coordinate system is transformed to the vacuum chamber coordinate system, and then the rectangular cleaning frame is marked on the rectangular unfolded diagram of the corresponding cylindrical model.

5. The method according to claim 4, characterized in that, The cleaning path and pose of the laser are planned based on the updated cylindrical surface model to ensure that the unit energy of the laser emitted by the laser remains constant when it reaches the surface to be cleaned, including: Set the distance between the laser and the surface to be cleaned; When the length of the short side of the surface to be cleaned is less than the length of the laser beam, the laser is planned to perform a one-time cleaning along the central axis of the short side of the surface to be cleaned, while maintaining a constant distance from the surface to be cleaned during the cleaning process. When the length of the short side of the surface to be cleaned is greater than the length of the laser beam, the laser is planned to clean along a serpentine path covering the entire surface to be cleaned, while maintaining a constant distance from the surface to be cleaned during the cleaning process.

6. The method according to claim 5, characterized in that, Before planning the cleaning path and pose of the laser based on the updated cylindrical surface model, the method further includes the step of expanding the four sides of the rectangular cleaning frame outward by a set length.

7. The method according to claim 4, characterized in that, The process of identifying the surface to be cleaned on the inner wall of the vacuum chamber based on the collected data and obtaining the corresponding rectangular cleaning frame in the camera coordinate system includes: The surface to be cleaned on the inner wall of the vacuum chamber is selected based on the collected data. The selected surface to be cleaned is binarized and segmented before contour extraction is performed to form a rectangular cleaning frame in the camera coordinate system.

8. The method according to claim 1, characterized in that, Also includes: The degree of pollution is determined based on data collected by a structured light camera. The laser's moving speed is adjusted according to the degree of contamination, so that the emitted laser irradiates the heavily contaminated surface for a longer time and the lightly contaminated surface for a shorter time.

9. A vacuum coating chamber laser cleaning device based on a mobile robot, characterized in that, include: A mobile robot having a tool system deployed at the end of its manipulator arm, the tool system including a structured light camera and a laser; The visual calibration module is used to establish a vacuum chamber coordinate system with the rotation center of the crucible in the vacuum coating chamber as the origin, select multiple corner points on the upper surface of the crucible as feature points, obtain the coordinates of these feature points in the vacuum chamber coordinate system to obtain the first feature pose of the crucible, move the robot to the vicinity of the vacuum coating chamber, use a structured light camera to obtain the second feature pose of the crucible in the camera coordinate system, and determine the first mapping relationship between the vacuum chamber coordinate system and the robot base coordinate system based on the first and second feature poses. The model processing module is used to fit the inner wall of the vacuum chamber into multiple cylindrical surface models with different radii in the vacuum chamber coordinate system. The image path planning module is used to plan the acquisition path of the structured light camera for each cylindrical surface model and transform it to the robot base coordinate system based on the first mapping relationship. The cleaning path planning module is used to identify the surface to be cleaned on the inner wall of the vacuum chamber based on the data collected by the structured light camera along the acquisition path and update it on the cylindrical surface model. Based on the updated cylindrical surface model, the cleaning path and pose of the laser are planned so that the unit energy of the laser emitted by the laser when it reaches the surface to be cleaned remains unchanged. Based on the first mapping relationship, the planned cleaning path and pose are converted to the robot base coordinate system. The control system is used to control the structured light camera to take pictures along the converted acquisition path, to make the robot move along the converted cleaning path, and to drive the manipulator to control the laser to carry out the operation in the converted pose.

10. The apparatus according to claim 9, characterized in that, It also includes a human-machine interface system deployed on the terminal device; the visual calibration module, model processing module, photo path planning module, cleaning path planning module and control system are deployed on the edge computer, and the vacuum chamber model, cleaning progress and alarm information are sent to the human-machine interface system through a wireless network.

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