Control method for automatic spraying track generation system of reinforcing and leak repairing robot

Abstract

The invention discloses a control method of an automatic spraying track generation system of a reinforcing and leak repairing robot, and relates to the field of industrial automation, and the method comprises the steps: initializing the robot, carrying out environment monitoring, moving the robot to an operation position, and carrying out the precise recognition and positioning of an operation point; and the robot unfolds a mechanical arm according to the recognition and positioning result and makes spraying preparation, a spraying track is generated based on the recognition and positioning result, spraying operation is conducted based on the generated spraying track, and the robot completes the spraying operation and cleans materials. According to the method, the high-precision spraying track can be dynamically generated according to the geometrical characteristics of actual operation points, the limitation of a preset track is avoided, efficient coverage of a complex-shape area in the spraying process is ensured, real-time changes of the environment can be coped with in the spraying operation process through the dynamic adjustment function, and the spraying efficiency is improved. And the spraying uniformity and effective utilization of materials are ensured, the stability and consistency of the spraying quality are improved, and material waste is avoided.

Description

Technical Field

[0001] The invention relates to the field of industrial automation, and in particular to a control method for an automatic generation system of spraying trajectories of a reinforcement and leak repairing robot. Background Art

[0002] With the rapid development of industrial automation technology, robots are increasingly used in the fields of manufacturing and maintenance, especially in reinforcement and leak repair operations in complex environments, where automated spraying robots are gradually becoming the mainstream solution. Traditional reinforcement and leak repair operations mainly rely on manual operations, and workers need to complete spraying operations in dangerous or unstable environments, which is not only inefficient but also poses a great safety hazard.

[0003] The current mainstream technology still has some obvious deficiencies in the generation and execution of spraying trajectories. First, for complex surfaces, existing spraying robots usually only rely on rough recognition of surface geometry and cannot accurately locate the operation point, resulting in inaccurate generation of spraying paths and affecting spraying quality. In addition, existing robots lack real-time monitoring and feedback mechanisms for the environment during the spraying operation, and cannot dynamically adjust spraying parameters according to real-time environmental changes or equipment status. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a control method for an automatic generation system of spray trajectories for a reinforcement and leak-proofing robot to solve the problem that, for complex surfaces, existing spray robots usually only rely on rough recognition of the surface geometry and are unable to accurately locate the working point, resulting in inaccurate generation of the spray path, affecting the spraying quality. In addition, the existing robots lack real-time monitoring and feedback mechanisms for the environment during the spraying operation and are unable to dynamically adjust the spraying parameters according to real-time environmental changes or equipment status.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a control method for a reinforcement and leak repair robot spray trajectory automatic generation system, which includes initializing the robot and performing environmental monitoring; Move the robot to the working position; Accurately identify and locate the operation point; The robot unfolds its arm and prepares for spraying based on the recognition and positioning results; Generate spraying trajectory based on the results of recognition and positioning; Perform spraying operation based on the generated spraying trajectory; The robot completes the spraying operation and cleans up the material; The robot moves to the next working position and repeats the operation.

[0007] As a preferred solution of the control method of the automatic generation system of spraying trajectory of the reinforcement and leak repairing robot of the present invention, the robot is initialized and the environment is monitored, which specifically includes the following steps: Check the chassis' drive motor and wheels by detecting the motor's feedback signal and displacement sensor; Confirm that the robot's tracks are aligned correctly; The six degrees of freedom joints of the robot arm are self-checked in turn, and the spray gun at the end of the robot arm is calibrated at the same time; Confirm whether the pressure and temperature of the leak-proof material in the tank are within the set range, and check the spraying pipeline, solenoid valve, heating and temperature control functions; Activate the robot's touch and collision avoidance device and check the sensor sensitivity and operation warning light; Calibrate the robot’s sensors and check the camera’s clarity and focus; The robot uses visual sensors to monitor whether there are people approaching in the working area and detect weather conditions.

[0008] As a preferred solution of the control method of the automatic generation system of spraying trajectory of the reinforcement and leak repairing robot of the present invention, wherein: moving the robot to the working position specifically includes the following steps: The robot central control unit receives the operation requirements of the current task; The car number recognition camera is used to identify the car that needs to be repaired. If the car number is successfully matched, the specific operation location is determined based on the geometric characteristics of the car, the operation task requirements and the car number, and a work environment map is constructed; Based on the work location and work environment map, a path planning algorithm is used to calculate the optimal path from the current location to the target location; Based on the optimal path, the central control unit issues a command to start the robot's drive motor, controlling the chassis to start moving, and the operation warning light continues to work during the movement; When the robot approaches the working position, it gradually slows down and controls the chassis to make final fine adjustments. After completing the alignment, it locks the current position.

[0009] As a preferred solution of the control method of the automatic generation system of spraying trajectory of the reinforcement and leak repairing robot of the present invention, the operation point is accurately identified and positioned, specifically including the following steps: Capturing image data of the vehicle cabin surface; Use the Canny edge detection algorithm to detect the edges of the car surface; Use Hough transform to identify geometric shapes in images; The geometric parameters and two-dimensional coordinates of the identified geometric shapes are calculated based on the recognition results of edge detection and Hough transform, and the Kalman filter is used to eliminate the noise and errors in the image data to generate the final work point positioning results; Set accuracy thresholds based on camera resolution, measurement errors caused by ambient lighting, and operational requirements; When the positioning result of the work point reaches the accuracy threshold, the two-dimensional coordinates and geometric parameters of the work point are locked to form the work point identification and positioning result.

[0010] As a preferred solution of the control method of the automatic generation system of spraying trajectory of the reinforcement and leak repairing robot of the present invention, the robot unfolds the mechanical arm and prepares for spraying according to the recognition and positioning results, which specifically includes the following steps: According to the instructions transmitted by the central control unit, the six degrees of freedom joints of the robot arm will start in sequence and gradually unfold according to the coordinates of the operation point; The robotic arm is deployed to the working position, and fine-tuned according to the geometric parameters of the working point, while the posture of the spray gun is corrected; Complete the spraying preparation by checking the air pressure and pipeline of the spraying pipeline to see if it is normal.

[0011] As a preferred solution of the control method of the automatic generation system of spraying trajectory of the reinforcement and leak repairing robot of the present invention, the spraying trajectory is generated based on the results of recognition and positioning, which specifically includes the following steps: Determine spraying parameters based on the identification and positioning results of the work point and the work requirements; Determine the initial spraying trajectory and moving step of the robot arm and spray gun according to the size and shape of the work point; Smoothing the initial spraying trajectory; The generated preliminary spraying trajectory is simulated by the simulation function, and the final spraying trajectory is obtained after simulation verification.

[0012] As a preferred solution of the control method of the automatic generation system of spraying trajectory of the reinforcement and leak repairing robot of the present invention, the spraying operation is performed based on the generated spraying trajectory, which specifically includes the following steps: The robot arm moves according to the final spraying trajectory and the spraying speed in the spraying parameters, while keeping the posture of the spray gun stable; Dynamically adjust the spraying width, pressure, flow, angle and distance according to the current working environment; During the spraying process, if it is detected that the working surface does not match the simulation results or the environmental conditions change, the spraying path and spraying parameters are adjusted.

[0013] As a preferred solution of the control method of the automatic generation system of spraying trajectory of the reinforcement and leak repairing robot of the present invention, wherein: the robot completes the spraying operation and cleans the material, and the robot moves to the next operation position to repeat the operation, specifically including the following steps: The central control unit will send out a spraying termination signal; Control the six degrees of freedom joints of the robot arm to retract to the initial state in sequence, and adjust the posture of the spray gun to the cleaning and maintenance position; Check whether the thickness, uniformity and coverage of the spraying area meet the operation requirements, collect images of the operation points, and record the unqualified areas; The material residue in the spray gun is cleaned by reverse airflow, and the material in the spray pipeline is automatically emptied; Check the amount of remaining material in the tank and monitor whether the pressure and temperature of the material are within the set range; After completing the current task, the robot will go to the next work location and repeat the operation until all tasks are completed.

[0014] In a second aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the control method of the automatic generation system of the spraying trajectory of the reinforcement and leak-proofing robot as described in the first aspect of the present invention is implemented.

[0015] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the control method of the automatic generation system of the spraying trajectory of the reinforcement and leak-proofing robot as described in the first aspect of the present invention is implemented.

[0016] The beneficial effects of the present invention are as follows: based on the results of identification and positioning, a specific spraying trajectory is generated. According to the size and shape of the operating point, the spraying parameters are determined to generate a preliminary spraying trajectory. At the same time, the trajectory is smoothed and simulated through the simulation function to finally determine the optimal spraying path. Through this step, a high-precision spraying trajectory can be dynamically generated according to the geometric characteristics of the actual operating point, avoiding the limitations of the preset trajectory, ensuring efficient coverage of complex shape areas during the spraying process, and further improving the accuracy and efficiency of the operation. In addition, according to the dynamic changes in the operating environment, the width, pressure, flow, angle and distance of the spraying are adjusted in real time. Through the dynamic adjustment function, the real-time changes in the environment can be responded to during the spraying operation, the uniformity of the spraying and the effective use of materials can be ensured, the stability and consistency of the spraying quality can be improved, and material waste can be avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 This is a flow chart of the control method of the automatic generation system of spraying trajectories of the reinforcement and leak repairing robot in Example 1.

[0019] Figure 2 Schematic diagram of the control method of the automatic generation system of spraying trajectories of the reinforcement and leak repairing robot in Example 1. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides a control method for a reinforcement leak repair robot spraying trajectory automatic generation system, comprising the following steps: S1. The feedback signal sensor on the drive motor monitors the working status of the motor and the displacement of the wheel in real time. The feedback signal can detect the current, voltage and speed of the motor to help determine whether the motor is in normal working condition.

[0024] S1.1. Check the relative position of the robot and the operating track to ensure that the robot is aligned with the track to avoid position deviation during operation.

[0025] S1.2. The robotic arm has six degrees of freedom, allowing it to move and adjust flexibly in three-dimensional space, ensuring that each joint is in normal working condition.

[0026] S1.3. Real-time monitoring of the pressure and temperature of the leak-proof material to see if they meet the process requirements.

[0027] For spray lines, solenoid valves, and heating and temperature control functions, ensure that material flows smoothly, lines are not blocked, and heating functions are normal.

[0028] Specifically, the built-in A tank and B tank have a capacity that can meet the spraying requirements of one shift (8 hours).

[0029] It is further explained that it is ensured that the leak-proof material is sprayed at a suitable temperature and pressure, thereby avoiding the problem of uneven spraying caused by abnormal material state.

[0030] S1.4. The touch collision avoidance device is used to detect objects or potential collision risks around the robot. When the touch collision avoidance device detects an obstacle, the robot will automatically stop moving to avoid collision.

[0031] The operation warning light sends out warning signals according to the robot's operating status, reminding surrounding personnel to stay away from the operating area.

[0032] It is further explained that by activating the touch anti-collision device and the operation warning light, the risk of collision of the robot during operation is effectively reduced, ensuring the safety of the operation. At the same time, the use of the warning light reminds the surrounding personnel to pay attention to the safety of the operation area, further reducing the risk of accidents during operation.

[0033] S1.5. Use image processing software to detect whether the camera image clarity and focal length are appropriate to ensure that high-quality image data can be captured.

[0034] S1.6. Monitor the dynamic situation in the working area in real time to determine whether there are people approaching the working area to ensure work safety.

[0035] When operating in rainy or snowy weather, the flexible part of the canopy will be unfolded to ensure that the robot can work normally.

[0036] Specifically, the robot can perform work tasks in an ambient temperature of -35℃~70℃, and in order to cope with the damage caused by the intrusion of solid objects and low-pressure water jets, the robot has IP55 protection measures and is equipped with protective clothing.

[0037] It is further explained that with strong protection capabilities, a wide range of working environment temperatures, coupled with protective clothing and canopies, the robot can cope with a variety of severe weather and temperature conditions to perform tasks normally, and complies with GB 146.2-2020 Standard Gauge Railway Limits Part 2: Building Limits Related Standards.

[0038] S2. The robot uses the car number recognition camera to identify the car number. The car number camera captures the car number and uses the image processing algorithm to recognize the car number. After successful recognition, the car number is matched with the task list in the database to confirm whether the car needs to be repaired.

[0039] S2.1. After the car number is matched successfully, the central control unit determines the specific location that needs to be repaired based on the geometric features of the car (such as car size, door gap position, etc.), task requirements and car number. At the same time, the geometric features of the car are scanned to generate a three-dimensional model of the car.

[0040] It is further explained that by constructing a map of the working environment, the geometric features of the carriage and the working position can be accurately grasped to ensure that the robot can accurately locate the area that needs to be repaired.

[0041] S2.2. Based on the generated work environment map and the determined work location, the central control unit uses a path planning algorithm (such as the Dijkstra algorithm) to calculate the optimal path for the robot from the current location to the target location. These path planning algorithms take into account factors such as the motion limitations of the robot chassis, track layout, and environmental obstacles to ensure that the robot can move to the work location along the shortest and safest path.

[0042] Specifically, the robot is powered by a cable drum (powered by 380V AC), which has a built-in slip ring device to ensure that the cable will not get tangled or be subjected to excessive tension when the robot moves. The cable drum drive automatically retracts and releases the cable according to the distance the robot moves, and the auxiliary cable guide device ensures that the cable always remains within the appropriate tension range to avoid affecting the robot's walking or operation. The maximum cable length is 120 meters (the robot's maximum walking distance is 120 meters), which can ensure that the robot can work continuously for 24 hours.

[0043] S2.3. After the path planning is completed, the central control unit issues a command to start the drive motor and control the chassis to move along the planned path. At the same time, the operation warning light continues to light up to remind the surrounding personnel that the robot is working.

[0044] Specifically, the track standard is a 30kg light rail with a track gauge of about 1000mm. The sliding device of the chassis matches the track to ensure stability and accuracy during movement. During the movement of the robot, the walking speed can be dynamically adjusted according to the real-time environment. Under standard conditions, the walking speed can be adjusted between 0~1000mm / sec.

[0045] When passing through narrow areas or approaching a work point, the robot will automatically slow down to ensure that it can accurately stop at the target position and avoid positioning errors caused by excessive speed.

[0046] S2.4. When the robot is very close to the target working position (usually within 10 cm), the chassis will automatically reduce the walking speed and enter the slow mode (usually at the millimeter level) to ensure that the robot can accurately stop at the target position.

[0047] When the robot is completely docked at the target position, the central control unit will lock the position to ensure that the robot does not deviate during operation.

[0048] Further explanation: the application of path planning algorithm enables the robot to choose the optimal path, avoiding unnecessary movement and energy consumption. Vehicle number recognition and work environment map construction ensure that the robot can accurately locate the work target.

[0049] S3. Real-time image capture of the carriage surface is performed to obtain image data of the carriage surface.

[0050] S3.1. Calculate the horizontal and vertical gradients of the image data using the Sobel operator, and then calculate the gradient amplitude and edge direction. The expressions are: ; ; in, represents the gradient amplitude, represents the horizontal gradient, represents the vertical gradient, represents the edge direction, represents the inverse tangent function.

[0051] These edges are important geometric features such as car doors, door gaps, and the contours of the car body.

[0052] S3.2. Hough transform is used to identify geometric shapes in the image. Hough transform can effectively detect the geometric shapes of the car surface and provide accurate geometric feature information. By identifying geometric shapes such as straight lines and circles, the geometric model of the car surface is further refined to help determine the specific location of the operation point.

[0053] S3.3. Based on the results of Canny edge detection and Hough transform, the geometric parameters (such as the length and angle of the straight line, the radius of the circle, etc.) and two-dimensional coordinates (i.e. the precise position of the geometric features on the surface of the carriage in the image) of the identified geometric shapes (such as the door gap, the top gap of the small door and the vertical gap of the middle door) are calculated. These geometric parameters and coordinates will be used to determine the location of the spraying operation.

[0054] S3.3.1. In order to improve positioning accuracy, Kalman filtering is used to filter out noise and errors in image data. Kalman filtering is an algorithm widely used in signal processing and estimation. It can optimize data through multiple iterations, eliminate errors introduced by factors such as ambient light and sensor noise, and generate more accurate positioning results for work points.

[0055] S3.4. Set the accuracy threshold according to the camera resolution, measurement error caused by ambient lighting, and operation requirements.

[0056] Specifically, the higher the camera resolution, the more image details it can capture, and the positioning accuracy of the work point will be improved accordingly. Changes in ambient lighting may cause increased noise in the image data, so the accuracy requirements are adjusted according to the lighting conditions. In addition, the accuracy threshold is set according to the current work requirements (such as the requirements for repairing leaks in different compartment door seams) to ensure that the work point positioning results meet the actual needs of the spraying operation.

[0057] It is further explained that it is possible to flexibly respond to different operating environments and ensure that the accuracy of the leak-filling operation is neither too low (resulting in leak-filling) nor too high (resulting in unnecessary computational burden).

[0058] S3.5. When it is detected that the positioning result of the working point has reached the set accuracy threshold, the robot central control unit will lock the two-dimensional coordinates and geometric parameters of the working point to ensure that subsequent spraying operations can be performed accurately.

[0059] S4. The two-dimensional coordinates and geometric parameters of the operating point are transmitted to the robot control unit.

[0060] Specifically, the robot arm activates the six degrees of freedom joints according to the coordinates of the work point. Each joint controls movement in one direction, including forward and backward, left and right, up and down translation, as well as rotation, tilt and other posture adjustments of the spray tool at the end of the robot arm. By coordinating the movement of each joint, the robot arm can gradually unfold to the designated work point position, ensuring that the spray gun can be aimed at the area that needs to be repaired.

[0061] S4.1. When the robot arm approaches the target operation point, the end position and posture of the robot arm are further fine-tuned according to the previously detected geometric parameters (such as the angle of the straight line, the radius of the circle, etc.).

[0062] Specifically, as the surface of the car may have slight changes in curvature or unevenness, precise fine-tuning is performed based on geometric parameters. For example, if the edge of the door gap is detected to be slightly tilted, the robot arm will adjust the position and direction of the spray gun to keep it parallel to the door gap to ensure uniform spraying effect.

[0063] At the same time, the spray gun posture is corrected according to the geometric characteristics of the working point (such as the inclination and curvature of the surface) to ensure that the spray gun maintains a suitable angle with the surface of the carriage. Usually, the spray gun needs to maintain a certain vertical or near vertical angle with the spraying surface to ensure that the spray material evenly covers the surface.

[0064] It is further explained that by accurately identifying the geometric features of the work point and combining the Kalman filter to eliminate noise, extremely high recognition accuracy and positioning accuracy can be achieved. Through edge detection and geometric feature analysis of the door seam of the car, the accuracy of successfully identifying the edge of the door seam reached 96%. This high accuracy is due to the in-depth analysis of complex geometric shapes, especially the real-time recognition and adjustment capabilities of subtle curvatures and inclinations. In addition, the positioning accuracy of the end of the robotic arm can reach 1 cm when locating the work point. The robotic arm can accurately reach the specified position on the surface of the car with extremely small errors, ensuring that the spraying material only covers the target area without overspraying or missing spraying. This high-precision positioning is due to the synergy of the high-resolution camera, precise geometric analysis algorithm and the six-degree-of-freedom control system of the robotic arm.

[0065] S4.2. Driven by air pressure, ensure that the spray material can be sprayed out from the spray gun at appropriate pressure.

[0066] Monitor the air pressure in the spray line in real time to ensure that it is maintained within the appropriate range. If the air pressure is insufficient, the spray may not cover the surface evenly; if the air pressure is too high, it may cause material waste or overspray.

[0067] S4.3. Check whether the spraying pipeline is unobstructed to ensure that the spraying material can be smoothly delivered to the spray gun. If there is a blockage or leakage in the pipeline, an alarm will be issued and the operation will be suspended to avoid spraying failure or material waste.

[0068] S5. Spraying parameters include spraying material flow, air pressure intensity, spraying coverage and spraying speed. These parameters will be adjusted according to the geometric characteristics of the work point (such as area, shape, edge characteristics, etc.) and environmental conditions (such as the material, light, temperature, etc. of the car surface).

[0069] For example, for larger surface areas on a train cabin, choose a larger spray coverage area and a higher material flow rate to speed up the job.

[0070] For narrow door gaps or small cracks, reduce the spray coverage area and reduce the flow rate and speed to ensure that the material accurately fills the gap.

[0071] S6. Generate a preliminary spraying trajectory based on the characteristics of the work point Specifically, if the work point is a straight line (such as the edge of a car door), a spraying trajectory aligned with the straight line is generated. The spray gun moves along this straight line trajectory to ensure that the material evenly covers the entire edge. The trajectory generation takes into account the spray coverage range, so that each moving step can allow the spray area to have appropriate overlap. If the work point is a circle (such as the edge of the car vent), a circular spraying trajectory is generated. The spray gun moves evenly along the circular trajectory to ensure that the spray material covers the entire circumference. For larger circular areas, multiple concentric circle trajectories are generated to gradually cover the entire area from the outside to the inside. For complex and irregular work points (such as cracks on the surface of the car), more complex spraying trajectories are generated based on the edge point set. Smooth curve trajectories are generated through fitting techniques (such as B-spline or Bezier curves) so that the spray gun can move along the contour of the work point. For irregular closed areas, a "grid" or "snake"-like trajectory is generated to ensure that every part is evenly covered.

[0072] S6.1. The trajectory generation is optimized based on the spray coverage of the spray gun to ensure that after each move, the new spray area has appropriate overlap with the previous spray area. This prevents waste of spray material or insufficient coverage. At the same time, the movement step of the spray gun is determined according to the size and shape of the work point. For larger work points, the step distance can be appropriately increased to speed up the work; for fine work points, the step distance will be reduced to ensure high-precision spraying effects.

[0073] S6.1.1. When a single layer is not sufficient to meet the leak repair needs, a multi-layer spraying trajectory will be planned according to the work requirements.

[0074] Specifically, for deep cracks or large areas of leak repair, multiple spraying paths are planned. Each spraying trajectory will be appropriately adjusted based on the previous trajectory to ensure that the material is covered layer by layer while avoiding excessive accumulation of material.

[0075] S6.2. Eliminate sharp turning points or discontinuous motion in the initial spray trajectory by using curve fitting algorithms (such as B-spline or Bezier curves). A smooth trajectory ensures that the spray gun can maintain a stable speed and trajectory throughout the movement process, avoiding uneven spraying due to abrupt turns or speed changes. The movement speed and posture of the spray gun will be adjusted according to the curvature of the trajectory. For example, when the trajectory curvature is large (such as in a complex curve area), the movement speed of the spray gun will be slowed down to ensure that the spray material can evenly cover the curved surface.

[0076] S6.3. Run the generated spray trajectory in a dedicated simulation environment to simulate the actual movements of the robot arm and spray gun. During the simulation, check whether the spray gun can accurately cover the operating point according to the preset trajectory and step length, and detect possible problems in the spraying process, such as missing spray range, too long or too short trajectory, improper spray gun posture, etc. If a problem with the trajectory is found in the simulation, the trajectory parameters are automatically adjusted and the spray trajectory is regenerated until the simulation results meet the operation requirements. After the simulation passes, the trajectory becomes the final spray trajectory and is uploaded to guide the actual operation.

[0077] It is further explained that by generating appropriate spraying trajectories for different working points, it is ensured that the spraying operation can cover all areas that need to be repaired regardless of the shape of the working point.

[0078] S6. The robot arm will perform the actual spraying operation according to the final generated spraying trajectory. According to the settings in the spraying parameters, the robot arm will control the movement speed of the spray gun. At the same time, in order to ensure the uniform distribution of the spraying material, the robot arm must keep the spray gun stable during the movement.

[0079] S6.1. Changes in the external environment will affect the spraying effect. It is necessary to have the ability to adjust the spraying parameters in real time to cope with changes in environmental conditions. For example, factors such as the material, temperature, and humidity of the car surface will affect the adhesion and diffusion of the spraying material.

[0080] Specifically, the spray path is automatically adjusted after detecting changes in the working surface or environmental conditions. For example, if new unevenness is detected on the working surface, the spray path is replanned so that the spray gun can adapt to the new surface shape. At the same time, the spray speed, angle and posture are also adjusted to ensure that the spray material can be evenly covered.

[0081] It is further explained that the robot arm is able to perform high-precision movements according to the final spraying trajectory and improve operating efficiency by dynamically adjusting the spraying parameters, especially in large areas or complex operating points, to ensure the uniformity of spraying, ensure that the material is accurately attached to the target area, and improve economic benefits.

[0082] For example, the repair work of the bottom seam of the small door of C6X.

[0083] After confirming that the location of the work point is the bottom seam of the small door, the central control unit automatically sets the spraying parameters according to the size and shape of the work point, including: Spraying width: According to the width of the bottom seam of the small door, adjust the spraying width so that the material can evenly cover the entire gap. Spraying flow rate: According to the depth of the work point and the size of the gap, adjust the flow rate of the spraying material to ensure that enough material can fill the gap. Spraying pressure and angle: Set the appropriate spraying pressure and tilt angle of the spray gun to ensure that the material can evenly adhere to the surface of the gap.

[0084] The six-degree-of-freedom robot arm starts spraying according to the previously generated spraying trajectory. The robot arm's motion trajectory ensures that the spray gun moves evenly along the entire length of the bottom seam of the small door, keeping the distance and angle between the spray gun and the gap stable to prevent over- or under-spraying of material. The spray function is activated, and the leak-proof material in the A / B tank is transported to the spray gun through the three-in-one-out mixing joint, mixed and sprayed.

[0085] When the spraying operation of the bottom seam of the small door is completed, the robot will check the spraying effect again through the operation camera to ensure that there is no omission or uneven spraying. After confirming that the operation is completed, the robot arm retracts to its initial position.

[0086] Specifically, the leak repairing material in the storage tank is sufficient to support continuous operation for more than 8 hours, so the robot can continue to the next operation without frequent replenishment of materials. The entire small door low seam leak repairing operation takes less than 1.2 minutes. Further explanation: the middle door leak repairing operation takes less than 2 minutes, and the operation time for a single carriage is less than 10 minutes.

[0087] S7. When the leak repairing operation is completed, a signal for spraying termination will be issued, and the six degrees of freedom joints of the control robot arm will retract to the initial state in sequence. The posture of the spray gun is adjusted to the cleaning and maintenance position, usually with the spray gun facing downward or vertical to the ground, to facilitate the cleaning of residual materials and prevent the material from clogging the nozzle or pipeline.

[0088] The S7.1 detects material thickness and uniformity in the sprayed area to ensure they meet standards. If areas of unevenness or insufficient thickness are detected, these areas are automatically recorded and marked.

[0089] The material remaining in the spray gun nozzle and internal pipeline is blown out through reverse airflow to prevent the material from solidifying or clogging the nozzle, and the emptying solenoid valve is opened to empty the unused material in the spray pipeline to ensure that the pipeline is clean and ready for the next spraying operation.

[0090] S7.2. Check the remaining amount of material in the A and B material tanks to ensure that it is sufficient for the next spraying operation. If the material is insufficient, issue a prompt to request additional material.

[0091] Detect the pressure and temperature of the material tank to ensure that they are within the set range. If the pressure is too low or the temperature does not meet the requirements, the heating and temperature control functions are automatically adjusted to avoid material performance degradation.

[0092] S7.3, after completing all the procedures at the current operation point, the robot will move to the next operation position through the robot track, ready to perform the next leak repair task. The entire process is automatically scheduled by the central control unit until all the operation points are completed.

[0093] It is further explained that the robot can move and work continuously, which reduces the working time and improves the overall efficiency. The robot can complete the work of a single carriage in less than 10 minutes, which greatly improves the working efficiency.

[0094] This embodiment also provides a computer device, which is suitable for the control method of the automatic generation system of the spray trajectory of the reinforcement and leak-proofing robot, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the control method of the automatic generation system of the spray trajectory of the reinforcement and leak-proofing robot proposed in the above embodiment.

[0095] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0096] The present embodiment also provides a storage medium on which a computer program is stored. When the program is executed by the processor, the control method for realizing the automatic generation system of the spraying trajectory of the reinforcement and leak repairing robot proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0097] In summary, the present invention generates a specific spraying trajectory based on the results of identification and positioning. According to the size and shape of the operating point, the spraying parameters are determined to generate a preliminary spraying trajectory. At the same time, the trajectory is smoothed and simulated through the simulation function to finally determine the optimal spraying path. Through this step, a high-precision spraying trajectory can be dynamically generated according to the geometric characteristics of the actual operating point, avoiding the limitations of the preset trajectory, ensuring efficient coverage of complex shape areas during the spraying process, and further improving the accuracy and efficiency of the operation. In addition, according to the dynamic changes of the operating environment, the width, pressure, flow, angle and distance of the spraying are adjusted in real time. Through the dynamic adjustment function, the real-time changes of the environment can be coped with during the spraying operation, the uniformity of the spraying and the effective use of materials can be ensured, the stability and consistency of the spraying quality can be improved, and material waste can be avoided.

[0098] Example 2, referring to Table 1, is the second example of the present invention. To further verify the technical solution of the present invention, experimental simulation data of the control method of the automatic generation system of the spraying trajectory of the reinforcement and leak repairing robot are provided.

[0099] This embodiment aims to verify the advantages of the control method of the automatic generation system of spraying trajectory of reinforcement and leak repairing robot in practical application, and compare it with the existing spraying method. The specific compared technologies are comparison technology A and comparison technology B, which represent two mainstream spraying control methods respectively.

[0100] Comparative Technology A: It uses the traditional manual assisted spraying method, where the operator manually controls the robotic arm to spray. The spraying trajectory depends on the operator's experience, and there is no automated trajectory generation method. In this method, the spraying path is pre-set, and the trajectory cannot be dynamically adjusted during the operation, resulting in the spraying effect being affected by human factors, and problems such as material waste and uneven spraying often occur.

[0101] Comparative Technology B: This method uses a basic automatic spray trajectory generation method, but it is based on simple geometric feature recognition and fixed trajectory planning algorithms, lacks the ability to adaptively adjust to real-time environmental changes, and cannot be dynamically corrected according to real-time sensor data during the spraying process. Although this method has a certain degree of automation, it is prone to uneven spraying and material waste in complex operating environments.

[0102] In order to verify the advantages of the invention, the test preparation and implementation steps are as follows: Robot initialization: Start the reinforcement and leak repair robot, check the chassis drive motor and wheels to see if they are operating normally, and confirm the alignment of the robot track. Calibrate the six degrees of freedom joints of the robot arm and the end spray gun to ensure accurate spraying posture. Automatically confirm whether the pressure and temperature of the leak repair material in the tank are within the set range, and check whether the spray pipeline, solenoid valve, heating and temperature control functions are normal. Start the touch anti-collision device, check the sensitivity of the sensor and the operation warning light, and finally calibrate the robot sensor to ensure that the camera clarity and focal length meet the operation requirements.

[0103] The robot moves to the working position: The central control unit receives the leak repair task, confirms the car and position to be worked on through the car number recognition camera, and generates a working environment map based on the geometric features and car number. The robot calculates the optimal path through the path planning algorithm, and moves along the track to the working position. When approaching the working position, the robot gradually slows down and makes fine adjustments to ensure that the position is aligned and then locks the current working point.

[0104] Identification and positioning of work points: The robot obtains image data of the car body surface through visual sensors, uses the Canny edge detection algorithm to identify the surface edge, and then combines Hough transform to identify the geometric shape. Based on these recognition results, the geometric parameters and two-dimensional coordinates of the work point are calculated, and the Kalman filter is used to eliminate noise to generate the final work point positioning result.

[0105] Generate spraying trajectory: Determine spraying parameters (spraying width, flow rate, angle, etc.) based on the identification and positioning results of the working point. Generate the initial spraying trajectory and smooth it. Use the simulation function to simulate the generated spraying trajectory to ensure its rationality and accuracy. Finally, confirm the spraying trajectory and enter the spraying preparation stage.

[0106] Spraying operation execution: The robot arm starts the operation according to the final generated spraying trajectory. During the spraying process, the working surface is monitored in real time and the spraying pressure, flow rate and angle are adjusted dynamically. If it is detected that the working surface does not match the simulation result, the spraying trajectory and parameters are automatically adjusted to ensure uniform and efficient spraying.

[0107] End of spraying operation: When the operation is completed, the central control unit sends a spraying termination signal, the robot arm gradually retracts to the initial state, and the spray gun is adjusted to the cleaning position. The residual material in the spray gun is cleaned by reverse airflow, and the pipeline is automatically emptied. The thickness, uniformity and coverage of the spraying area are detected, and the image of the working point is collected and the unqualified areas are recorded. Then, the robot moves to the next working point and repeats the operation.

[0108] The details are shown in Table 1 below: Table 1 Comparison of spraying effect

[0109] By comparing the performance of the three technologies (comparative technology A, comparative technology B and the present invention) in actual applications, it can be seen that the present invention has significant advantages in multiple key performance indicators.

[0110] Material utilization rate: The material utilization rate of comparison technology A is 67.5%, while that of comparison technology B is slightly improved to 72.3%. The material utilization rates of these two technologies are low, mainly because the spraying path cannot be accurately controlled, resulting in the material being sprayed into non-operating areas. However, the present invention increases the material utilization rate to 83.8% through the automatically generated precise spraying trajectory, and even reaches 91.2% in the dynamic adjustment mode. Therefore, the present invention can adjust the spraying parameters and paths according to the real-time environment to ensure that the material is only sprayed where it is needed.

[0111] Spraying uniformity: Comparative technology A performs poorly in spraying uniformity, with an error of ±55 microns, because it is difficult to maintain consistent spraying speed and pressure with manual assisted spraying. Comparative technology B is slightly improved, with a spraying uniformity error of ±40 microns. The present invention greatly reduces the spraying error to ±15 microns through precise trajectory generation algorithm and dynamic adjustment mechanism, and even reduces it to ±9 microns in dynamic adjustment mode.

[0112] Operation time: The operation time of comparison technology A is 16.7 minutes per car, while that of comparison technology B is reduced to 13.5 minutes. The present invention significantly shortens the operation time, which is only 9.1 minutes in automatic trajectory generation mode and further reduced to 8.7 minutes in dynamic adjustment mode. The present invention adopts more advanced path planning and trajectory generation algorithms, which can quickly generate the optimal spraying trajectory and reduce the time wasted by manual intervention through automated operations.

[0113] Positioning accuracy: The positioning accuracy of the comparison technology A is 3.5 cm, while that of the comparison technology B is improved to 2.8 cm. By adopting advanced image processing technologies such as Canny edge detection and Hough transform, the positioning accuracy of the present invention is improved to 1.1 cm, and the accuracy in the dynamic adjustment mode is 0.9 cm. This means that the present invention can more accurately identify the working point, ensure that the spraying trajectory is highly matched with the working point position, and reduce errors.

[0114] Spraying coverage: The spraying coverage of comparison technologies A and B is 87.9% and 90.2% respectively, with a slight difference, mainly due to inaccurate trajectory planning and environmental changes that lead to missed spraying in some areas. The present invention increases the coverage rate to 97.1% by automatically generating trajectories and dynamically adjusting spraying parameters, and reaches 98.4% in dynamic adjustment mode, almost achieving full coverage. This shows that the present invention can ensure that the spraying material accurately covers all areas that need to be reinforced based on the geometry of the work point and real-time environmental data.

[0115] Material waste: The material waste of comparison technology A is 2.8 kg / carriage, and that of comparison technology B is 2.2 kg. The present invention reduces the waste to 1.3 kg in the automatic trajectory generation mode and only 0.7 kg in the dynamic adjustment mode. By optimizing the spray trajectory in real time and dynamically adjusting the spray parameters, material waste can be greatly reduced, reducing operating costs.

[0116] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A control method for an automatic generation system of spraying trajectories of a reinforcement and leak repairing robot, characterized in that: include, Initialize the robot and perform environmental monitoring; Move the robot to the working position; Accurately identify and locate the operation point; The robot unfolds its arm and prepares for spraying based on the recognition and positioning results; Generate spraying trajectory based on the results of recognition and positioning; Perform spraying operation based on the generated spraying trajectory; The robot completes the spraying operation and cleans up the material; The robot moves to the next working position and repeats the operation.

2. The control method of the automatic generation system of spraying trajectory of reinforcement and leak repairing robot according to claim 1 is characterized by: Initialize the robot and perform environmental monitoring, which includes the following steps: Check the chassis' drive motors and wheels; Confirm that the robot's tracks are aligned correctly; The six degrees of freedom joints of the robot arm are self-checked in turn, and the spray gun at the end of the robot arm is calibrated at the same time; Confirm whether the pressure and temperature of the leak-proof material in the tank are within the set range, and check the spraying pipeline, solenoid valve, heating and temperature control functions; Activate the robot's touch and collision avoidance device and check the sensor sensitivity and operation warning light; Calibrate the robot’s sensors and check the camera’s clarity and focus; The robot uses visual sensors to monitor whether there are people approaching in the working area and detect weather conditions.

3. The control method of the automatic generation system of spraying trajectory of reinforcement and leak repairing robot according to claim 2 is characterized by: Moving the robot to the working position includes the following steps: The robot central control unit receives the operation requirements of the current task; The car number recognition camera is used to identify the car that needs to be repaired. If the car number is successfully matched, the specific operation location is determined based on the geometric characteristics of the car, the operation task requirements and the car number, and a work environment map is constructed; Based on the work location and work environment map, a path planning algorithm is used to calculate the optimal path from the current location to the target location; Based on the optimal path, the central control unit issues a command to start the robot's drive motor, controlling the chassis to start moving, and the operation warning light continues to work during the movement; When the robot approaches the working position, it gradually slows down and controls the chassis to make final fine adjustments. After completing the alignment, it locks the current position.

4. The control method of the automatic generation system of spraying trajectory of reinforcement and leak repairing robot according to claim 3 is characterized by: Accurately identify and locate the work point, including the following steps: Capturing image data of the vehicle cabin surface; Use the Canny edge detection algorithm to detect the edges of the car surface; Use Hough transform to identify geometric shapes in images; Based on the recognition results of edge detection and Hough transform, the geometric parameters and two-dimensional coordinates of the recognized geometric shapes are calculated, and Kalman filtering is used to eliminate noise and errors in the image data to generate the final work point positioning results; Set accuracy thresholds based on camera resolution, measurement errors caused by ambient lighting, and operational requirements; When the positioning result of the work point reaches the accuracy threshold, the two-dimensional coordinates and geometric parameters of the work point are locked to form the work point identification and positioning result.

5. The control method of the automatic generation system of spraying trajectory of reinforcement and leak repairing robot according to claim 4 is characterized in that: The robot unfolds its arm and prepares for spraying according to the recognition and positioning results, which includes the following steps: According to the instructions transmitted by the central control unit, the six degrees of freedom joints of the robot arm will start in sequence and gradually unfold according to the coordinates of the operation point; The robotic arm is deployed to the working position, and fine-tuned according to the geometric parameters of the working point, while the posture of the spray gun is corrected; Complete the spraying preparation by checking the air pressure and pipeline of the spraying pipeline to see if it is normal.

6. The control method of the automatic generation system of spraying trajectory of reinforcement and leak repairing robot according to claim 5 is characterized by: The spraying trajectory is generated based on the results of recognition and positioning, which specifically includes the following steps: Determine spraying parameters based on the identification and positioning results of the work point and the work requirements; Determine the initial spraying trajectory and moving step of the robot arm and spray gun according to the size and shape of the work point; Smoothing the initial spraying trajectory; The generated preliminary spraying trajectory is simulated by the simulation function, and the final spraying trajectory is obtained after simulation verification.

7. The control method of the automatic generation system of spraying trajectory of reinforcement and leak repairing robot according to claim 6 is characterized by: The spraying operation is performed based on the generated spraying trajectory, which specifically includes the following steps: The robot arm moves according to the final spraying trajectory and the spraying speed in the spraying parameters, while keeping the posture of the spray gun stable; Dynamically adjust the spraying width, pressure, flow, angle and distance according to the current working environment; During the spraying process, if it is detected that the working surface does not match the simulation results or the environmental conditions change, the spraying path and spraying parameters are adjusted.

8. The control method of the automatic generation system of spraying trajectory of reinforcement and leak repairing robot according to claim 7 is characterized by: After the robot completes the spraying operation and cleans the material, it moves to the next operation position and repeats the operation. The specific steps include: The central control unit will send out a spraying termination signal; Control the six degrees of freedom joints of the robot arm to retract to the initial state in sequence, and adjust the posture of the spray gun to the cleaning and maintenance position; Check whether the thickness, uniformity and coverage of the spraying area meet the operation requirements, collect images of the operation points, and record the unqualified areas; The material residue in the spray gun is cleaned by reverse airflow, and the material in the spray pipeline is automatically emptied; Check the amount of remaining material in the tank and monitor whether the pressure and temperature of the material are within the set range; After completing the current task, the robot will go to the next work location and repeat the operation until all tasks are completed.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the control method of the reinforcement leak repair robot spray trajectory automatic generation system according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the control method of the reinforcement leak repair robot spray trajectory automatic generation system according to any one of claims 1 to 8 are implemented.

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