Intelligent polishing robot automatic polishing decision planning system and planning method

Abstract

The application discloses an intelligent polishing robot automatic polishing decision planning system and a planning method, relates to the technical field of intelligent polishing robots, and the system comprises: an image acquisition module: the surface of a workpiece to be polished is photographed, and the image of the workpiece surface is acquired; an image processing module: the height of each point on the surface of the workpiece in the image is determined, the polishing area is determined according to the height of each point on the surface of the workpiece, and the roughness of each polishing area is determined; a polishing decision module: the optimal polishing parameter combination is determined according to the roughness in the polishing area; and an execution module: automatic polishing of each polishing area of the surface of the workpiece is realized according to the optimal polishing parameter combination. The polishing parameters can be dynamically adjusted according to the roughness of the surface of the workpiece, and the polishing effect is improved.

Description

Technical Field

[0001] This invention belongs to the field of intelligent grinding robot technology, specifically relating to an automatic grinding decision-making and planning system and planning method for intelligent grinding robots. Background Technology

[0002] Grinding is a common surface treatment process that can improve the surface quality and geometric accuracy of workpieces, remove surface defects and oxide layers, and improve the service life and performance of workpieces. Grinding usually requires manual operation, which is time-consuming and labor-intensive, and there are also problems such as safety hazards and unstable quality.

[0003] A grinding robot is an automated device specifically designed for surface grinding, polishing, deburring, and other similar tasks. They are widely used in manufacturing, particularly in the surface treatment of materials such as metals, plastics, and wood. Grinding robots typically possess the following characteristics: High precision: They can precisely control the grinding force and position, ensuring consistent surface treatment quality for each workpiece; High efficiency: Compared to manual grinding, robots can work continuously, significantly improving production efficiency.

[0004] Existing intelligent grinding robots typically use pre-set grinding strategies. Although they can make grinding decisions relatively accurately, the grinding parameters, such as grinding speed, grinding force, and angle, are often fixed values ​​or ranges obtained from experience or experiments. They cannot be dynamically adjusted according to different workpiece surface characteristics and defects, resulting in poor grinding effects.

[0005] For example, Chinese patent document, publication number CN116533103A, publication date August 4, 2023, entitled "Grinding Actuator, Grinding Robot and Grinding Method", describes a prior art grinding actuator that can be installed on a general robot to perform automated grinding. During the grinding process, the grinding actuator can adjust the grinding pressure itself to achieve constant force grinding.

[0006] The aforementioned prior art sets a pre-set grinding pressure, which is maintained by the grinding actuator. However, the grinding pressure varies for different workpiece surfaces, so the prior art cannot dynamically adjust according to different workpiece surfaces, resulting in poor grinding effect. Summary of the Invention

[0007] To address the shortcomings of the existing technology, this invention provides an intelligent grinding robot automatic grinding decision-making and planning system and method, which can dynamically adjust grinding parameters according to the surface roughness of the workpiece to improve the grinding effect.

[0008] This invention is achieved through the following technical solution: The intelligent grinding robot's automatic grinding decision-making and planning method is characterized by the following steps: S1. Take a picture of the surface of the workpiece to be polished to obtain an image of the workpiece surface; S2. Process the image in step S1 to determine the height of each point on the workpiece surface in the image. Determine the grinding area based on the height of each point on the workpiece surface, and determine the roughness of each grinding area. The roughness is the average of the heights of all points in the grinding area. S3. Based on the roughness of the grinding area, set the grinding parameters and the range of grinding parameters, and determine the optimal combination of grinding parameters through a genetic algorithm; S4. Based on the optimal combination of grinding parameters, the intelligent grinding robot is controlled to automatically grind each grinding area on the surface of the workpiece.

[0009] Furthermore, step S2 specifically includes, S2.1. Draw a circle with point i as the center and a preset radius R, and calculate the height difference HDa = |Ha' - Hi|, where Ha' represents the height of the a-th point inside the circle, and Hi represents the height of point i. When there is a height difference greater than or equal to a preset difference threshold, subtract a preset radius correction value from the preset radius R. R obtains a new radius R1; S2.2 Repeat step S2.1 with the newly obtained radius R1 until there is no height difference greater than or equal to the preset difference threshold, and take the corresponding circular area as a polishing area. S2.3. Using points not belonging to the grinding area as the center, draw circles with a preset radius R, and repeat the above steps to determine all grinding areas and their corresponding roughness.

[0010] Furthermore, in step S2.1, when there is no height difference greater than or equal to a preset difference threshold, the preset radius R is added to a preset radius correction value. R obtains a new radius R2, and the height difference is calculated again until the height difference is greater than or equal to the preset difference threshold for the first time. The area of ​​the circle corresponding to this time is taken as a polishing area.

[0011] Furthermore, in step S2.3, points not belonging to the grinding area are designated as undetermined points. A circle with a preset radius R is drawn with the undetermined point as the center. If the circle does not intersect with the determined grinding area, the grinding area is determined as follows: First, several gradient value ranges are set from low to high. Then, the gradient values ​​of several undetermined points are calculated. The gradient value of each undetermined point is placed within its corresponding gradient value range, and the area formed by undetermined points within the same gradient value range is determined as the grinding area. The gradient value is calculated using the following formula. G K Indicates the calculation of the firstK Gradient values ​​at points to be determined K =0, 1, 2, ..., n, .

[0012] Furthermore, step S2 also includes obtaining the roughness of all polished areas and generating a judgment set C = (C1, C2, C3, ..., Cn), and obtaining the maximum roughness C based on the judgment set C. max and the minimum roughness C min Where Cn represents the roughness of the nth polishing area, when C... max When Cfir is less than Cfir, no grinding is required on the workpiece; Cfir represents the preset first roughness threshold. min When the value is greater than or equal to Csec, a warning message is sent to report an error. Csec = Cfir + C, where C represents the preset roughness correction value.

[0013] Furthermore, step S3 specifically includes, S3.1 Set the grinding parameter range, which includes the grinding force range [Fmin, Fmax], the grinding speed range [Vmin, Vmax], and the grinding time range [Tmin, Tmax]. The grinding force is the force F during grinding, the grinding speed is the moving speed V of the grinding tool on the workpiece surface, and the grinding time is the grinding time T in each grinding area. S3.2 Obtain the roughness of the A-th grinding region, and use the negative value of the corresponding roughness as the fitness function. Determine the optimal grinding parameter combination (FA', VA', TA') in the A-th grinding region according to the genetic algorithm, where FA' represents the optimal grinding force in the A-th grinding region, VA' represents the optimal grinding speed in the A-th grinding region, and TA' represents the optimal grinding time in the A-th grinding region.

[0014] An intelligent grinding robot automatic grinding decision-making and planning system that implements the intelligent grinding robot automatic grinding decision-making and planning method described in any one of the above-mentioned methods is characterized by comprising an image acquisition module, an image processing module, a grinding decision module, and a grinding execution module. The image acquisition module is used to capture images of the workpiece surface to be polished. The image processing module processes the images acquired by the image acquisition module, determines the grinding area based on the height of each point on the workpiece surface, and determines the roughness of each grinding area. The grinding decision module sets grinding parameters and their range based on the roughness of the grinding area, and determines the optimal combination of grinding parameters through a genetic algorithm. The grinding execution module automatically grinds each grinding area on the workpiece surface according to the optimal combination of grinding parameters.

[0015] The beneficial effects of this invention are as follows: The workpiece is fixed on the plane of the worktable or fixture. First, an image of the workpiece surface is acquired, which forms the basis for subsequent processing. It is important to note that when acquiring the height of each point on the workpiece surface, only one side is acquired, not all surfaces simultaneously. The height of each point on the workpiece surface is then determined, serving as a reference standard for subsequently determining the grinding area and quantifying the surface roughness. Lower roughness results in a smoother surface. Next, the grinding area is determined, ensuring that the height of each point within the grinding area is within a certain range, without significant fluctuations that could lead to deviations in the subsequent roughness and the optimal grinding parameter set determined based on roughness, affecting the grinding effect. Finally, the grinding parameter range is set, ensuring that the final optimal grinding parameter set is within the range and will not damage the workpiece. A genetic algorithm is then used to determine the optimal grinding parameter combination for each grinding area. Automatic grinding is then performed on each grinding area of ​​the workpiece surface based on the optimal grinding parameter combination. The grinding parameters can be dynamically adjusted according to the surface roughness to improve the grinding effect. Attached Figure Description

[0016] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1 The intelligent grinding robot's automatic grinding decision-making and planning method includes the following steps. S1. Take a picture of the surface of the workpiece to be polished to obtain an image of the workpiece surface; S2. Process the image in step S1 to determine the height of each point on the workpiece surface in the image. Determine the grinding area based on the height of each point on the workpiece surface, and determine the roughness of each grinding area. The roughness is the average of the heights of all points in the grinding area. S3. Based on the roughness of the grinding area, set the grinding parameters and the range of grinding parameters, and determine the optimal combination of grinding parameters through a genetic algorithm; S4. Based on the optimal combination of grinding parameters, the intelligent grinding robot is controlled to automatically grind each grinding area on the surface of the workpiece.

[0019] During implementation, the workpiece is fixed on the plane of the worktable or fixture. First, an image of the workpiece surface is acquired, which forms the basis for subsequent processing. It is important to note that when acquiring the height of each point on the workpiece surface, only one side is acquired, not all surfaces simultaneously. Then, the height of each point on the workpiece surface is determined, serving as a reference standard for subsequently determining the grinding area and quantifying the surface roughness. The lower the roughness, the smoother the workpiece surface. Next, the grinding area is determined, ensuring that the height of each point within the grinding area is within a certain range, without significant fluctuations that could lead to deviations in the subsequent roughness and the optimal grinding parameter set determined based on the roughness, affecting the grinding effect. Finally, the grinding parameter range is set, ensuring that the final optimal grinding parameter set is within the range and will not damage the workpiece. The optimal grinding parameter combination for each grinding area is determined using a genetic algorithm, and automatic grinding is achieved for each grinding area on the workpiece surface based on the optimal grinding parameter combination.

[0020] Example 2 This embodiment further elaborates and supplements the implementation of the present invention based on Embodiment 1.

[0021] Step S2 specifically includes, S2.1. Draw a circle with point i as the center and a preset radius R, and calculate the height difference HDa = |Ha' - Hi|, where Ha' represents the height of the a-th point inside the circle, and Hi represents the height of point i. When there is a height difference greater than or equal to a preset difference threshold, subtract a preset radius correction value from the preset radius R. R obtains a new radius R1; S2.2 Repeat step S2.1 with the newly obtained radius R1 until there is no height difference greater than or equal to the preset difference threshold, and take the corresponding circular area as a polishing area. S2.3. Using points not belonging to the grinding area as the center, draw circles with a preset radius R, and repeat the above steps to determine all grinding areas and their corresponding roughness.

[0022] In practice, the difference between the height of each point within the circle and the height of the circle's center is calculated. When the absolute value of the difference is greater than or equal to a preset difference threshold, the radius of the circle is adjusted to ensure that the height of all points within the same circle is within a certain range. This avoids excessive height differences within a polishing area, which could lead to deviations in the subsequent roughness and the optimal set of polishing parameters determined based on the roughness, thus affecting the polishing effect.

[0023] In another implementation of this embodiment, in step S2.1, when there is no height difference greater than or equal to a preset difference threshold, the preset radius R is added to a preset radius correction value. R obtains a new radius R2, and the height difference is calculated again until the height difference is greater than or equal to the preset difference threshold for the first time. The area of ​​the circle corresponding to this time is taken as a polishing area.

[0024] In practice, there may be cases where the height within the circle corresponding to the initially set radius range is relatively uniform. By gradually increasing the radius, the maximum grinding area can be determined without significant height differences, thereby reducing the amount of data that needs to be processed subsequently.

[0025] In another implementation of this embodiment, in step S2.3, points not belonging to the grinding area are designated as undetermined points. A circle with the undetermined point as the center and a preset radius R is drawn. If the circle does not intersect with the determined grinding area, the grinding area is determined as follows: First, several gradient value ranges are set from low to high. Then, the gradient values ​​of several undetermined points are calculated. The gradient value of each undetermined point is placed within its corresponding gradient value range, and the area formed by undetermined points within the same gradient value range is determined as the grinding area. The gradient value is calculated using the following formula. G K Indicates the calculation of the first K Gradient values ​​at points to be determined K =0, 1, 2, ..., n, .

[0026] The gradient is a vector whose components are the partial derivatives of the function in various directions. It can reflect the rate of change of the height of the workpiece surface. A larger gradient value indicates that the height of the surface at that point changes more drastically, and can represent that the height at that point is relatively large. If the height itself is small, even if it suddenly drops to 0, there will not be a large gradient value. A smaller gradient value indicates that the height change is gradual.

[0027] In another implementation of this embodiment, step S2 further includes obtaining the roughness of all polished areas and generating a judgment set C = (C1, C2, C3, ..., Cn), and obtaining the maximum roughness value C based on the judgment set C. max and the minimum roughness C min Where Cn represents the roughness of the nth polishing area, when C... max When Cfir is less than Cfir, no grinding is required on the workpiece; Cfir represents the preset first roughness threshold. min When the value is greater than or equal to Csec, a warning message is sent to report an error. Csec = Cfir + C, where C represents the preset roughness correction value.

[0028] It is understandable that when C max When Cfir < C, it means the workpiece already meets the standard and does not require grinding; when C min If the roughness is ≥Csec, it indicates that the workpiece roughness is too high, which may be due to substandard previous processes. Therefore, a warning message is sent to remind the staff.

[0029] Example 3 This embodiment further elaborates and supplements the implementation of the present invention based on Embodiment 1 or Embodiment 2.

[0030] Step S3 specifically includes, S3.1 Set the grinding parameter range, which includes the grinding force range [Fmin, Fmax], the grinding speed range [Vmin, Vmax], and the grinding time range [Tmin, Tmax]. The grinding force is the force F during grinding, the grinding speed is the moving speed V of the grinding tool on the workpiece surface, and the grinding time is the grinding time T in each grinding area. S3.2 Obtain the roughness of the A-th grinding region, and use the negative value of the corresponding roughness as the fitness function. Determine the optimal grinding parameter combination (FA', VA', TA') in the A-th grinding region according to the genetic algorithm, where FA' represents the optimal grinding force in the A-th grinding region, VA' represents the optimal grinding speed in the A-th grinding region, and TA' represents the optimal grinding time in the A-th grinding region.

[0031] The fitness function represents an individual's ability to survive or its superiority in the population. The lower the roughness, the smoother the workpiece surface and the better the polishing effect. Therefore, in order to maximize the fitness, the negative value of the roughness is used as the fitness function. The genetic algorithm is used to simulate the natural selection process, continuously optimizing the combination of polishing parameters from the initial random solution to gradually obtain the optimal combination of polishing parameters.

[0032] Example 4 An intelligent grinding robot automatic grinding decision-making and planning system that implements the intelligent grinding robot automatic grinding decision-making and planning method described in any of the above embodiments includes an image acquisition module, an image processing module, a grinding decision module, and a grinding execution module. The image acquisition module is used to capture images of the workpiece surface to be polished. The image processing module processes the images acquired by the image acquisition module, determines the grinding area based on the height of each point on the workpiece surface, and determines the roughness of each grinding area. The grinding decision module sets grinding parameters and their range based on the roughness of the grinding area, and determines the optimal combination of grinding parameters through a genetic algorithm.

[0033] The grinding execution module automatically grinds each grinding area on the workpiece surface according to the optimal combination of grinding parameters.

[0034] As an example, in implementation, the image acquisition module can be set above the workbench or fixture, or on the grinding arm of the intelligent grinding robot, to acquire images of each surface of the workpiece. After all surfaces are acquired, the images are transmitted to the image processing module for image processing. Each image is processed to obtain the height of each point on the workpiece surface, determine the grinding area, and determine the roughness of each grinding area. The roughness of all grinding areas is obtained. When the maximum roughness is less than the preset first roughness threshold, the workpiece does not need to be ground. If the minimum roughness is greater than or equal to the sum of the preset first roughness threshold and the preset roughness correction value, an early warning message is sent to report an error. If neither of the above two situations applies, the grinding decision module sets grinding parameters and grinding parameter ranges according to the roughness of the grinding area, and determines the optimal combination of grinding parameters for each grinding area through a genetic algorithm. The grinding execution module controls the intelligent grinding robot to automatically grind each grinding area on the workpiece surface.

Claims

1. An automatic grinding decision-making and planning method for intelligent grinding robots, characterized in that: Includes the following steps, S1. Take a picture of the surface of the workpiece to be polished to obtain an image of the workpiece surface; S2. Process the image in step S1 to determine the height of each point on the workpiece surface in the image. Determine the grinding area based on the height of each point on the workpiece surface, and determine the roughness of each grinding area. The roughness is the average of the heights of all points in the grinding area. S3. Based on the roughness of the grinding area, set the grinding parameters and the range of grinding parameters, and determine the optimal combination of grinding parameters through a genetic algorithm; S4. Based on the optimal combination of grinding parameters, the intelligent grinding robot is controlled to automatically grind each grinding area on the surface of the workpiece. Step S2 specifically includes: S2.

1. Draw a circle with point i as the center and a preset radius R, and calculate the height difference HDa = |Ha' - Hi|, where Ha' represents the height of the a-th point inside the circle, and Hi represents the height of point i. When there is a height difference greater than or equal to a preset difference threshold, subtract a preset radius correction value from the preset radius R. R obtains a new radius R1; S2.2 Repeat step S2.1 with the newly obtained radius R1 until there is no height difference greater than or equal to the preset difference threshold, and take the corresponding circular area as a polishing area. S2.

3. Using the points that are not within the grinding area as the center, draw a circle with a preset radius R, and repeat the above steps to determine all grinding areas and their corresponding roughness. In step S2.3, points not belonging to the grinding area are designated as undetermined points. A circle with the undetermined point as the center and a preset radius R is drawn. If the circle does not intersect with the determined grinding area, the grinding area is determined as follows: First, several gradient value ranges are set from low to high. Then, the gradient values ​​of several undetermined points are calculated. The gradient value of each undetermined point is placed within its corresponding gradient value range, and the area formed by undetermined points within the same gradient value range is determined as the grinding area. The gradient value is calculated using the following formula. G K Indicates the calculation of the first K Gradient values ​​at points to be determined K =0, 1, 2, ..., n; 。 2. The automatic grinding decision-making and planning method for intelligent grinding robots as described in claim 1, characterized in that: In step S2.1, when there is no height difference greater than or equal to a preset difference threshold, the preset radius R is added to the preset radius correction value. R obtains a new radius R2, and the height difference is calculated again until the height difference is greater than or equal to the preset difference threshold for the first time. The area of ​​the circle corresponding to this time is taken as a polishing area.

3. The automatic grinding decision-making and planning method for intelligent grinding robots as described in claim 1 or 2, characterized in that: Step S2 also includes obtaining the roughness of all polished areas and generating a judgment set C = (C1, C2, C3, ..., Cn), and obtaining the maximum roughness C based on the judgment set C. max and the minimum roughness C min Where Cn represents the roughness of the nth polishing area, when C... max When Cfir is less than the threshold value, no grinding is required on the workpiece. Cfir represents the preset first roughness threshold value. When C exists min When the value is greater than or equal to Csec, a warning message is sent to report an error. Csec = Cfir + C, where C represents the preset roughness correction value.

4. The automatic grinding decision-making and planning method for intelligent grinding robots as described in claim 3, characterized in that: Step S3 specifically includes, S3.1 Set the grinding parameter range, which includes the grinding force range [Fmin, Fmax], the grinding speed range [Vmin, Vmax], and the grinding time range [Tmin, Tmax]. The grinding force is the force F during grinding, the grinding speed is the moving speed V of the grinding tool on the workpiece surface, and the grinding time is the grinding time T in each grinding area. S3.2 Obtain the roughness of the A-th polishing region, and use the negative value of the corresponding roughness as the fitness function. Determine the optimal combination of polishing parameters (FA', VA', TA') in the A-th polishing region according to the genetic algorithm, where FA' represents the optimal polishing force in the A-th polishing region, VA' represents the optimal polishing speed in the A-th polishing region, and TA' represents the optimal polishing time in the A-th polishing region.

5. An intelligent grinding robot automatic grinding decision-making and planning system that implements the intelligent grinding robot automatic grinding decision-making and planning method according to any one of claims 1-4, characterized in that: It includes an image acquisition module, an image processing module, a polishing decision module, and a polishing execution module. The image acquisition module is used to capture images of the workpiece surface to be polished. The image processing module processes the images acquired by the image acquisition module, determines the grinding area based on the height of each point on the workpiece surface, and determines the roughness of each grinding area. The grinding decision module sets grinding parameters and their range based on the roughness of the grinding area, and determines the optimal combination of grinding parameters through a genetic algorithm. The grinding execution module automatically grinds each grinding area on the workpiece surface according to the optimal combination of grinding parameters.

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