Laser burning path planning method based on plant contour

Abstract

The embodiment of the invention discloses a laser burning path planning method based on a plant contour, relates to the technical field of laser burning, and can improve laser burning processing precision and adaptability, optimize processing energy consumption and efficiency, improve operation continuity and improve equipment safety. The method comprises the steps of obtaining point cloud data of a target plant contour based on laser scanning; performing mathematical modeling based on the point cloud data of the target plant contour, and constructing an environment model of the target plant; path planning is carried out based on the environment model of the target plant, and a first laser burning path is obtained; and path smoothing is conducted on the first laser burning path, and a second laser burning path is obtained. The method is suitable for laser burning path planning of various plant contours.

Description

Technical Field

[0001] The present invention relates to the technical field of laser ablation, and particularly to a method for planning a laser ablation path based on the contour of a plant. Background Art

[0002] Laser processing technology involves using a high-energy laser beam to cut, engrave, mark, or weld various materials. This technology has a wide range of applications in multiple fields, including manufacturing, medical, art reproduction, etc. In these applications, path planning is particularly important because it directly affects the processing speed, energy consumption, and quality of the finished product.

[0003] Traditional laser processing path planning methods often rely on simple straight or circular arc paths, which limits the flexibility and efficiency of the processing process, fails to effectively optimize energy consumption and processing time, resulting in higher processing costs and lower efficiency.

[0004] In addition, in existing laser processing technologies, there are also common problems such as insufficiently fine processing of complex contours, easy occurrence of overburn or too large heat-affected zones during processing.

[0005] One of the implementation solutions closest to the present invention involves using computer vision and image processing technologies to assist in laser path planning. By analyzing the image data of the material to be processed, a laser processing path is automatically generated. This method can automate the path generation process to a certain extent, reduce manual intervention, and improve the accuracy and efficiency of path planning. However, this method often ignores the influence of physical phenomena such as material deformation and heat diffusion during the processing, which may lead to a deviation between the actual processing quality and the expectation.

[0006] In short, the existing laser processing path planning methods have the following problems:

[0007] 1) The path planning of laser ablation often relies on simplified models and algorithms, and these methods often fail to meet the high-precision requirements when dealing with complex or irregular plant contours;

[0008] 2) In the traditional laser processing process, energy consumption and processing time are not effectively optimized, resulting in higher processing costs and lower efficiency;

[0009] 3) When the existing technology executes complex paths, mechanical operation interruptions or errors may occur due to insufficiently smooth path planning, which not only affects the processing effect but also may damage the equipment. Summary of the Invention

[0010] In view of this, an embodiment of the present invention provides a method for planning a laser ablation path based on the contour of a plant to solve the above problems existing in the prior art.

[0011] An embodiment of the present invention provides a method for laser burning path planning based on a plant contour. The method includes:

[0012] Based on laser scanning, obtain point cloud data of the target plant contour;

[0013] Based on the point cloud data of the target plant contour, perform mathematical modeling to construct an environmental model of the target plant; wherein, the environmental model of the target plant includes the target plant contour;

[0014] Based on the environmental model of the target plant, perform path planning to obtain a first laser burning path;

[0015] Perform path smoothing on the first laser burning path to obtain a second laser burning path.

[0016] In a first implementation manner, after obtaining the second laser burning path, the method further includes:

[0017] Obtain theoretical contour data corresponding to the second laser burning path;

[0018] Perform laser burning on the target plant according to the second laser burning path, and measure actual contour data after laser burning;

[0019] According to the difference between the theoretical contour data and the actual contour data, adjust the laser burning path planning parameters, and then return to execute the step of performing path planning based on the environmental model of the target plant; wherein, the laser burning path planning parameters include parameters for performing path smoothing on the first laser burning path and laser burning device configuration parameters.

[0020] In a second implementation manner, the performing path planning based on the environmental model of the target plant to obtain a first laser burning path includes:

[0021] Based on the environmental model of the target plant, perform path planning through an improved ant colony algorithm to obtain a first laser burning path; wherein, the improved ant colony algorithm evaluates and selects a path in each iteration through a predefined composite optimization objective function;

[0022] The expression of the composite optimization objective function J is:

[0023] In the above expression of the composite optimization objective function J: w1, w2, and w3 are respectively predefined energy consumption weight factor, time weight factor, and smoothness weight factor; E is the energy consumption for completing the current path task, T is the time required to complete the current path task, and S is the smoothness of the current path.

[0024] In the third embodiment, the smoothness S of the current path is obtained by integrating the squares of the curvatures of the points on the current path.

[0025] In the fourth embodiment, the mathematical modeling based on the point cloud data of the target plant contour to construct the environmental model of the target plant includes:

[0026] Performing quadratic surface fitting on the point cloud data of the target plant contour to construct the environmental model of the target plant.

[0027] In the fifth embodiment, the path smoothing of the first laser ablation path to obtain the second laser ablation path includes:

[0028] Performing path smoothing on the first laser ablation path through a spline curve to obtain the second laser ablation path.

[0029] In the sixth embodiment, the formula for performing path smoothing on the first laser ablation path through a spline curve is:

[0030] In this formula, P(t) is the path position calculated at time t or parameter t; i = 1, 2, …, M; M is the total number of control points when performing path smoothing on the first laser ablation path, pi is the i-th control point, and ni(t) is the spline basis function of the i-th control point defined in advance.

[0031] In the seventh embodiment, the difference between the theoretical contour data and the actual contour data is determined based on the method of minimizing the sum of squared errors.

[0032] In the eighth embodiment, the obtaining of the point cloud data of the target plant contour based on laser scanning of the target scene includes:

[0033] Performing laser scanning on the target scene including the target plant to obtain the point cloud data of the target scene;

[0034] Removing the noise in the point cloud data of the target scene through a Gaussian filter to obtain the denoised target scene data;

[0035] Extracting the point cloud data of the target plant contour from the denoised target scene data.

[0036] The laser ablation path planning method based on plant contour provided by the embodiments of the present invention has the following beneficial effects:

[0037] 1) Higher processing precision and adaptability: The present invention uses advanced surface fitting techniques to construct an accurate three-dimensional model of the plant contour and introduces a real-time feedback mechanism to adjust the path planning according to the real-time data during the laser processing. It can more precisely model complex plant contours and adjust the laser path in real time to adapt to the physical changes of the material during processing, such as thermal expansion or deformation. This adaptability is difficult to achieve with traditional technologies because traditional technologies usually only rely on pre-set fixed paths and have no ability to adapt to real-time changes, thus improving the accuracy and adaptability of path planning.

[0038] 2) Optimize energy consumption and efficiency: In order to optimize energy consumption, processing time, and path smoothness simultaneously, the present invention adopts a multi-objective optimization strategy based on an improved ant colony algorithm. By setting weight factors (such as energy consumption weight, time weight, and smoothness weight), the algorithm can balance between multiple objectives, find the optimal path planning, effectively optimize energy consumption and processing time. This optimization strategy can significantly reduce unnecessary path repetitions and movements, thereby reducing energy consumption and increasing processing speed, and reducing production costs. This is often a difficult point in traditional methods because traditional algorithms are difficult to achieve the optimization of energy efficiency and time while maintaining high precision.

[0039] 3) Improve the continuity of laser burning operation and equipment safety: By performing advanced smoothing processing on the path, the present invention significantly reduces the sudden pauses and sharp turns that may occur when the laser head executes complex paths, significantly improving the continuity and safety of mechanical operations, avoiding damage to the equipment caused by stress concentration, reducing equipment wear and failure rates, and at the same time improving the quality of the processed surface, avoiding processing defects caused by uneven paths. In traditional technologies, path smoothness is usually not fully emphasized, resulting in mechanical failures and operation risks that may occur during processing. Description of the Drawings

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0041] Figure 1 It is a flowchart of the first embodiment of a laser burning path planning method based on plant contours of the present invention;

[0042] Figure 2 It is a flowchart of the second embodiment of a laser burning path planning method based on plant contours of the present invention. Detailed Embodiments

[0043] The present invention relates to a laser ablation path planning method based on plant contours, aiming to improve the accuracy and efficiency of laser processing by advanced data processing techniques and algorithm optimization. This method is divided into five main steps: data acquisition and preprocessing, environmental modeling, path planning and optimization, path smoothing, and experimental verification and adjustment. First, three-dimensional point cloud data of the plant is collected through laser scanning technology, and denoising and other preprocessing are performed to ensure the accuracy and usability of the data. Secondly, using the processed data, mathematical modeling technology is applied to accurately construct an environmental model of the plant contour. Then, based on this model, path planning is carried out, and multiple optimization objectives such as energy consumption, time, and path smoothness are considered during the path planning process. To ensure the smoothness of the path and the continuity of mechanical operations, this method also includes the step of smoothing the planned path. Finally, the effect of path planning is verified through actual laser ablation operations, and the path and parameters are adjusted and optimized according to the experimental results to achieve the best processing effect. This comprehensive method not only improves the accuracy and efficiency of laser processing, but also significantly enhances the adaptability and reliability of the processing process through continuous feedback and optimization mechanisms. This patent is applicable to various fields requiring high-precision laser processing, such as precision manufacturing, art reproduction, and biomedical research, etc.

[0044] The following describes in detail an embodiment of a laser ablation path planning method based on plant contours of the present invention with reference to the accompanying drawings.

[0045] It should be clear that the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0046] Figure 1 It is a flowchart of Embodiment 1 of a laser ablation path planning method based on plant contours of the present invention. As Figure 1 shown, the method of this embodiment may include the following steps 101-104:

[0047] Step 101: Obtain the point cloud data of the target plant contour based on laser scanning.

[0048] In this embodiment, first, a target scene including the target plant and its environment is scanned by laser scanning technology to obtain the point cloud data of the target scene; then, methods such as Gaussian filtering are used to denoise the point cloud data of the target scene to reduce the noise impact brought by the environment and equipment, and the denoised target scene data is obtained; finally, the point cloud data of the contour of the target plant is separated from the denoised target scene data through image processing and existing point cloud data processing algorithms (such as edge detection, clustering analysis, etc.). This step is the basis for ensuring the accuracy of subsequent model establishment and path planning, and the processed data can significantly improve the operation efficiency of the entire system and the accuracy of the results.

[0049] In this embodiment, by using laser scanning technology, point cloud data representing the plant contour can be collected. These data are usually represented as P = {p1, p2, ..., pn}, and the data of each point pi = (xi, yi, zi) includes the coordinates of the point in three-dimensional space. The advantage of this data acquisition method is that it can capture complex shapes and fine textures with high precision, and it is an ideal choice when dealing with the surface of natural objects, such as plant contours. Laser scanning measures the distance between the object and the device by emitting a laser beam and receiving the laser reflected from the object surface. By recording multiple such ranging points, an accurate three-dimensional model of the entire object can be constructed.

[0050] Laser scanning data usually contains noise, which may stem from the errors of the device itself, the natural surface irregularities of the scanned object, or the interference of external environmental factors. To improve the data quality, after collecting the point cloud data, it is necessary to preprocess the data, especially denoise it. In the embodiment of the present invention, a Gaussian filter is used to denoise the point cloud data of the target scene, and the formula of the Gaussian filter is:

[0051] In this formula: is the new point height value after filtering, is the Gaussian weight, and these weights are calculated according to the Gaussian distribution function. The weights are negatively correlated with the distance of the points. is the height value of the original point cloud data before filtering, and k is the filter window size, which determines the range considered by the filter and is a preset value.

[0052] In practical applications, such as in plant growth monitoring or agricultural robots, accurate point cloud data can help the robot perform effective path planning to avoid damaging plants and optimize the operation path. The preprocessed data can be used to simulate the growth of plants, conduct health assessments, or as part of precision agriculture to guide decisions such as fertilization and irrigation. Such high-precision data collection and complex preprocessing not only improve the usability of the data but also greatly enhance the efficiency and reliability of the final application. Through such technologies, every detail of the plant contour can be accurately captured and optimized, laying a solid foundation for subsequent research and commercial applications.

[0053] Step 102: Based on the point cloud data of the target plant contour, perform mathematical modeling to construct an environmental model of the target plant.

[0054] Among them, the environmental model of the target plant includes the target plant contour.

[0055] Since the natural form of plants is often complex and variable, in this embodiment, the point cloud data collected and processed in Step 101 is used to establish an environmental model of the target plant by applying mathematical and geometric methods (such as quadratic surface fitting). This model simplifies the complex three-dimensional data into mathematical equations, facilitating computer processing and analysis. This environmental model is not limited to the three-dimensional contour of the target plant itself but includes all relevant factors in the environment where the target plant is located (such as obstacles around the target plant, other plants, or any factors that may affect the laser processing process). The purpose of this is to optimize the path planning of laser ablation, ensure processing accuracy and adaptability, while considering the continuity of operation and the safety of the equipment. The accuracy of the environmental model is directly related to the feasibility of path planning and the precision of operation, which is a prerequisite for optimizing the path.

[0056] Surface fitting technology allows extracting meaningful geometric information from the scattered point cloud data and establishing a continuous surface. This process usually involves fitting the three-dimensional data points to a mathematically well-defined surface equation. In particular, in the embodiment of the present invention, quadratic surface fitting is performed on the point cloud data of the target plant contour to construct an environmental model of the target plant. Among them, the quadratic surface fitting equation can be expressed as:

[0057] In this equation, x, y, z are the coordinates of any point in space, and a, b, c, d, e, f, g, h, m, l are coefficients to be determined through data fitting.

[0058] Among them:

[0059] a, b, c control the curvature in the directions of each coordinate axis, affecting the opening direction and shape of the surface;

[0060] d, e, and f are the coefficients of the mixed terms, which determine the curvature of the combinations in different coordinate axes and have an important impact on the degree of distortion of the surface.

[0061] g, h, and m are the linear terms, which affect the inclination of the surface along each coordinate axis.

[0062] l is the constant term, representing the position of the surface relative to the origin.

[0063] To determine these coefficients, the least squares method is adopted in this embodiment. The core of this method is to minimize the difference between the predicted value and the actual value. Specifically, it is to minimize the sum of the squares of the perpendicular distances from all data points to the fitted surface. The optimal solutions of these coefficients can be obtained through analytical calculations or numerical methods.

[0064] In the application of laser burning of plant contours, the modeling method provided by the embodiment of the present invention allows us to accurately depict the geometric shape of the plant, which is a prerequisite for optimizing the burning path. Through an accurate environmental model, the movement path of the laser head can be effectively planned to avoid unnecessary damage to the plant while ensuring the uniformity and comprehensiveness of the burning effect. For example, for plant leaves with complex geometric shapes, the optimal burning path can be designed through an accurate model, which not only improves the processing efficiency but also greatly improves the processing quality. In addition, this model can also be used to simulate the physical responses of plant leaves under different environmental conditions, providing a scientific basis for agricultural research. Through such a detailed technical description and the explanation of practical applications, it not only demonstrates the scientific nature and technical depth of the environmental modeling steps but also reflects its important value and broad application prospects in practical applications.

[0065] Step 103: Perform path planning based on the environmental model of the target plant to obtain the first laser burning path.

[0066] In this embodiment, after obtaining an accurate environmental model, a path planning algorithm (such as a genetic algorithm or an ant colony algorithm) is used for path planning to obtain the optimal planned path.

[0067] In some preferred embodiments, in order to achieve efficient and accurate path planning, the present invention proposes an improved ant colony algorithm. When performing path planning in step 103, multiple optimization objectives are considered, such as the shortest path, the lowest energy consumption, the optimal time, and the smoothness of the path. A composite optimization objective function is set. For the environmental model of the target plant, path planning is performed through the improved ant colony algorithm to obtain the optimal first laser burning path. The setting of the composite optimization objective makes the path planning more in line with the actual operation requirements and improves the efficiency and quality of the laser burning process.

[0068] Among them, the expression of the composite optimization objective function J is:

[0069] In the expression of the above composite optimization objective function J:

[0070] w1, w2, and w3 are respectively the pre-set energy consumption weight factor, time weight factor, and smoothness weight factor;

[0071] E is the energy consumption for completing the current path task. If the path task is a laser ablation task, E is related to the current path length and the laser power;

[0072] T is the time required to complete the current path task. If the path task is a laser ablation task, T is determined by the current path length and the movement speed of the laser head during laser ablation;

[0073] S is the smoothness of the current path, which reflects the continuity and curvature change of the path and has an important impact on the processing quality.

[0074] In the traditional ant colony algorithm, the algorithm mainly finds the shortest path by simulating the behavior of ants searching for food. Ants release and sense pheromones to determine their paths, and paths with higher pheromone concentrations are more likely to be selected. In the embodiments of the present invention, when planning the laser ablation path, the designed improved ant colony algorithm includes modifying the pheromone update rule to adapt to specific optimization objectives, such as energy consumption, time, and path smoothness. For example, the evaporation rate or deposition strategy of pheromones can be modified to enable the algorithm to more effectively explore and utilize potential paths, thereby optimizing multiple objectives. In the improved ant colony algorithm, the composite optimization objective function J is used to evaluate and select paths in each iteration of the improved ant colony algorithm. This means that not only is this objective function considered when finally selecting the path, but during the process of constructing the path, after each time an ant completes a path search, the current path will be evaluated according to this objective function. This method enables the algorithm to not only find the path with the minimum length (or cost), but also find the optimal path in terms of energy consumption, required time, and smoothness, etc. Thus, by combining multiple key performance indicators, the advantages and disadvantages of the laser ablation path are comprehensively evaluated. Specifically, J is the weighted sum of these performance indicators, and each indicator corresponds to a specific weight factor, and these factors reflect the relative importance of each performance indicator in the overall objective. The design of the composite optimization objective function J is to optimize the laser ablation path planning on the premise of meeting multiple objectives. By adjusting the values of the weight factors of different performance indicators, the optimization strategy can be customized according to specific production requirements and equipment characteristics. The calculation result of this function will affect the decision-making process of the improved ant colony algorithm when searching and updating paths, making the finally selected path reach the best balance in terms of energy consumption, time, and quality, etc. Such a path selection method makes the final path planning result more in line with the actual processing requirements, makes the path planning more comprehensive and adaptable to specific processing requirements, and ensures efficiency and quality.

[0075] Preferably, the smoothness S of the current path is obtained by integrating the square of the curvature of each point on the current path, and the specific calculation formula is:

[0076] where: k(s) is the curvature of the point s on the current path, which describes the degree of bending of the path at that point; ds represents a tiny line segment on the path. The calculation of the curvature k(s) depends on the geometric shape of the path, and generally can be determined by mathematical modeling of the path and solving its derivative. The upper and lower limits of the integral are usually the arc length parameters corresponding to the start and end points of the path. The above integral formula is carried out for the entire length of the current path, effectively integrating the curvature magnitudes of each point on the path, so that the calculated result reflects the overall smoothness of the current path.

[0077] In practical applications, such as in plant processing in the agricultural field or material cutting in an industrial production line, an optimized path not only saves operation time and energy, but also significantly improves the processing quality. In this embodiment, in the laser burning of plant contours, by optimizing the path smoothness, unnecessary thermal damage to plants can be prevented, while maintaining the uniformity and aesthetics of the burning effect. In addition, path planning also needs to consider how to avoid obstacles, optimize the start and stop points, and how to effectively handle the boundary regions. The comprehensive consideration and optimization of these factors require the use of advanced algorithms such as genetic algorithms, particle swarm optimization or deep learning techniques to achieve. By integrating these technologies and methods, step 103 ensures the high efficiency and high quality of the entire laser burning work, providing reliable technical support for various application scenarios. This not only improves production efficiency, but also reduces energy consumption and operation costs, which is of great significance for promoting technological progress and achieving sustainable development.

[0078] Step 104: Smooth the first laser burning path to obtain a second laser burning path.

[0079] In the embodiment of the present invention, in order to ensure the continuity of the movement of the laser head and reduce potential damage to the material, mathematical tools such as spline curves are introduced to perform path smoothing on the planned first laser burning path to eliminate sharp corners and unnecessary jumps in the path. Use mathematical methods such as spline curves to optimize the path. The path smoothing can reduce the jitter of the mechanical equipment when executing the laser burning path, improve the processing accuracy and efficiency, contribute to improving the processing accuracy and reducing mechanical wear, improve the quality of laser burning products, and also help to extend the service life of the equipment and reduce the maintenance cost.

[0080] In the embodiment of the present invention, the first laser burning path is smoothed by a spline curve to obtain a second laser burning path.

[0081] Preferably, the formula for path smoothing of the first laser ablation path by a spline curve is:

[0082] In this formula:

[0083] P(t) is the path position calculated at time t or parameter t;

[0084] i = 1, 2, …, M; M is the total number of control points when performing path smoothing on the first laser ablation path;

[0085] pi is the i-th control point. These control points define the shape of the spline curve. By adjusting the positions of these points, the geometric characteristics of the curve can be finely controlled. The control points pi can be determined in various ways. In some applications, the control points are manually set based on design requirements to ensure that the curve passes through specific key positions or meets certain design constraints; in more automated systems, the control points may be automatically generated by optimization algorithms. For example, techniques such as the least squares method can be used to fit the best control points from a set of data points.

[0086] ni(t) is the spline basis function of the i-th control point defined in advance, usually determined in the mathematical definition of the spline curve. These basis functions are based on the type of spline curve (such as B-spline or NURBS), and they control the shape of the curve on each segment. Different basis functions have different mathematical expressions; the choice of spline basis function is crucial for the smoothness and flexibility of the curve. For example, in a B-spline curve, the basis function is locally defined, which means that each control point only affects a small segment of the curve, making local adjustment possible without affecting other parts of the entire curve.

[0087] In the laser ablation operation, the smoothness of the path is directly related to the processing quality. For example, when processing complex graphics or delicate parts, any sharp turns on the path may cause material burns or uneven processing. Using a spline curve to smooth the path can effectively avoid these problems and achieve high-quality processing effects. In addition, a smooth path can also reduce mechanical wear and extend the service life of the equipment. This technology is not only applied in industrial production but also widely used in many fields such as robot path planning, animation production, and automotive road testing. In the embodiments of the present invention, by precisely controlling the shape and smoothness of the path, the accuracy and efficiency of the operation are greatly improved. This step ensures that the path not only meets the design requirements but also can achieve the expected effect in actual operation, which has a decisive role in improving the overall quality of the final product and optimizing the production process.

[0088] Figure 2 This is the flowchart of the second embodiment of a laser ablation path planning method based on plant contours according to the present invention, asFigure 2 As shown in Figure 2 , the method of this embodiment may include the following steps 201-207:

[0089] Step 201: Based on laser scanning, obtain the point cloud data of the target plant contour.

[0090] Step 202: Based on the point cloud data of the target plant contour, perform mathematical modeling to construct an environmental model of the target plant; wherein, the environmental model of the target plant includes the target plant contour.

[0091] Step 203: Based on the environmental model of the target plant, perform path planning to obtain the first laser burning path.

[0092] Step 204: Smooth the first laser burning path to obtain the second laser burning path.

[0093] In this embodiment, the processes of steps 201-204 are similar to those of steps 101-104 in the above method embodiment, and will not be elaborated here.

[0094] Step 205: Obtain the theoretical contour data corresponding to the second laser burning path.

[0095] In this embodiment, according to the preset sampling frequency, obtain the position data of several sampling points on the second laser burning path as the theoretical contour data.

[0096] Step 206: Perform laser burning on the target plant according to the second laser burning path, and measure the actual contour data after laser burning.

[0097] In this embodiment, corresponding to the theoretical contour data obtained in step 205, obtain the position data of several sampling points on the actual contour after laser burning.

[0098] Step 207: According to the difference between the theoretical contour data and the actual contour data, adjust the laser burning path planning parameters, and then return to execute step 203.

[0099] In this embodiment, for example, there are a total of 5 points ABCDE in sequence on the second laser ablation path obtained through steps 201-204. Among them, point A is the starting point of the second laser ablation path. Then, in step 206, the path between point A and B on the second laser ablation path can be first subjected to laser ablation, and then the actual contour data between A and B after laser ablation is measured in real time. Then, in step 207, the difference between the theoretical contour data and the actual contour data between A and B is calculated. After adjusting the laser ablation path planning parameters according to the difference situation, return to execute step 203 to update the path in the target plant contour that has not been subjected to laser ablation, and re-plan the path for the target plant contour after point B. In this way, the effect of path planning is verified through the actual contour data after real-time laser ablation, and the data collected in real time is fed back to adjust the laser ablation path planning parameters, continuously optimizing the algorithm to achieve the best processing effect.

[0100] Among them, the laser ablation path planning parameters include parameters for path smoothing of the first laser ablation path (path smoothness parameters) and laser ablation equipment configuration parameters. The path smoothness parameters usually involve adjusting the mathematical models or algorithm parameters used when generating the path, such as the choice of control points or basis functions in spline curves, in order to better control the smoothness of the path. For example, it may be necessary to adjust the subdivision degree of the spline curve or select different types of splines (such as B-splines or NURBS) to achieve a smoother path. The laser ablation equipment configuration parameters include laser power and speed settings, etc. These parameters directly affect the quality and efficiency of laser ablation; adjusting the laser power can control the penetration depth and ablation width of the laser on the material, while adjusting the laser speed affects the contact time between the laser and the material, thereby affecting the processing quality. According to the difference between the theoretical contour and the actual contour, these parameters can be adjusted in real time or at regular intervals to optimize the result of laser ablation.

[0101] Furthermore, the laser ablation path planning parameters can also include other parameters, such as the overlap degree of the scanning path, the movement strategy of the laser head, etc. These factors can all affect the quality and processing efficiency of the final product. The laser ablation equipment configuration parameters not only involve the operating parameters of the laser (such as power and speed), but can also include more extensive system settings, such as the choice of path generation algorithm, the filtering method of data during processing, etc. By carefully adjusting these parameters, while maintaining or improving the processing accuracy, the energy consumption and processing time can be optimized, and ultimately a more efficient and safer laser ablation operation can be achieved.

[0102] In the theoretical and simulation stages of steps 201 - 205, although seemingly optimal paths and parameter configurations can be predicted and planned, the complexity of actual laser ablation often exceeds the prediction scope of the model. Experimental verification allows us to observe various deviations and unforeseen factors in actual operations, such as the physical limitations of the equipment, the impact of environmental changes, and the handling performance of actual materials. Therefore, in the embodiments of the present invention, the actual operation in step 206 is also combined with step 207 to verify the effect of the theoretical model, so as to adjust the parameters according to the verification results to ensure that the path planning method of the present invention achieves optimal performance in practical applications.

[0103] In this embodiment, the difference between the theoretical profile data and the actual profile data is determined based on the method of minimizing the mean squared error (MSE). The mathematical expression of this method is:

[0104] In this formula:

[0105] MSE represents the mean squared error, which is a quantitative index for measuring the deviation between the predicted value and the actual observed value;

[0106] N is the total number of evaluations or total number of samples, that is, the number of sampling points used for comparing the theoretical profile and the actual profile;

[0107] observed_i is the data of the i-th sampling point of the actual profile;

[0108] predicted_i is the data of the i-th sampling point of the theoretical profile.

[0109] In laser ablation operations, such as when machining metal components with specific shapes, experimental verification can help determine whether all contours are accurately traced and ablated. By measuring the difference between the actually ablated component and the expected contour generated by the computer, the MSE can be used to evaluate the accuracy of path planning. If the MSE value is high, it indicates that the laser ablation path planning parameters need to be adjusted, such as changing path smoothness, adjusting the movement speed of the laser head, or reconfiguring the laser power. In addition, the MSE can also be used to evaluate the performance under different algorithms or different settings. By comparing the MSE values of various configurations, the most suitable configuration for a specific application can be selected. By analyzing the MSE, it can be judged whether the current configuration of the laser ablation path planning parameters can achieve the expected processing accuracy. If the MSE is high, it indicates that the laser ablation path planning parameters need to be adjusted. Through continuous monitoring and analysis of the MSE, adjustments can be made not only after a single experiment, but also data and experience can be accumulated for long-term optimization of the entire system. This method enables the laser ablation technology to adapt to changing production requirements and material characteristics, improving flexibility and application breadth. Through experimental verification and adjustment steps, we can ensure a high degree of consistency between theory and practice, maximizing the efficiency and accuracy of the system. This is not only crucial for production quality, but also provides an empirical basis for future technology upgrades and innovations

[0110] The following uses a specific embodiment to elaborate in detail on the technical solution of the method embodiment of the present invention

[0111] For example, the technical solution of the present invention is applied to a specific plant contour laser ablation project. In this project, the goal is to finely engrave a specific type of wood to create a decorative pattern. The following is a detailed description of the technical implementation steps and results

[0112] Implementation steps

[0113] (1) Data collection and preprocessing: Use a high-resolution laser scanning device to collect three-dimensional point cloud data of the wood surface. Perform Gaussian filtering on the collected data to eliminate noise caused by equipment vibration and external light changes

[0114] (2) Environmental modeling: Through existing software, apply quadratic surface fitting technology to convert the processed point cloud data into an accurate three-dimensional model that accurately reflects the surface details and contours of the wood

[0115] (3) Path planning and optimization: Use an improved ant colony algorithm to optimize the laser ablation path, considering minimizing path length and time, while ensuring path smoothness to avoid frequent pauses and turns of the laser head. Add a real-time feedback mechanism to the path planning to adjust the speed and power of the laser head in real time to adapt to different densities and thicknesses of the wood

[0116] (4)Path smoothing: The optimized path is smoothed using B-spline curve technology to ensure the continuity and uniformity of the laser head movement, thereby improving the processing quality and reducing mechanical wear.

[0117] (5)Experimental verification and adjustment: In a laboratory environment, a laser ablation test is conducted on the selected wood samples. Based on the preliminary processing results, the deviation between the actual processing path and the predetermined path is calculated, and the processing quality is evaluated by calculating the mean square error (MSE). According to the MSE results and the observed processing effects, the parameters and laser settings in steps (3) and (4), such as power adjustment and speed change, are adjusted to optimize the final processing effect.

[0118] Implementation results:

[0119] In this embodiment, through the technical solution of the present invention, laser ablation of complex and delicate decorative patterns is successfully achieved on wood. The path optimization and smoothing during the processing significantly improve the processing speed and quality, achieving high-efficiency and high-precision laser processing. The details of the final product are precise, the surface is smooth, and there are no problems such as overburning or excessive heat-affected zones. This embodiment demonstrates the practical application potential of the present invention in improving the accuracy and efficiency of laser processing, and proves its wide applicability and superiority in the field of fine processing.

[0120] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0121] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0122] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A laser burning path planning method based on plant contour, characterized in that: The method comprises: Based on laser scanning, point cloud data of the target plant outline is obtained; Performing mathematical modeling based on the point cloud data of the target plant outline to construct an environmental model including the target plant; wherein the environmental model of the target plant includes the target plant outline; Performing path planning based on the environmental model of the target plant to obtain a first laser burning path; The first laser burning path is smoothed to obtain a second laser burning path.

2. The method for laser burning path planning based on plant contour according to claim 1, characterized in that: After obtaining the second laser burning path, the method further includes: Acquiring theoretical profile data corresponding to the second laser burning path; Laser burning the target plant according to the second laser burning path, and measuring and obtaining actual contour data after laser burning; According to the difference between the theoretical contour data and the actual contour data, the laser burning path planning parameters are adjusted, and then the step of performing path planning based on the environmental model of the target plant is returned to execute; wherein the laser burning path planning parameters include parameters for path smoothing of the first laser burning path and laser burning equipment configuration parameters.

3. The method for laser burning path planning based on plant contour according to claim 1, characterized in that: The path planning is performed based on the environment model of the target plant to obtain a first laser burning path, including: Based on the environmental model of the target plant, path planning is performed by using an improved ant colony algorithm to obtain a first laser burning path; wherein the improved ant colony algorithm evaluates and selects a path in each iteration by using a predefined composite optimization objective function; The expression of the composite optimization objective function J is: ； In the expression of the above composite optimization objective function J: w1, w2, w3 are the pre-set energy consumption weight factor, time weight factor and smoothness weight factor respectively; E is the energy consumption to complete the current path task, T is the time required to complete the current path task, and S is the smoothness of the current path.

4. The method for laser burning path planning based on plant contour according to claim 3, characterized in that: The smoothness S of the current path is obtained by integrating the square of the curvature of each point on the current path.

5. The method for laser burning path planning based on plant contour according to claim 1, characterized in that: The step of performing mathematical modeling based on the point cloud data of the target plant contour to construct an environmental model of the target plant includes: Perform quadratic surface fitting on the point cloud data of the target plant contour to construct the environmental model of the target plant.

6. The method for laser burning path planning based on plant contour according to claim 1, characterized in that: The step of smoothing the first laser burning path to obtain a second laser burning path includes: The first laser burning path is smoothed by using a spline curve to obtain a second laser burning path.

7. The method for laser burning path planning based on plant contour according to claim 6, characterized in that: The formula for smoothing the first laser burning path by using a spline curve is: ； In this formula, P(t) is the path position calculated at time t or parameter t; i=1,2,…,M; M is the total number of control points when smoothing the first laser burning path, p i is the i-th control point, n i(t) is the spline basis function of the predefined i-th control point.

8. The method for laser burning path planning based on plant contour according to claim 2, characterized in that: The difference between the theoretical profile data and the actual profile data is determined based on a method of minimizing the sum of squared errors.

9. The method for laser burning path planning based on plant contour according to claim 1, characterized in that: The method of obtaining point cloud data of the target plant contour based on laser scanning includes: By laser scanning a target scene including a target plant, point cloud data of the target scene is obtained; Removing noise from the point cloud data of the target scene by using a Gaussian filter to obtain noise-reduced target scene data; The point cloud data of the target plant outline is extracted from the denoised target scene data.

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