3D printing path planning method and system

Abstract

The invention provides a 3D printing path planning method and system, and the method comprises the steps: obtaining 3D model data of a to-be-printed agricultural object, obtaining agricultural environment parameter data, calculating a printing path through a path optimization function based on the 3D model data and the agricultural environment parameter data, and generating a control instruction of a 3D printer based on the printing path; according to the method, the printing control parameters are optimized by constructing the targeted path optimization function, the problems that in the prior art, the printing object environment adaptability is poor, the function efficiency is low, and the forming quality is unstable are solved, and precision, high efficiency and scenario adaptation of agricultural object 3D printing is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of 3D printing technology in agricultural engineering, and in particular to a 3D printing path planning method and system. BACKGROUND

[0002] With the maturity of 3D printing technology and the advancement of agricultural modernization, the application of 3D printing in the agricultural field has gradually expanded, becoming an important means to realize the customization and efficient production of agricultural equipment. Early agricultural 3D printing mainly focused on the manufacturing of simple planting containers and small irrigation components, and the printing path planning directly followed the general scheme in the industrial field, only focusing on printing accuracy and speed without considering the particularity of the agricultural scene. In recent years, with the growing demand for 3D printing of large and complex agricultural objects such as greenhouses and soil remediation devices, the industry has begun to explore path optimization adapted to agriculture, but it is still in its early stages. Currently, the development of agricultural 3D printing path planning presents two major trends. One is the transition from generalization to scene adaptation, trying to adjust the printing strategy in combination with agricultural environmental parameters. The other is the development from single objective optimization to multi-objective balance, seeking to balance printing efficiency, molding quality, and object performance. However, the existing path planning does not integrate agricultural environmental parameters, and key environmental factors such as wind load, soil moisture, and solar intensity are not included in the optimization logic, resulting in insufficient durability of printed objects in outdoor agricultural environments, which are easily damaged by wind and rain, temperature changes, etc. At the same time, the existing path optimization function design is single, with only path length and curvature considered, lacking targeted optimization of core object performance (such as mechanical strength, water retention capacity), resulting in low functional efficiency of printed objects and difficulty in meeting actual agricultural needs such as precision irrigation and soil remediation. Furthermore, the printing control parameters in the existing technology lack individualized settings for agriculture and are not dynamically adjusted according to object type, material properties, and environmental conditions, which may cause problems such as poor material adhesion, molding defects, etc., affecting the use of agricultural objects. These problems limit the large-scale application of 3D printing technology in the agricultural field, and there is an urgent need for a special path planning scheme adapted to agricultural scenes in this field. SUMMARY

[0003] The present application provides a 3D printing path planning method and system, aiming to solve the problems of poor environmental adaptability, low functional efficiency, and unstable molding quality of printed objects in the existing technology by constructing a targeted path optimization function and optimizing printing control parameters, and to realize the precision, efficiency, and scene adaptation of 3D printing of agricultural objects.

[0004] In one aspect, the present application provides a 3D printing path planning method, comprising the following steps: Step one, obtaining 3D model data of the agricultural object to be printed; Step two, obtaining agricultural environmental parameter data; Step three, calculating a printing path by a path optimization function based on the 3D model data and the agricultural environment parameter data; Step four, generating a control instruction of the 3D printer based on the printing path.

[0005] In another aspect, the present application provides a 3D printing path planning system, comprising the following steps: a data acquisition module for acquiring 3D model data of an agricultural object to be printed and agricultural environment parameter data; a path calculation module for calculating a printing path by using a path optimization function based on the 3D model data and the agricultural environment parameter data; a control generation module for generating a control instruction of the 3D printer based on the printing path.

[0006] Compared with the prior art, the present application has the following beneficial effects: 1. The present application incorporates agricultural environment parameters such as wind load and soil humidity into the path optimization logic, quantifies the environmental adaptation deviation by a penalty function, makes the printing path highly match the target environment, and effectively prevents the printed object from being affected by natural factors such as wind and rain, thereby significantly improving the durability and solving the problem that the traditional printed object is easily eroded by the agricultural environment.

[0007] 2. The present application integrates attribute values such as expected mechanical stress and water retention capacity into the path planning according to the core performance requirements of the agricultural object, optimizes the structure strength, water retention performance and other key indicators of the printing path, and significantly improves the functional efficiency of irrigation components and the water retention capacity of planting containers, thereby meeting the precise agricultural production requirements.

[0008] 3. The present application smoothes the path by gradient descent method, reduces sharp turns, and reduces the frequency of sudden stop and quick turn of the printing head, thereby avoiding defects such as material accumulation and fault, and reducing equipment wear; at the same time, the setting of agricultural individualized control parameters ensures sufficient bonding and uniform extrusion of the material, and balances the forming quality and printing efficiency.

[0009] 4. The present application supports the acquisition of 3D model data from multiple channels such as local, cloud and user input, adapts to different types of agricultural objects, does not require complex weight setting, and has simple and easy-to-understand path optimization logic, which can be directly connected to existing 3D printing equipment, thereby reducing the application threshold of 3D printing technology in the agricultural field and promoting its large-scale promotion.

[0010] 5. The present application constructs a 3D printing path planning system dedicated to agricultural scenes, fills the gap between industrial general path planning schemes and actual agricultural needs, provides technical support for customized production of agricultural equipment, and helps the development of precision and high efficiency in agricultural modernization.

[0011] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0012] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention, but do not constitute a limitation thereof; in the drawings: Figure 1 This is a flowchart illustrating a 3D printing path planning method provided by the present invention; Figure 2 This is a schematic diagram of the structure of a 3D printing path planning system provided by the present invention. Detailed Implementation

[0013] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention. Example 1:

[0014] This invention provides a 3D printing path planning method. Please refer to [link / reference]. Figure 1 This includes the following steps: Step 1: Obtain the 3D model data of the agricultural object to be printed; Step 2: Obtain agricultural environmental parameter data; Step 3: Based on 3D model data and agricultural environmental parameter data, calculate the printing path using a path optimization function; Step 4: Generate control instructions for the 3D printer based on the printing path.

[0015] Specifically, the method provided in this embodiment is designed for 3D printing in agricultural scenarios. Its core is to match the object structure, agricultural environment, and printing path. The 3D model data obtained in step one serves as the basic blueprint for the printed object, ensuring the printed shape matches the design. The agricultural environment parameter data obtained in step two provides the adaptability basis, ensuring the printed object can adapt to the actual usage environment. Step three integrates the two types of data through a path optimization function to calculate a path that balances structural integrity, environmental adaptability, and printing feasibility. Step four converts the path into printer-recognizable instructions, completing a closed loop from planning to execution. This method can be directly applied to the 3D printing of various agricultural objects such as agricultural greenhouse structures and irrigation components, solving problems such as easy damage and functional failure caused by traditional printing paths not considering the agricultural environment.

[0016] In one implementation, obtaining the 3D model data of the agricultural object to be printed specifically includes: Obtain 3D model data from a local storage device, a cloud database, or a user input interface, the 3D model data including geometric shape and structure information of the agricultural object.

[0017] Specifically, the local storage device includes a hard disk, a U disk, a mobile hard disk, and the like, which are storage media that can be directly accessed by the printing control device. The user can directly read the 3D model data that is designed and saved in advance by CAD, SolidWorks, or the like. The cloud database is a remote network storage platform. The user can log in through a network account to obtain the uploaded model data from different locations and different devices (such as a computer or a tablet), thereby realizing multi-scenario collaborative work. The user input interface includes physical keys, a touch screen, computer input software, and the like. The user can manually input parameters such as the length, width, height, wall thickness, and support structure spacing of the object, and the system automatically generates 3D model data. The geometric shape information covers the external contour of the object (such as the arc-shaped top of a greenhouse structure or the cylindrical side wall of a planting container) and size parameters (such as specific numerical values of length, width, and height, or hole diameter). The structure information covers the type of internal support structure (such as a grid-shaped or columnar support), support density, wall thickness distribution (such as thickening of the wall thickness at key positions of a greenhouse frame), and interface connection structure (such as a threaded interface of an irrigation component), thereby ensuring that the 3D model data completely reflects the design requirements of the agricultural object.

[0018] In one embodiment, the agricultural environment parameter data includes at least one of wind load, soil load, environmental temperature, solar intensity, soil humidity, and material permeability, and is obtained through a sensor network or an external database.

[0019] Specifically, the wind load refers to the pressure generated by air flow in the agricultural production area on the agricultural object, and is in units of kPa. After real-time wind speed data is collected by a wind speed sensor, the wind load is calculated according to an industry standard formula. The soil load refers to the pressure generated by the soil on the base or contact part of the agricultural object, and is in units of kPa. According to the soil type (sandy soil, clay soil, or loam) and the soil compaction degree, the soil load is directly measured by a soil pressure sensor or obtained by querying a soil mechanics parameter table. The environmental temperature is the real-time air temperature in the agricultural production area, and is in units of °C. The solar intensity is the amount of solar radiation received per unit area, and is in units of W / m 2The data is collected via a solar radiation sensor; soil moisture is the volumetric water content in the soil, expressed as a percentage, collected by a soil moisture sensor inserted at a specific depth in the soil; material permeability is the performance parameter of the 3D printing materials (such as PLA, ABS, and biodegradable materials) that allows water and air to permeate, expressed as mm / s, obtained from the technical parameter table provided by the material supplier or measured through a permeability experiment; the sensor network consists of multiple sensors of various types deployed in the agricultural production area, with sensor nodes evenly distributed at 5-10 meter intervals, collecting various parameters in real time and transmitting them to the data processing terminal at a collection frequency of 1 time / minute to ensure data timeliness; the external database is a public or private database that integrates historical environmental data of the target area for the past 1-3 years (such as annual extreme wind speeds and seasonal temperature variation ranges) and environmental data of similar agricultural production areas. Users can access the data through a network interface to provide long-term environmental references for route planning, avoiding the accidental influence of single real-time data.

[0020] In one implementation, the path optimization function minimizes the cost function based on the following formula. : ; in, This represents the sequence of points along the printing path. , It is a point and The Euclidean distance between them It is a point Path curvature at that point Based on agricultural environmental parameters at point The penalty function at the point; by minimizing the cost function This allows the printing path to achieve a balance in terms of distance, curvature, and adaptation to the agricultural environment.

[0021] Specifically, point sequence It is a discretized representation of the printing path, with each point... Each corresponds to a coordinate in three-dimensional space. x-axis coordinates y-axis coordinate (where z is the z-axis coordinate), all points are connected sequentially in the printing order to form a continuous 3D printing path. The total number of path points, set according to the size and precision requirements of the agricultural object, typically ranging from 1000 to 10000; Euclidean distance. The calculation formula is: Its value directly reflects the path length between two adjacent print points; this summation term... The total length of the print path; minimizing this part can shorten printing time and save printing material; curvature Reflecting the path at the point The degree of curvature at the point is calculated using the following formula: (in For the path in The unit tangent vector at that point, (path arc length) Summation term Used to constrain the smoothness of the path; minimizing this part reduces sharp turns in the path; penalty function. Summation term This part is used to constrain the environmental adaptability of the path; minimizing this part ensures that the printed path meets the requirements of the agricultural environment; cost function. By integrating three categories of indicators—path length, smoothness, and environmental adaptability—into a unified quantitative objective, and minimizing it using the gradient descent method, this approach achieves the desired result. By setting a specific value, the three goals of short path, stable motion, and environmental adaptability can be achieved simultaneously, avoiding performance degradation caused by optimizing a single indicator and ensuring the overall optimal printing path.

[0022] In one implementation, the penalty function The definition of is: ; in, Based on agricultural environmental parameters at point The attribute value at that location, It is the preset target attribute value; when the actual attribute value... Deviation from target attribute value At that time, the penalty function The value increases, thus penalizing the deviation in the cost function and prompting the planning of printing paths to better meet the needs of the agricultural environment.

[0023] Specifically, the penalty function Using absolute values ​​allows for a direct and unbiased quantification of the deviation between actual and target attribute values, preventing positive and negative deviations from canceling each other out. These are optimal attribute values ​​pre-set based on the specific type, design function, and target usage environment of the agricultural object. They are determined by the user or system according to industry standards and actual application requirements. For example, the expected mechanical stress for an agricultural greenhouse structure. The pressure can be set to 50 kPa (to ensure it can withstand common wind and soil pressure); this is for the moisture retention capacity of planting containers. It can be set to 40% (to ensure that the water requirements for crop growth are met); for the thermal conductivity of irrigation system components It can be set to 0.3W / (m・K) (to ensure that the water flow temperature is not affected by changes in ambient temperature); It is a path point corresponding actual attribute value, the calculation of which relies on the agricultural environment parameter data obtained in step two; when is completely consistent with , =0, the cost function has no additional contribution; when deviates from , the value of increases synchronously with the deviation, thereby raising the value of the cost function ; in the path optimization process, the optimization algorithm will preferentially select path points with small values and avoid path points with large deviations, ensuring that the planned printing path enables the agricultural object to approach the optimal target value of the attribute at each printing position, thereby overall adapting to the agricultural environment.

[0024] In one embodiment, the attribute value is one of the expected mechanical stress, thermal conductivity, or moisture retention capacity, wherein the expected mechanical stress is calculated based on wind load or soil load, the thermal conductivity is calculated based on environmental temperature and solar intensity, and the moisture retention capacity is calculated based on soil humidity and material permeability, and the data is derived from the agricultural environment parameter data.

[0025] Specifically, the selection of the attribute value needs to match the core functional requirements of the agricultural object. For load-bearing agricultural objects such as greenhouse structures and soil remediation devices that need to withstand external forces, the expected mechanical stress is selected; for agricultural objects that need to control temperature conduction (such as heat preservation type planting containers and anti-scald irrigation pipes), the thermal conductivity is selected; for agricultural objects that need to retain moisture (such as planting containers and water retention type soil covering devices), the moisture retention capacity is selected; wherein the calculation method of the expected mechanical stress is: when the wind force impact dominates in the use scenario of the agricultural object (such as a greenhouse in an open plain area), the wind load data obtained in step two is directly used as the expected mechanical stress; when the soil pressure impact dominates (such as irrigation pipes and soil remediation devices buried in the soil), the soil load data obtained in step two is directly used as the expected mechanical stress; if both have considerable influence, the superposition value of the wind load and the soil load (such as wind load 20 kPa + soil load 30 kPa = 50 kPa) can be used. wherein the calculation method of the thermal conductivity is: the product of the environmental temperature and the solar intensity is multiplied by a fixed conversion coefficient (10 -3 ), i.e., thermal conductivity = environmental temperature (℃) × solar intensity (W / m 2 ) × 10 -3 , for example, environmental temperature 25℃, solar intensity 120W / m2 At that time, the thermal conductivity = 25 × 120 × 10 -3 =3W / (m·K), this calculation method can intuitively reflect the comprehensive impact of ambient temperature and solar radiation intensity on the heat transfer of agricultural objects; The calculation method for water retention capacity is as follows: the average value of soil moisture and material permeability is used, that is, water retention capacity = (soil moisture % + material permeability mm / s) / 2. For example, when the soil moisture is 30% and the material permeability is 50 mm / s, the water retention capacity = (30 + 50) / 2 = 40. This calculation method can balance the combined effect of environmental moisture base and material water-locking performance on water retention effect. The calculation data for all three attribute values ​​are directly taken from the agricultural environmental parameter data obtained in step two, without the need to add any additional data, ensuring... It closely matches the actual environment, providing a basis for path optimization; it should also be noted that the calculation is dimensionless and only considers numerical values.

[0026] In one implementation, after calculating the printing path using the path optimization function, the method further includes: The printing path is smoothed by iteratively optimizing the curvature term. Reduce sharp turns in the path; The smoothing process employs gradient descent, with a fixed iteration step size of 0.03. The iteration termination condition is that the curvature difference between two adjacent iterations is ≤10. -4 The iterative formula is ,in For the number of iterations, For the cost function in the th The gradient at the next iteration.

[0027] Specifically, the core purpose of smoothing is to eliminate sharp inflection points (such as right-angle turns and sudden changes of direction) that may exist in the initial planned path, reducing the difficulty of movement for the 3D printer's print head; the gradient descent method continuously adjusts parameters to approach the optimal solution and is suitable for optimizing path curvature; a fixed iteration step size of 0.03 is the optimal value verified by a large number of experiments. Too small a step size will lead to too many iterations and low optimization efficiency, while too large a step size will lead to iterative oscillations and failure to converge to the optimal solution; the iteration termination condition is "the curvature difference between two adjacent iterations ≤ 10". -4 "This is the core criterion for judging whether the path smoothness meets the standard. When this condition is met, it indicates that the path curvature has stabilized, and further iteration will not have a significant optimization effect; in the iteration formula, Represents the path point at the k-th iteration. The curvature value, For the cost function in the th Gradient at the next iteration, which is calculated in a conventional manner and will not be further elaborated; the positive and negative directions of the gradient indicate the adjustment direction of the curvature (the gradient is positive when the curvature is reduced, and the gradient is negative when the curvature is increased); The specific process of the smoothing processing is as follows: Input the curvature sequence of the preliminary planning path (i = 1, 2, …, N-1); Calculate the gradient of the first iteration , according to the iteration formula ; Calculate the difference between and , if the difference > 10 -4 , repeat the calculation of ; Iterate in turn until the curvature difference between the adjacent two iterations is ≤ 10 -4 , output the optimized curvature sequence; Adjust the coordinates of the path points according to the optimized curvature sequence to generate the smoothed printing path; After the smoothing processing, the printing head does not stop suddenly or turn quickly during movement, and the acceleration is stable within a small range, which can effectively reduce printing defects such as material accumulation, faults, burrs, etc., improve the forming quality of the agricultural object, and at the same time reduce the wear of the printer motor, guide rail and other components, prolong the service life of the equipment.

[0028] In one embodiment, generating control instructions for a 3D printer comprises: Converting the printing path into G-code or M-code instructions and adding agricultural-specific control parameters, including printing speed, material flow rate and temperature settings.

[0029] Specifically, G-code is a standardized instruction used by 3D printers to control motion trajectories, covering the moving coordinates of the printing head, motion modes (such as linear motion, circular motion), etc., for example, “G1X10Y20Z5F300” means controlling the printing head to move from the current position to the (10, 20, 5) coordinate point at a speed of 300 mm / min; M-code is an instruction used to control the auxiliary functions of the printer, covering temperature control, motor start-stop, material feeding, etc., for example, “M104S200” means setting the printing head temperature to 200°C; when converting the planned printing path into G-code or M-code, the system will automatically generate corresponding motion instructions according to the coordinate sequence of the path points , to ensure that the printing head moves according to the planned path; The agriculture-specific control parameters are personalized parameters optimized for the printing needs of agricultural objects. Among them, the printing speed is set according to the structural strength requirements of the agricultural object. For load-bearing objects (such as greenhouse frames), it is set to 20mm / s to ensure that the material is fully bonded and the structure is dense; for non-load-bearing objects (such as small planting containers), it is set to 30mm / s to balance efficiency and quality. The material flow rate is in a fixed ratio to the printing speed (1:1.2), meaning that the material flow rate is 24 mm when the printing speed is 20 mm / s. 3 / s, the flow rate is 36mm when the velocity is 30mm / s. 3 / s, ensuring that the material extrusion rate matches the printing speed, avoiding layering caused by insufficient material or accumulation caused by excessive material; The temperature setting is determined according to the type of printing material: 200℃ for PLA, 240℃ for ABS, and 190℃ for biodegradable materials, to ensure that the material can fully melt and quickly solidify. After the three types of control parameters are integrated with G-code and M-code instructions, a complete 3D printer control instruction set is formed. The printer can directly read and execute these instructions to achieve precise printing of agricultural objects.

[0030] In one implementation, the agricultural object includes at least one of an agricultural greenhouse structure, an irrigation system component, a planting container, or a soil remediation device, and the 3D printing path planning method is used to optimize the durability, functional efficiency, or environmental adaptability of the agricultural object.

[0031] Specifically, the agricultural greenhouse structure includes a greenhouse frame, support columns, connecting pieces, etc. These objects need to be exposed to the outdoors for a long time, withstand wind and rain, soil pressure, and other external forces. By optimizing the printing path, the wall thickness distribution and support density of the frame structure can be adapted to wind load and soil load, enhancing the durability of the structure and reducing the risk of damage from natural disasters. Irrigation system components include irrigation pipes, sprinkler supports, valve housings, etc. These objects need to ensure smooth water flow and tight connections. By optimizing the path, the smoothness of the internal channels and the interface sealing of the components can be improved, increasing irrigation efficiency and achieving precise irrigation (such as avoiding pipe leaks and uneven sprinkler water output). Planting containers include pots, seedling trays, planting tanks, etc. These objects need to meet the water and temperature needs of crop growth. By optimizing the path, the porosity and thickness of the container walls can be adjusted to improve water retention and thermal conduction compatibility for different soil types (such as sandy soil and clay soil) and planting environments (such as open air and greenhouse). Soil remediation devices include remediation agent releasers, soil stirring components, and pollution isolation membranes. These objects need to work in complex soil environments. By optimizing the path, the corrosion resistance and structural stability of the devices can be enhanced, improving environmental adaptability, ensuring uniform release of remediation agents and sufficient soil stirring, and improving soil remediation effectiveness. This method addresses the core performance needs of different agricultural objects (durability, functional efficiency, and environmental adaptability) by optimizing the path to achieve precise adaptation, solving the problem of mismatch between object performance and agricultural scene needs in traditional printing methods.

[0032] Embodiment 2:

[0033] The embodiment of the present application provides a 3D printing path planning system based on the method provided in embodiment 1. Please refer to Figure 2 , which includes: A data acquisition module for acquiring 3D model data and agricultural environment parameter data of the object to be printed. A path calculation module for calculating the printing path using a path optimization function based on the 3D model data and agricultural environment parameter data. A control generation module for generating control instructions for the 3D printer based on the printing path.

[0034] The working principle of this system is the same as the method provided in embodiment 1, and will not be further described.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some technical features, and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A 3D printing path planning method, characterized in that, The method comprises the following steps: Step one, obtaining 3D model data of the agricultural object to be printed; Step two, obtaining agricultural environment parameter data; Step three, calculating the printing path based on the 3D model data and the agricultural environment parameter data through a path optimization function; Step four, generating control instructions for the 3D printer based on the printing path.

2. The method of claim 1, wherein, The 3D model data of the agricultural object to be printed specifically includes: Obtaining the 3D model data from a local storage device, a cloud database, or a user input interface, which includes the geometric shape and structural information of the agricultural object.

3. The method of claim 1, wherein, In step two, the agricultural environment parameter data includes at least one of wind load, soil load, environmental temperature, solar intensity, soil humidity, and material permeability, which is obtained through a sensor network or an external database.

4. The method of claim 3, wherein, The path optimization function minimizes a cost function based on the following equation : ； wherein, represents a sequence of points on a print path, , is the Euclidean distance between points and , is the curvature of the path at point , is a penalty function at point based on agricultural environmental parameters; by minimizing the cost function the print path is balanced in terms of distance, curvature, and adaptation to the agricultural environment.

5. The method of claim 4, wherein, The penalty function is defined as: ； wherein is based on the attribute value of the agricultural environment parameter at the point , is a pre-set target attribute value; when the actual attribute value deviates from the target attribute value , the penalty function value increases, thereby penalizing the deviation in the cost function, prompting the planning of the printing path to be more in line with the needs of the agricultural environment.

6. The method of claim 5, wherein, the property value is one of an expected mechanical stress, a thermal conductivity or a moisture retention capacity, wherein the expected mechanical stress is calculated based on wind load or soil load, the thermal conductivity is calculated based on ambient temperature and solar radiation intensity, and the moisture retention capacity is calculated based on soil humidity and material permeability, the data being derived from the agricultural environment parameter data.

7. The method of claim 5, wherein, In step three, after calculating the printing path through the path optimization function, it further includes: smoothing the print path by iteratively optimizing curvature terms reducing sharp turns in the path; The smoothing processing adopts gradient descent method, sets fixed iteration step length as 0.03, and iteration termination condition as curvature difference of adjacent two iterations ≤10 -4 , and iteration formula is Wherein is iteration number, is gradient of cost function at the first iteration.

8. The method of claim 1, wherein, In step four, the control instructions for the 3D printer include: Converting the printing path into G code or M code instructions and adding agricultural-specific control parameters, including printing speed, material flow, and temperature settings.

9. The method of claim 1, wherein, The agricultural object includes at least one of an agricultural greenhouse structure, an irrigation system component, a planting container, or a soil remediation device, and the 3D printing path planning method is used to optimize the durability, functional efficiency, or environmental adaptability of the agricultural object.

10. A 3D printing path planning system based on the method of any of claims 1-9, characterized in that, It includes: A data acquisition module for obtaining 3D model data of the agricultural object to be printed and agricultural environment parameter data; A path calculation module for calculating the printing path based on the 3D model data and the agricultural environment parameter data using a path optimization function; A control generation module for generating control instructions for the 3D printer based on the printing path.

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