Multi-laser collaborative scanning path planning method, device, electronic equipment and medium

Abstract

This invention relates to the field of 3D printing technology and discloses a method, apparatus, electronic device, and medium for multi-laser cooperative scanning path planning. The method includes: in a discrete simulation environment, decomposing the two-dimensional layered data to be printed into multiple fine-grained scanning task packages, and setting the priority of each scanning task package and the initial state of each laser; based on the priority of each scanning task package and the initial state of each laser, performing an iterative scheduling simulation based on a greedy strategy until all scanning task packages are successfully scheduled, obtaining a scheduling sequence containing timing; and generating multi-laser cooperative control instructions for each laser based on the scheduling sequence containing timing. This invention performs a complete virtual printing simulation on a computer before the laser printing work of the additive manufacturing equipment begins, thereby generating an optimal, conflict-free multi-laser cooperative control instruction, achieving the effect of improving both printing efficiency and forming quality.

Description

Technical Field

[0001] This invention relates to the field of 3D printing technology, specifically to a method, apparatus, electronic device, and medium for multi-laser collaborative scanning path planning. Background Technology

[0002] In additive manufacturing equipment, such as multi-laser selective laser melting (SLM) equipment, multiple laser beams are typically used to simultaneously scan and sinter the powder bed to improve printing efficiency. However, lasers generate high-temperature spatter and fumes when melting metal powder. If the optical path of one laser (such as a downwind laser) is blocked by the fumes generated by another laser (such as an upwind laser), laser energy attenuation will occur, severely affecting the metallurgical quality and mechanical properties of the final shaped part.

[0003] To address this issue, for example, a multi-mirror scanning control method is employed. This method first divides the sintering plane into zones according to preset rules, and then pre-assigns these zones to different "scanning time periods." Its core avoidance principle is: within the same time period, areas that do not overlap along the wind direction can be scanned; for two areas within the same time period and along the scanning direction (perpendicular to the wind direction), if their distance is greater than a fixed "smoke diffusion threshold," they can be scanned simultaneously; otherwise, they must be scanned sequentially. This approach has the following significant drawbacks:

[0004] The scheduling strategy is rigid and lacks efficiency optimization: This method is a static, rule-based pre-planning approach. Once the "time period" and sequence are determined, it lacks flexibility during execution. When the distance between two regions is less than a threshold, only a simple "sequential scanning" strategy can be used, which leads to unnecessary long periods of idle waiting for the lasers, failing to maximize the efficiency of parallel operation.

[0005] The interference model is oversimplified and lacks accuracy: it uses only a fixed "maximum width of smoke diffusion" as the criterion, which is a "one-size-fits-all" model. In reality, the diffusion range of smoke is closely related to process parameters such as laser power, scanning speed, and gas flow rate. A fixed threshold cannot accurately adapt to complex actual working conditions and may lead to excessive avoidance (sacrificing efficiency) or insufficient avoidance (sacrificing quality).

[0006] Therefore, there is an urgent need for a collaborative scanning path planning method that can balance printing efficiency and printing quality. Summary of the Invention

[0007] This invention provides a method, apparatus, electronic device, and medium for multi-laser collaborative scanning path planning, in order to solve the problems of low printing efficiency and quality caused by rigid scheduling strategies and overly simplified interference models in existing multi-laser scanning technologies.

[0008] In a first aspect, the present invention provides a multi-laser cooperative scanning path planning method, the method comprising:

[0009] In a discrete simulation environment, the two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages, and the priority of each scanning task package and the initial state of each laser are set.

[0010] Based on the priority of each scanning task package and the initial state of each laser, an iterative scheduling simulation based on a greedy strategy is performed until all scanning task packages are successfully scheduled, resulting in a scheduling sequence containing timing information.

[0011] Based on the scheduling sequence including timing, multi-laser cooperative control instructions are generated for each laser.

[0012] This invention provides a multi-laser collaborative scanning path planning method that greatly improves scheduling flexibility and optimization space by "atomicting" tasks into fine-grained task packages. It can adapt to various complex and irregular part cross-sections. Combined with iterative scheduling simulation based on a greedy strategy, it achieves efficient multi-laser collaboration (reducing idle time). It makes a locally optimal choice at each decision point, seeks all possible parallel working opportunities, and minimizes the idle waiting time of the lasers, thereby significantly shortening the overall printing time. At the same time, it accurately avoids inter-laser interference by using an offline discrete simulation environment. The final generated time-sequential collaborative control instructions balance printing efficiency and forming quality. Moreover, the offline processing mode significantly reduces the performance requirements of the equipment's real-time control system. It covers the core logic chain of task preprocessing, scheduling simulation optimization, and execution instruction generation, realizing a technical closed loop of multi-laser collaborative path planning from data preparation to actual execution. It solves the problems of low printing efficiency and quality caused by rigid scheduling strategies and overly simplified interference models in existing multi-laser scanning technologies.

[0013] In one optional implementation, the two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages, and the priority of each scanning task package and the initial state of each laser are set, including:

[0014] According to the preset division rules, the two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages;

[0015] Each scanning task package is assigned a priority according to the preset priority setting rules;

[0016] Create task priority queues for multiple lasers, store scanning task packages in the corresponding laser's task priority queue, initialize the simulation time, and set the simulation status of all lasers to idle.

[0017] This invention provides a multi-laser collaborative scanning path planning method. Fine-grained task package decomposition overcomes the limitations of coarse-grained division, greatly improving scheduling flexibility and optimization space. It can adapt to various complex and irregular part cross-sections, providing a more flexible optimization space for multi-laser collaborative scheduling. Based on preset rule-based priority setting and queue allocation, it can combine process objectives (such as thermal management and spatial requirements) to achieve orderly task sequencing, ensuring that critical tasks are executed first. Furthermore, the unified initialization of simulation time and laser initial states lays a standardized and controllable foundation for subsequent iterative scheduling simulations, ensuring consistency and traceability throughout the entire scheduling process from the outset.

[0018] In one optional implementation, the two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages according to a preset partitioning rule, including:

[0019] The two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages according to at least one of the following: checkerboard division rules, strip division rules along a preset direction, and adaptive division rules based on the geometric features of the part.

[0020] This invention provides a multi-laser collaborative scanning path planning method, offering various partitioning rules such as checkerboard, strip-shaped partitions along preset directions, and adaptive partitioning based on part geometric features. This allows for flexible adaptation to the structural characteristics of different parts (such as regular shapes, specific heat flow direction requirements, thin walls / overhangs, and other complex geometries), ensuring both the versatility of the decomposition and precise partitioning of key geometric areas. Furthermore, the fine-grained decomposition breaks through the limitations of coarse-grained region partitioning, providing flexible units for subsequent fine-grained collaborative scheduling of multiple lasers, laying the foundation for improving scheduling efficiency and adapting to the printing needs of complex parts from a basic data perspective.

[0021] In one optional implementation, based on the priority of each scanning task package and the initial state of each laser, an iterative scheduling simulation based on a greedy strategy is performed until all scanning task packages are successfully scheduled, resulting in a scheduling sequence containing timing information, including:

[0022] At the current simulation time point, the highest priority scanning task package is selected from the task priority queue of each idle laser as a candidate task package;

[0023] Determine whether there is a spatiotemporal geometric conflict between the scan path of the candidate task package during execution and the dynamic influence area of ​​other currently executing scan task packages;

[0024] If there is no conflict, record the scheduling information to the scheduling sequence, update the simulation status of the laser, and calculate the estimated completion time of the corresponding laser; if there is a conflict, keep the laser in an idle state; the scheduling information includes laser ID, candidate task package ID, and simulation start time.

[0025] After all idle lasers have completed their scheduling decisions at the current simulation time, the estimated execution time of the scanning task package is calculated. Based on the estimated execution time, the earliest estimated completion time of all lasers currently executing simulation tasks is found. The earliest estimated completion time is advanced to the current simulation time, and the simulation state of the corresponding laser is reset to idle to trigger the next round of scheduling decisions. This process continues until all scanning task packages are successfully scheduled, resulting in a scheduling sequence that includes timing information.

[0026] This invention provides a multi-laser collaborative scanning path planning method. It employs a greedy strategy to prioritize the highest-priority candidate task package in the idle laser task queue, quickly locking in the locally optimal scheduling choice and minimizing laser idle time. Combined with spatiotemporal geometric conflict judgment of the dynamic influence region, it can accurately avoid mutual interference during multi-laser scanning, effectively ensuring print quality. Simultaneously, by finding the earliest estimated completion time of all busy lasers to advance the simulation time and resetting the corresponding lasers to an idle state, it can skip the "waiting period" without state changes, avoiding redundant time simulation consumption and efficiently triggering the next round of scheduling decisions. Related technologies use a large "scanning area" as the coarse-grained basic unit for planning. This coarse-grained division limits the fineness of scheduling optimization and cannot achieve fine-grained collaborative work. This invention, by "atomicing" tasks into fine-grained task packages, greatly improves the flexibility and optimization space of scheduling, achieving fine-grained collaborative work. Ultimately, it not only ensures that all scanning task packages are scheduled in an orderly manner but also generates a time-accurate and conflict-free scheduling sequence, laying a reliable foundation for the subsequent generation of multi-laser collaborative control commands.

[0027] In one optional implementation, determining whether there is a spatiotemporal geometric conflict between the scan path of a candidate task package during execution and the dynamic influence region of other currently executing scan task packages includes:

[0028] The dynamic interference prediction model is invoked to detect the intersection of the scanning path of the candidate task package during execution with the dynamic influence area of ​​other currently executing scanning task packages. If an intersection exists, it is determined that there is a spatiotemporal geometric conflict; otherwise, there is no spatiotemporal geometric conflict.

[0029] This invention provides a multi-laser collaborative scanning path planning method. By calling a dynamic interference prediction model for detection, it abandons the "one-size-fits-all" approach of fixed distance thresholds in existing technologies. It can dynamically generate an influence area (ZoI) that fits the real-time operating conditions by combining the actual process parameters (such as laser power and scanning speed) of candidate task packages with those of other currently executing task packages and the gas flow field conditions of the equipment. This makes the basis for conflict judgment more accurate and more adaptable to complex printing scenarios. At the same time, it focuses on the intersection detection of the "temporal-spatial scanning trajectory of candidate task packages" and the "dynamic influence area of ​​other task packages changing over time," achieving comprehensive verification in both time and space dimensions. This avoids misjudgments caused by detection in only one dimension (such as ignoring spatial overlaps that do not overlap in time or temporal conflicts that do not overlap in space). Ultimately, it can accurately identify real interference risks and exclude scenarios without actual interference. This effectively avoids laser energy attenuation and metallurgical quality problems of formed parts caused by insufficient avoidance, and also prevents the idle waste of lasers caused by excessive avoidance. It provides a core guarantee for safe and efficient parallel scanning of multiple lasers.

[0030] In one alternative implementation, the estimated execution time of the scanning task package is calculated using the following formula:

[0031] Estimated execution time of the scan task package = total length of scan vectors / laser scanning speed.

[0032] In one alternative implementation, based on a timing-included scheduling sequence, multi-laser cooperative control instructions for each laser are generated, including:

[0033] Group the tasks by laser ID to form a task list for each laser, and sort the task list for each laser in ascending order by start timestamp;

[0034] Based on the sorted task list for each laser, each task is converted into a timestamped instruction stream that can be recognized by the specified device. All timestamped instruction streams are combined to obtain multi-laser collaborative control instructions. The timestamped instruction stream includes laser ID, instruction execution timestamp, laser power, scanning speed, and scanning vector segment information. This invention provides a multi-laser collaborative scanning path planning method. First, tasks are grouped by laser ID and sorted in ascending order by start timestamp, ensuring a clear and coherent task sequence for each laser and preventing task order confusion during single-laser execution. Then, the sorted tasks are converted into a timestamped instruction stream that the device can directly recognize. This instruction stream contains complete information such as laser ID, execution timestamp, laser power, scanning speed, and scanning vector segments. This eliminates the need for additional data parsing by the device and allows the laser to accurately obtain the execution parameters and spatiotemporal requirements for each step. Finally, the collaborative control command formed by combining all instruction streams ensures precise synchronization of multiple lasers in the time dimension and accurate execution of process parameters, effectively avoiding collaborative errors caused by missing instruction information or timing misalignment. This provides a direct and implementable execution basis for efficient and high-quality parallel scanning with multiple lasers.

[0035] In a second aspect, the present invention provides a multi-laser cooperative scanning path planning device, the device comprising:

[0036] The task decomposition module is used to decompose the two-dimensional layered data to be printed into multiple fine-grained scanning task packages in a discrete simulation environment, and to set the priority of each scanning task package and the initial state of each laser.

[0037] The offline scheduling engine module is used to perform iterative scheduling simulation based on a greedy strategy, according to the priority of each scanning task package and the initial state of each laser, until all scanning task packages are successfully scheduled, and a scheduling sequence containing time sequence is obtained.

[0038] The control command generation module is used to generate multi-laser collaborative control commands for each laser based on a scheduling sequence that includes timing.

[0039] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the multi-laser cooperative scanning path planning method described in the first aspect or any corresponding embodiment thereof.

[0040] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the multi-laser cooperative scanning path planning method described in the first aspect or any corresponding embodiment thereof.

[0041] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the multi-laser cooperative scanning path planning method described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0042] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0043] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of the first process of a multi-laser cooperative scanning path planning method according to an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of the second process of the multi-laser cooperative scanning path planning method according to an embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram of the third process of the multi-laser cooperative scanning path planning method according to an embodiment of the present invention;

[0047] Figure 5 This is a schematic diagram of the fourth process of the multi-laser cooperative scanning path planning method according to an embodiment of the present invention;

[0048] Figure 6 This is a schematic diagram illustrating the execution of the dynamic interferometric prediction model of the multi-laser cooperative scanning path planning method according to an embodiment of the present invention;

[0049] Figure 7 This is a structural block diagram of a multi-laser cooperative scanning path planning device according to an embodiment of the present invention;

[0050] Figure 8 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, 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.

[0052] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0053] As an optional application scenario of this invention, such as Figure 1 As shown, application 101 is installed in terminal device 110, and user 130 can interact with application 101 through terminal device 110 and / or access device of terminal device 110.

[0054] For example, application 101 can be any application that provides question-and-answer related services. For instance, application 101 could be a question-and-answer interactive application, such as a text-to-text application, an image-to-text application, etc. Figure 1 In the application scenario shown, if application 101 is active, the terminal device 110 can display the interface 102 of application 101. The interface 102 may include various pages that application 101 can provide, such as interactive pages, settings pages, query pages, etc.

[0055] In some embodiments, terminal device 110 is communicatively connected to server 120 to provide services to application 101. Terminal device 110 may be a mobile terminal, fixed terminal, or portable terminal, etc., including but not limited to mobile phones, desktop computers, laptop computers, multimedia tablets, e-book devices, gaming devices, or any combination thereof, including accessories and peripherals of these devices or any combination thereof. In some embodiments, terminal device 110 may also support any type of interface, and server 120 may be various types of computing systems or servers capable of providing computing power, including but not limited to mainframes, edge computing nodes, computing devices in cloud environments, etc.

[0056] It should be noted that, Figure 1 This is merely an example of an application scenario and does not limit the scope of protection of this invention.

[0057] The embodiments of the present invention will now be described with reference to the accompanying drawings. It should be understood that the pages shown in the drawings are merely examples, and various page designs are possible in practice. The various graphic elements on the page may have different arrangements and different visual representations; one or more elements may be omitted or replaced, and one or more other elements may also be present, without any limitation in the embodiments of the present invention. Furthermore, the embodiments described below primarily pertain to terminal device 110. It should be understood that the actions described relative to terminal device 110 can be performed by application 101 on terminal device 110, or can be performed by application 101 in conjunction with its server (e.g., server 120).

[0058] Existing technologies suffer from problems such as rigid scheduling strategies, overly simplified interference models, and low parallel efficiency in multi-laser scanning. This invention provides a multi-laser collaborative scanning path planning method. Before the laser printing operation of the additive manufacturing equipment begins, a complete virtual printing simulation is performed by a computer to generate an optimal, conflict-free multi-laser collaborative control command, thereby improving both printing efficiency and forming quality.

[0059] According to an embodiment of the present invention, a method for multi-laser cooperative scanning path planning is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0060] This embodiment provides a multi-laser cooperative scanning path planning method, which can be used in the aforementioned electronic or terminal devices. The electronic or terminal device is equipped with a multi-laser cooperative scanning path planning device, which includes: a task decomposition module, an offline scheduling engine module, and a control command generation module. Figure 2 This is a flowchart of a multi-laser cooperative scanning path planning method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0061] Step S201: In a discrete simulation environment, the two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages, and the priority of each scanning task package and the initial state of each laser are set.

[0062] Specifically, this step is the preparatory stage for all optimization calculations and is completed by the task decomposition module. That is, the task decomposition module performs the initialization of the offline simulation environment.

[0063] An offline simulation environment refers to a virtual computing environment built in a computer to simulate the working process of a laser before the additive manufacturing equipment (such as a multi-laser SLM device) actually performs a printing task.

[0064] The core components of initializing the offline simulation environment include: decomposed fine-grained scan task package data, task priority queues for each laser, simulation time initialized to 0 (represented by SimTime), and idle states of all lasers (represented by IDLE), among other basic parameters and logical frameworks. This virtual environment allows for pre-simulation of the task scheduling process for multiple lasers (such as conflict resolution and priority execution), ultimately generating an optimized scheduling sequence and avoiding the efficiency losses and risks associated with direct debugging on physical equipment.

[0065] Step S202: Based on the priority of each scanning task package and the initial state of each laser, perform an iterative scheduling simulation based on a greedy strategy until all scanning task packages are successfully scheduled, and obtain a scheduling sequence containing timing information.

[0066] Specifically, at the current simulation time point, the offline scheduling engine module selects the highest priority task package from the task priority queue of the idle lasers as a candidate, and determines whether there is a spatiotemporal geometric conflict between its scanning path and other currently executing tasks. If there is no conflict, the scheduling information (including laser ID, scanning task package ID, and start time) is recorded and the laser status and estimated completion time are updated. If there is a conflict, the laser is kept idle. After all idle lasers at the current simulation time point have completed their decisions, the simulation time is advanced to the earliest estimated completion time of all busy lasers and the corresponding lasers are reset to idle. The above process is repeated until all task packages are scheduled, resulting in a scheduling sequence containing time information.

[0067] The current simulation time point is a specific virtual time node used to execute task scheduling decisions (such as judging the laser status, selecting candidate tasks, and detecting conflicts) during the offline simulation of multi-laser scheduling. It is not the real-time time of the actual physical printing, but a virtual time coordinate set within the simulation system.

[0068] When some lasers are busy, the system will find the earliest estimated completion time of the current task among these lasers and update the current simulation time point directly to that time point. At this time, the laser that completes the task earliest will switch to an idle state. The system will then start the next round of task scheduling decisions for the idle lasers (such as selecting new candidate tasks, detecting conflicts, etc.) at this new current simulation time point.

[0069] Step S203: Based on the scheduling sequence including timing, generate multi-laser cooperative control instructions for each laser.

[0070] Specifically, the control command generation module uses a scheduling sequence containing timing information to group tasks by laser ID and sort them by start timestamp. The sorted tasks are then converted into a timestamped command stream that the device can recognize (including laser ID, execution timestamp, laser power, scanning speed, and scanning vector segment information). All command streams are combined to generate multi-laser collaborative control commands.

[0071] The multi-laser collaborative scanning path planning method provided in this embodiment greatly improves the scheduling flexibility and optimization space by "atomicting" tasks into fine-grained task packages. It can adapt to various complex and irregular part cross-sections. Combined with iterative scheduling simulation based on a greedy strategy, it achieves efficient multi-laser collaboration (reducing idle time). It makes a locally optimal choice at each decision point, seeks all possible parallel working opportunities, and minimizes the idle waiting time of the lasers, thereby significantly shortening the overall printing time. At the same time, it accurately avoids inter-laser interference by using an offline discrete simulation environment. The final generated time-sequential collaborative control instructions take into account both printing efficiency and forming quality. Moreover, the offline processing mode greatly reduces the performance requirements of the real-time control system of the equipment. It covers the core logic chain of task preprocessing, scheduling simulation optimization, and execution instruction generation, realizing a technical closed loop of multi-laser collaborative path planning from data preparation to actual execution. It solves the problems of low printing efficiency and quality caused by rigid scheduling strategies and overly simplified interference models in existing multi-laser scanning technologies.

[0072] This embodiment provides a multi-laser cooperative scanning path planning method, which can be used in the aforementioned electronic or terminal devices. The electronic or terminal device is equipped with a multi-laser cooperative scanning path planning device, which includes: a task decomposition module, an offline scheduling engine module, and a control command generation module. Figure 3 This is a flowchart of a multi-laser cooperative scanning path planning method according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps:

[0073] Step S301: In a discrete simulation environment, the two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages, and the priority of each scanning task package and the initial state of each laser are set.

[0074] Specifically, the two-dimensional layer data to be printed is decomposed into multiple fine-grained "scanning task packages", and a task priority queue is established for each laser; at the same time, the simulation time is initialized to 0, and the simulation status of all lasers is set to idle.

[0075] Step S301 above includes:

[0076] Step S3011: According to the preset division rules, the two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages.

[0077] In an optional implementation, step S3011 includes:

[0078] Step a: Decompose the two-dimensional layered data to be printed into multiple fine-grained scanning task packages according to at least one of the following: checkerboard division rules, strip division rules along a preset direction, and adaptive division rules based on the geometric features of the part.

[0079] The task decomposition module breaks down the current complex 2D layered geometric contour data into hundreds or thousands of independent, fine-grained "scanning task packages" according to preset partitioning rules. The partitioning rules can be flexibly set; for example, they can be a simple checkerboard partition, a strip partition along a specific direction (such as the direction of maximum heat flow), or a more advanced adaptive partition based on the geometric features of the part (such as thin walls, overhangs, etc.). Each scanning task package is essentially a set of one or more continuous scanning vector segments.

[0080] The multi-laser collaborative scanning path planning method provided in this embodiment offers various partitioning rules, such as checkerboard, strip along a preset direction, and adaptive partitioning based on part geometric features. These rules can flexibly adapt to the structural characteristics of different parts (such as regular shapes, specific heat flow direction requirements, thin walls / overhangs, and other complex geometries). This ensures both the versatility of the decomposition and the precise partitioning of key geometric areas. At the same time, the fine-grained decomposition form breaks the limitations of coarse-grained region partitioning, providing flexible units for subsequent fine-grained collaborative scheduling of multiple lasers. This lays the foundation for improving scheduling efficiency and adapting to the printing needs of complex parts from the basic data level.

[0081] Step S3012: Assign a priority to each scan task package according to the preset priority setting rules.

[0082] Specifically, the task decomposition module assigns one or more priorities to each generated task package. Priority setting is one of the key aspects of the intelligent scheduling implemented in this embodiment, and its rules can comprehensively consider various process objectives, such as:

[0083] Spatial location priority: In order to facilitate the uniform distribution and release of thermal stress during the printing process, task packages located in the geometric center of the part can be given higher priority, while scan task packages close to the contour boundary can be given lower priority.

[0084] Thermal Management Priority: The device can embed a simplified thermal simulation model. After task decomposition, it predicts potential heat accumulation areas during printing through rapid thermal simulation. To avoid localized overheating, the system automatically lowers the priority of scan tasks in these high-temperature areas and their adjacent areas, forcing them to be scanned later, thus allowing sufficient cooling time.

[0085] Priority unlocking is crucial: In multi-laser collaborative operation, the completion of task packages at certain critical locations (e.g., task packages located at the boundary of the working areas of two lasers) may "unlock" a large, conflict-free, workable area for other lasers. The system can identify these critical scanning task packages and dynamically increase their priority to quickly remove "bottlenecks" and improve overall parallel efficiency.

[0086] Step S3013: Create task priority queues for multiple lasers, store scanning task packages in the corresponding laser's task priority queue, initialize simulation time, and set the simulation status of all lasers to idle state.

[0087] Specifically, for each of the n lasers in a physical device (such as an additive manufacturing device), a virtual task priority queue is created, and the task packets with assigned priorities are stored in the corresponding laser's queue. Simultaneously, the device establishes a simulation clock, SimTime, in memory and initializes it to 0, while marking the virtual state of all lasers as IDLE (idle state).

[0088] Step S302: Based on the priority of each scanning task package and the initial state of each laser, perform an iterative scheduling simulation based on a greedy strategy until all scanning task packages are successfully scheduled, obtaining a scheduling sequence including timing information. For details, please refer to [link to relevant documentation]. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0089] Step S303: Based on the scheduling sequence including timing, generate multi-laser cooperative control commands for each laser. See details below. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0090] In related technologies, a large "scanning area" is used as the coarse-grained basic unit for planning. This coarse-grained division limits the fineness of scheduling optimization and cannot achieve fine-grained collaborative work by "filling in the gaps". The multi-laser collaborative scanning path planning method provided in this embodiment breaks through the limitations of coarse-grained division by decomposing scanning task packages into fine-grained ones. It greatly improves the flexibility of scheduling and optimization space, and can adapt to various complex and irregular part cross sections, providing a more flexible optimization space for multi-laser collaborative scheduling. Based on the priority setting and queue allocation of preset rules, the orderly sorting of tasks can be achieved in combination with process objectives (such as thermal management and spatial location requirements), ensuring that critical tasks are executed first. The unified initialization of simulation time and laser initial state lays a standardized and controllable foundation for subsequent iterative scheduling simulation, ensuring that the entire scheduling process has consistency and traceability from the starting point.

[0091] This embodiment provides a multi-laser cooperative scanning path planning method, which can be used in the aforementioned electronic device or terminal device. The electronic device or terminal device is equipped with a multi-laser cooperative scanning path planning device, which includes: a task decomposition module, an offline scheduling engine module, and a control command generation module. Figure 4 This is a flowchart of a multi-laser cooperative scanning path planning method according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps:

[0092] Step S401: In the discrete simulation environment, the two-dimensional layered data to be printed is decomposed into multiple fine-grained scanning task packages, and the priority of each scanning task package and the initial state of each laser are set. For details, please refer to [link to relevant documentation]. Figure 3 Step S301 of the illustrated embodiment will not be described again here.

[0093] Step S402: Based on the priority of each scanning task package and the initial state of each laser, perform an iterative scheduling simulation based on a greedy strategy until all scanning task packages are successfully scheduled, and obtain a scheduling sequence containing timing information.

[0094] Specifically, this step is the core of the technical solution of this embodiment of the invention and is executed by the offline scheduling engine module. Its goal is to fully "rehearse" the printing process of the current layer in a virtual environment, thereby generating a conflict-free scheduling sequence with optimal execution time, which is represented by ScheduleLog.

[0095] The whole process follows Figure 5 The loop logic shown above includes the following steps in step S402:

[0096] Step S4021: At the current simulation time point, select the highest priority scanning task package from the task priority queue of each idle laser as a candidate task package.

[0097] Specifically, it determines whether all scanning task packages have been scheduled; if not, it determines whether there are any lasers in an idle state.

[0098] Circular decision-making: As long as there are still unscheduled tasks, the offline scheduling engine module will make a decision on all virtual lasers in the IDLE state within the current simulation time (SimTime). For one of the idle lasers L... i The offline scheduling engine module will look for the highest priority scan task package T_candidate in its task priority queue as a candidate task package.

[0099] Step S4022: Determine whether there is a spatiotemporal geometric conflict between the scanning path of the candidate task package during execution and the dynamic influence area of ​​other currently executing scanning task packages.

[0100] Specifically, this step is a conflict determination operation: the offline scheduling engine module calls a dynamic interference prediction model (Zone of Influence Model, or ZoI model for short) to determine whether the startup candidate task package T_candidate is safe.

[0101] In some optional implementations, step S4022 above includes:

[0102] Step b: Invoke the dynamic interferometry prediction model to perform intersection detection on the scanning path of the candidate task package during execution and the dynamic influence area of ​​other currently executing scanning task packages. If an intersection exists, it is determined that there is a spatiotemporal geometric conflict; otherwise, there is no spatiotemporal geometric conflict.

[0103] A schematic diagram of the execution of the dynamic interferometric prediction model is shown below. Figure 6 As shown, a laser 11 is positioned above a horizontally placed powder bed 12, with a vertical dashed line pointing downwards to the powder bed 12 below, representing the laser's scanning area. The horizontally placed powder bed 12 is divided into eight consecutive vertical sections, numbered D1 to D8 from bottom to top. The dynamic interferometric prediction model abandons the fixed distance threshold used in existing technologies. It is a multivariate input dynamic model, as detailed below:

[0104] Model inputs include the process parameters carried by the candidate task package T_candidate itself, such as the preset laser power P, scanning speed V, and the gas flow field vector F (including direction and velocity) read from the system configuration.

[0105] Model Principle: This model can fit or simplify computational fluid dynamics (CFD) simulations based on a large amount of experimental data, establishing a mathematical function or lookup table. This function describes the dynamic morphology of the three-dimensional influence area (ZoI) formed by smoke and splashes around the laser scanning point under specific input parameters. For example... Figure 6 As shown, under the influence of airflow A, the region is typically asymmetrical (e.g., trailing a long "tail" downwind).

[0106] Model output: Given an input, the model will calculate a geometry (Zone of Influence Model, ZoI) with a precisely defined spatial extent in real time.

[0107] Conflict Detection: The offline scheduling engine module performs spatiotemporal geometric collision detection on the scan path of the candidate task package T_candidate throughout the entire execution period (from SimTime to SimTime + ExecutionTime) and the dynamic ZoI regions of all other currently executing tasks recorded in the current scheduling sequence ScheduleLog. If any intersection is detected, it is determined that there is a "conflict". ExecutionTime represents the estimated execution time of the scanned task package.

[0108] Step S4023: If there is no conflict, record the scheduling information to the scheduling sequence, update the simulation status of the laser, and calculate the estimated completion time of the corresponding laser; if there is a conflict, keep the laser in an idle state; the scheduling information includes laser ID, candidate task package ID and simulation start time.

[0109] Specifically, if the conflict determination result is "no" (no conflict), it means that this is a feasible locally optimal decision. The engine immediately records this allocation result, i.e., the tuple (laser ID, scan task package ID, SimTime), in the final scheduling sequence ScheduleLog. Simultaneously, it records the laser L... i The virtual state is updated to BUSY, and its estimated completion time T_finish is calculated based on the length of the task package and the scanning speed. If the judgment result is "yes" (conflict exists), the laser cannot execute its optimal task in this round of SimTime and can only remain in the IDLE state to wait.

[0110] Step S4024: After all idle lasers have completed the scheduling decision at the current simulation time point, calculate the estimated execution time of the scanning task package. Based on the estimated execution time, find the earliest estimated completion time of all lasers currently executing simulation tasks, advance the earliest estimated completion time to the current simulation time point, and reset the simulation state of the corresponding laser to idle to trigger the next round of scheduling decision, until all scanning task packages are successfully scheduled, and obtain a scheduling sequence containing time sequence.

[0111] Specifically, when all idle lasers at a given simulation time point SimTime have completed their decisions (i.e., whether there are any other idle lasers that have not been checked and determined to be "no"), or when there are no idle lasers at all, the offline scheduling engine module needs to advance the simulation time. It checks all virtual lasers in the BUSY state, finds the task with the earliest T_finish, and directly "fast-forwards" the simulation time SimTime to this earliest expected completion time. Simultaneously, it resets the state of the laser that just completed its task to IDLE. The advancement of time and the change in laser state trigger new events, allowing the entire simulation loop to continue, returning to step S4012 to begin a new round of decision-making.

[0112] This process is repeated until all task packages are successfully scheduled into the ScheduleLog.

[0113] In one alternative implementation, the estimated execution time of the scanning task package is calculated using the following formula:

[0114] Estimated execution time of the scan task package = total length of scan vectors / laser scanning speed.

[0115] Step S403: Based on the scheduling sequence including timing, generate multi-laser cooperative control instructions for each laser.

[0116] Specifically, the simulation process ends after all task packages have been scheduled. At this point, the offline scheduling engine module has generated a complete scheduling sequence with precise timing information. This sequence is passed to the control command generation module, and step S403 includes:

[0117] Step S4031: Group the tasks by laser ID to form a task list for each laser, and sort the task list for each laser in ascending order by start timestamp.

[0118] Specifically, the control instruction generation module extracts key information for all tasks from the scheduling sequence (ScheduleLog) which includes time sequence, including: laser ID (corresponding to a specific laser), task start timestamp (corresponding to the simulation time SimTime), the set of scanning vectors (path coordinates) contained in the scanning task package, and laser process parameters (power P, scanning speed V, etc.).

[0119] Tasks are grouped by laser ID to form an independent task list for each laser. The task list for each laser is then sorted in ascending order by the start timestamp to ensure the sequential continuity of task execution.

[0120] Step S4032: Based on the sorted task list for each laser, convert each task into a timestamped instruction stream that can be recognized by the specified device, and combine all the timestamped instruction streams to obtain multi-laser collaborative control instructions; the timestamped instruction stream includes laser ID, instruction execution timestamp, laser power, scanning speed, and scanning vector segment information.

[0121] Specifically, the control command generation module is responsible for "translating" high-level, abstract scheduling sequences into machine instruction files that can be directly recognized and executed by the underlying hardware (such as motion control cards, galvanometer controllers, and laser controllers). This file format can be enhanced G-code or a manufacturer-defined binary format. Its core function is to generate a command stream with a precise timestamp for each laser, for example: "Laser 11, at timestamp t=10.52s, begins scanning vector segment V_1_1 with laser power P1 and scanning speed V1; at t=10.58s, jumps to the next segment...".

[0122] Ultimately, the operator only needs to load the two-dimensional layered data processed by the slicing software into the SLM device. The program will automatically calculate using the multi-laser collaborative scanning path planning method provided in this embodiment, thus initiating a highly optimized, interference-free, and high-quality automated printing process.

[0123] The multi-laser collaborative scanning path planning method provided in this embodiment first groups tasks by laser ID and sorts them in ascending order by start timestamp. This ensures that the task sequence of each laser is clear and coherent, avoiding task order confusion when a single laser is executed. Then, the sorted tasks are converted into timestamped instruction streams that can be directly recognized by the equipment. The instruction streams contain complete information such as laser ID, execution timestamp, laser power, scanning speed, and scanning vector segments. This not only saves the equipment from additional data parsing but also allows the lasers to accurately obtain the execution parameters and spatiotemporal requirements of each step. Finally, the collaborative control command formed by combining all instruction streams ensures that multiple lasers are accurately synchronized in the time dimension and accurately executed in terms of process parameters. This effectively avoids collaborative errors caused by missing instruction information or timing misalignment, providing a direct and implementable execution basis for efficient and high-quality parallel scanning of multiple lasers.

[0124] As one or more specific application embodiments of the present invention, combined with Figure 5The multi-laser collaborative scanning path planning provided by this invention will be further described in detail. In a typical application scenario, the system first receives user-input 3D model data (such as an STL (Stereo Lithography File) file), and calls existing slicing software to process it into a series of 2D layered data. Subsequently, for any one of the 2D layered data, the following will be executed: Figure 5 The path planning method shown below has the following specific steps:

[0125] Step S1: Initialize the offline scheduling simulation environment.

[0126] This step is the preparatory stage for all optimization calculations and is completed by the task decomposition module.

[0127] First, the task decomposition module breaks down the current complex two-dimensional layered geometric contour data into hundreds or thousands of independent, fine-grained "scan task packages" according to preset partitioning rules. The partitioning rules can be flexibly set; for example, they can be a simple checkerboard partition, a strip partition along a specific direction (such as the direction of maximum heat flow), or a more advanced adaptive partition based on the geometric features of the part (such as thin walls, overhangs, etc.). Each task package is essentially a set of one or more continuous scan vector segments.

[0128] Next, the task decomposition module assigns one or more priorities to each generated task package. Priority setting is one of the key aspects of achieving intelligent scheduling in this invention; its rules can comprehensively consider multiple process objectives, such as:

[0129] Spatial location priority: In order to facilitate the uniform distribution and release of thermal stress during the printing process, task packages located in the geometric center of the part can be given higher priority, while task packages closer to the contour boundary can be given lower priority.

[0130] Thermal Management Priority: The device can embed a simplified thermal simulation model. After task decomposition, it predicts potential heat accumulation areas during printing through rapid thermal simulation. To avoid localized overheating, the device automatically lowers the priority of task packages in these high-temperature areas and their adjacent areas, forcing them to be scanned later, thus allowing sufficient cooling time.

[0131] Priority-based unlocking: In multi-laser collaborative operation, the completion of task packages at certain critical locations (e.g., task packages located at the intersection of the working areas of two lasers) may "unlock" a large area of ​​conflict-free working space for other lasers. The device can identify such critical task packages and dynamically increase their priority to quickly remove "bottlenecks" and improve overall parallel efficiency.

[0132] Finally, the device creates a virtual task priority queue for each of the n lasers in the physical device, and stores the task packets with assigned priorities into the corresponding laser's queue. Simultaneously, the system establishes a simulation clock, SimTime, in memory, initializes it to 0, and marks the virtual state of all lasers as IDLE (idle).

[0133] Step S2: Perform an iterative scheduling simulation based on a greedy strategy.

[0134] This step is the core of the technical solution in this embodiment of the invention and is executed by the offline scheduling engine module. Its goal is to completely "rehearse" the printing process of the current layer in a virtual environment, thereby generating a conflict-free scheduling sequence ScheduleLog with optimal execution time. The entire process follows... Figure 5 The loop logic shown:

[0135] Circular decision-making: As long as there are still unscheduled tasks, the offline scheduling engine module will make a decision on all virtual lasers in the IDLE state within the current simulation time (SimTime). For one of the idle lasers L... i The offline scheduling engine module will look for the highest priority scan task package T_candidate in its task priority queue as a candidate task package.

[0136] Conflict detection: This is the most critical technical innovation in this embodiment. The conflict detection operation in this step includes: the offline scheduling engine module calls a dynamic interference prediction model (Zone of Influence Model, or ZoI model) to determine whether the startup candidate task package T_candidate is safe, such as... Figure 6 As shown, this model abandons the fixed distance threshold in existing technologies and is a dynamic model with multivariate inputs:

[0137] Model inputs include the process parameters carried by the T_candidate itself, such as the preset laser power P, scanning speed V, and the gas flow field vector F (including direction and velocity) read from the device configuration.

[0138] Model Principle: This model can fit or simplify computational fluid dynamics (CFD) simulations based on a large amount of experimental data, establishing a mathematical function or lookup table. This function describes the dynamic morphology of the three-dimensional influence area (ZoI) formed by smoke and splashes around the laser scanning point under specific input parameters. For example... Figure 6As shown, under the influence of airflow A, the region is typically asymmetrical (e.g., trailing a long "tail" downwind).

[0139] Model output: Given an input, the model will calculate a geometry (Zone of Influence Model, ZoI) with a precisely defined spatial extent in real time.

[0140] Conflict detection: The engine performs spatiotemporal geometric collision detection on the scan path of T_candidate throughout the entire execution period (from SimTime to SimTime + ExecutionTime) and the dynamic ZoI of all other currently executing tasks recorded in the ScheduleLog. If any intersection is detected, it is determined that "there is a conflict".

[0141] Recording and Waiting: If the conflict determination result is "No" (no conflict), it means that this is a feasible locally optimal decision. The engine immediately records this allocation result, i.e., the tuple (laser ID, scan task package ID, SimTime), into the final scheduling sequence ScheduleLog. Simultaneously, it records the laser L... i The virtual state is updated to BUSY, and its estimated completion time T_finish is calculated based on the length of the task package and the scanning speed. If the judgment result is "yes" (conflict exists), the laser cannot execute its optimal task in this round of SimTime and can only remain in the IDLE state to wait.

[0142] Time Advancement: When all idle lasers at a given simulation time point SimTime have completed their decisions (i.e., whether there are any other idle lasers that haven't been checked and determined to be "no"), or when there are no idle lasers at all, the offline scheduling engine module needs to advance the simulation time. It checks all virtual lasers in the BUSY state, finds the task with the earliest expected T_finish, and directly "fast-forwards" the simulation time SimTime to this earliest estimated completion time. Simultaneously, it resets the state of the laser that just completed its task to IDLE. The advancement of time and the change in laser state trigger new events, allowing the entire simulation loop to continue, returning to the loop decision to begin a new round of decision-making.

[0143] This process is repeated until all task packages are successfully scheduled into the ScheduleLog.

[0144] Step S3: Generate machine control instructions.

[0145] Once all task packages have been scheduled, the simulation process ends. At this point, the offline scheduling engine module has generated a complete scheduling sequence with precise timing information. This sequence is then passed to the control command generation module.

[0146] The control command generation module is responsible for translating high-level, abstract scheduling sequences into machine instruction files that can be directly recognized and executed by the underlying hardware (such as motion control cards, galvanometer controllers, and laser controllers). This file format can be enhanced G-code or a manufacturer-defined binary format. Its core function is to generate a command stream with precise timestamps for each laser, for example: "Laser 11, at timestamp t=10.52s, begins scanning vector segment V_1_1 with laser power P1 and scanning speed V1; at t=10.58s, jumps to the next segment...".

[0147] Ultimately, the operator only needs to load the two-dimensional layered data processed by the slicing software into the SLM device. The program will automatically calculate using the multi-laser collaborative scanning path planning method provided in this embodiment, thus initiating a highly optimized, interference-free, and high-quality automated printing process.

[0148] The multi-laser cooperative scanning path planning method provided in this embodiment has the following beneficial effects:

[0149] Extremely efficient: Through refined task decomposition and intelligent scheduling simulation, the parallel working potential of the laser is maximized, achieving refined collaboration in a "seize every opportunity" manner. Compared with the rigid waiting of existing technologies, printing efficiency is significantly improved.

[0150] Reliable quality: Based on a dynamic interference model, precise avoidance is achieved, which can better prevent the impact of smoke and dust compared to a fixed threshold, thus ensuring the metallurgical quality of the formed parts.

[0151] Highly adaptable: It is well adapted to complex and irregularly shaped parts because fine-grained task packages can be flexibly combined.

[0152] Low device load: Complex calculation tasks are all performed offline, and the device only needs to execute simple instructions during printing, which reduces the performance requirements of the device's real-time control system.

[0153] Process traceability and verification: The generated instruction file is deterministic, allowing for complete simulation and verification before printing, which facilitates process optimization and quality traceability.

[0154] This embodiment also provides a multi-laser cooperative scanning path planning device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0155] This embodiment provides a multi-laser collaborative scanning path planning device, such as... Figure 7 As shown, it includes:

[0156] The task decomposition module 701 is used to decompose the two-dimensional layered data to be printed into multiple fine-grained scanning task packages in a discrete simulation environment, and to set the priority of each scanning task package and the initial state of each laser.

[0157] The offline scheduling engine module 702 is used to perform iterative scheduling simulation based on a greedy strategy, based on the priority of each scanning task package and the initial state of each laser, until all scanning task packages are successfully scheduled, and a scheduling sequence containing timing information is obtained.

[0158] The control command generation module 703 is used to generate multi-laser cooperative control commands for each laser based on a scheduling sequence including timing.

[0159] In some alternative implementations, the task decomposition module 701 includes:

[0160] The scanning task package division unit is used to decompose the two-dimensional layered data to be printed into multiple fine-grained scanning task packages according to preset division rules.

[0161] The priority setting unit is used to set a priority for each scan task package according to preset priority setting rules.

[0162] The laser status setting unit is used to create task priority queues for multiple lasers, store scanning task packages into the corresponding laser's task priority queue, initialize the simulation time, and set the simulation status of all lasers to idle state.

[0163] In some optional implementations, the scan task packet partitioning unit includes:

[0164] The scanning task package is divided into sub-units to decompose the two-dimensional layered data to be printed into multiple fine-grained scanning task packages according to at least one of the following: checkerboard division rules, strip division rules along a preset direction, and adaptive division rules based on the geometric features of the part.

[0165] In some alternative implementations, the offline scheduling engine module 702 includes:

[0166] The candidate task package selection unit is used to select the highest priority scanning task package as a candidate task package from the task priority queue of each idle laser at the current simulation time point.

[0167] The conflict detection unit is used to determine whether there is a spatiotemporal geometric conflict between the scan path of the candidate task package during execution and the dynamic influence area of ​​other currently executing scan task packages.

[0168] The recording and waiting unit is used to record scheduling information to the scheduling sequence and update the simulation state of the laser if there is no conflict, and calculate the estimated completion time of the corresponding laser; if there is a conflict, the laser is kept idle; the scheduling information includes laser ID, candidate task package ID and simulation start time.

[0169] The time advance unit is used to calculate the estimated execution time of the scanning task package after all idle lasers have completed the scheduling decision at the current simulation time point. Based on the estimated execution time, it finds the earliest estimated completion time of all lasers currently executing simulation tasks, advances the earliest estimated completion time to the current simulation time point, and resets the simulation state of the corresponding laser to idle to trigger the next round of scheduling decision, until all scanning task packages are successfully scheduled, resulting in a scheduling sequence containing time sequence.

[0170] In some optional implementations, the collision detection unit includes:

[0171] The conflict detection subunit is used to call the dynamic interference prediction model to detect the intersection of the scanning path of the candidate task package during execution with the dynamic influence area of ​​other currently executing scanning task packages. If an intersection exists, it is determined that there is a spatiotemporal geometric conflict; otherwise, there is no spatiotemporal geometric conflict.

[0172] In one alternative implementation, the estimated execution time of the scanning task package is calculated using the following formula:

[0173] Estimated execution time of the scan task package = total length of scan vectors / laser scanning speed.

[0174] In some alternative implementations, the control command generation module 703 includes:

[0175] The sorting unit is used to group tasks by laser ID, forming a task list for each laser, and sorting the task list for each laser in ascending order by start timestamp.

[0176] The instruction generation unit is used to convert each task into a timestamped instruction stream that can be recognized by the specified device based on the sorted task list for each laser. The multi-laser collaborative control instruction is obtained by combining all the timestamped instruction streams. The timestamped instruction stream includes laser ID, instruction execution timestamp, laser power, scanning speed and scanning vector segment information.

[0177] The multi-laser cooperative scanning path planning device provided in this embodiment of the invention can execute the multi-laser cooperative scanning path planning method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments above, and will not be repeated here.

[0178] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0179] The following is a detailed reference. Figure 8 This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 801, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 802 or a program loaded from memory 808 into random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the electronic device. The processor 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0180] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 808 including, for example, magnetic tapes, hard disks, etc.; and communication devices 809. Communication device 809 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0181] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a memory 808, or installed from a ROM 802. When the computer program is executed by the processor 801, it performs the functions defined in the multi-laser cooperative scanning path planning method of the embodiments of the present invention.

[0182] Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0183] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the multi-laser cooperative scanning path planning method shown in the above embodiments is implemented.

[0184] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0185] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A multi-laser coordinated scanning path planning method, characterized in that, The method comprises: In a discrete simulation environment, two-dimensional layered data to be printed is divided into a plurality of fine-grained scanning task packages, and a priority of each scanning task package and an initial state of each laser are set; Based on the priority of each scanning task package and the initial state of each laser, iterative scheduling simulation based on a greedy strategy is performed until all scanning task packages are successfully scheduled, to obtain a scheduling sequence containing timing; Based on the priority of each scanning task package and the initial state of each laser, iterative scheduling simulation based on a greedy strategy is performed until all scanning task packages are successfully scheduled, to obtain a scheduling sequence containing timing, comprising: selecting, at a current simulation time point, a scanning task package with the highest priority from a task priority queue of each idle-state laser as a candidate task package; determining whether a scanning path of the candidate task package during execution has a space-time geometric conflict with a dynamic influence area of another scanning task package being executed; The determination of whether the scanning path of the candidate task package during execution has a space-time geometric conflict with the dynamic influence area of the other scanning task package being executed comprises: calling a dynamic interference prediction model to perform intersection detection on the scanning path of the candidate task package during execution and the dynamic influence area of the other scanning task package being executed, and determining that there is a space-time geometric conflict if there is an intersection, otherwise, there is no space-time geometric conflict; If there is no conflict, scheduling information is recorded to the scheduling sequence, and the simulation state of the laser is updated, and the expected completion time of the corresponding laser is calculated; if there is a conflict, the state of the laser remains idle; the scheduling information comprises a laser ID, a candidate task package ID and a simulation start time; After all idle-state lasers at the current simulation time point complete scheduling decision, the expected execution time of the scanning task package is calculated, the earliest expected completion time of all simulation task lasers being executed is found based on the expected execution time, the earliest expected completion time is advanced to the current simulation time point, and the simulation state of the corresponding laser is reset to idle, to trigger the next round of scheduling decision, until all scanning task packages are successfully scheduled, to obtain a scheduling sequence containing timing; Based on the scheduling sequence containing timing, multi-laser cooperative control instructions of each laser are generated.

2. The method of claim 1, wherein, The two-dimensional layered data to be printed is divided into a plurality of fine-grained scanning task packages, and the priority of each scanning task package and the initial state of each laser are set, comprising: The two-dimensional layered data to be printed is divided into a plurality of fine-grained scanning task packages according to a preset division rule; The priority of each scanning task package is set according to a preset priority setting rule; Task priority queues are respectively created for a plurality of lasers, the scanning task packages are stored in the task priority queues of the corresponding lasers, and the simulation time is initialized and the simulation states of all lasers are set to idle states.

3. The method of claim 2, wherein, The two-dimensional layered data to be printed is divided into a plurality of fine-grained scanning task packages according to a preset division rule, comprising: The two-dimensional layered data to be printed is decomposed into a plurality of fine-grained scanning task packages according to at least one of a chessboard division rule, a strip division rule in a preset direction, and an adaptive division rule based on part geometric features.

4. The method of claim 1, wherein, The predicted execution time of the scanning task package is calculated by the following formula: Predicted execution time of scanning task package = Total length of scanning vector / Laser scanning speed.

5. The method of claim 1, wherein, The multi-laser cooperative control instruction for each laser is generated based on the scheduling sequence containing timing, including: Grouping tasks by laser ID to form a task list for each laser, and sorting the task list for each laser in ascending order of start time stamp; Based on the sorted task list for each laser, converting each task into a timestamped instruction stream recognizable by the specified device, and combining all the timestamped instruction streams to obtain the multi-laser cooperative control instruction; the timestamped instruction stream includes laser ID, instruction execution timestamp, laser power, scanning speed, and scanning vector segment information.

6. A multi-laser coordinated scanning path planning apparatus, characterized by, The device includes: A task decomposition module for decomposing two-dimensional layered data to be printed into a plurality of fine-grained scanning task packages in a discrete simulation environment, and setting a priority of each scanning task package and an initial state of each laser; An offline scheduling engine module for performing iterative scheduling simulation based on a greedy strategy based on the priority of each scanning task package and the initial state of each laser until all scanning task packages are successfully scheduled to obtain a scheduling sequence containing timing; The offline scheduling engine module includes: A candidate task package selection unit for selecting the highest priority scanning task package from the task priority queue of each idle state laser at the current simulation time point as a candidate task package; A conflict detection unit for determining whether the scanning path of the candidate task package during execution has a spatiotemporal geometric conflict with the dynamic influence area of other scanning task packages being executed; The conflict detection unit includes: A conflict detection subunit for calling a dynamic interference prediction model to perform intersection detection between the scanning path of the candidate task package during execution and the dynamic influence area of other scanning task packages being executed, and determining that there is a spatiotemporal geometric conflict if there is an intersection, otherwise, there is no spatiotemporal geometric conflict; A record and wait unit for recording scheduling information to the scheduling sequence and updating the simulation state of the laser if there is no conflict, and calculating the predicted completion time of the corresponding laser; if there is a conflict, the laser remains in an idle state; the scheduling information includes laser ID, candidate task package ID, and simulation start time; A time advancing unit for calculating the predicted execution time of the scanning task package after all idle state lasers at the current simulation time point complete scheduling decisions, finding the earliest predicted completion time of all simulation task lasers being executed based on the predicted execution time, advancing the earliest predicted completion time to the current simulation time point, and resetting the simulation state of the corresponding laser to idle to trigger the next round of scheduling decisions until all scanning task packages are successfully scheduled to obtain a scheduling sequence containing timing. The control instruction generation module is configured to generate the multi-laser cooperative control instruction of each laser based on the scheduling sequence containing the time sequence.

7. An electronic device, comprising: The method comprises the following steps: The memory and the processor are connected in communication with each other, and the memory stores computer instructions.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing a computer to execute the multi-laser cooperative scanning path planning method according to any one of claims 1 to 5.

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