Intelligent aerial 3D printing and spraying system and method based on unmanned aerial vehicle cluster

Abstract

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to an intelligent aerial 3D printing and spraying system and method based on an unmanned aerial vehicle cluster, and the system comprises a spatial three-dimensional laser ranging scanning modeling module for generating a real-size scene model, a three-dimensional positioning network module, and a three-dimensional positioning network composed of a plurality of laser radar arrays. Wherein the laser radar or the wireless positioning beacon array is arranged on a working plane to construct a three-dimensional space coordinate reference system; the printing module is integrated on the unmanned aerial vehicle, compared with traditional high-altitude operation, the construction efficiency is improved, the constraint of tedious procedures such as scaffold building and manual high-altitude operation is thoroughly eliminated, the unmanned aerial vehicle cluster can be rapidly deployed in a short time, and operation tasks such as large-area single-color or full-color spraying, repairing, modeling and printing are efficiently completed with high precision; the project construction period is greatly shortened, the comprehensive construction cost is reduced, the safety construction level is improved, the engineering income is improved, and the construction accident risk is reduced.

Description

Technical Field

[0001] The present invention relates to the field of drone technology, and in particular to an intelligent aerial 3D printing and spraying system and method based on drone clusters. Background Art

[0002] Traditional aerial work relies on scaffolding or hanging baskets, resulting in low efficiency, high costs, high risk, and insufficient manual spraying precision, making it difficult to spray complex patterns or three-dimensional structures. Existing drone spraying systems lack positioning accuracy, with errors typically exceeding 5mm. They are only capable of single-color spraying and cannot meet the requirements of 3D stacking and full-color photo-based painting. They also lack multi-machine coordination and dynamic positioning capabilities, making them difficult to adapt to irregular curved surfaces. Military camouflage simulation relies on prefabricated camouflage nets, which cannot quickly achieve real-time environmental integration. Multi-machine coordination lacks intelligent scheduling algorithms, resulting in limited efficiency gains and making it difficult to meet market development needs.

[0003] Therefore, we propose an intelligent aerial 3D printing and spraying system and method based on drone clusters to solve the above problems. Summary of the Invention

[0004] (1) Technical problems solved In response to the shortcomings of the existing technology, the present invention provides an intelligent aerial 3D printing and spraying system and method based on drone clusters, which solves the problems raised in the above background technology.

[0005] (2) Technical solution

[0006] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solutions: An intelligent aerial 3D printing and spraying system based on drone swarms, comprising: Spatial 3D laser ranging scanning and modeling module: This module includes a drone payload platform, a six-degree-of-freedom active vibration-damping gimbal, and a 3D laser radar or spatial 3D laser scanner. The 3D laser scanner uses the laser ranging principle to measure the time difference between laser emission and reflection. Combining the scanning angle and distance information, it calculates the 3D coordinates of points on the object's surface and generates a high-density point cloud model. After processing this point cloud data, a 1:1 model that is identical to the actual object's dimensions is constructed. Three-dimensional spatial positioning network module: A three-dimensional spatial positioning network composed of multiple laser radar arrays, where the laser radar arrays are arranged on the work surface to build a three-dimensional physical space reference coordinate system for reference coordinates in subsequent printing and spraying operations; Printing module: The printing module integrated on the drone includes a microfluidic printing nozzle and a rapid material switching mechanism; Spraying module: The spraying module integrated on the drone includes microfluidic multi-color nozzles and a material rapid switching mechanism; Distributed control system module: As the control core of the entire system, the distributed control system module includes a drone cluster control module, a three-dimensional scanning modeling system, a distributed computing unit, an image processing unit, an adaptive path planning algorithm and a material property database.

[0007] Furthermore, the microfluidic print head supports the control of printing materials with a particle size in the range of 0.1-500 μm, and performs high-precision material jetting and spraying; The material quick switching mechanism can complete the replacement of different printing materials within 5 seconds; The printing module can detect the printing quality in real time during the flight process, and automatically start the path correction and re-spray fine-tuning program when it detects that the printing error exceeds the set threshold.

[0008] Furthermore, the distributed computing unit is composed of edge computing nodes and cloud collaboration, responsible for distributed processing and intelligent scheduling of printing tasks, realizing efficient collaborative operation of drone clusters; The adaptive path planning algorithm is based on B-spline curves and dynamically optimizes the printing path according to the geometric shape of the work surface and environmental parameters; the material property database stores the surface adhesion parameters of more than 300 substrates, providing material property data support for the print head.

[0009] Furthermore, the positioning network also includes a multi-spectral fusion positioning algorithm and a dynamic coordinate calibration mechanism; the multi-spectral fusion positioning algorithm integrates multiple spectral data such as visible light, thermal imaging and laser ranging; the dynamic coordinate calibration mechanism calibrates and updates the positioning coordinates in real time; In an environment with simple operating requirements, the positioning network also uses multiple positioning QR code tags for spatial positioning identification, establishes a coordinate calibration mechanism, and calibrates and updates the positioning coordinates in real time; In some simple operation requirements, the positioning network also uses multiple positioning QR code tags for spatial positioning identification, establishes a coordinate calibration mechanism, and calibrates and updates the positioning coordinates in real time. Furthermore, the printing module also includes a gas-liquid two-phase flow control module, a self-cleaning and anti-clogging mechanism, and a material viscosity real-time monitoring unit; The gas-liquid two-phase flow control module accurately controls the gas-liquid two-phase flow of the printing material; The self-cleaning and anti-clogging mechanism can automatically clear the nozzle blockage; The material viscosity real-time monitoring unit monitors the viscosity changes of the printing material in real time and automatically adjusts the printing parameters according to the monitoring results.

[0010] Furthermore, the distributed control system module also has a digital twin engine, a multi-machine collaborative algorithm, and a material failure early warning system; The digital twin engine renders the printing progress in real time, generates a virtual digital model of the work surface, and interacts and compares it with the physical entity in real time, enabling visual monitoring and management of the printing process; The multi-machine collaborative algorithm realizes intelligent collaboration and operation between drones by sharing learning models and data among drone clusters; the material failure warning system monitors the working status of the printing nozzle in real time and warns of material failure in advance.

[0011] Furthermore, the drone cluster control module: as the multi-task control core of the entire system, the drone cluster control module adds binding or unbinding of multiple drones to form a cluster formation. The control module automatically allocates or cancels work tasks according to the cluster status. After the drone receives the task, it realizes autonomous printing or spraying in the partition and completes the task in parallel with multiple effects.

[0012] A method for intelligent aerial 3D printing and spraying based on a drone swarm, which is based on the intelligent aerial 3D printing and spraying system based on a drone swarm, comprises the following steps: Establish a mapping relationship library between environmental parameters and printing parameters: Through field measurements and experimental analysis, obtain the mapping relationship between the target three-dimensional spatial size model, substrate surface temperature gradient, atmospheric charged particle concentration, and electromagnetic interference intensity between drone groups and the viscosity, fluidity, and adhesion printing parameters of the printing material, and establish a corresponding database.

[0013] Realizing virtual-real interaction through digital twins: Before printing, the work surface is scanned with high precision using laser scanning and photogrammetry technology to generate a digital twin model of the work surface. During the printing process, the physical printing data is fed back into the digital twin model in real time. Simultaneously, the physical printing process is optimized and adjusted based on the analysis results of the digital twin model, achieving deep integration and interaction between the virtual and real worlds, ensuring that the printed results are consistent with the design model. Print monitoring: During the printing process, sensors are used to monitor the signals generated by the deposition and curing process of the printing material in real time. The printing quality status is analyzed based on the characteristics of the signals, defects and problems in the printing process are discovered in time, and corresponding measures are taken to adjust and optimize.

[0014] Furthermore, before establishing the mapping relationship library between environmental parameters and printing parameters, the method also includes a step of performing non-contact scanning of the work surface, using a UAV-mounted millimeter-wave radar and an RGB-D camera to perform high-precision scanning of the work surface to obtain the three-dimensional geometric shape and surface roughness information of the work surface, providing basic data support for subsequent printing path planning and parameter optimization; The process of realizing virtual-reality interaction through digital twins also includes the step of real-time matching of the mapping relationship between physical coordinates and virtual models. The coordinate information of the physical world is obtained in real time through laser scanning and photogrammetry technology, and is matched and calibrated with the coordinate information in the virtual model to ensure high consistency and synchronization between the digital twin model and the physical entity.

[0015] Furthermore, when the print head is performing a printing operation, the spray pressure, flow rate, and spray angle parameters of the print head are adjusted in real time according to environmental parameters such as wind speed, temperature, and substrate surface roughness, as well as dynamic factors such as coating rheological properties and multi-machine operation status information; When multiple drones work together, the spraying area of ​​the drone cluster is divided and adjusted in real time through a dynamic spraying area division algorithm based on game theory to avoid spraying area conflicts and cross-contamination between drones. At the same time, the electromagnetic field interference early warning mechanism is used to monitor the electromagnetic field interference between drones in real time, and measures are taken in advance to provide early warning and avoidance.

[0016] Furthermore, it also includes fault emergency protocols: Record the operation progress and realize the breakpoint resume function; When strong wind or insufficient power is detected, emergency curing agent is automatically sprayed to achieve instant curing of the material.

[0017] (3) Beneficial effects

[0018] Compared with the existing technology, the present invention provides an intelligent aerial 3D printing and spraying system and method based on drone clusters, which has the following beneficial effects: Compared with traditional high-altitude operations, the construction efficiency has been improved and the constraints of tedious processes such as scaffolding construction and manual high-altitude operations have been completely eliminated. UAV clusters can be quickly deployed in a short period of time and complete large-area monochrome or full-color spraying, repair, modeling, printing and other tasks efficiently and with high precision, greatly shortening the project schedule, reducing the overall construction cost, improving the level of safe construction, increasing project benefits, and reducing the risk of construction accidents.

[0019] The spraying accuracy of complex curved surfaces is improved. Whether it is the complex hyperbolic shape of building facades or the streamlined structure of military equipment, the printing system can accurately fit the surface features and spray materials evenly to ensure clear patterns and firm coatings, creating high-quality appearance and functional performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Schematic diagram of the control system of the present invention; Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] like Figure 1 As shown, an embodiment of the present invention proposes an intelligent aerial 3D printing and spraying system based on a drone cluster, comprising: Spatial 3D laser ranging scanning and modeling module: This module is used to generate a real-size scene model and includes a drone payload platform, a six-degree-of-freedom active vibration reduction gimbal, a 3D laser radar, or a 3D laser scanner that builds space. The 3D laser scanner uses the laser ranging principle to measure the time difference between laser emission and reflection. Combining the scanning angle and distance information, it calculates the 3D coordinates of points on the object's surface and generates a high-density point cloud model. After processing this point cloud data, a 1:1 model that is completely consistent with the actual object size is constructed. The 3D spatial positioning network module is composed of multiple LiDAR arrays, which are arranged on the work surface to construct a 3D solid space reference coordinate system for subsequent printing and spraying operations. The LiDAR arrays can also be arrayed with wireless positioning beacons or QR code pattern beacons. The 3D spatial positioning network module is used for high-precision spatial scanning and positioning of the work area. Laser anchor points are used to provide high-precision reference positioning signals to ensure the stability and security of the positioning network. This positioning network can achieve real-time dynamic positioning of drone clusters in 3D space with a positioning accuracy of 0.1mm, meeting the positioning requirements of high-precision printing and spraying operations on complex curved surfaces.

[0023] A lidar array, equipped with anti-interference coding, is deployed on the work surface to effectively resist external interference, ensuring the stability and accuracy of the positioning signal. The drone-mounted multispectral sensor integrates multiple technologies, including visible light, thermal imaging, and laser ranging, to achieve comprehensive perception of the work environment and provide rich data support for precise positioning. The surface acoustic wave positioning module is primarily used for the precise positioning of metal substrates, effectively eliminating the interference problem caused by metal materials on traditional positioning methods and further improving positioning accuracy.

[0024] Printing Module: Integrated into the drone, the printing module includes a microfluidic print head and a rapid material switching mechanism. The six-degree-of-freedom (DOF) active vibration-damping gimbal effectively suppresses vibration during flight, ensuring print head stability, with a vibration suppression rate exceeding 90%. The six-degree-of-freedom (DOF) active vibration-damping gimbal suppresses vibration by 90% or more, significantly reducing the impact of flight vibration on print quality, ensuring clear printed patterns and stable three-dimensional structures. The microfluidic print head precisely controls particle sizes from 0.1 to 500 μm, meeting printing requirements for diverse materials and precision requirements, accurately rendering everything from subtle textures to larger structural units. The rapid material switching mechanism allows for switching between different materials in under 5 seconds, significantly improving printing efficiency. This is particularly advantageous in multi-material composite printing operations, enabling seamless material switching and the completion of complex printing tasks in one go.

[0025] Distributed Control System Module: Serving as the control core of the entire system, the distributed control system module includes a drone cluster control module, a 3D scanning modeling system, a distributed computing unit, an image processing unit, an adaptive path planning algorithm, and a material property database. A digital twin engine renders the printing progress in real time, constructing a virtual model synchronized with the actual printing job. This model allows staff to intuitively monitor the printing status, promptly identify potential problems, and remotely intervene, enabling refined management of the printing process. A multi-machine collaborative algorithm enables the drone cluster to collaborate efficiently, dynamically allocating printing areas based on each drone's mission performance, battery status, and location information. This optimizes flight paths, avoids collisions and interference, and fully leverages the advantages of the cluster, significantly improving overall printing efficiency. The material failure warning system uses detection technology to monitor the printhead status in real time. If issues such as material blockage, abnormal flow, and viscosity changes that could lead to printing failure are detected, an immediate warning signal is issued, alerting the operator to timely maintenance and treatment, effectively reducing material waste and operational risks, and ensuring the continuity and reliability of printing tasks.

[0026] Drone cluster control module: As the multi-task control core of the entire system, the drone cluster control module adds binding or unbinding of multiple drones to form a cluster formation. The control module automatically assigns or cancels work tasks according to the cluster status. After the drone receives the task, it realizes autonomous printing or spraying in partitions and completes the task in parallel with multiple effects.

[0027] Path: First, 3D scan the target to generate a 1:1 model, then perform image and model matching processing, and finally perform drone 3D printing or spraying operations.

[0028] like Figure 1As shown, in some embodiments, the microfluidic print head supports precise control of printing materials with a particle size range of 0.1-500μm, and performs high-precision material jetting and spraying; the material rapid switching mechanism can complete the replacement of different printing materials within 5 seconds to meet the needs of multi-material printing, and the printing module can detect the printing quality in real time during flight. When it is detected that the printing error exceeds the set threshold (such as 0.3mm), the path correction and re-spray fine-tuning program is automatically started to ensure printing quality.

[0029] like Figure 1 As shown, in some embodiments, the distributed computing unit is composed of edge computing nodes and cloud collaboration, which is responsible for distributed processing and intelligent scheduling of printing tasks to achieve efficient collaborative operation of drone clusters; the adaptive path planning algorithm is based on B-spline curves, which can dynamically optimize the printing path according to the geometric shape of the working surface and environmental parameters, and trigger electromagnetic field interference warning to improve printing efficiency and quality; the material property database stores the surface adhesion parameters of 300+ substrates, providing material property data support for the print head to ensure good adhesion of the printing material to the substrate.

[0030] like Figure 1 As shown, in some embodiments, the positioning network further includes a multi-spectral fusion positioning algorithm and a dynamic coordinate calibration mechanism; the multi-spectral fusion positioning algorithm fuses multiple spectral data such as visible light, thermal imaging, and laser ranging to improve the accuracy and robustness of positioning; the dynamic coordinate calibration mechanism calibrates and updates the positioning coordinates in real time to ensure that the positioning accuracy is not affected by environmental changes.

[0031] like Figure 1 As shown, in some embodiments, the printing module also includes a gas-liquid two-phase flow control module, a self-cleaning anti-clogging mechanism, and a material viscosity real-time monitoring unit; the gas-liquid two-phase flow control module accurately controls the gas-liquid two-phase flow of the printing material to ensure uniform injection of the material; the self-cleaning anti-clogging mechanism can automatically clear the nozzle blockage and keep the nozzle unobstructed; the material viscosity real-time monitoring unit monitors the viscosity changes of the printing material in real time, and automatically adjusts the printing parameters according to the monitoring results to ensure printing quality.

[0032] like Figure 1As shown, in some embodiments, the distributed control system also has a digital twin engine, a multi-machine collaborative algorithm, and a material failure warning system; the digital twin engine renders the printing progress in real time, generates a virtual digital model of the work surface, and interacts and compares with the physical entity in real time to achieve visual monitoring and management of the printing process; the multi-machine collaborative algorithm achieves intelligent collaboration and efficient operation between drones by sharing learning models and data among drone clusters; the material failure warning system monitors the working status of the print head in real time, and warns of material failure in advance to ensure the stability and reliability of the printing process.

[0033] A method for intelligent aerial 3D printing and spraying based on a drone swarm, which is based on the intelligent aerial 3D printing and spraying system based on a drone swarm, comprises the following steps: Establish a mapping relationship library between environmental parameters and printing parameters: Through field measurements and experimental analysis, obtain the mapping relationship between the target three-dimensional spatial size model, substrate surface temperature gradient, atmospheric charged particle concentration, and electromagnetic interference intensity between drone groups and the viscosity, fluidity, and adhesion printing parameters of the printing material, and establish a corresponding database to provide data support for parameter optimization during the printing process.

[0034] Realizing virtual-real interaction through digital twins: Before printing, the work surface is scanned with high precision using laser scanning and photogrammetry technology to generate a digital twin model of the work surface. During the printing process, the physical printing data is fed back into the digital twin model in real time. Simultaneously, the physical printing process is optimized and adjusted based on the analysis results of the digital twin model, achieving deep integration and interaction between the virtual and real worlds, ensuring that the printed results are highly consistent with the design model. Print monitoring: During the printing process, sensors are used to monitor the signals generated by the deposition and curing process of the printing material in real time. The printing quality status is analyzed based on the characteristics of the signals, defects and problems in the printing process are discovered in time, and corresponding measures are taken to adjust and optimize them, thereby improving the stability and reliability of the printing quality.

[0035] like Figure 2 As shown, in some embodiments, before establishing the mapping relationship library between environmental parameters and printing parameters, a step of non-contact scanning of the work surface is also included, using a UAV-borne millimeter-wave radar and an RGB-D camera to perform high-precision scanning of the work surface to obtain the three-dimensional geometric shape and surface roughness information of the work surface, providing basic data support for subsequent printing path planning and parameter optimization; The process of realizing virtual-reality interaction through digital twins also includes the step of real-time matching of the mapping relationship between physical coordinates and virtual models. The coordinate information of the physical world is obtained in real time through laser scanning and photogrammetry technology, and is matched and calibrated with the coordinate information in the virtual model to ensure high consistency and synchronization between the digital twin model and the physical entity.

[0036] like Figure 2 As shown, in some embodiments, the print head adjusts the spray pressure, flow rate, and spray angle parameters of the print head in real time during printing according to environmental parameters such as wind speed, temperature, and substrate surface roughness, as well as dynamic factors such as coating rheological properties and multi-machine operation status information, to ensure uniform deposition and good adhesion of the printing material under different environmental conditions, thereby improving printing quality and efficiency; When multiple drones are working together, the spraying area of ​​the drone cluster is divided and adjusted in real time through a dynamic spraying area division algorithm based on game theory to avoid spraying area conflicts and cross-contamination between drones. At the same time, the electromagnetic field interference early warning mechanism is used to monitor the electromagnetic field interference between drones in real time, and measures are taken in advance for early warning and avoidance to ensure the safety and stability of multi-machine collaborative operations.

[0037] It also includes a fault emergency protocol: the operation progress is recorded through the blockchain to achieve the function of resume spraying at the breakpoint; When strong wind or insufficient power is detected, emergency curing agent is automatically sprayed to achieve instant curing of the material.

[0038] It also includes an online monitoring print quality module that triggers an automatic re-spraying mechanism when a printhead anomaly or coating error > 0.3mm is detected.

[0039] Specifically, through advanced curvature analysis algorithms, the curvature changes of the working surface are calculated in real time, and the printing path spacing is automatically adjusted to ensure that the printed material is evenly distributed. Whether it is a gentle arc surface or a steep curved surface, it can maintain high-quality printing effects and avoid material accumulation or omissions caused by improper path spacing; the real-time surface defect compensation algorithm based on deep learning can quickly identify and analyze surface defects such as cracks, pits, and bumps on the working surface, automatically adjust printing parameters, and accurately repair or compensate for defective areas, effectively improving the surface flatness and overall performance of the printed product, just like "tailoring" the working surface, making it easy to handle complex curved surface printing operations.

[0040] Specifically, a wind speed-viscosity coupling control model is constructed to precisely regulate the viscosity and fluidity of the printed material to adapt it to different wind speed environments. In strong winds, the material viscosity is increased to enhance its wind resistance and prevent the material from being blown away. In light or no wind conditions, the viscosity is appropriately reduced to ensure that the material is easy to spread and shape, achieving a "wind-adapted" printing effect. The color calibration algorithm under the influence of sunlight angle comprehensively considers factors such as the sun's position, light intensity, and the material of the work surface, and adjusts the hue, saturation, and brightness of the printed color in real time to ensure the color consistency and accuracy of the printed pattern under different sunlight conditions. This makes the printed work shine in the sun, with vivid and lifelike colors, like a self-adjusting "chameleon" that perfectly blends into various lighting environments.

[0041] Specifically, the multi-spectral dynamic matching database covers spectral feature data from multiple bands, including visible light, infrared, and radar. It can adjust the spectral reflectivity and emissivity of printed materials in real time based on spectral changes in the surrounding environment, enabling military equipment to achieve a high degree of camouflage under various reconnaissance methods. Whether observed by the naked eye or detected by advanced sensors, it can be cleverly concealed, achieving "full-band stealth." The radar wave phase modulation coating spraying process precisely controls the coating's thickness, composition, and structure to phase modulate radar waves, causing interference and confusion in the reflected signals. This effectively reduces the radar cross-section (RCS) of military targets, making it difficult for enemy radars to capture accurate target information. This acts like a "cloak" of invisibility for military equipment, allowing it to operate silently on the battlefield.

[0042] Specifically, the tracking system keeps detailed records of the entire printing process, including key information such as drone flight paths, printing parameter settings, material usage, and operator instructions. All data is stored in the blockchain's distributed ledger, making it tamper-proof and traceable. In the event of quality issues, safety incidents, or operational disputes, the source of the problem can be quickly and accurately located, and responsibility can be clearly identified, providing a strong basis for subsequent improvement measures and accountability. It is like putting a "safety helmet" on the printing operation, protecting it throughout the entire process. The instant material curing technology for emergency situations can instantly trigger the material curing reaction when encountering emergencies such as strong winds, rain, and equipment failures that may endanger operational safety or printing quality. This allows the uncured printed material to quickly harden, fixing the current printing results and preventing the material from flowing, deforming, or being damaged. This buys valuable time for subsequent emergency response and recovery work, effectively reducing losses and risks, and is a "first aid artifact" for responding to emergencies.

[0043] Example 1: Repair of irregular building facades: 16 laser anchor points are arranged around the building facade. These anchor points act as precise "space locators", building a high-precision three-dimensional coordinate framework for the entire operation area, ensuring that the drone can accurately locate its position and posture, providing a solid spatial reference for subsequent repair work.

[0044] A swarm of four drones, like four nimble bees, employed a spiral scanning path, scanning and modeling the building's facade in all directions. Working closely together and sharing data in real time, they rapidly acquired detailed information, including the facade's three-dimensional form and crack distribution, providing a precise basis for developing a repair plan.

[0045] AI automatically identifies cracks and generates repair plans. Relying on deep learning algorithms, it intelligently analyzes the shape, size, direction and other characteristics of the cracks. Combining the principles of building structural mechanics and material performance data, it develops the optimal repair path, material usage and printing process parameters. Like an experienced "building doctor", it quickly prescribes an accurate "repair prescription."

[0046] During the printing process, the digital twin model is compared in real time, and automatic re-spraying is performed if the error exceeds 0.3mm. The digital twin model acts as a "smart mirror," mapping the actual printing progress against the preset model in real time. If an error exceeds the standard, the system automatically triggers a re-spraying mechanism, ensuring the restored building facade is smooth and flat, restoring its original strength and beauty, and giving it a revitalized look.

[0047] Example 2: Dynamic Camouflage for Field Equipment: Using a phase-change material with a flexibly adjustable melting point between 35°C and 50°C, this material possesses a "temperature-changing superpower," capable of controlled transitions between solid and liquid states in response to ambient temperature fluctuations. This provides excellent camouflage in diverse climates, perfectly adapting to both scorching deserts and freezing mountainous terrain.

[0048] The optimal spraying timing is calculated based on the satellite's overhead pass. Through precise celestial motion models and analysis of battlefield environmental parameters, the optimal camouflage time window is planned in advance. Just before the satellite passes overhead, the drone swarm rapidly initiates the spraying operation, ensuring the equipment is optimally camouflaged during satellite reconnaissance. This meticulously planned "camouflage ambush" ensures the enemy satellite returns empty-handed. Within two hours of application, the infrared signature automatically changes with the ambient temperature. This camouflage coating acts as an "intelligent skin" for the equipment, sensing the ambient temperature in real time and automatically adjusting its infrared radiation characteristics to blend in with the infrared signature of the surrounding environment, rendering the equipment invisible to infrared reconnaissance equipment and significantly enhancing the survivability and combat effectiveness of field equipment.

[0049] The application scenarios are as follows: Field Armaments: Real-time spraying for outdoor combat, camouflage coating that quickly blends in with the environment, and satellite-undetectable detection. In vast outdoor battlefields, whether forests, deserts, or wilderness, drone swarms can quickly coat military equipment with camouflage patterns that blend seamlessly with the surrounding environment, making them difficult to detect during satellite reconnaissance and enemy ground searches. Spraying materials containing metal powders quickly reduce thermal infrared radiation and thermal imaging clarity, effectively evading enemy infrared thermal imagers and giving military equipment excellent stealth capabilities in the thermal perception dimension. Colored foam extrusion materials enable rapid generation of 3D physical simulation props on the ground, such as simulated military facilities and terrain, for use in tactical drills and battlefield deception. Individual camouflage coatings can also be applied in real time, providing soldiers with personalized camouflage.

[0050] Engineering Maintenance: Suitable for large-scale aerial color painting of elevated bridge piers and bridge tunnels on highways and high-speed railways. Creative painting of these large-scale transportation infrastructure not only promotes cultural communication and advertising, but also enhances the aesthetics of the infrastructure and creates unique landscapes. Wall inspection, repair, renovation, and painting are also available for office buildings, communities, factories, scenic areas, and more. Cracks, peeling, and other defects can be quickly located, accurately repaired, and aesthetically pleasingly sprayed as needed, extending the service life of building facades and enhancing their overall image. Color painting of fences and guardrails along urban roadsides and overpasses adds vibrant color to the city streetscape, contributing to urban beautification projects while improving the recognition and durability of public facilities.

[0051] Children's Hobby: It can be used to DIY castles, bridges, and other miniature toys outdoors. It stimulates children's imagination and creativity, allowing them to experience the joy of architecture and artistic creation through play. DIY model design and rapid generation of 3D model stacking operations provide model enthusiasts with a convenient and efficient production method. From conception to finished product, one-click printing is achieved, promoting the popularization and development of the creative cultural industry.

[0052] Aerial 3D printing project scenarios: (1) Low-altitude operation: printing, spraying, and stacking can be performed within 300 meters from the ground; (2) Working principle: First, multiple laser emission points are arranged to establish anchor reference coordinate points for ranging. Then, a drone payload with a steady-state cloud platform is used to perform 3D high-precision scanning of the target site, perform 3D modeling, and establish the aerial position coordinate information of the target to be printed. The image or model file to be printed is processed through a dedicated aerial printing software to generate various information data of the printing target (aerial pixel position information, pixel color information, parallel operation information, etc.), and then output to the intelligent four-color print head (or spray gun). The drone carries a four-color print head (or spray gun) to spray and print accurately in real time. It can operate as a single machine or in parallel with multiple machines.

[0053] (3) Printing scenario: The printing surface can be a large wall plane, cylindrical surface, special-shaped surface, or a three-dimensional surface with irregular height.

[0054] (4) Printing and spraying: It can print multi-color camouflage patterns, print color patterns, 3D solid printing, and 3D modeling stacking.

[0055] (4) Application scenarios: (a) Large-scale aerial color spray painting of viaduct piers and bridge tunnels of various highways and high-speed railways; (b) Wall inspection, repair, renovation, spraying, etc. of office buildings, communities, factories, scenic spots, etc.; (c) Color spraying of fences and guardrails along urban roads and overpasses; (d) Especially for outdoor field operations, real-time spraying, camouflage painting that quickly blends in with the environment, and satellite-undetected reconnaissance.

[0056] (e) Using spray materials with metal powder can quickly reduce thermal infrared radiation and reduce thermal imaging clarity (f) The use of colored foam extrusion materials can achieve rapid 3D solid modeling of the ground.

[0057] (g) Rapidly generate 3D modeling stacking operations based on the characteristics of the stacking model.

[0058] (5) Technical framework: Combining low-altitude UAV technology, steady-state cloud platform technology, AI attitude algorithm, graphic model processing software, laser ranging and positioning technology, 3D spray printing head, etc.

[0059] (6) Social Value: This technology significantly reduces the construction difficulty, construction cost, and risk factor of high-altitude spraying operations. It can achieve uninterrupted operation 24 hours a day, greatly improving the completion efficiency of spraying operations, achieving the goals of cost reduction, efficiency improvement, and safe construction. It also has a wide range of application scenarios, adding cultural and creative value and environmental friendliness to society.

[0060] To sum up, compared with the traditional high-altitude operation construction efficiency improvement, completely get rid of the constraints of tedious processes such as scaffolding construction and manual high-altitude operation, drone clusters can be quickly deployed in a short time, and efficiently and accurately complete large-area monochrome or full-color spraying, repair, modeling, printing and other operations, greatly shortening the project schedule, reducing the overall construction cost, improving the level of safe construction, increasing project benefits, and reducing the risk of construction accidents.

[0061] The spraying accuracy of complex curved surfaces is improved. Whether it is the complex hyperbolic shape of building facades or the streamlined structure of military equipment, the printing system can accurately fit the surface features and spray materials evenly to ensure clear patterns and firm coatings, creating high-quality appearance and functional performance.

[0062] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. An intelligent aerial 3D printing and spraying system based on drone clusters, characterized by: include: Spatial 3D laser ranging scanning and modeling module: This module includes a drone payload platform, a six-degree-of-freedom active vibration-damping gimbal, and a 3D laser radar or spatial 3D laser scanner. The 3D laser scanner uses the laser ranging principle to measure the time difference between laser emission and reflection. Combining the scanning angle and distance information, it calculates the 3D coordinates of points on the object's surface and generates a high-density point cloud model. After processing this point cloud data, a 1:1 model that is identical to the actual object's dimensions is constructed. Three-dimensional spatial positioning network module: A three-dimensional spatial positioning network composed of multiple laser radar arrays, where the laser radar arrays are arranged on the work surface to build a three-dimensional physical space reference coordinate system for reference coordinates in subsequent printing and spraying operations; Printing module: The printing module integrated on the drone includes a microfluidic printing nozzle and a rapid material switching mechanism; Spraying module: The spraying module integrated on the drone includes microfluidic multi-color nozzles and a material rapid switching mechanism; Distributed control system module: As the control core of the entire system, the distributed control system module includes a drone cluster control module, a three-dimensional scanning modeling system, a distributed computing unit, an image processing unit, an adaptive path planning algorithm and a material property database.

2. The intelligent aerial 3D printing and spraying system based on drone swarms according to claim 1, characterized in that: The microfluidic print head supports the control of printing materials with particle sizes ranging from 0.1 to 500 μm, and performs high-precision material jetting and spraying; The material quick switching mechanism can complete the replacement of different printing materials within 5 seconds; The printing module can detect the printing quality in real time during flight, and automatically start the path correction and re-spray fine-tuning program when it detects that the printing error exceeds the set threshold.

3. The intelligent aerial 3D printing and spraying system based on drone swarms according to claim 1, characterized in that: The distributed computing unit is composed of edge computing nodes and cloud collaboration, responsible for distributed processing and intelligent scheduling of printing tasks, realizing efficient collaborative operation of drone clusters; The adaptive path planning algorithm is based on B-spline curves and dynamically optimizes the printing path according to the geometric shape of the work surface and environmental parameters; the material property database stores the surface adhesion parameters of more than 300 substrates, providing material property data support for the print head.

4. The intelligent aerial 3D printing and spraying system based on drone swarms according to claim 1, characterized in that: The positioning network also includes a multi-spectral fusion positioning algorithm and a dynamic coordinate calibration mechanism; the multi-spectral fusion positioning algorithm integrates multiple spectral data such as visible light, thermal imaging and laser ranging; the dynamic coordinate calibration mechanism calibrates and updates the positioning coordinates in real time; In an environment with simple operating requirements, the positioning network also uses multiple positioning QR code tags for spatial positioning identification, establishes a coordinate calibration mechanism, and calibrates and updates the positioning coordinates in real time.

5. The intelligent aerial 3D printing and spraying system based on drone swarms according to claim 1, characterized in that: The printing module also includes a gas-liquid two-phase flow control module, a self-cleaning anti-blocking mechanism, and a material viscosity real-time monitoring unit; The gas-liquid two-phase flow control module accurately controls the gas-liquid two-phase flow of the printing material; The self-cleaning and anti-clogging mechanism can automatically clear the nozzle blockage; The material viscosity real-time monitoring unit monitors the viscosity changes of the printing material in real time and automatically adjusts the printing parameters according to the monitoring results.

6. The intelligent aerial 3D printing and spraying system based on drone swarms according to claim 1, characterized in that: The distributed control system module also has a digital twin engine, a multi-machine collaborative algorithm, and a material failure early warning system; The digital twin engine renders the printing progress in real time, generates a virtual digital model of the work surface, and interacts and compares it with the physical entity in real time, enabling visual monitoring and management of the printing process; The multi-machine collaborative algorithm enables intelligent collaboration and operation between drones by sharing learning models and data among drone clusters; The material failure warning system monitors the working status of the print head in real time and provides early warning of material failure.

7. The intelligent aerial 3D printing and spraying system based on drone swarms according to claim 1, characterized in that: The drone cluster control module: As the multi-task control core of the entire system, the drone cluster control module adds binding or unbinding of multiple drones to form a cluster formation. The control module automatically allocates or cancels work tasks according to the cluster status. After the drone receives the task, it realizes autonomous printing or spraying in the partition and completes the task in parallel with multiple effects.

8. A method for intelligent aerial 3D printing and spraying based on drone swarms, the method being based on the intelligent aerial 3D printing and spraying system based on drone swarms according to any one of claims 1 to 7, characterized in that: The following steps are involved: Establish a mapping relationship database between environmental parameters and printing parameters: Through field measurements and experimental analysis, obtain the mapping relationship between the target 3D spatial dimension model, substrate surface temperature gradient, atmospheric charged particle concentration, and electromagnetic interference intensity between drone groups and the viscosity, fluidity, and adhesion printing parameters of the printing material, and establish a corresponding database; Realizing virtual-real interaction through digital twins: Before printing, the work surface is scanned with high precision using laser scanning and photogrammetry technology to generate a digital twin model of the work surface. During the printing process, the physical printing data is fed back into the digital twin model in real time. Simultaneously, the physical printing process is optimized and adjusted based on the analysis results of the digital twin model, achieving deep integration and interaction between the virtual and real worlds, ensuring that the printed results are consistent with the design model. Print monitoring: During the printing process, sensors are used to monitor the signals generated by the deposition and curing process of the printing material in real time. The printing quality status is analyzed based on the characteristics of the signals, defects and problems in the printing process are discovered in time, and corresponding measures are taken to make adjustments.

9. The intelligent aerial 3D printing and spraying method based on drone swarms according to claim 8, characterized in that: Before establishing the mapping relationship library between environmental parameters and printing parameters, a non-contact scanning step is also included. The millimeter-wave radar and RGB-D camera on the drone are used to perform high-precision scanning of the work surface to obtain the three-dimensional geometric shape and surface roughness information of the work surface, providing basic data support for subsequent printing path planning and parameter optimization. The process of realizing virtual-reality interaction through digital twins also includes the step of real-time matching of the mapping relationship between physical coordinates and virtual models. The coordinate information of the physical world is obtained in real time through laser scanning and photogrammetry technology, and is matched and calibrated with the coordinate information in the virtual model to ensure high consistency and synchronization between the digital twin model and the physical entity.

10. The intelligent aerial 3D printing and spraying method based on drone swarms according to claim 8, characterized in that: When the print head is performing a printing operation, the spray pressure, flow rate, and spray angle parameters of the print head are adjusted in real time according to environmental parameters such as wind speed, temperature, and substrate surface roughness, as well as dynamic factors such as coating rheological properties and multi-machine operation status information; When multiple drones work together, the spraying area of ​​the drone cluster is divided and adjusted in real time through a dynamic spraying area division algorithm based on game theory to avoid spraying area conflicts and cross-contamination between drones. At the same time, the electromagnetic field interference early warning mechanism is used to monitor the electromagnetic field interference between drones in real time, and measures are taken in advance to provide early warning and avoidance.

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