Method, device and equipment for generating aerial light effect based on unmanned aerial vehicle cluster and medium

Abstract

The application provides a method and device for generating aerial light effects based on a UAV cluster, equipment and a medium. The method comprises the following steps: analyzing and space-time modeling a preset light effect script to generate a space-time task graph; based on the space-time task graph, performing task allocation and trajectory generation on the UAV cluster to obtain a four-dimensional control sequence of each UAV; and based on the four-dimensional control sequence, controlling the UAV cluster to perform corresponding flight, laser projection and mirror reflection actions to generate dynamic light effects. Compared with the prior art, the application can realize the effects of active projection, directional reflection, multiple reflection and dynamic light path reconstruction of laser in the air, so as to improve the visual performance of the UAV cluster performance.

Description

Technical Field

[0001] This invention relates to the field of drone swarm performance technology, specifically to a method, apparatus, equipment, and medium for generating aerial light effects based on drone swarms. Background Technology

[0002] With the integration of technology and artistic performance, swarm drone shows have become an important visual presentation method in large-scale cultural tourism night tours, sports event openings, concerts, and other scenarios. Traditional swarm drone shows mainly involve mounting LED light arrays on the drones, arranging static or simple dynamic graphics, text, or patterns in the air through precise swarm flight control. The working principle involves pre-programming the flight trajectory and lighting status (such as color and brightness) of each drone. During the performance, the drone swarm acts as a whole, creating visual effects through changes in spatial position and combinations of the on / off states of individual light sources. This technology has been widely applied to various light shows and celebratory events.

[0003] However, the traditional visual performance of swarm drone shows is limited by LED dot matrix, which can only generate discrete light dot patterns and has a single dimension of light effect, resulting in insufficient visual expressiveness of swarm drone performances. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, equipment and medium for generating aerial light effects based on drone swarms, which can realize the effects of active projection, directional reflection, multiple reflection and dynamic optical path reconstruction of laser in the air, so as to improve the visual expressiveness of drone swarm performances.

[0005] In a first aspect, the present invention provides a method for generating aerial light effects based on a drone swarm, comprising:

[0006] The preset lighting effect script is analyzed and spatiotemporally modeled to generate a spatiotemporal mission map;

[0007] Based on the spatiotemporal task map, task allocation and trajectory generation are performed on the UAV swarm to obtain the four-dimensional control sequence of each UAV.

[0008] The four-dimensional control sequence controls the drone cluster to perform corresponding flight, laser projection, and mirror reflection actions to generate dynamic light effects; wherein, the drone includes a gimbal and a reflective mirror, and the gimbal is equipped with a laser.

[0009] According to one embodiment of the present invention, the step of parsing and spatiotemporally modeling a preset lighting effect script to generate a spatiotemporal mission map includes: calling a ray tracing engine to simulate the reverse ray propagation of the target dynamic lighting effects in the lighting effect script, initially generating a beam path and an initial set of positions and attitudes of the UAV cluster; constructing an optimization problem based on kinematic and energy consumption models, with the goal of minimizing the overall maneuvering energy consumption of the cluster and the theoretical optical path error; solving the initial position and attitude set using an iterative optimization algorithm, dynamically adjusting the mission timing and spatial layout of each UAV, and outputting the optimized spatiotemporal mission map.

[0010] According to one embodiment of the present invention, the step of allocating tasks and generating trajectories for a UAV swarm based on the spatiotemporal task map to obtain a four-dimensional control sequence for each UAV includes: parsing the spatiotemporal task map; dynamically allocating tasks to eligible UAV nodes according to the spatiotemporal attributes, hardware resource requirements, and communication topology between UAVs; for each UAV assigned a task, extracting discrete key state frames containing position and attitude information from its corresponding task timeline; using a spline curve fitting algorithm to interpolate adjacent key state frames in three-dimensional space and time dimensions to generate flight trajectory curves and fuselage attitude change curves; and aligning and encapsulating the flight trajectory curves, fuselage attitude change curves, and corresponding laser emission commands and gimbal pointing commands in time sequence to form the four-dimensional control sequence.

[0011] According to one embodiment of the present invention, the step of controlling the UAV cluster to perform corresponding flight, laser projection, and specular reflection actions based on the four-dimensional control sequence to generate dynamic light effects includes: after the four-dimensional control sequence is generated and before it is issued, performing virtual optical path pre-simulation on each laser emission command contained therein, and determining whether its beam path intersects with a preset three-dimensional model of a geographical no-fly zone; if there is a spatial intersection, it is determined that there is a risk of the beam illuminating the no-fly zone, and the emission power of the laser emission command is automatically reduced to a safe level or marked as canceled, and the scheduling system is notified to make corresponding task adjustments; during the execution of the laser emission command, the flight stability data of the executing UAV is monitored in real time, and if the detection exceeds the safety threshold, the power output of the UAV laser is cut off through a hardware interrupt signal.

[0012] According to one embodiment of the present invention, the step of controlling a cluster of drones to perform corresponding flight, laser projection, and specular reflection actions based on the four-dimensional control sequence to generate dynamic light effects includes: controlling at least three drones to form a chain-like reflection light path, wherein the at least three drones include a first drone as an initial light source, a second drone as a primary reflector, and a third drone as a secondary reflector; controlling the first drone to activate its own laser according to the four-dimensional control sequence and emit a first laser beam in a predetermined spatial direction; controlling the second drone to adjust the orientation of the reflector on its fuselage in real time so that the first laser beam is incident on the reflector of the second drone; based on the law of specular reflection, directing the incident first laser beam to the third drone through the reflector of the second drone; controlling the third drone to perform a secondary reflection using the same principle to guide the first laser beam to a target area or other drones, thereby realizing the continuous transmission and direction reconstruction of the laser beam in a dynamic reflection chain composed of multiple drones to generate dynamic light effects.

[0013] According to one embodiment of the present invention, the step of controlling the UAV cluster to perform corresponding flight, laser projection, and specular reflection actions based on the four-dimensional control sequence to generate dynamic light effects includes: during the generation of dynamic light effects, continuously receiving real-time status telemetry data transmitted back by each UAV via a wireless data link, wherein the status telemetry data includes the UAV's positioning coordinates, real-time attitude angle, actual gimbal angle, and laser operating parameters; based on the transmitted status telemetry data, combined with the expected optical path model in the spatiotemporal mission map, calculating in real-time the positional deviation and directional deviation between the currently formed aerial beam and the expected beam; determining whether the positional deviation and directional deviation exceed preset position error tolerance thresholds and directional error tolerance thresholds, respectively; if the positional deviation and directional deviation exceed the preset position error tolerance thresholds and directional error tolerance thresholds, generating a local fine-tuning command and issuing it for execution through a real-time command channel, wherein the local fine-tuning command is used to adjust the gimbal pointing angle or local tilt angle of the mirror of the corresponding UAV to compensate for the positional deviation and directional deviation.

[0014] According to one embodiment of the present invention, the method further includes: maintaining and updating in real time a safe area database containing a three-dimensional geofence, dynamic obstacle locations, and a real-time crowd distribution heatmap during the generation of dynamic light effects; predicting the complete three-dimensional spatial irradiation path of the laser beam corresponding to each laser emission command and its final landing area before each laser emission command is generated and during the duration of the laser beam; performing real-time collision detection and human eye safety level assessment on the predicted irradiation path and landing area data with the safe area database; and dynamically deciding and executing at least one of the following safety intervention operations based on the assessment results: laser power graded control, emergency beam path redirection, or cutting off laser output. The present invention also provides a safety intervention operation, and all safety events are recorded in the audit log.

[0015] The present invention also provides an aerial light effect generation device based on a drone swarm, comprising:

[0016] The Light Effect Script Parsing and Spatiotemporal Modeling module is used to parse and spatiotemporally model the preset light effect scripts to generate a spatiotemporal task map.

[0017] The task allocation and trajectory generation module is used to allocate tasks and generate trajectories for the UAV cluster based on the spatiotemporal task map, so as to obtain the four-dimensional control sequence of each UAV.

[0018] The real-time synchronization and execution module is used to control the UAV cluster to perform corresponding flight, laser projection and mirror reflection actions based on the four-dimensional control sequence to generate dynamic light effects; wherein, the UAV includes a gimbal and a reflective mirror, and the gimbal is equipped with a laser.

[0019] Thirdly, the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the aerial light effect generation method based on UAV swarms described above.

[0020] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the aerial light effect generation method based on UAV swarms described above.

[0021] The present invention produces at least the following beneficial effects:

[0022] This invention transforms the traditional discrete light point generation mode based on LED dot arrays into a continuous light path construction mode based on the synergy of laser projection and specular reflection. This method allows a single laser beam to be reflected by a drone equipped with a mirror, forming a visible beam path in the air. Through the coordinated positions and attitudes of multiple drones, the laser beam path can be dynamically spliced ​​and reused to generate continuous beams, dynamic light pillars, and even three-dimensional light structures. This improves the visual expressiveness of drone swarm performances while requiring fewer laser-equipped drones per unit airspace. Compared to the traditional dot array lighting effects of existing technologies, this invention enhances spatial light and shadow density and expressiveness, while also reducing system hardware size and energy consumption.

[0023] The present invention also provides an aerial light effect generation device based on a drone swarm, a computer device, and a computer-readable storage medium, which have the above-mentioned beneficial effects, and will not be elaborated here. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments 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 based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of an aerial light effect generation method based on a drone swarm, according to an embodiment of the present invention.

[0026] Figure 2 yes Figure 1 A schematic diagram of a specific implementation method for step S10;

[0027] Figure 3 yes Figure 1 A schematic diagram of a specific implementation method for step S20;

[0028] Figure 4 yes Figure 1 A flowchart illustrating the first specific implementation method of step S30;

[0029] Figure 5 yes Figure 1 A flowchart illustrating the second specific implementation method of step S30;

[0030] Figure 6 yes Figure 1 A schematic diagram of the third specific implementation method of step S30;

[0031] Figure 7 yes Figure 1A schematic diagram of a specific implementation method for real-time security prediction and intervention after step S30;

[0032] Figure 8 This is a schematic block diagram of an aerial light effect generation device based on a drone swarm, according to an embodiment of the present invention. Detailed Implementation

[0033] 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, not all, of the embodiments of the present invention. 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.

[0034] It should be understood that, when used in this specification and the appended claims, the terms “comprising” and “including” indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more of its features, integrals, steps, operations, elements, components and / or collections thereof.

[0035] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0036] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0037] To facilitate the description of this application, the following concepts related to this application are introduced.

[0038] UAV Cluster Performance: This refers to an artistic performance where multiple drones, under the unified control system, coordinate their flight trajectories and synchronize changes in onboard equipment status to create dynamic patterns or shapes in the air. In this embodiment, it specifically refers to a performance system that uses drones equipped with gimbal laser modules and mirror reflection structures to generate dynamic light effects such as beams and pillars of light in the air.

[0039] Ray tracing engine: A computer graphics software tool used to simulate optical phenomena such as the propagation, reflection, and refraction of light in a virtual scene. It renders highly realistic lighting images by tracing the path of light rays backward from the camera (or observer). In this embodiment, it is used to simulate the backward propagation of light rays to initially determine the beam path and the spatial position of the drone required to generate the dynamic lighting effect.

[0040] Four-dimensional control sequence: refers to a set of control instructions that includes three-dimensional spatial position and one-dimensional time information. In this embodiment, it refers to the time sequence of instructions generated for each UAV, including the spatial position (X, Y, Z coordinates) to be reached at a specific time point, the fuselage attitude (pitch, roll, yaw angle) to be held, and the synchronous gimbal laser module's emission status, pointing angle, and other instructions.

[0041] Spline curve fitting algorithm: This refers to a mathematical method used to construct a smooth curve from a series of discrete control points (or nodes), such that the curve smoothly passes through or approximates these points. In this embodiment, it is used to interpolate key state frames in the UAV's flight path to generate a physically feasible, continuous, and smooth flight trajectory curve and attitude change curve.

[0042] A spatio-temporal task graph is a data structure or model used to describe a specific task that needs to be performed at a specific time and location. Nodes in the graph represent tasks (e.g., emitting a laser, specular reflection), and edges represent the spatio-temporal dependencies between tasks (e.g., A reflects, B receives). In this embodiment, it is core task planning data generated after parsing and optimizing a light effect performance script, used to guide the collaborative work of the entire drone swarm.

[0043] Precision Gimbal: A multi-axis mechanical stabilization platform driven by servo motors or stepper motors, capable of maintaining the pointing or attitude of its load (such as a laser) unaffected by changes in the attitude or vibration of the platform (such as the drone fuselage), achieving high-precision angle control. In this embodiment, it refers to a two-axis or three-axis stabilizing electromechanical structure installed on a drone for precisely controlling the laser emission direction independently of the fuselage attitude. The gimbal includes a gimbal servo motor, the laser is mounted on the gimbal, and the laser includes a laser drive module.

[0044] GPS PPS (Pulse Per Second) signal: A standard second pulse signal output by a Global Positioning System receiver, whose rising edge is precisely synchronized with the UTC (Coordinated Universal Time) second boundary, with an accuracy down to the nanosecond level. In this embodiment, it is used as an external reference signal source for microsecond-level time synchronization of the UAV swarm, ensuring the coordinated execution of control commands from each UAV.

[0045] Spline interpolation is a mathematical method that constructs a sufficiently smooth polynomial curve (such as a B-spline or a non-uniform rational B-spline) to pass through or approximate a given set of discrete data points. In this embodiment, it refers to generating a flight trajectory for the UAV with continuous position and attitude and smooth acceleration changes based on keyframe information in the spatiotemporal mission map.

[0046] This application provides a method for generating aerial light effects based on a drone swarm, referring to... Figure 1 ,include:

[0047] S10: Analyze and spatiotemporally model the preset lighting effect script to generate a spatiotemporal task map. The purpose of this step is to transform the abstract lighting effect concept created by the designer into a specific, quantifiable set of task instructions that can be executed by the drone swarm. Specifically, it reads the lighting effect script from the designer's 3D lighting animation (FBX / GLTF format) or parametric script (JSON / YAML), which describes, for example, generating a red laser beam pointing from coordinates (x1, y1, z1) to (x2, y2, z2) at t=10s. Through semantic parsing of these descriptions, the basic optical events (emission, reflection) and their temporal and spatial parameters required to constitute the lighting effect are extracted, and the logical relationships between the events are established, ultimately constructing a spatiotemporal task map containing a time axis and spatial position constraints.

[0048] S20: Based on the spatiotemporal task map, task allocation and trajectory generation are performed on the UAV swarm to obtain a four-dimensional control sequence for each UAV. The purpose of this step is to decompose the spatiotemporal task map and assign it to each specific UAV in the swarm, and to plan a safe, smooth, and executable flight and maneuver path for it. Specifically, based on the requirements of each task in the spatiotemporal task map for the UAV's hardware capabilities (whether it has a laser, whether it has a reflector), current position, and battery power, tasks are dynamically assigned to suitable UAVs. Then, based on the task timeline assigned to each UAV, a series of key waypoints are generated using differential evolution, and B-spline curves are used for fitting to generate a four-dimensional trajectory curve for each UAV that is continuous in both three-dimensional space and time.

[0049] S30: Based on the four-dimensional control sequence, the drone swarm is controlled to perform corresponding flight, laser projection, and mirror reflection actions to generate dynamic light effects. Each drone includes a gimbal and a reflective mirror, with a laser mounted on the gimbal. The purpose of this step is to send a planned virtual command sequence to the drone swarm, driving its coordinated movement and synthesizing the desired dynamic light effects in real time. Specifically, through a high-speed wireless data link (such as a 5G private network or a customized RF link), the sub-commands in the four-dimensional control sequence are sent one by one to the flight controller, gimbal servo motor, and laser drive module of each drone. The flight controller performs trajectory tracking, the gimbal adjusts the laser pointing angle, the laser drive module controls laser emission and power, and multiple drones work together to complete the emission and relay reflection of the beam, ultimately forming dynamic light effects such as continuous beams, dynamic light pillars, and three-dimensional light structures at the viewer's perspective.

[0050] The embodiments of this application employ the above method, which produces at least the following beneficial effects:

[0051] By coordinating the flight, laser projection, and specular reflection of drones based on a four-dimensional control sequence, dynamic orientation, relay, and reconstruction of laser beams in the air are achieved. This method solves the problem that existing technologies can only statically illuminate or project in one direction, failing to generate three-dimensional, continuous, and dynamically changing beam structures. This enables visual lighting effects such as continuous beams, dynamic light pillars, and three-dimensional light structures, which are impossible for traditional LED drones, achieving a leap in lighting effect and enhancing the visual expressiveness of drone swarm performances. Furthermore, the multiplexing of a single laser beam through reflection from multiple drones increases the light and shadow density within a unit of airspace, improving space utilization.

[0052] This method can be applied to the opening ceremony or core performance of large-scale cultural tourism nighttime projects. Addressing the visual impact and narrative requirements of such scenarios, this method can construct virtual aerial structures or energy flows by generating dynamically interwoven light networks and rotating, rising light pillars. This allows the storyline to be presented in a three-dimensional way using the language of light and shadow, providing the audience with an immersive audiovisual feast and enhancing the artistic level and technological value of the performance.

[0053] This method can be applied to customized stage effects for high-end brand launches or concerts. In this scenario, the method can generate dynamic beams of light in real time that are highly compatible with the atmosphere, based on the rhythm of the music or the content of the speech. For example, a dome of light can be instantly constructed above the stage during the climax of the music, or the beams of light can be made to point precisely at the new product like a pointer, achieving a high degree of synchronization and deep interaction between the light and shadow effects and the on-site events, creating an unforgettable live experience.

[0054] This method can be applied to the dynamic upgrading of future urban landscape lighting and public art installations. By using a swarm of drones equipped with this system as mobile, programmable aerial light and shadow painters, customized light shows can be staged regularly above urban landmarks, or dynamic aerial light sculptures can be created on specific holidays. This will not only enrich the cultural life of citizens but also become a new highlight of science and technology tourism, achieving a dual improvement in social and economic benefits.

[0055] In some embodiments, refer to Figure 2 Step S10 includes:

[0056] S11: Call the ray tracing engine to simulate the reverse ray propagation of the target dynamic light effect in the light effect script, and initially generate the beam path and the initial position and attitude set of the drone cluster;

[0057] S12: Based on kinematic and energy consumption models, construct an optimization problem with the goal of minimizing the overall maneuvering energy consumption of the cluster and the theoretical optical path error;

[0058] S13: Use an iterative optimization algorithm to solve for the initial position and attitude set, dynamically adjust the mission timing and spatial layout of each UAV, and output the optimized spatiotemporal mission map.

[0059] The purpose of this step is to provide a specific method for generating efficient and feasible spatiotemporal mission maps by performing physical optics simulation and multi-objective optimization of target light effects. The specific implementation steps are as follows:

[0060] The first step involves importing the final visual effect described in the lighting script (e.g., a blue light band winding from point A to point B) using POV-Ray, Blender Cycles, or another ray tracing engine. The ray tracing engine traces all the light paths that make up the light band from the viewer's perspective, inversely deriving the possible emission source position, reflection point position, and corresponding specular normal direction for each light ray. This point and direction information is then mapped to the initial deployment position set and initial attitude set of the drone.

[0061] Optionally, in the first step, the ray tracing engine can be invoked without being limited to a standard graphics rendering engine; a custom interface based on physically based optical simulation software (such as Zemax or CODE V) can also be used. Specifically, for complex optical systems (such as those containing prisms or diffraction elements), optical design software is used to perform ray tracing and aberration analysis, thereby obtaining more accurate initial pose requirements for the UAV, which is particularly suitable for scientific demonstrations or precision lighting scenarios with extremely high beam quality requirements.

[0062] The second step involves establishing a multi-objective optimization mathematical model based on the initial deployment position set and initial attitude set generated in the first step. Objective function 1, F1, represents the overall swarm maneuver energy consumption, defined as the weighted sum of the energy required for all UAVs to move from their current positions to their mission positions and adjust their attitudes. Objective function 2, F2, represents the theoretical optical path error, defined as the sum of the geometric deviations between the optimized beam path and the ideal path from the initial inverse simulation. Constraints include the minimum safe interval between UAVs, maximum speed and acceleration limits, and the effective range of the laser.

[0063] The third step involves using multi-objective iterative optimization algorithms, such as genetic algorithms or particle swarm optimization, to solve the above model. Based on the initial set, the algorithm continuously adjusts the task allocation for each UAV (e.g., changing from a reflector to a light source), fine-tunes the timing of task execution, and minor spatial offsets. After multiple iterations, the algorithm converges to one or a set of Pareto optimal solutions. One of these optimal solutions is selected and solidified as the final spatiotemporal task map, which includes the expected optical path model.

[0064] By combining ray tracing inverse simulation with multi-objective optimization to generate a map, the optimal solution mapping from artistic effect to engineering feasibility is achieved. This method solves the problems that may arise from relying solely on script parsing, such as unreasonable drone deployment, excessive maneuvering load, or large beam path distortion. Thus, it can minimize swarm energy consumption and improve the feasibility and reliability of the performance while ensuring the realism of the visual effects.

[0065] In some embodiments, refer to Figure 3 Step S20 includes:

[0066] S21: Analyze the spatiotemporal task map and dynamically assign tasks to eligible UAV nodes based on the spatiotemporal attributes, hardware resource requirements, and communication topology between UAVs.

[0067] S22: For each drone assigned a task, extract discrete key state frames containing position and attitude information from its corresponding task timeline.

[0068] S23: Using a spline curve fitting algorithm, interpolation calculations are performed on adjacent key state frames in three-dimensional space and time dimensions to generate flight trajectory curves and fuselage attitude change curves.

[0069] S24: The flight trajectory curve, the fuselage attitude change curve, and the laser emission command and gimbal pointing command at the corresponding time are time-series aligned and encapsulated to form the four-dimensional control sequence.

[0070] The specific implementation steps of step S20 are as follows:

[0071] The first step is to read the spatiotemporal task graph. For each task node in the spatiotemporal task graph (e.g., emitting a laser beam at position P at time t), all drone nodes in the current cluster are traversed to filter out drones that meet the hardware requirements (e.g., equipped with a laser), are reachable (e.g., can stably receive commands in the network topology), and are spatiotemporally feasible (e.g., can fly to the vicinity of point P before time t), forming a candidate set. Then, based on strategies such as load balancing and remaining battery power, a drone is dynamically selected from the candidate set to be assigned this task.

[0072] The second step involves identifying a series of discrete event points on the task timeline of a drone assigned a mission. For example, for a drone used to reflect laser light, the event points include: arriving at the reflection point, adjusting the drone's attitude to align the reflector with the incident light, maintaining the reflection attitude, and ending the mission and departing. The spatial coordinates (latitude, longitude, and altitude) and the drone's attitude angles (pitch, roll, and yaw) of these event points are extracted and used as key state frames for trajectory planning.

[0073] The third step involves using a non-uniform rational B-spline curve fitting algorithm to perform spline interpolation on all key state frames. In the position dimension, a smooth 3D spatial trajectory curve is fitted; in the attitude dimension, three time-varying attitude angle curves (pitch-time curve, roll-time curve, and yaw-time curve) are fitted. The fitting process must satisfy the UAV's dynamic constraints, ensuring that the second derivative (acceleration) of the generated curves is continuous and does not exceed the physical limits of the UAV.

[0074] The fourth step involves sampling the fitted 3D spatial trajectory curve and attitude angle curve at fixed time intervals (e.g., 10 milliseconds) to generate a dense sequence of path points. Simultaneously, discrete commands marked on the mission timeline, such as laser emission (on / off, color, power) and gimbal rotation (target pointing angle), are precisely aligned with these path points on the timeline. Finally, each UAV is encapsulated into a timestamp-sorted 4D control sequence file, containing the desired position, desired attitude, laser commands, and gimbal commands at each moment.

[0075] Through the aforementioned dynamic task allocation and spline curve-based trajectory planning process, flexible scheduling and smooth motion control of swarm tasks are achieved. This method solves the problems of inflexible fixed task allocation and the uneven motion and high energy consumption caused by straight-line waypoint planning, thereby enabling better utilization of swarm resources and generating smooth, natural, and energy-efficient drone swarm performances for the audience.

[0076] Optionally, in step S23, the spline curve fitting algorithm is not limited to B-splines; it can also use Bézier curves, NURBS curves, or polynomial curves fitted by the least squares method. Different curve types have their own characteristics in terms of smoothness, computational complexity, and accuracy at points, and can be selected according to the processing capability of the UAV flight control system and the requirements for trajectory accuracy. The UAV includes a gimbal and a reflector, and a laser is mounted on the gimbal.

[0077] In some embodiments, refer to Figure 4 Step S30 includes:

[0078] S311: After the four-dimensional control sequence is generated and before it is issued, a virtual optical path pre-simulation is performed on each laser emission command contained therein to determine whether its beam path intersects with the preset three-dimensional model of the geographical no-fly zone.

[0079] S312: If there is spatial intersection, it is determined that there is a risk of the laser beam illuminating the no-fly zone. The transmission power of the laser emission command is automatically reduced to the safety level or marked as canceled, and the corresponding task adjustment is notified.

[0080] S313: During the execution of the laser emission command, the flight stability data of the UAV is monitored in real time. If the data exceeds the safety threshold, the power output of the UAV laser is cut off through a hardware interrupt signal.

[0081] The purpose of this step is to prevent the laser beam from accidentally illuminating sensitive areas or from going out of control due to drone instability. The specific implementation steps are as follows:

[0082] The first step is to load a 3D model (formatted as 3DMAX or GIS model) of a geographic no-fly zone, including buildings, high-voltage power line towers, and sensitive facilities, into the simulation environment of the central control server. For each laser emission command in the four-dimensional control sequence (including emission time, emission source coordinates, and beam direction vector), an intersection test between the ray and the 3D model is performed using a spatial geometry calculation library (such as CGAL). If the calculated beam or its extension intersects with any no-fly zone model within the effective distance, a risk warning is triggered.

[0083] The second step involves the safety module immediately implementing preset strategies upon detecting an intersection risk. For example, it might automatically reduce the laser power of the command to Class I (eye-safe) level, ensuring it is harmless even if the laser hits the target; or, in critical situations, directly mark the command as canceled. Simultaneously, an alarm is sent to the scheduling module, which may trigger local task replanning, such as fine-tuning the pose of the launching drone to change the beam direction and bypass no-fly zones.

[0084] The third step involves the real-time execution of the drone swarm performance. The safety monitoring thread continuously receives telemetry data on the flight control status of each drone, particularly indicators reflecting flight stability such as attitude angular velocity and motor vibration amplitude. Preset safety thresholds are established (e.g., angular velocity exceeding 50 degrees / second). When the stability data of a drone emitting a laser exceeds the threshold, instead of relying on software commands, a hardware interrupt signal is directly sent to the drone's laser driver module, forcibly cutting off its power output and achieving a millisecond-level emergency stop. This prevents the laser beam from sweeping across the audience or other unsafe areas due to violent shaking of the drone.

[0085] By combining offline pre-performance testing with online monitoring and emergency stop, a multi-level, in-depth laser safety management system was constructed. This method addresses potential public safety hazards associated with laser performances in complex outdoor environments.

[0086] In some embodiments, refer to Figure 5 Step S30 further includes:

[0087] S321: Control at least three drones to form a chain-like reflective optical path: wherein the at least three drones include a first drone as an initial light source, a second drone as a primary reflector, and a third drone as a secondary reflector;

[0088] S322: Control the first UAV to activate its own laser according to its four-dimensional control sequence and emit a first laser beam in a predetermined spatial direction;

[0089] S323: Control the second UAV to adjust the orientation of the reflector on its body in real time so that the first laser beam is incident on the reflector of the second UAV;

[0090] S324: Based on the law of specular reflection, the incident first laser beam is directionally reflected to the third drone through the reflective mirror of the second drone;

[0091] S325: Control the third UAV to perform secondary reflection using the same principle, and guide the first laser beam to the target area or other UAVs, so as to realize the continuous transmission and direction reconstruction of the laser beam in the dynamic reflection chain composed of multiple UAVs, so as to generate dynamic light effects.

[0092] The purpose of this step is to provide a specific collaborative mode for using multi-machine relay reflection to extend the light beam and change its direction to construct complex lighting effects. The specific implementation steps are as follows:

[0093] The first step, based on the spatiotemporal mission map plan, is to designate at least three drones with specific functions to form a reflective chain. The first drone is equipped with a gimbal and a laser; the second and third drones have electrically adjustable plane mirrors or reflective prisms installed on their surfaces.

[0094] The second step is for the light source to emit a laser beam: At a predetermined time, the first UAV flies to the designated airspace, and its gimbal laser is activated according to the instructions of the four-dimensional control sequence and points to an initial direction, emitting a visible laser beam, namely the first laser beam.

[0095] Third, the second UAV simultaneously arrives at its predetermined position and adjusts its flight attitude to align with the normal direction of the reflector, precisely satisfying the specular reflection law that the angle of incidence equals the angle of reflection. This ensures that the first laser beam is incident on the reflector and accurately reflected towards the approximate direction of the third UAV. This process requires the second UAV to perform dynamic calculations and servo control based on its real-time relative positions with the first and third UAVs.

[0096] Fourth, the third drone, using the same principle as the second drone, adjusts the orientation of its reflector in real time to reflect the incident beam from the second drone again. This time, the target direction of the reflection can be a fixed ground target area to form a dynamic illumination point, or it can be the next drone, forming a longer reflection chain, thereby achieving multiple turns and extensions of the beam in the air.

[0097] Optionally, in steps S323 and S324, the orientation adjustment of the second UAV reflector can be achieved not only by adjusting the attitude of the entire UAV body, but also by individually controlling the rotation angle of the reflector using an onboard high-speed galvanometer system or a micro servo gimbal. Specifically, while the UAV body maintains relatively stable flight, the reflector onboard is controlled to achieve rapid and high-precision fine-tuning of the beam incident angle, thereby allowing for more flexible control of the reflected beam direction without affecting flight stability.

[0098] By employing the aforementioned collaborative control method of chain-reflection optical paths, multiple turns and spatial extensions of a single laser beam in the air were achieved. This method solves the problem of limited laser range and direction for a single UAV, enabling the use of lower-power lasers to create complex beam trajectories in the air far exceeding the range of a single UAV through relay by multiple UAVs, thereby enhancing the spatial hierarchy and dynamic possibilities of the light effect.

[0099] In some embodiments, refer to Figure 6 Step S30 includes:

[0100] S331: During the generation of dynamic light effects, the status telemetry data transmitted back in real time by each UAV is continuously received through a wireless data link. The status telemetry data includes the UAV's positioning coordinates, real-time attitude angle, actual gimbal angle, and laser operating parameters.

[0101] S332: Based on the returned state telemetry data, and combined with the expected optical path model in the spatiotemporal mission map, calculate in real time the positional and directional deviations between the currently formed aerial beam and the expected beam.

[0102] S333: Determine whether the position deviation and orientation deviation exceed the preset position error tolerance threshold and orientation error tolerance threshold, respectively;

[0103] S334: If the position deviation and direction deviation exceed the preset position error tolerance threshold and direction error tolerance threshold respectively, a local fine-tuning command is generated and executed through the real-time command channel. The local fine-tuning command is used to adjust the gimbal pointing angle or reflector tilt angle of the corresponding UAV to compensate for the position deviation and direction deviation.

[0104] The purpose of this step is to provide a closed-loop correction mechanism based on real-time feedback. The specific implementation steps are as follows:

[0105] The first step is for each drone in the drone swarm to transmit its RTK / GNSS positioning coordinates, real-time attitude angle measured by the IMU, actual angle fed back by the gimbal, and working parameters such as laser current / temperature back to the ground control station via a wireless data link or GPSPPS (Pulse Per Second) signal at a fixed frequency (e.g., 10Hz).

[0106] The second step involves the central processing module maintaining a projected optical path model based on a spatiotemporal mission map. When a reflection chain is operational, based on the real-time data transmitted back—the actual position and gimbal pointing angle of the first UAV, and the actual position and reflector normal direction of the second UAV (calculated jointly by the fuselage attitude and the reflector adjustment mechanism angle)—the actual reflection path of the current first laser beam is calculated in real time. This actual path is compared with the projected path, and the positional deviation (in meters) of the beam's landing point (e.g., the point illuminating the reflector of the third UAV) and the directional deviation (in degrees) of the beam's central axis are quantitatively calculated.

[0107] The third step involves setting preset position error tolerance thresholds (e.g., 0.1 meters) and orientation error tolerance thresholds (e.g., 0.5 degrees). The position deviation value calculated in the second step is compared with the position error tolerance threshold, and the orientation deviation value calculated in the second step is compared with the orientation error tolerance threshold. If either deviation exceeds its corresponding threshold, the current optical path quality is considered substandard, requiring intervention and correction.

[0108] The fourth step involves the correction algorithm quickly calculating the adjustment required to compensate for the deviation based on its direction and magnitude. For example, if the beam's point of impact is off to the left, a command is generated to instruct the second UAV to fine-tune the tilt angle of its reflector (via a piezoelectric ceramic actuator) by turning it slightly to the right. This fine-tuning command is marked as high priority and immediately sent to the corresponding UAV actuator via a dedicated real-time command channel (such as a low-latency UDP link).

[0109] The aforementioned closed-loop feedback correction method based on real-time telemetry achieves dynamic stability and precise control of the aerial light effect generation process. This method solves the problems of open-loop control being greatly affected by environmental interference and accumulating execution errors, thereby significantly improving the accuracy of beam positioning and optical path stability. This ensures that even in windy or slightly positioning-error-prone outdoor environments, drone swarm performances can present clear and stable light effects.

[0110] In some embodiments, refer to Figure 7 After step S30, the method further includes:

[0111] S41: During the generation of dynamic lighting effects, maintain and update in real time a safe zone database containing 3D geofences, dynamic obstacle locations, and real-time crowd distribution heatmaps;

[0112] S42: Before each laser emission command is generated and during the duration of the laser beam, predict the complete three-dimensional spatial illumination path of the laser beam corresponding to the laser emission command and its final landing area.

[0113] S43: Perform real-time collision detection and human eye safety level assessment by comparing the predicted illumination path and impact area data with the safe area database;

[0114] S44: Based on the assessment results, make dynamic decisions and execute at least one safety intervention operation, including laser power graded control, emergency beam path redirection, or laser output cutoff, and record all safety events in the audit log.

[0115] The purpose of this step is to achieve dynamic perception, prediction, and proactive intervention of laser safety risks. The specific implementation steps are as follows:

[0116] The first step is to build a dynamic security database. This database includes not only static electronic fences (such as building boundaries) but also dynamic data streams from external systems. For example, coordinates of dynamic obstacles (such as intruding birds or other drones) accessed via radar or vision systems; and real-time crowd distribution heat maps generated by ticketing systems or video audience flow statistics systems to identify high-density areas where audiences gather.

[0117] The second step involves calculating, in real time, the three-dimensional cone-shaped illumination body in the air for each laser beam that is planned to be launched or is being launched, based on the real-time position of the source, the gimbal pointing angle, and the beam divergence angle parameters. It also predicts the final point of impact on the ground or distant obstacles under unobstructed conditions.

[0118] The third step involves performing real-time spatial intersection detection between the predicted 3D cone-shaped irradiation body and the impact area and all area models in the safety database. For beams that intersect with high-density areas of the real-time population distribution heatmap, an eye safety level assessment is required. Based on the laser wavelength, power, irradiation distance, and duration, it is determined whether the beam exceeds the irradiance limit.

[0119] The fourth step involves implementing a tiered strategy based on the detection and evaluation results. For example, if the predicted path intersects with a dynamic obstacle, the gimbal may be fine-tuned immediately to redirect the beam path and avoid it; if the impact area enters a high-density population zone and is assessed as unsafe, the laser power will be automatically and instantly reduced to Class 1 safety level; if a more serious and unavoidable risk occurs, the laser output will be cut off. All laser commands, prediction results, evaluation conclusions, and final intervention actions are timestamped and recorded in an immutable audit log for post-event review and compliance verification.

[0120] By combining real-time safety prediction and intervention methods with dynamic environmental perception, an upgrade from static protection to dynamic intelligent protection is achieved. This method solves the problems of lag and limitations of traditional safety measures that rely solely on fixed fences and manual monitoring. It proactively addresses various unexpected risks that may arise during performances, improves the safety and reliability of large-scale aerial light effect generation performances based on drone swarms in complex dynamic environments, and provides complete data for defining safety responsibilities.

[0121] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0122] Reference Figure 8 This invention provides an aerial light effect generation device 100 based on a drone swarm, comprising:

[0123] The light effect script parsing and spatiotemporal modeling module 101 is used to parse and spatiotemporally model the preset light effect scripts and generate a spatiotemporal task map.

[0124] The task allocation and trajectory generation module 102 is used to allocate tasks and generate trajectories for the UAV cluster based on the spatiotemporal task map, so as to obtain the four-dimensional control sequence of each UAV.

[0125] The real-time synchronization and execution module 103 is used to control the UAV cluster to perform corresponding flight, laser projection and mirror reflection actions based on the four-dimensional control sequence to generate dynamic light effects; wherein, the UAV includes a gimbal and a reflective mirror, and the gimbal is equipped with a laser.

[0126] Specific limitations regarding the aerial light effect generation device 100 based on UAV swarms can be found in the limitations of the aerial light effect generation method based on UAV swarms described above, and will not be repeated here. Each module in the aforementioned aerial light effect generation device based on UAV swarms can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0127] This invention provides a computer device including a processor, a memory, a network interface, and a database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface communicates with external clients via a network connection. When executed by the processor, the computer program implements the functions or steps of a method for generating aerial light effects based on a drone swarm.

[0128] This invention also provides a computer-readable storage medium storing a computer program that, when executed, can perform the steps provided in the above embodiments.

[0129] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0130] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0131] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0132] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for generating aerial light effects based on unmanned aerial vehicle (UAV) swarms, characterized in that, include: The preset lighting effect script is analyzed and spatiotemporally modeled to generate a spatiotemporal mission map; Based on the spatiotemporal task map, task allocation and trajectory generation are performed on the UAV swarm to obtain the four-dimensional control sequence of each UAV. The four-dimensional control sequence controls the drone swarm to perform corresponding flight, laser projection, and mirror reflection actions to generate dynamic light effects; wherein, the drone includes a gimbal and a reflective mirror, and the gimbal is equipped with a laser. The process of controlling the UAV swarm based on the four-dimensional control sequence to perform corresponding flight, laser projection, and specular reflection actions to generate dynamic light effects includes: Control at least three drones to form a chain-like reflective optical path: wherein the at least three drones include a first drone as an initial light source, a second drone as a primary reflector, and a third drone as a secondary reflector; The first UAV is controlled to activate its own laser according to its four-dimensional control sequence, and emit a first laser beam in a predetermined spatial direction. Control the second UAV to adjust the orientation of the reflector on its body in real time so that the first laser beam is incident on the reflector of the second UAV; Based on the law of specular reflection, the incident first laser beam is directionally reflected to the third drone through the reflective mirror of the second drone; The third UAV is controlled to perform secondary reflection using the same principle, guiding the first laser beam to the target area or other UAVs, thereby enabling the laser beam to be continuously transmitted and reconstructed in a dynamic reflection chain composed of multiple UAVs to generate dynamic light effects.

2. The method for generating aerial light effects based on UAV swarms according to claim 1, characterized in that, The process of parsing and spatiotemporally modeling the preset lighting effect script to generate a spatiotemporal task map includes: The ray tracing engine is invoked to simulate the reverse ray propagation of the target dynamic lighting effects in the lighting effect script, and the initial beam path and the initial position and attitude set of the drone cluster are initially generated. Based on kinematic and energy consumption models, an optimization problem is constructed with the goal of minimizing the overall maneuvering energy consumption of the cluster and the theoretical optical path error. An iterative optimization algorithm is used to solve for the initial position and attitude set, dynamically adjust the mission timing and spatial layout of each UAV, and output the optimized spatiotemporal mission map.

3. The method for generating aerial light effects based on UAV swarms according to claim 1, characterized in that, Based on the spatiotemporal task map, task allocation and trajectory generation are performed on the UAV swarm to obtain a four-dimensional control sequence for each UAV, including: The spatiotemporal task map is analyzed, and tasks are dynamically assigned to eligible UAV nodes based on the spatiotemporal attributes of each task, hardware resource requirements, and communication topology between UAVs. For each drone assigned a task, extract discrete key state frames containing position and attitude information from its corresponding task timeline. Using a spline curve fitting algorithm, interpolation calculations are performed on adjacent key state frames in three-dimensional space and time to generate flight trajectory curves and fuselage attitude change curves. The flight trajectory curve, the fuselage attitude change curve, and the laser emission command and gimbal pointing command at the corresponding time are time-sequentially aligned and encapsulated to form the four-dimensional control sequence.

4. The method for generating aerial light effects based on UAV swarms according to claim 1, characterized in that, The process of controlling the UAV swarm based on the four-dimensional control sequence to perform corresponding flight, laser projection, and specular reflection actions to generate dynamic light effects includes: After the four-dimensional control sequence is generated and before it is issued, a virtual optical path pre-simulation is performed on each laser emission command contained therein to determine whether its beam path intersects with the preset three-dimensional model of the geographical no-fly zone. If there is spatial intersection, it is determined that there is a risk of the laser beam illuminating the no-fly zone. The transmission power of the laser emission command is automatically reduced to the safety level or marked as canceled, and the scheduling system is notified to make corresponding task adjustments. During the execution of the laser emission command, the flight stability data of the drone is monitored in real time. If the data exceeds the safety threshold, the power output of the drone's laser is cut off through a hardware interrupt signal.

5. The method for generating aerial light effects based on UAV swarms according to claim 1, characterized in that, The process of controlling the UAV swarm based on the four-dimensional control sequence to perform corresponding flight, laser projection, and specular reflection actions to generate dynamic light effects includes: During the generation of dynamic light effects, the system continuously receives real-time status telemetry data from each UAV via a wireless data link. The status telemetry data includes the UAV's positioning coordinates, real-time attitude angle, actual gimbal angle, and laser operating parameters. Based on the returned state telemetry data, and combined with the expected optical path model in the spatiotemporal mission map, the positional and directional deviations between the currently formed aerial beam and the expected beam are calculated in real time. Determine whether the position deviation and orientation deviation exceed the preset position error tolerance threshold and orientation error tolerance threshold, respectively; If the position deviation and direction deviation exceed the preset position error tolerance threshold and direction error tolerance threshold, respectively, a local fine-tuning command is generated and executed through the real-time command channel. The local fine-tuning command is used to adjust the gimbal pointing angle or local tilt angle of the mirror of the corresponding UAV to compensate for the position deviation and direction deviation.

6. The method for generating aerial light effects based on UAV swarms according to claim 1, characterized in that, Also includes: During the generation of dynamic lighting effects, a database of safe zones containing 3D geofences, dynamic obstacle locations, and real-time crowd distribution heatmaps is maintained and updated in real time. Before each laser emission command is generated and during the duration of the laser beam, the complete three-dimensional spatial illumination path of the laser beam corresponding to the laser emission command and its final landing area are predicted. The predicted illumination path and impact area data are compared with the safe area database in real time for collision detection and human eye safety level assessment. Based on the assessment results, make dynamic decisions and execute at least one safety intervention operation, including laser power graded control, emergency beam path redirection, or cutting off laser output, and record all safety events in the audit log.

7. An aerial light effect generation device based on a drone swarm, characterized in that, include: The Light Effect Script Parsing and Spatiotemporal Modeling module is used to parse and spatiotemporally model the preset light effect scripts to generate a spatiotemporal task map. The task allocation and trajectory generation module is used to allocate tasks and generate trajectories for the UAV cluster based on the spatiotemporal task map, so as to obtain the four-dimensional control sequence of each UAV. A real-time synchronous distribution and execution module is used to control the UAV cluster to perform corresponding flight, laser projection, and mirror reflection actions based on the four-dimensional control sequence to generate dynamic light effects; wherein, the UAV includes a gimbal and a reflective mirror, and the gimbal is equipped with a laser; The real-time synchronous transmission and execution module is specifically used for: controlling at least three drones to form a chain-like reflection optical path, wherein the at least three drones include a first drone as an initial light source, a second drone as a primary reflector, and a third drone as a secondary reflector; controlling the first drone to activate its own laser according to its four-dimensional control sequence and emit a first laser beam in a predetermined spatial direction; controlling the second drone to adjust the orientation of its reflective mirrors in real time so that the first laser beam is incident on the reflective mirrors of the second drone; based on the law of specular reflection, directing the incident first laser beam to the third drone through the reflective mirrors of the second drone; controlling the third drone to perform a secondary reflection using the same principle to guide the first laser beam to a target area or other drones, thereby realizing the continuous transmission and direction reconstruction of the laser beam in a dynamic reflection chain composed of multiple drones to generate dynamic light effects.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements a method for generating aerial light effects based on a drone swarm as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a method for generating aerial light effects based on a drone swarm as described in any one of claims 1 to 6.

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