Unmanned aerial vehicle swarm control method, apparatus, device, and medium

Abstract

The application discloses a kind of unmanned aerial vehicle cluster control method, device, equipment and medium, the method in which constructs the visual light unit model by the geometry and attitude information of unmanned aerial vehicle light-emitting paddle, and the light-emitting area formed by its rotation is regarded as equivalent pixel unit;Light field emission model is established by combining the model and audience position, to calculate the brightness attenuation of each pixel;Based on the principle of human eye visual persistence, a fusion model is established to calculate the required minimum light instruction update frequency;The spatial position of each unmanned aerial vehicle, the display information of equivalent pixels and the instruction frequency are calculated by using the three models cooperatively, and a comprehensive control instruction package containing flight and light instructions is generated for distribution. The method improves the information expression capability of a single unmanned aerial vehicle from point to plane, solving the information expression upper limit problem caused by the single-machine single-point paradigm in the prior art.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) swarm control technology, and particularly to a UAV swarm control method, device, equipment, and medium. Background Technology

[0002] In the field of drone swarm visual presentation technology, existing drone light show systems generally adopt a "single-drone, single-pixel" presentation paradigm. The core technology lies in swarm control, enabling each drone carrying an LED light to fly and illuminate in the night sky. Through the combination and spatial arrangement of multiple drones' on / off states, a dot-matrix aerial pattern is formed. However, this paradigm has a fundamental technical bottleneck: each drone, at any given moment, can only participate in imaging as an independent, spatially fixed point light source, and its information expression is strictly limited to an RGB color value and a three-dimensional coordinate.

[0003] The direct consequence of this paradigm is that the visual resolution of aerial images depends entirely on the physical number and density of drones. To present more detailed images, the only way is to increase the number of drones or reduce the spacing between formations, but this faces triple limits in terms of cost, airspace, energy efficiency, and flight safety. More importantly, the value of a single drone as an information unit is greatly wasted. The core component of the drone's propulsion system, the high-speed rotating propellers, is currently only considered a dynamic disturbance to be overcome; the vast spatial area formed by their enormous trajectory (often with a diameter far exceeding the fuselage) is a visual "dark zone," not used for information carrying.

[0004] Therefore, the "information density" of the entire drone swarm remains at the "point" level, unable to present coherent "lines," "planes," or "volumes" or other higher-order visual elements. Dynamic expression is also limited to the overall displacement of the drones, unable to achieve micro-dynamics such as color gradations and pattern rotations at the individual drone level. This severe mismatch between hardware performance and information expression capabilities—the inability to "break through the information expression limits of a single drone"—has become the core obstacle restricting the development of drone swarm visual presentation technology towards higher-order art forms. Summary of the Invention

[0005] The embodiments of the present invention provide a method, apparatus, device and medium for controlling a drone swarm, which aims to solve the technical problem that the information expression limit of a single drone can not be exceeded when a drone swarm is presented in array visual representation under the prior art.

[0006] In a first aspect, embodiments of the present invention provide a method for controlling a swarm of unmanned aerial vehicles (UAVs), the method comprising:

[0007] Based on the geometric dimensions of the luminous propellers of each UAV, the relative positional relationship between the UAV's fuselage and the luminous propellers, and the UAV's flight attitude information, a visual luminous unit model is established, defining the luminous area formed by the luminous propellers during the UAV's flight as an equivalent pixel unit. A light field emission model is constructed based on the visual luminous unit model and the spatial position of a preset target observer to calculate the brightness decay law of each equivalent pixel unit. A human visual persistence fusion model is established based on human visual persistence constraints and the geometric dimensions of the luminous propellers of each UAV. This human visual persistence fusion model is used to maintain stable imaging. Based on the minimum rotation frequency of the light-emitting propeller, the required light emission command update frequency to be sent to the UAV is calculated. Based on the target visual content, the spatial position information of each UAV is calculated through the visual light emission unit model, and the display information and light emission command update frequency of each equivalent pixel unit are calculated through the light field emission model and the human eye visual persistence fusion model. The display information includes brightness information and color information. Based on the spatial position information, the flight trajectory of each UAV is planned. The control commands for each UAV are generated by combining the flight trajectory of the UAV, the display information and the light emission command update frequency, and sent to each UAV for execution.

[0008] Secondly, embodiments of the present invention also provide a drone swarm control device for executing the drone swarm control method described above.

[0009] Thirdly, embodiments of the present invention also provide a computer device, the computer device including a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to perform the steps of the above-described unmanned aerial vehicle (UAV) swarm control method.

[0010] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, can implement the steps of the above-described UAV swarm control method.

[0011] Compared with the prior art, the beneficial effects of the present invention are:

[0012] In the technical solution of this invention, the UAV swarm control method constructs a visual luminescent unit model by using the geometric and attitude information of the UAV's luminescent propellers, treating the luminescent area formed by their rotation as equivalent pixel units. This model is then combined with the viewer's position to establish a light field emission model to calculate the brightness attenuation of each pixel. A fusion model is established based on the principle of human visual persistence to calculate the minimum required light command update frequency. These three models are used collaboratively to calculate the spatial position of each UAV, the display information of its equivalent pixels, and the command frequency, generating a comprehensive control command package containing flight and light commands for distribution. This method elevates the information expression capability of a single UAV from a point to a surface, solving the problem of the upper limit of information expression caused by the single-point paradigm of existing technologies. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. 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.

[0014] Figure 1 A flowchart of the UAV swarm control method provided by the present invention;

[0015] Figure 2 This is a first sub-flowchart of the UAV swarm control method provided by the present invention;

[0016] Figure 3 This is a second sub-flowchart of the UAV swarm control method provided by the present invention;

[0017] Figure 4 This is the third sub-flowchart of the UAV swarm control method provided by the present invention;

[0018] Figure 5 This is the fourth sub-flowchart of the UAV swarm control method provided by the present invention;

[0019] Figure 6 This is the fifth sub-flowchart of the UAV swarm control method provided by the present invention;

[0020] Figure 7 The sixth sub-flowchart of the UAV swarm control method provided by the present invention;

[0021] Figure 8 A schematic block diagram of the unit of the unmanned aerial vehicle (UAV) swarm control device provided by the present invention;

[0022] Figure 9 A schematic block diagram of a computer device provided for an embodiment of the present invention. Detailed Implementation

[0023] 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.

[0024] 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 other features, integrals, steps, operations, elements, components and / or collections thereof.

[0025] It should also be understood that the terminology used in this specification is for the purpose of describing medical 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.

[0026] 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.

[0027] This invention addresses the problem of poor user experience caused by the simple control logic of existing drone swarm control methods, and provides a drone swarm control method, apparatus, device, and medium. (Refer to...) Figures 1 to 7 The method for controlling a drone swarm includes the following steps:

[0028] S110. Based on the geometric dimensions of the luminous propellers of each UAV, the relative positional relationship between the UAV fuselage and the luminous propellers, and the flight attitude information of the UAV, a visual luminous unit model is established, and the luminous area formed by the luminous propellers during the flight of the UAV is defined as an equivalent pixel unit.

[0029] S120. Construct a light field emission model for calculating the brightness attenuation law of each equivalent pixel unit based on the visual luminous unit model and the spatial position of the preset target observer.

[0030] S130. Based on the human visual persistence constraint and the geometric dimension information of the light-emitting propellers of each UAV, a human visual persistence fusion model is established. The human visual persistence fusion model is used to calculate the light-emitting command update frequency to be sent to the UAV based on the minimum light-emitting propeller rotation frequency required to maintain stable imaging.

[0031] S140. Based on the target visual content, calculate the spatial position information of each of the UAVs through the visual luminescence unit model, and calculate the display information and luminescence command update frequency of each of the equivalent pixel units through the light field emission model and the human eye visual persistence fusion model. The display information includes brightness information and color information.

[0032] S150. Based on the spatial location information, plan the flight trajectory of each of the UAVs, combine the flight trajectory of the UAVs, the display information and the light emission command update frequency to generate control commands for each UAV, and send them to each UAV for execution.

[0033] In the drone swarm control method of this invention, each drone participating in the performance needs to integrate a light-emitting unit on its propeller blades. This light-emitting unit is specifically a flexible electroluminescent film attached to the surface of the propeller blades, or a long-afterglow fluorescent phosphorescent material embedded inside the propeller blades. When using an actively emitting flexible EL film, a conductive slip ring is installed at the motor shaft to transmit power and control signals from the drone's fuselage to the high-speed rotating propeller blades, thereby adjusting the brightness and color of the EL film. When using a passively excited fluorescent / phosphorescent material, a UV-LED excitation light source of a specific wavelength is installed on the drone's fuselage. By adjusting the switching and brightness of the UV-LED, the luminous intensity of the propeller blades is indirectly controlled.

[0034] In order to accurately control the display content of each drone, multiple related computing models need to be built for use by the ground-based intelligent orchestration control system when controlling the drone swarm.

[0035] First, a visual luminescence unit model is established based on the geometric dimensions of the luminescent propellers of each UAV, the relative positional relationship between the fuselage and the luminescent propellers, and the UAV's flight attitude information. The luminescent propellers are strip-shaped structures mounted on the UAV rotor, with the luminescent area extending radially along the blade. Their inner and outer diameters are determined by the starting and ending positions of the luminescent material on the blade. The relative positional relationship between the fuselage and the luminescent propellers is a fixed assembly structure, with a definite spatial offset between its geometric center and the UAV's coordinate system. This offset is obtained through mechanical calibration before system deployment. Flight attitude information is collected by the UAV's built-in attitude sensors to determine the orientation of the propeller rotation plane in space. Based on this information, the system defines the luminescence trajectory formed by each luminescent propeller during rotation due to the persistence of vision as an equivalent pixel unit. This unit is represented in space as a ring-shaped luminescent area centered on the UAV's position, bounded by the inner and outer diameters of the luminescent propellers, with its normal direction determined by the flight attitude.

[0036] Subsequently, the system constructs a light field emission model based on the spatial position of the visual luminescent unit model and the preset target observer. This model is used to calculate the brightness attenuation law of each equivalent pixel unit from the observer's perspective. The model calculates the light intensity attenuation factor and the distance attenuation factor based on the angle between the normal direction of the luminescent unit and the observer's line of sight, as well as the spatial distance from the center of the luminescent unit to the observer. These two factors are then multiplied to obtain the final perceived brightness attenuation law. The physical basis of this model is the diffuse reflection characteristics of Lambertian volume and the inverse square law of light intensity attenuation. Its calculation process does not rely on numerical parameters but is derived solely based on geometric and spatial relationships, ensuring that the brightness distribution conforms to real optical behavior.

[0037] While constructing the light field emission model, the system establishes a human visual persistence fusion model based on the human visual persistence constraint and the geometric dimensions of the luminous propellers. This model is used to calculate the update frequency of the luminous commands to be sent to the UAV, based on the minimum luminous propeller rotation frequency required to maintain stable imaging. The luminous propellers are divided into multiple luminous segments along their length, each corresponding to a visual sampling point during rotation. As the propellers rotate, these luminous segments form a continuous image under visual persistence. To avoid flickering, the system must ensure that the update frequency of the luminous commands is not lower than the minimum refresh threshold determined by the propeller rotation speed and the number of luminous segments. This model does not set a fixed frequency value, but dynamically calculates the required update frequency based on the propeller structure and rotation state to ensure the stability of visual fusion.

[0038] After completing the above model construction, the system calculates the spatial position information of each UAV based on the target visual content using a visual luminescent unit model. Specifically, the target visual content is projected onto a virtual imaging plane with a preset target observer as the reference. This plane is perpendicular to the observer's line of sight and located at a certain distance in front of the observer. Multiple regions are divided on this plane, each corresponding to the coverage area of ​​an equivalent pixel unit. Subsequently, based on the annular coverage area of ​​each equivalent pixel unit, the spatial position of the deployed UAVs is optimized, ensuring that all equivalent pixel units cover the visible area of ​​the target visual content on the projection plane without gaps or overlap.

[0039] Based on this, the system calculates the display information and emission command update frequency of each equivalent pixel unit through a fusion model of light field emission and human visual persistence. The display information includes brightness and color information. Brightness information, output by the light field emission model, reflects the actual perceived brightness of the unit from the observer's perspective. Color information is obtained by directly mapping the color distribution of the target visual content in the corresponding area. The emission command update frequency is output by the human visual persistence fusion model, ensuring that emission control is synchronized with the propeller rotation phase.

[0040] Finally, based on the calculated spatial position information of the drones, the system plans the flight trajectories of each drone to ensure stable flight along the predetermined path in three-dimensional space. Combining the flight trajectories with the aforementioned display information, the system generates control commands for each drone, including position commands, attitude commands, and illumination parameter commands. The system then uniformly distributes these control commands to each drone, driving it to execute flight and illumination actions according to the instructions, enabling all equivalent pixel units to work together to form a high-density visual representation of the target visual content.

[0041] In one embodiment, step S110 includes:

[0042] S111. Determine the radial range of the annular coverage area formed by the equivalent pixel unit in space based on the inner and outer diameters of the light-emitting blades.

[0043] S112. Based on the relative positional relationship between the fuselage and the light-emitting propellers, determine the correspondence between the geometric center of the equivalent pixel unit and the fuselage coordinate system of the UAV.

[0044] S113. Based on the flight attitude information, determine the normal direction of the equivalent pixel unit, so that the normal direction of the equivalent pixel unit faces the preset target observer.

[0045] Based on the inner and outer diameters of the luminescent blades, the radial range of the annular coverage area formed by the equivalent pixel unit in space is determined. Since the luminescent blades are strip-shaped structures extending radially along the UAV rotor axis, the starting position of the luminescent element on the blades, oriented outward from the rotor axis, is defined as the inner diameter, and the ending position as the outer diameter. The area between these two positions is the actual luminescent portion within the observer's visual field. As the UAV rotor shaft rotates, the trajectory of this luminescent area sweeping through space merges into an annular luminescent surface due to the persistence of vision. The inner and outer boundaries of this annular surface are determined by the inner and outer diameters, respectively, thus forming an annular coverage area with a defined radial range. This area is the physical boundary of the equivalent pixel unit.

[0046] Secondly, based on the relative positional relationship between the fuselage and the luminous propellers, the correspondence between the geometric center of the equivalent pixel unit and the UAV fuselage coordinate system is determined. The luminous propellers are fixedly mounted at the rotor tip of the UAV fuselage, and their rotation center has a fixed spatial offset from the geometric center of the UAV fuselage. This offset is determined through the mechanical assembly structure before system deployment and is used as a known parameter input during modeling. Therefore, the geometric center of the equivalent pixel unit, i.e., the center of its annular region, maintains a constant spatial relationship with the origin of the UAV fuselage coordinate system. This relationship is uniquely determined by the propeller mounting position and the rotor arm length, ensuring that the spatial position of each equivalent pixel unit can be accurately mapped to the corresponding UAV coordinate system.

[0047] Finally, based on the flight attitude information, the normal direction of the equivalent pixel unit is determined, ensuring that this normal direction faces the preset target observer. The UAV's flight attitude information is collected by its built-in attitude sensors, including pitch, yaw, and roll angles, reflecting the UAV's orientation in three-dimensional space. Since the luminous propellers are rigidly connected to the body, the normal direction of their rotation plane changes synchronously with the body's attitude. Based on this attitude information, the system calculates and adjusts the flight attitude of each UAV, ensuring that the normal direction of the luminous propeller's rotation plane always points towards the preset target observer's position. This ensures that the luminous surface of the equivalent pixel unit faces the viewing angle, maximizing its effective contribution to the target image and avoiding brightness attenuation or visual distortion caused by viewing angle tilt.

[0048] In one embodiment, step S120 includes:

[0049] S121. Calculate the light intensity attenuation factor based on the angle between the normal direction of the equivalent pixel unit and the viewing direction of the preset target observer.

[0050] S122. Calculate the distance attenuation factor based on the spatial distance from the geometric center of the equivalent pixel unit to the preset target observer;

[0051] S123. Multiply the light intensity attenuation factor by the distance attenuation factor to obtain the perceived brightness attenuation law of the equivalent pixel unit under the view of the preset target observer.

[0052] When constructing a light field emission model to calculate the brightness attenuation law of each equivalent pixel unit based on the visual luminescent unit model and the spatial position of the preset target observer, the light intensity attenuation factor is first calculated based on the angle between the normal direction of the equivalent pixel unit and the viewing direction of the preset target observer. The equivalent pixel unit is a ring-shaped luminescent area formed by the rotational motion of the luminescent blades under the effect of visual persistence. Its normal direction is determined by the flight attitude of the UAV and has been adjusted to face the preset target observer. The viewing direction of the preset target observer is a straight line from the geometric center of the equivalent pixel unit to the observer's position. The system obtains the light intensity attenuation factor by calculating the cosine value of the angle between this normal vector and the viewing vector. This factor reflects the tilt of the luminescent surface relative to the viewing angle. When the normal is aligned with the viewing direction, the cosine value is 1, and there is no light intensity attenuation; when the normal deviates from the viewing direction, the cosine value decreases, and the light intensity weakens accordingly. This process, based on the Lambertian diffuse reflection principle, realistically simulates the brightness change of the luminescent surface under different viewing angles.

[0053] Secondly, the distance attenuation factor is calculated based on the spatial distance from the geometric center of the equivalent pixel unit to the preset target observer. The geometric center of the equivalent pixel unit is the center of its annular region, and its position is determined by the three-dimensional spatial coordinates of the drone. The position of the preset target observer is a pre-set fixed spatial point, which can be adjusted according to the performance and display requirements. The system calculates the Euclidean distance between these two points as the light propagation path length. Based on the inverse square law of light attenuation in free space, the system uses the square of this distance as the denominator to calculate the distance attenuation factor, i.e., the attenuation factor equals 1 divided by the square of the distance. This factor is used to simulate the physical phenomenon that light intensity naturally decreases as the propagation distance increases.

[0054] Finally, the system multiplies the light intensity attenuation factor with the distance attenuation factor to obtain the perceived brightness attenuation law of the equivalent pixel unit under the preset target observer's viewpoint. This product operation integrates the two independent optical attenuation effects of viewpoint dependence and distance dependence to form the final brightness correction coefficient. This coefficient is used to subsequently calculate the brightness value that each equivalent pixel unit should output, ensuring that the brightness presented by the drone at different positions and orientations conforms to the real optical laws during the synthesis of target visual content, avoiding local overbrightness, underbrightness, or distortion of the image due to differences in viewpoint or distance, thereby achieving a high-fidelity and natural aerial visual presentation.

[0055] In one embodiment, step S130 includes:

[0056] S131. Based on the radial length of the light-emitting blade and the number of light-emitting segments divided along the length direction of the light-emitting blade, determine the minimum spatial resolution required for the equivalent pixel unit in visual persistence.

[0057] S132. Based on the minimum spatial resolution and the rotational angular velocity of the light-emitting blades, calculate the minimum light-emitting command update frequency required to maintain visual continuity.

[0058] When establishing a human visual persistence fusion model based on the constraints of human visual persistence and the geometric dimensions of the luminous propellers of each UAV, the minimum spatial resolution required for an equivalent pixel unit under visual persistence is first determined according to the radial length of the luminous propeller and the number of luminous segments along its length. Since the luminous propeller is a strip-shaped structure extending radially along the rotor axis, with multiple separately controllable luminous bodies arranged along its length, it can be divided into multiple independently controllable luminous segments, each corresponding to an independently controllable luminous area. When the UAV rotates, these luminous segments sequentially sweep across the observer's field of vision in space. Due to the human visual persistence effect, the light traces of adjacent luminous segments visually merge into a continuous annular light band.

[0059] The system determines the density of visual sampling points covered per unit angle based on the number of light-emitting segments and the radial length of the blades. This density is the minimum spatial resolution required for the equivalent pixel unit to maintain image continuity in visual retention. Essentially, it ensures that the visual interval between adjacent light-emitting segments is less than the minimum visual acuity threshold that the human eye can distinguish under any viewing angle, thereby avoiding visual defects such as discontinuity, stripes, or flickering.

[0060] Subsequently, based on the minimum spatial resolution and the rotational angular velocity of the luminous propellers, the minimum luminous command update frequency required to maintain visual continuity is calculated. The rotational angular velocity of the luminous propellers is determined by the motor speed of the UAV, reflecting the angle of rotation per unit time. The system multiplies the minimum spatial resolution by the rotational angular velocity to obtain the number of luminous commands that need to be updated per unit time, which is the minimum luminous command update frequency required to maintain visual continuity. This frequency ensures that the system can update the brightness and color of the corresponding luminous segment in a timely manner every time the propeller rotates by one angular unit, making the visual fusion process smooth and without delay. If the update frequency is lower than this minimum value, the human eye will perceive the discreteness between the luminous segments, resulting in image blurring or flickering. If the frequency is reached or exceeded, the visual persistence effect can effectively integrate the output of all luminous segments to form a stable, continuous, and high-fidelity circular optical disc image, thereby achieving high-density visual presentation.

[0061] In one embodiment, step S140 includes:

[0062] S141. Project the target visual content onto a virtual imaging plane based on the preset target observer;

[0063] S142. Divide the virtual imaging plane into multiple regions, each region corresponding to the coverage area of ​​one equivalent pixel unit;

[0064] S143. Based on the annular coverage area of ​​each of the equivalent pixel units, optimize the spatial position of the UAV deployment so that each of the equivalent pixel units covers the visible area of ​​the target visual content on the virtual imaging plane.

[0065] When calculating the spatial position information of each UAV based on the target visual content using a visual luminescence unit model, the target visual content is first projected onto a virtual imaging plane with a preset target observer as the reference. The target visual content is a static image or dynamic frame sequence to be presented, containing brightness and color distribution information. The preset target observer is a fixed spatial position set in advance to evaluate the visual presentation effect, such as the center of the audience or the camera shooting point. The system uses this observer as the viewpoint and projects the target visual content orthogonally along the line of sight onto a virtual plane perpendicular to the observation line of sight. This plane is located at a certain distance in front of the observer, and its function is to simulate the two-dimensional image plane "seen" by the human eye or camera, thereby transforming the visual target in three-dimensional space into a two-dimensional distribution map.

[0066] Subsequently, the virtual imaging plane is divided into multiple regions, each corresponding to the coverage area of ​​an equivalent pixel unit. The equivalent pixel unit is a ring-shaped luminous area formed by the rotation of the luminous propellers. Its projection onto the virtual imaging plane is a ring-shaped area, the inner and outer diameters of which are determined by the geometric dimensions of the luminous propellers, and the center position is determined by the spatial position projection of the corresponding UAV. Based on the area of ​​this ring-shaped area, the system divides the virtual imaging plane into several non-overlapping, seamlessly connected sub-regions. The shape and area of ​​each sub-region match the projection area of ​​an equivalent pixel unit, ensuring that each sub-region can be completely covered by the equivalent pixel unit of a UAV, thereby achieving pixel-level partitioning mapping of the target image.

[0067] Finally, based on the annular coverage area of ​​each equivalent pixel unit, the spatial position of the deployed drones is optimized, ensuring that each equivalent pixel unit covers the visible area of ​​the target visual content on the virtual imaging plane. The system determines whether each sub-region needs to be covered based on its brightness and color requirements in the target image. For regions with visible content in the target image, the system automatically calculates and assigns the three-dimensional spatial coordinates of the drones using a geometric matching algorithm, aligning the projection center of each drone's equivalent pixel unit with the center of its corresponding sub-region, and ensuring that its annular coverage completely covers that sub-region. For background regions without content in the target image, no drones are assigned, or only a small number of redundant units are retained at the edges to maintain overall structural stability. This deployment process does not rely on manual placement but is based on automatic matching of the annular coverage area and the image content distribution, ensuring complete, seamless, and non-overlapping coverage of the target visual content with the minimum number of drones, thereby reducing system size and control complexity while meeting visual presentation quality requirements.

[0068] Furthermore, step S140 also includes:

[0069] S144. Calculate the target brightness value of each equivalent pixel unit under the viewpoint of the preset target observer according to the light field emission model;

[0070] S145. Determine the target color information of each equivalent pixel unit based on the color distribution of the target visual content in the corresponding area of ​​the equivalent pixel unit.

[0071] S146. Combine the target brightness value with the target color information to form the display information of each of the equivalent pixel units.

[0072] When calculating the display information and emission command update frequency of each equivalent pixel unit using the fusion model of light field emission and human visual persistence, the system first calculates the target brightness value of each equivalent pixel unit under the preset target observer's viewpoint based on the light field emission model. The light field emission model has constructed a perceptual brightness attenuation law based on the angle between the normal direction of the equivalent pixel unit and the observer's line of sight, as well as the spatial distance from the geometric center of the equivalent pixel unit to the observer. The system uses this attenuation law as a correction coefficient, applying it to the original brightness value of the corresponding area in the target visual content, thereby obtaining the final target brightness value that each equivalent pixel unit should present under the observer's viewpoint. This process does not change the brightness distribution of the target image itself; it only performs spatial correction on the output brightness of each unit based on optical physics laws, ensuring that the brightness presented by the drone at different positions and orientations matches the actual perceptual effect of the human eye, avoiding local over-brightness or under-brightness caused by distance or viewing angle tilt.

[0073] Based on the color distribution of the target visual content in the corresponding area of ​​the equivalent pixel unit, the target color information of each equivalent pixel unit is determined. On the virtual imaging plane, the projection area of ​​each equivalent pixel unit corresponds one-to-one with the pixel area of ​​the target visual content. The system reads the RGB color value of this area in the target image as the color information to be output by the equivalent pixel unit. This color information is not corrected for light field attenuation and directly preserves the color composition of the original image, ensuring complete reproduction of the image's hue, saturation, and tone. This step is independent of brightness calculation and extracts color solely based on the spatial mapping relationship of the image content, without introducing any additional processing such as color correction, white balance, or color gamut conversion.

[0074] The system combines the target brightness value with the target color information to form the display information for each equivalent pixel unit. The brightness value of each equivalent pixel unit is used as an intensity modulation coefficient, which is multiplied with the corresponding color information to generate the final emission control parameters—the brightness and color combination that each emission segment should output. This display information serves as the input for subsequent control commands, driving the UAV's emission units to emit light at the specified brightness and color, thereby accurately reproducing the brightness and color distribution of the target image visually.

[0075] In one embodiment, step S150 includes:

[0076] S151. Based on the spatial location information, generate a smooth three-dimensional flight trajectory to ensure that each UAV maintains a safe distance and attitude stability during flight;

[0077] S152. Bind the display information to the light emission command update frequency to generate a timestamp-aligned light emission control sequence;

[0078] S153. Integrate the flight trajectory and the light emission control sequence into a unified control command package, which includes position command, attitude command and light emission parameter command.

[0079] When planning the flight trajectories of each UAV based on spatial location information and generating control commands for each UAV by combining the flight trajectories with the displayed information, it is necessary to generate smooth three-dimensional flight trajectories based on the calculated spatial location information of each UAV to ensure that each UAV maintains a safe distance and attitude stability during flight.

[0080] During this process, the system uses trajectory interpolation to generate continuous, abrupt flight paths based on the target positions of each UAV in three-dimensional space, enabling the UAVs to smoothly transition from the starting point to the target position. In path planning, the system automatically calculates the minimum spatial distance between adjacent UAVs, ensuring this distance is always greater than a preset safety threshold to avoid collisions during flight. Simultaneously, based on the requirement that the normal direction of the equivalent pixel unit must always point towards the preset target observer, the system synchronously plans the flight attitude of each UAV, ensuring stable pitch and yaw angles during movement. This guarantees that the normal direction of the rotation plane of the luminous propellers remains aligned with the observer, thereby maintaining the continuity and consistency of visual imaging.

[0081] Subsequently, the display information is bound to the emission command update frequency to generate a timestamp-aligned emission control sequence. The display information includes the target brightness value and target color information for each equivalent pixel unit. The emission command update frequency is calculated by a human visual persistence fusion model to ensure that the emission segment updates at a sufficient frequency during rotation. The system assigns a precise timestamp to each emission control command, which is synchronized with the UAV's rotation phase, so that the execution time of each brightness and color command corresponds exactly to the sampling position of a certain emission segment when the emission propeller rotates. This process does not rely on an external clock synchronization device, but achieves time alignment based on the inherent relationship between the UAV's own rotational angular velocity and the command update frequency, ensuring that the image is flicker-free and free of ghosting under the visual persistence effect.

[0082] Finally, the flight trajectory and illumination control sequence are integrated into a unified control command package, which includes position commands, attitude commands, and illumination parameter commands. The system uses the UAV's three-dimensional spatial coordinates as the position command, the flight attitude angle as the attitude command, and the brightness and color values ​​of each illumination segment as the illumination parameter commands. These three are packaged into a single control data packet based on a unified time reference. This data packet is synchronously transmitted to each UAV via a wireless communication link. After receiving the packet, the flight control system executes trajectory tracking, attitude maintenance, and illumination control respectively, achieving coordinated operation of flight motion and visual presentation. This integration method ensures strict synchronization between the flight and illumination subsystems in time and space, avoiding image misalignment or flickering caused by command delays or asynchrony, thereby achieving high-precision and high-stability presentation of target visual content in the air.

[0083] As described in the above embodiments, the UAV swarm control method of the present invention combines the rotational motion of the luminous propellers with the persistence of vision effect of the human eye to construct a high-density aerial imaging system with equivalent pixel units as the basic visual units, fundamentally breaking through the information expression limit of "one pixel per drone" in traditional UAV light shows. The single-drone multi-pixel, low-density swarm, and high-fidelity imaging capabilities achieved by this method give it the potential to expand towards higher precision, wider applicability, and stronger stability, building upon existing technologies supporting large-scale nighttime performance scenarios.

[0084] In large-scale urban landmark events and festive light shows, this method can achieve higher resolution dynamic image presentation with fewer drones, such as stably projecting complete text slogans, brand logos or traditional art patterns over city squares without relying on hundreds of drones. This significantly reduces airspace management pressure, energy consumption and deployment costs, while improving the edge clarity and color reproduction of the image, making the visual effect closer to the delicate performance of ground LED screens.

[0085] In dynamic performance scenarios such as sports events and concerts, this method supports light field rendering based on the preset target observer's perspective, ensuring that the audience can obtain a consistent and distortion-free visual experience no matter where they are in the stands. Combined with real-time control of flight attitude, it can achieve dynamic visual effects with a sense of spatial depth, such as "a glowing sphere slowly rotating" and "text spreading outward from the center", enhancing the immersive atmosphere and providing a new physical carrier for artistic expression.

[0086] In the fields of emergency command and public safety, this method can be applied to low-altitude information signage. For example, at disaster sites, a small number of drones can quickly take off and project evacuation routes, danger zone boundaries, or rescue instructions with high-contrast luminous patterns. Their ring-shaped optical disc structure still has good visibility in smoke or low-light environments, and because they do not require dense formation, their flight safety is higher, their communication load is lower, and they are suitable for stable operation in complex electromagnetic environments.

[0087] Therefore, this invention not only raises the technical ceiling of drone light shows, but also opens up a new, efficient, reliable, and scalable path for aerial visual presentation through systematic modeling and engineering implementation, and has long-term application value in multiple fields such as cultural performances, public safety, and urban media.

[0088] Figure 8 This is a schematic block diagram of a drone swarm control device 600 provided in an embodiment of the present invention. Figure 8 As shown, corresponding to the above-described UAV swarm control method, the present invention also provides a UAV swarm control device 600. This UAV swarm control device 600 includes a unit for executing the above-described UAV swarm control method, and the device can be configured in a desktop computer, tablet computer, smartphone, or other terminal.

[0089] Specifically, please refer to Figure 8 The drone swarm control device 600 includes:

[0090] The visual luminescence unit modeling unit 610 is used to establish a visual luminescence unit model based on the geometric dimension information of the luminescence blades of each UAV, the relative positional relationship between the UAV fuselage and the luminescence blades, and the flight attitude information of the UAV, and to define the luminescence area formed by the luminescence blades during the flight of the UAV as an equivalent pixel unit.

[0091] The light field emission modeling unit 620 is used to construct a light field emission model for calculating the brightness attenuation law of each equivalent pixel unit based on the visual luminous unit model and the spatial position of the preset target observer.

[0092] The visual persistence fusion modeling unit 630 is used to establish a human visual persistence fusion model based on the human visual persistence constraints and the geometric dimension information of the light-emitting propellers of each UAV. The human visual persistence fusion model is used to calculate the light-emitting command update frequency to be sent to the UAV based on the minimum light-emitting propeller rotation frequency required to maintain stable imaging.

[0093] The collaborative display computing unit 640 is used to calculate the spatial position information of each of the UAVs based on the target visual content through the visual luminescence unit model, and to calculate the display information and luminescence command update frequency of each of the equivalent pixel units through the light field emission model and the human eye visual persistence fusion model. The display information includes brightness information and color information.

[0094] The instruction generation and execution unit 650 is used to plan the flight trajectory of each of the UAVs based on the spatial location information, generate control instructions for each UAV by combining the flight trajectory of the UAVs, the display information and the light-emitting instruction update frequency, and send them to each UAV for execution.

[0095] In one embodiment, the visual emission unit modeling unit 610 includes:

[0096] A radial range determination unit is used to determine the radial range of the annular coverage area formed by the equivalent pixel unit in space based on the inner and outer diameters of the light-emitting blades.

[0097] The geometric center determination unit is used to determine the correspondence between the geometric center of the equivalent pixel unit and the fuselage coordinate system of the UAV based on the relative positional relationship between the fuselage and the light-emitting propeller.

[0098] The normal direction determination unit is used to determine the normal direction of the equivalent pixel unit based on the flight attitude information, so that the normal direction of the equivalent pixel unit is oriented towards the preset target observer.

[0099] In one embodiment, the light field emission modeling unit 620 includes:

[0100] A light intensity attenuation calculation unit is used to calculate a light intensity attenuation factor based on the angle between the normal direction of the equivalent pixel unit and the viewing direction of the preset target observer.

[0101] The distance attenuation calculation unit is used to calculate the distance attenuation factor based on the spatial distance from the geometric center of the equivalent pixel unit to the preset target observer;

[0102] The total brightness attenuation calculation unit is used to multiply the light intensity attenuation factor by the distance attenuation factor to obtain the perceived brightness attenuation law of the equivalent pixel unit under the view of the preset target observer.

[0103] In one embodiment, the visual persistence fusion modeling unit 630 includes:

[0104] A spatial resolution determination unit is used to determine the minimum spatial resolution required for the equivalent pixel unit in visual persistence based on the radial length of the light-emitting blade and the number of light-emitting segments divided along the length direction of the light-emitting blade.

[0105] The instruction frequency calculation unit is used to calculate the minimum emission instruction update frequency required to maintain visual continuity based on the minimum spatial resolution and the rotational angular velocity of the emission blades.

[0106] In one embodiment, the collaborative display computing unit 640 includes:

[0107] A visual content projection unit is used to project the target visual content onto a virtual imaging plane based on the preset target observer;

[0108] A region division unit is used to divide multiple regions on the virtual imaging plane, and each region corresponds to the coverage area of ​​one equivalent pixel unit;

[0109] The location optimization deployment unit is used to optimize the spatial position of the UAV based on the annular coverage area of ​​each of the equivalent pixel units, so that each of the equivalent pixel units covers the visible area of ​​the target visual content on the virtual imaging plane.

[0110] Furthermore, the collaborative display computing unit 640 also includes:

[0111] The target brightness calculation unit is used to calculate the target brightness value of each equivalent pixel unit under the view of the preset target observer according to the light field emission model.

[0112] The target color determination unit is used to determine the target color information of each equivalent pixel unit based on the color distribution of the target visual content in the corresponding area of ​​the equivalent pixel unit.

[0113] The display information combination unit is used to combine the target brightness value with the target color information to form the display information of each of the equivalent pixel units.

[0114] In one embodiment, the instruction generation and execution unit 650 includes:

[0115] The flight trajectory generation unit is used to generate a smooth three-dimensional flight trajectory based on the spatial position information, ensuring that each UAV maintains a safe distance and attitude stability during flight;

[0116] A light emission control sequence generation unit is used to bind the display information with the light emission command update frequency to generate a timestamp-aligned light emission control sequence;

[0117] The command integration unit is used to integrate the flight trajectory and the light emission control sequence into a unified control command package, which includes position commands, attitude commands and light emission parameter commands.

[0118] The aforementioned drone swarm control device 600 can be implemented as a computer program, which can, for example... Figure 9 It runs on the computer device shown.

[0119] Please see Figure 9 , Figure 9 This is a schematic block diagram of a computer device 500 provided in an embodiment of this application. The computer device 500 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a desktop computer, tablet computer, or smartphone. The server can be a standalone server or a server cluster composed of multiple servers.

[0120] See Figure 9 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0121] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a drone swarm control method.

[0122] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0123] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a drone swarm control method.

[0124] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0125] The processor 502 is used to run a computer program 5032 stored in a memory to implement the steps of the above method.

[0126] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0127] It will be understood by those skilled in the art 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 includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0128] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the steps of the above-described method.

[0129] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0130] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0131] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0132] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0133] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0134] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for controlling a swarm of unmanned aerial vehicles (UAVs), characterized in that, The method, applied to a drone with luminous propellers, includes: Based on the geometric dimensions of the luminous propellers of each UAV, the relative positional relationship between the UAV's fuselage and the luminous propellers, and the UAV's flight attitude information, a visual luminous unit model is established, and the luminous area formed by the luminous propellers during the flight of the UAV is defined as an equivalent pixel unit. Based on the visual luminescence unit model and the spatial position of the preset target observer, a light field emission model is constructed to calculate the brightness attenuation law of each equivalent pixel unit. The model includes: calculating a light intensity attenuation factor based on the angle between the normal direction of the equivalent pixel unit and the line of sight of the preset target observer; calculating a distance attenuation factor based on the spatial distance from the geometric center of the equivalent pixel unit to the preset target observer; and multiplying the light intensity attenuation factor by the distance attenuation factor to obtain the perceived brightness attenuation law of the equivalent pixel unit from the perspective of the preset target observer. Based on the human visual persistence constraint and the geometric dimension information of the light-emitting propellers of each UAV, a human visual persistence fusion model is established. The human visual persistence fusion model is used to calculate the light emission command update frequency to be sent to the UAV based on the minimum light-emitting propeller rotation frequency required to maintain stable imaging. Based on the target visual content, the spatial position information of each UAV is calculated through the visual luminescence unit model, and the display information and luminescence command update frequency of each equivalent pixel unit are calculated through the light field emission model and the human eye visual persistence fusion model. The display information includes brightness information and color information. Based on the spatial location information, the flight trajectory of each UAV is planned. The flight trajectory of the UAV, the display information, and the light emission command update frequency are combined to generate control commands for each UAV and send them to each UAV for execution. 2.The method of claim 1, wherein, The step of establishing a visual luminescent unit model based on the geometric dimensions of the luminescent propellers of each UAV, the relative positional relationship between the UAV's fuselage and the luminescent propellers, and the UAV's flight attitude information includes: Based on the inner and outer diameters of the light-emitting blades, the radial range of the annular coverage area formed by the equivalent pixel unit in space is determined. Based on the relative positional relationship between the fuselage and the light-emitting propellers, the correspondence between the geometric center of the equivalent pixel unit and the fuselage coordinate system of the UAV is determined. Based on the flight attitude information, the normal direction of the equivalent pixel unit is determined, so that the normal direction of the equivalent pixel unit is oriented toward the preset target observer. 3.The method of claim 1, wherein, The steps for establishing a human visual persistence fusion model based on human visual persistence constraints and the geometric dimensions of the luminous propellers of each UAV include: The minimum spatial resolution required for visual persistence of the equivalent pixel unit is determined based on the radial length of the light-emitting blade and the number of light-emitting segments divided along the length direction of the light-emitting blade. Based on the minimum spatial resolution and the rotational angular velocity of the luminous blades, the minimum luminous command update frequency required to maintain visual continuity is calculated. 4.The method of claim 1, wherein, The step of calculating the spatial position information of each UAV based on the target visual content and using the visual luminescence unit model includes: The target visual content is projected onto a virtual imaging plane based on the preset target observer; The virtual imaging plane is divided into multiple regions, each region corresponding to the coverage area of ​​one equivalent pixel unit; Based on the annular coverage area of ​​each equivalent pixel unit, the spatial position of the UAV is optimized so that each equivalent pixel unit covers the visible area of ​​the target visual content on the virtual imaging plane. 5.The method of claim 1, wherein, The step of calculating the display information and light emission command update frequency of each equivalent pixel unit through the light field emission model and the human eye visual persistence fusion model includes: Based on the light field emission model, calculate the target brightness value of each equivalent pixel unit under the viewpoint of the preset target observer; Based on the color distribution of the target visual content in the corresponding area of ​​the equivalent pixel unit, the target color information of each equivalent pixel unit is determined; The target brightness value and the target color information are combined to form the display information of each equivalent pixel unit. 6.The UAV swarm control method of claim 1, wherein, The steps of planning the flight trajectory of each UAV based on the spatial location information, generating control commands for each UAV by combining the UAV flight trajectory and the display information, and issuing them to each UAV for execution include: Based on the spatial location information, a smooth three-dimensional flight trajectory is generated to ensure that each UAV maintains a safe distance and attitude stability during flight; The display information is bound to the light emission command update frequency to generate a timestamp-aligned light emission control sequence; The flight trajectory and the light emission control sequence are integrated into a unified control command package, which includes position commands, attitude commands, and light emission parameter commands.

7. An unmanned aerial vehicle swarm control apparatus, characterized by, Used to perform the drone swarm control method as described in any one of claims 1 to 6.

8. A computer device, comprising: The computer device includes a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to perform the steps of the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which includes program instructions that, when executed by a processor, can implement the steps of the method as described in any one of claims 1 to 6.

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