A virtual-real fusion interaction control method and system based on five-dimensional dynamic topology

Abstract

This invention discloses a virtual-real fusion interactive control method and system based on five-dimensional dynamic topology, relating to the field of virtual reality technology. By performing hierarchical processing and interaction density clustering of five-dimensional topological data, this invention can more comprehensively depict the dynamic relationships between multi-dimensional nodes, ensuring the rationality and real-time nature of sub-topology partitioning. Furthermore, by dynamically adjusting the sub-topology structure through collaborative coding information and historical state weights, the stability and accuracy of interactive mapping are improved. Simultaneously, by leveraging a cultural symbol dictionary to generate symbolic rendering parameters, not only is the cultural expressiveness of virtual-real interaction enhanced, but the precise correspondence between multi-level, multi-dimensional symbols and physical rendering is also guaranteed.

Description

Technical Field

[0001] This invention relates to the field of virtual reality technology, and in particular to a virtual-real fusion interactive control method and system based on five-dimensional dynamic topology. Background Technology

[0002] With the rapid development of information technology, artificial intelligence, and multimedia rendering technology, virtual reality (VR), augmented reality (AR), and mixed reality (MR) are increasingly being applied to scenarios such as large-scale public performances, sporting events, and immersive interactive experiences. In these applications, achieving real-time fusion and interactive control of virtual elements and real-world events has become a core research direction. In recent years, edge computing and distributed control architectures have been introduced into virtual-real fusion systems to alleviate the computational pressure on central servers and improve response speed. Simultaneously, dynamic topology theory and multidimensional data modeling have been applied to the structured representation of complex scenes, enabling the system to more accurately depict the interactive relationships between audience groups, environmental signals, and device nodes.

[0003] Existing technologies primarily focus on two-dimensional or three-dimensional spatiotemporal modeling and unidirectional rendering synchronization. While these technologies can meet some real-time rendering and synchronization requirements, they still have significant limitations in areas such as multi-node collaboration, cross-regional synchronization, and the expression of cultural symbols. For example, in complex performances or large-scale events, interactions between nodes have multi-dimensional and multi-level characteristics. Traditional two-dimensional or three-dimensional topological models struggle to fully express the dynamic evolution process, resulting in insufficient abstraction of interactive information and affecting the accuracy of rendering control. Secondly, existing synchronization mechanisms often employ centralized scheduling or single timestamp alignment, which can easily lead to latency accumulation and command drift when dealing with a large number of edge nodes, making it difficult to meet the millisecond-level latency requirements of virtual-real fusion scenarios. Furthermore, existing systems lack structured modeling methods for cultural symbol mapping, often remaining at a single mapping level of color and shape. This makes it difficult to support an efficient correspondence between multi-dimensional cultural semantics and visual expression, resulting in a discrepancy between the rendering effect and the cultural intent. Summary of the Invention

[0004] In view of the problems existing in the virtual-real fusion control technology, this invention is proposed.

[0005] Therefore, the problem to be solved by this invention is how to achieve high-precision fusion between virtual scenes and real scenes as a whole.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a virtual-real fusion interactive control method based on five-dimensional dynamic topology, comprising: edge nodes processing the collected five-dimensional topology data and dividing it into multiple sub-topologies according to node interaction density, generating co-coding information for each sub-topology at the edge; a central control unit receiving the co-coding information, allocating neighborhood weights based on historical states, and distributing it to the corresponding edge nodes; the edge nodes correcting the sub-topologies to generate updated co-coding information; the central control unit mapping the updated co-coding information to concentric circle rendering parameters according to a cultural symbol dictionary, and distributing it to the edge nodes; the edge nodes performing linkage mapping based on the rendering parameters and sub-topologies to generate local rendering instructions; the central control unit calculating the synchronization deviation based on the time stamp information of the edge nodes and distributing synchronization compensation amounts to the edge nodes; the edge nodes adjusting the execution timing of the local rendering instructions according to the synchronization compensation amounts, and simultaneously outputting rendering results to the on-site display terminal and the broadcast system.

[0008] As a preferred embodiment of the virtual-real fusion interactive control method based on five-dimensional dynamic topology described in this invention, the following steps are included: processing the collected five-dimensional topology data includes: edge nodes receiving five-dimensional topology data from the central controller and performing initial layering according to ground layer, facade layer, space layer, audience layer, and virtual layer to form a layered topology input set; dividing the data into multiple sub-topologies based on node interaction density includes: in the layered topology input set, edge nodes perform local clustering based on node interaction density, dividing high-density interaction areas in the same layer into sub-topology units; generating collaborative coding information includes: after forming sub-topology units, edge nodes assign a level identifier and a position identifier to each node according to its topology level and spatial position in the sub-topology; edge nodes combine the level identifier, intra-layer spatial position, and inter-node interaction density of each node in the sub-topology to form collaborative coding information.

[0009] As a preferred embodiment of the virtual-real fusion interactive control method based on five-dimensional dynamic topology described in this invention, the following steps are included: Local clustering based on node interaction density includes: statistically analyzing the communication frequency, data exchange count, or operation trigger count between each node and its neighboring nodes, and calculating the average interaction value with all neighboring nodes, using this average value as the node's interaction density value; after obtaining the interaction density values ​​of all nodes within the topology layer, setting the density threshold of the topology layer based on the average interaction density and fluctuation amplitude of each node; when the node's interaction density value is higher than the density threshold, the node is marked as a candidate core node; otherwise, it is considered an ordinary node; for each candidate core node, the neighborhood radius is increased layer by layer along concentric circles until the average interaction density of the new extended layer is lower than the density threshold, forming a sub-topology unit.

[0010] As a preferred embodiment of the virtual-real fusion interactive control method based on five-dimensional dynamic topology described in this invention, the method of allocating neighborhood weights based on historical states includes: the central control unit receiving the co-coding information uploaded by each edge node, including the hierarchical identifier, concentric circle expansion layer number, and interaction density of the sub-topology unit where each candidate core node is located, and obtaining the historical interaction density record of the sub-topology unit; for each candidate core node, calculating the difference between the current interaction density and the historical interaction density as the real-time deviation; the neighborhood weight is composed of the candidate core node's own interaction density contribution and the interaction intensity contribution between sub-topology units through weighting, wherein the own interaction density contribution is the current candidate core node's interaction density divided by the sum of the interaction densities of candidate core nodes within the sub-topology unit; the neighborhood interaction contribution is the sum of the interaction densities of the current sub-topology unit and its neighboring sub-topology units divided by the sum of all neighborhood interaction densities.

[0011] As a preferred embodiment of the virtual-real fusion interactive control method based on five-dimensional dynamic topology described in this invention, the edge nodes correct the sub-topology by: sorting the neighborhood weights from high to low; wherein, high neighborhood weight nodes are distributed in the inner layer closer to the center of the sub-topology unit, and low neighborhood weight nodes are distributed in the outer layer; the relative distance between candidate core nodes within the same layer is linearly adjusted according to the weight, while maintaining the hierarchical order; the radius position of each candidate core node is adjusted by combining historical interaction density and real-time deviation: if the real-time deviation is positive and the neighborhood weight is higher than the average neighborhood weight, the radius is reduced by the product of the scaling factor and the real-time deviation; if the real-time deviation is negative and the neighborhood weight is lower than the average neighborhood weight, the radius is increased by the product of the scaling factor and the absolute value of the real-time deviation; if the real-time deviation is 0, the radius remains unchanged; the hierarchical identifier of each candidate core node, the adjusted intra-layer spatial position, and the original or real-time interaction density are combined to form updated co-coding information.

[0012] As a preferred embodiment of the virtual-real fusion interactive control method based on five-dimensional dynamic topology described in this invention, the step of mapping the updated co-coding information to concentric circle rendering parameters includes: dividing the sub-topology units and reading the hierarchical identifier and intra-layer spatial position of each candidate core node; searching for the symbol set corresponding to the hierarchical level of the candidate core node from the cultural symbol dictionary; mapping the hierarchical identifier to the radius of the concentric circle, the intra-layer spatial position to the circumferential angle or offset, and the interaction density value to the symbol rendering intensity; generating concentric circle rendering parameters for each candidate core node, including: radius, angle, rendering symbol, and symbol rendering intensity.

[0013] As a preferred embodiment of the virtual-real fusion interactive control method based on five-dimensional dynamic topology described in this invention, the generation of local rendering instructions includes: traversing the concentric circle rendering parameters of each candidate core node and calculating the corresponding coordinates on the actual display device; mapping the radius to the display layer position, the angle to the relative position within the layer, and the rendering symbol and symbol rendering intensity to the light point and brightness control of the device rendering instructions; performing linkage mapping on the concentric circle rendering parameters of candidate core nodes within the same sub-topology to ensure the continuity of the concentric circle layer and the consistency of the relative positions between candidate core nodes, thereby generating a complete set of local rendering instructions; the set of local rendering instructions includes the output commands of each candidate core node on the display device.

[0014] As a preferred embodiment of the virtual-real fusion interactive control method based on five-dimensional dynamic topology described in this invention, the generation of the synchronization compensation amount includes: for each candidate core node, calculating the time difference between the local time stamp and the unified reference time of the central control unit; correcting the time difference according to the level of the candidate core node by different level allocation ratios; multiplying the time difference by the radius ratio coefficient according to the radius position of the candidate core node in the concentric circle level to obtain the corrected time deviation of the candidate core node; and averaging the corrected time deviations of all candidate core nodes in the same sub-topology to generate the synchronization compensation amount.

[0015] As a preferred embodiment of the virtual-real fusion interactive control method based on five-dimensional dynamic topology described in this invention, the step of adjusting the execution timing of local rendering instructions according to the synchronization compensation amount includes: traversing the local rendering instructions of all candidate core nodes within the sub-topology unit, and linearly offsetting the execution time of the local rendering instructions according to the synchronization compensation amount: if the synchronization compensation amount is positive, then delaying the execution of the instruction corresponding to the synchronization compensation amount; if the synchronization compensation amount is negative, then advancing the execution of the instruction corresponding to the absolute value of the synchronization compensation amount; maintaining the hierarchical order and concentric circle hierarchical position of the candidate core nodes within the sub-topology unchanged; and outputting the adjusted rendering instruction set to the on-site display terminal and the broadcasting system to achieve multi-terminal synchronous rendering.

[0016] Secondly, the present invention provides a virtual-real fusion interactive control system based on a five-dimensional dynamic topology, comprising:

[0017] The sub-topology generation module is used by edge nodes to process the collected five-dimensional topology data and divide it into multiple sub-topologies based on node interaction density. Cooperative coding information is generated for each sub-topology on the edge side.

[0018] The weight allocation module is used by the central control unit to receive the co-coding information, allocate neighborhood weights in combination with historical states, and send them to the corresponding edge nodes; the edge nodes correct the sub-topology to generate updated co-coding information.

[0019] The rendering mapping module is used by the central control unit to map the updated co-coding information into concentric circle rendering parameters based on the cultural symbol dictionary, and distribute them to the edge nodes. The edge nodes perform linkage mapping based on the rendering parameters and sub-topology to generate local rendering instructions.

[0020] The synchronization compensation module is used by the central control unit to calculate the synchronization deviation based on the time stamp information of each edge node, and to send the synchronization compensation amount to the edge node. The edge node adjusts the execution timing of local rendering instructions according to the synchronization compensation amount, and outputs the rendering results to the on-site display terminal and the broadcast system.

[0021] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, they implement the steps of the virtual-real fusion interactive control method based on five-dimensional dynamic topology as described in the first aspect of the present invention.

[0022] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, they implement the steps of the virtual-real fusion interactive control method based on five-dimensional dynamic topology as described in the first aspect of the present invention.

[0023] The beneficial effects of this invention are as follows: By performing hierarchical processing and interaction density clustering on five-dimensional topological data, this invention can more comprehensively depict the dynamic relationships between multi-dimensional nodes, ensuring the rationality and real-time nature of sub-topology partitioning; on this basis, by dynamically adjusting the sub-topological structure through collaborative coding information and historical state weights, the stability and accuracy of interaction mapping are improved; at the same time, by using a cultural symbol dictionary to generate symbolic rendering parameters, not only is the cultural expressiveness of virtual-real interaction enhanced, but also the accurate correspondence between multi-level, multi-dimensional symbols and physical rendering is ensured.

[0024] Overall, this invention breaks through the limitations of traditional two-dimensional or three-dimensional modeling and rendering, and forms a systematic optimization in topology modeling, rendering expression and time synchronization. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of a virtual-real fusion interactive control method based on five-dimensional dynamic topology.

[0027] Figure 2 This is a structural diagram of a virtual-real fusion interactive control system based on a five-dimensional dynamic topology. Detailed Implementation

[0028] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0029] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0030] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0031] Figure 1 This is a flowchart of a virtual-real fusion interactive control method based on five-dimensional dynamic topology according to an embodiment of the present invention. Figure 1 As shown, the virtual-real fusion interactive control method based on five-dimensional dynamic topology includes:

[0032] S1: Edge nodes process the collected five-dimensional topology data and divide it into multiple sub-topologies based on node interaction density, generating collaborative coding information for each sub-topology on the edge side.

[0033] S1.1: Process the collected five-dimensional topology data.

[0034] Edge nodes receive five-dimensional topology data from the central controller and perform initial layering according to ground layer, facade layer, space layer, audience layer, and virtual layer to form a layered topology input set.

[0035] It should be noted that conventional layering methods typically only divide spatial coordinates into three dimensions, ignoring audience interaction and the overlay effect of virtual rendering layers, making it difficult to support complex multi-terminal interactions. This invention adopts a five-dimensional topological input structure, explicitly dividing topological information into five independent dimensions: ground layer, facade layer, spatial layer, audience layer, and virtual layer, thereby ensuring that the data features of each layer can be independently identified and processed.

[0036] Specifically, after receiving the five-dimensional topology data, the edge nodes will perform initial layer mapping according to a preset hierarchical structure. For example, the ground layer is used to record the spatial layout of ground equipment and light strip nodes, the facade layer is used to describe the distribution relationship of multi-layer mechanical light rings, the space layer is used for the position and dynamic trajectory of the drone array, the audience layer is used to describe the interactive behavior patterns of different audience areas, and the virtual layer is used to describe the virtual mapping relationship generated by the light field AR rendering engine.

[0037] Through the above layered operations, a layered topology input set is formed, which enables subsequent interaction density calculations and sub-topology partitioning to be carried out independently within the layer, thereby effectively reducing cross-layer interference and improving the controllability and stability of data processing.

[0038] S1.2: Divide into multiple sub-topologies based on node interaction density.

[0039] In the hierarchical topology input set, edge nodes are locally clustered based on node interaction density, dividing high-density interaction regions within the same layer into sub-topological units. The specific operation is as follows:

[0040] First, for each node, the communication frequency, data exchange count, or operation trigger count with neighboring nodes are counted, and the average interaction value with all neighboring nodes is calculated. This average interaction value is used as the node's interaction density value.

[0041] Secondly, after obtaining the interaction density values ​​of all nodes in the topology layer, the density threshold of the topology layer is set according to the average interaction density and fluctuation amplitude of each node. When the interaction density value of a node is higher than the density threshold, the node is marked as a candidate core node; otherwise, it is regarded as an ordinary node.

[0042] Furthermore, for each candidate core node, the neighborhood radius is increased layer by layer along the concentric circle hierarchy, and nodes in the neighborhood are included one by one. The average interaction density of the new expansion layer is dynamically calculated until the average interaction density of the new expansion layer is lower than the density threshold. The expansion process is then terminated, and the candidate core node and its covered neighborhood area are divided into a complete sub-topology unit.

[0043] By combining this layer-by-layer expansion with threshold control, we can ensure that the formed sub-topological units have high interaction consistency and clear boundaries, thereby avoiding the problems of ambiguous regions or over-division that occur in traditional clustering.

[0044] S1.3: Generate cooperative coding information.

[0045] After forming a sub-topology unit, the edge nodes assign a hierarchy identifier and a location identifier to each node based on its topology hierarchy and spatial position in the sub-topology. The edge nodes combine the hierarchy identifier, intra-layer spatial position, and inter-node interaction density of each node in the sub-topology to form collaborative coding information.

[0046] Among them, the hierarchical identifier is used to record the five-dimensional hierarchy (i.e., ground layer, facade layer, space layer, audience layer or virtual layer) to which the corresponding candidate core node belongs, while the location identifier is used to mark the relative spatial coordinates or concentric circle radius position in the sub-topology.

[0047] The resulting collaborative coding information can not only fully express the spatial distribution characteristics of sub-topological units, but also reflect the dynamic interaction strength between nodes.

[0048] S2: The central control unit receives the co-coding information, allocates neighborhood weights based on historical states, and sends them to the corresponding edge nodes; the edge nodes correct the sub-topology and generate updated co-coding information.

[0049] S2.1: Assign neighborhood weights based on historical states.

[0050] S2.1.1: The central control unit receives the collaborative coding information uploaded by each edge node, including the hierarchical identifier of the sub-topology unit where each candidate core node is located, the number of concentric circle expansion layers and the interaction density, and obtains the historical interaction density record of the sub-topology unit.

[0051] It should be noted that the purpose of assigning neighborhood weights based on historical states is to give the current state of candidate core nodes a comparable index at the central end, so that the central end can consider both instantaneous interaction intensity and long-term behavioral characteristics when making global correction decisions, thereby avoiding erroneous topology adjustments or rendering offsets caused by transient noise.

[0052] Among them, the historical interaction density record uses the moving average and variance within a preset time window to describe historical behavior characteristics, so as to distinguish between long-term stability and short-term volatility.

[0053] S2.1.2: For each candidate core node, calculate the difference between the current interaction density and the historical interaction density as the real-time deviation.

[0054] S2.1.3: The neighborhood weight is composed of the interaction density contribution of the candidate core node itself and the interaction strength contribution between sub-topological units through weighting.

[0055] The self-interaction density contribution is the current candidate core node interaction density divided by the sum of the candidate core node interaction densities within the sub-topological unit; the neighborhood interaction contribution is the sum of the interaction densities between the current sub-topological unit and its neighboring sub-topological units divided by the sum of all neighborhood interaction densities.

[0056] During the normalization process, the central control unit performs numerical standardization on each contribution item to eliminate the influence of different scales, and applies a small smoothing filter to the normalization result to avoid frequent jitter. After normalization, each contribution item is in the same numerical range, which facilitates linear combination according to the weight coefficient.

[0057] The weighting coefficients are set based on historical stability. For example, for long-term stable sub-topology units, the proportion of the weight contributed by the candidate core node's own interaction density is increased, while for sub-topology units with large short-term fluctuations, the proportion of the weight contributed by the interaction strength between sub-topology units is increased, to ensure the balance of dynamic topology adjustments. Specific values ​​can be set according to actual operations.

[0058] S2.2: Edge nodes correct the sub-topology.

[0059] The neighborhood weights are sorted from high to low; high neighborhood weight nodes are distributed in the inner layer near the center of the sub-topological unit, while low neighborhood weight nodes are distributed in the outer layer.

[0060] The relative distance between candidate core nodes within the same layer is adjusted linearly according to the weight. That is, based on the inner and outer radius limits of the concentric circle layer bandwidth of the sub-topology unit, the neighborhood weights are mapped to the target radius interval position according to the linear mapping rule, ensuring that high neighborhood weight nodes are close to the center and low neighborhood weight nodes are on the outside, while maintaining the layer order.

[0061] Preferably, for ease of implementation, the mapping from neighborhood weight to radius adopts a standardization process: first, the final neighborhood weight within the same sub-topological unit is standardized to the interval between 0 and 1; second, the standardized neighborhood weight value is mapped to the minimum and maximum radius interval of the corresponding concentric circle level according to the linear mapping rule; the above mapping process ensures that the adjustment of node position within the same level will not cross the boundary of adjacent levels, thereby maintaining the unchanged level order.

[0062] Furthermore, by combining historical interaction density and real-time deviation, the radius position of each candidate core node is adjusted:

[0063] If the real-time deviation is positive and the neighborhood weight is higher than the average neighborhood weight, the radius is reduced by multiplying the scaling factor and the real-time deviation. If the real-time deviation is negative and the neighborhood weight is lower than the average neighborhood weight, the radius is increased by multiplying the scaling factor and the absolute value of the real-time deviation. If the real-time deviation is 0, the radius remains unchanged. The scaling factor can be selected within a suitable range (e.g., 0.1–0.5) based on the radius convergence speed obtained from historical rendering stability experiments to ensure that the radius adjustment process is neither oscillating nor doesn't converge quickly.

[0064] The hierarchical identifier of each candidate core node, the adjusted intra-layer spatial position, and the original or real-time interaction density are combined to form updated collaborative coding information.

[0065] It should be noted that, in order to ensure coordination and consistency, before adjusting the candidate core nodes at the boundary, the edge nodes exchange and compare the proposed adjustment plan with the immediate neighboring edge nodes. In the event of a conflict, the edge nodes revise the proposed adjustment plan according to the preset consistency rules (such as prioritizing smaller relative adjustments or adopting a centrally designated arbitration strategy). The final consistent boundary adjustment is applied simultaneously by all participating edge nodes.

[0066] Edge nodes will update the cooperative coding information and report it to the central control unit according to the predetermined communication cycle or immediately after the adjustment is completed. The updated items will be cached locally for short-term neighborhood cooperative confirmation and possible secondary fine-tuning. The above reporting behavior also includes the time stamp of the correction change, so that the central control unit can include this correction in the historical statistics in the subsequent weight allocation cycle, forming a closed-loop historical-real-time linkage control system.

[0067] As can be seen, this invention differs from static correction schemes that rely solely on single observations. By linking historical trajectories with real-time deviations, it can respond differently to sudden disturbances and long-term trends, thereby improving the robustness of dynamic topology reconstruction and the coherence of rendering synchronization.

[0068] S3: The central control unit maps the updated co-coding information to concentric circle rendering parameters based on the cultural symbol dictionary and distributes them to the edge nodes. The edge nodes perform linkage mapping based on the rendering parameters and sub-topology to generate local rendering instructions.

[0069] S3.1: Map the updated co-coding information to concentric circle rendering parameters.

[0070] Dividing by sub-topological units, the hierarchical identifier and intra-layer spatial position of each candidate core node are read, and the symbol set corresponding to the candidate core node's hierarchy is searched from a pre-stored cultural symbol dictionary. If a certain hierarchical identifier corresponds to multiple candidate symbols, the symbol with the highest frequency of use in the historical corresponding hierarchy is selected first to ensure consistency in symbol rendering.

[0071] The system maps layer identifiers to concentric circle radii, spatial positions within layers to circumferential angles or offsets, and interaction density values ​​to symbol rendering intensities, based on a pre-defined mapping table. This generates concentric circle rendering parameters for each candidate core node, including radius, angle, rendered symbol, and symbol rendering intensity. The mapping table defines the radius ranges for different layer identifiers, the angle or offset ranges for different spatial positions, and the symbol rendering intensity levels for different interaction densities. The mapping table is loaded during system initialization.

[0072] S3.2: Generate local rendering instructions.

[0073] S3.2.1: Traverse the concentric circle rendering parameters of each candidate core node, calculate the corresponding coordinates on the actual display device (ED floor screen, multi-layer mechanical light ring, drone array, audience zone light strip), and map the angle to the device circumferential direction coordinates or zone index:

[0074] The radius is mapped to the display layer position, the angle is mapped to the relative position within the layer, and the rendering symbol and symbol rendering intensity are mapped to the spot / halo encoding and brightness control of the device rendering command.

[0075] Specifically, the radius and angle are converted into actual execution coordinates (x, y, z). For example, x = r i ×cosθ j y = r i ×sinθ j z represents the device hierarchy height (if a multi-layer structure exists). This transformation ensures that all rendering parameters fall within the device's executable coordinate range. Edge nodes map symbol encoding to device-recognizable spot / halo encoding, such as corresponding to different LED light groups, drone lighting effects, or ground screen pixel patterns; they also map symbol rendering intensity to device brightness control values, directly serving as PWM duty cycle or current adjustment inputs.

[0076] S3.2.3: Perform linked mapping of concentric circle rendering parameters for candidate core nodes within the same sub-topology to ensure continuous concentric circle hierarchy and consistent relative positions between candidate core nodes, generating a complete local rendering instruction set. The local rendering instruction set includes the output commands (light spot position coordinates, brightness, symbol encoding) of each candidate core node on the display device.

[0077] The linkage mapping includes: if multiple candidate core nodes are located at the same level, the edge nodes ensure that the angle interval is above the minimum angle interval (which can be set according to actual operation); if multiple levels are continuous, the edge node correction radius ensures that the level spacing is consistent with the radial spacing between adjacent concentric circle levels, thus avoiding visual discontinuity.

[0078] During the linkage mapping process, if the device capacity is insufficient to handle the rendering of all candidate core nodes, edge nodes will prioritize retaining the parameters of nodes with high neighborhood weights and discarding or merging nodes with low neighborhood weights.

[0079] S4: The central control unit calculates the synchronization deviation based on the time stamp information of the edge nodes and sends the synchronization compensation amount to the edge nodes. The edge nodes adjust the execution timing of local rendering instructions according to the synchronization compensation amount, and output the rendering results to the on-site display terminal and the broadcast system.

[0080] S4.1: Generate synchronization compensation amount.

[0081] For each candidate core node, calculate the time difference between the local time stamp and the unified reference time of the central control unit.

[0082] Based on the level of the candidate core nodes, the time difference is adjusted according to the allocation ratio of different levels. Specifically, the central control unit presets the allocation ratio for different levels, for example: ground level 0.4, facade level 0.2, space level 0.15, audience level 0.15, and virtual level 0.1. The reason for setting the above allocation ratio is that the ground level usually carries the most core performance images and visual focus, so the importance of time synchronization is higher than other levels; while the virtual level, since it mainly plays a supporting role in visual performance, has a higher tolerance for time deviation, and therefore its proportion is set lower.

[0083] This allocation ratio design prioritizes ensuring the time accuracy of the core performance area during global synchronous correction.

[0084] Furthermore, based on the radial position of the candidate core node in the concentric circle hierarchy, the time difference is multiplied by the radius proportionality coefficient (the larger the radius, the smaller the coefficient, prioritizing the time synchronization of inner nodes) to obtain the corrected time deviation of the candidate core node. The corrected time deviations of all candidate core nodes within the same sub-topology are then averaged to generate the synchronization compensation amount.

[0085] It should be noted that the effect of averaging is to eliminate deviations caused by local device status or temporary network fluctuations in individual nodes, thereby ensuring the stability and global consistency of the synchronization compensation.

[0086] As can be seen, this invention combines the characteristics of concentric circle rendering structure, so that the time synchronization strategy is not only based on the allocation of topology level, but also considers the physical distribution characteristics of candidate core nodes in concentric circles, thereby achieving dual precision guarantee of global and local.

[0087] S4.2: Adjust the execution sequence of local rendering instructions based on the synchronization compensation amount.

[0088] It should be noted that after the synchronization compensation is generated and distributed to the edge nodes, the edge nodes need to adjust the timing of their local rendering instruction sets to ensure that the execution time is consistent with the unified reference time of the central control unit. Conventional timing adjustment methods often directly delay or advance instruction execution, but they do not consider the continuity of sub-topology hierarchy and concentric circle structure, which often leads to hierarchical misalignment or broken halo in local scenes. This invention, however, ensures that the corrected rendering effect remains complete and smooth by maintaining the constraints of hierarchical order and spatial continuity during the adjustment process.

[0089] The specific operation steps are as follows: traverse the local rendering instructions of all candidate core nodes in the sub-topology unit, and linearly offset the execution time of the local rendering instructions according to the synchronization compensation amount: if the synchronization compensation amount is positive, then delay the execution of the instruction corresponding to the synchronization compensation amount; if the synchronization compensation amount is negative, then advance the execution of the instruction corresponding to the absolute value of the synchronization compensation amount.

[0090] Furthermore, when performing the correction, only the time parameter is adjusted, and the spatial parameters such as radius and angle are not modified, so as to ensure that the geometry of the rendered image is not affected, that is, to keep the hierarchical order of candidate core nodes and the concentric circle hierarchical position unchanged within the subtopology.

[0091] The adjusted rendering instruction set is output to the on-site display and broadcasting system to achieve synchronous rendering across multiple terminals.

[0092] Through the above operations, it is possible to achieve synchronous rendering of multiple devices at the performance site and maintain global time consistency in the broadcast, thereby ensuring that the audience can obtain a consistent visual effect whether they are at the scene or watching through the broadcast.

[0093] Furthermore, such as Figure 2 As shown, this embodiment also provides a virtual-real fusion interactive control system based on five-dimensional dynamic topology, including,

[0094] The sub-topology generation module is used by edge nodes to process the collected five-dimensional topology data and divide it into multiple sub-topologies based on node interaction density. Cooperative coding information is generated for each sub-topology on the edge side.

[0095] The weight allocation module is used by the central control unit to receive co-coding information, allocate neighborhood weights based on historical states, and distribute them to the corresponding edge nodes; the edge nodes correct the sub-topology to generate updated co-coding information.

[0096] The rendering mapping module is used by the central control unit to map the updated co-coding information into concentric circle rendering parameters based on the cultural symbol dictionary, and distribute them to the edge nodes. The edge nodes perform linkage mapping based on the rendering parameters and sub-topology to generate local rendering instructions.

[0097] The synchronization compensation module is used by the central control unit to calculate the synchronization deviation based on the time stamp information of each edge node, and to send the synchronization compensation amount to the edge node. The edge node adjusts the execution timing of local rendering instructions according to the synchronization compensation amount, and outputs the rendering results to the on-site display terminal and the broadcast system.

[0098] This embodiment also provides a computer device applicable to the virtual-real fusion interactive control method based on five-dimensional dynamic topology, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the virtual-real fusion interactive control method based on five-dimensional dynamic topology proposed in the above embodiment.

[0099] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0100] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements the virtual-real fusion interactive control method based on five-dimensional dynamic topology proposed in the above embodiment.

[0101] In summary, this invention, through hierarchical processing and interaction density clustering of five-dimensional topological data, can more comprehensively depict the dynamic relationships between multi-dimensional nodes, ensuring the rationality and real-time nature of sub-topology partitioning. Furthermore, by dynamically adjusting the sub-topological structure using collaborative coding information and historical state weights, the stability and accuracy of interaction mapping are improved. Simultaneously, by leveraging a cultural symbol dictionary to generate symbolic rendering parameters, not only is the cultural expressiveness of virtual-real interaction enhanced, but the precise correspondence between multi-level, multi-dimensional symbols and physical rendering is also guaranteed.

[0102] Overall, this invention breaks through the limitations of traditional two-dimensional or three-dimensional modeling and rendering, and forms a systematic optimization in topology modeling, rendering expression and time synchronization.

[0103] It should be noted that the above 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 preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A virtual-real fusion interactive control method based on five-dimensional dynamic topology, characterized in that: include: Edge nodes process the collected five-dimensional topology data and divide it into multiple sub-topologies based on node interaction density, generating collaborative coding information for each sub-topology on the edge side; The central control unit receives the co-coding information, allocates neighborhood weights based on historical states, and distributes the information to the corresponding edge nodes; the edge nodes correct the sub-topology to generate updated co-coding information. The central control unit maps the updated co-coding information to concentric circle rendering parameters based on the cultural symbol dictionary and distributes them to the edge nodes. The edge nodes perform linkage mapping based on the rendering parameters and sub-topology to generate local rendering instructions. The central control unit calculates the synchronization deviation based on the time stamp information of the edge nodes and sends the synchronization compensation amount to the edge nodes. The edge nodes adjust the execution timing of local rendering instructions according to the synchronization compensation amount and output the rendering results to the on-site display terminal and the broadcasting system. The processing of the collected five-dimensional topology data includes: edge nodes receiving five-dimensional topology data from the central controller and performing initial layering according to the ground layer, facade layer, space layer, audience layer, and virtual layer to form a layered topology input set; the division into multiple sub-topologies based on node interaction density includes: in the layered topology input set, edge nodes perform local clustering based on node interaction density, dividing high-density interaction areas in the same layer into sub-topology units; the generation of collaborative coding information includes: after forming sub-topology units, edge nodes assign a layer identifier and a location identifier to each node according to its topology layer and spatial position in the sub-topology; edge nodes combine the layer identifier, intra-layer spatial position, and inter-node interaction density of each node in the sub-topology to form collaborative coding information; The local clustering based on node interaction density includes: statistically analyzing the communication frequency, data exchange count, or operation trigger count between each node and its neighboring nodes, and calculating the average interaction value with all neighboring nodes, using the average interaction value as the node's interaction density value; after obtaining the interaction density values ​​of all nodes within the topology layer, setting the density threshold of the topology layer based on the average interaction density and fluctuation amplitude of each node; when the interaction density value of a node is higher than the density threshold, the node is marked as a candidate core node; otherwise, it is considered an ordinary node; for each candidate core node, the neighborhood radius is increased layer by layer along the concentric circle hierarchy until the average interaction density of the new extended layer is lower than the density threshold, forming a sub-topology unit; The method of allocating neighborhood weights based on historical states includes: the central control unit receiving co-coding information uploaded by each edge node, including the hierarchical identifier, concentric circle expansion layer number, and interaction density of the sub-topology unit where each candidate core node is located, and obtaining the historical interaction density record of the sub-topology unit; for each candidate core node, calculating the difference between the current interaction density and the historical interaction density as the real-time deviation; the neighborhood weight is composed of the candidate core node's own interaction density contribution and the interaction strength contribution between sub-topology units through weighting, wherein the own interaction density contribution is the current candidate core node's interaction density divided by the sum of the interaction densities of candidate core nodes within the sub-topology unit; the neighborhood interaction contribution is the sum of the interaction densities of the current sub-topology unit and its neighboring sub-topology units divided by the sum of all neighborhood interaction densities; The edge node correction of the sub-topology includes: sorting the neighborhood weights from high to low; wherein, high-weight neighborhood nodes are distributed in the inner layer closer to the center of the sub-topology unit, and low-weight neighborhood nodes are distributed in the outer layer; the relative distance between candidate core nodes within the same layer is linearly adjusted according to the weights, while maintaining the hierarchical order; and the radius position of each candidate core node is adjusted by combining historical interaction density and real-time deviation. If the real-time deviation is positive and the neighborhood weight is higher than the average neighborhood weight, the radius is reduced by the product of the scaling factor and the real-time deviation; if the real-time deviation is negative and the neighborhood weight is lower than the average neighborhood weight, the radius is increased by the product of the scaling factor and the absolute value of the real-time deviation; if the real-time deviation is 0, the radius remains unchanged; the hierarchical identifier of each candidate core node, the adjusted intra-layer spatial position, and the original or real-time interaction density are combined to form the updated co-coding information. The step of mapping the updated co-coding information to concentric circle rendering parameters includes: dividing the sub-topology units and reading the hierarchical identifier and intra-layer spatial position of each candidate core node; searching for the symbol set corresponding to the candidate core node hierarchy from the cultural symbol dictionary; mapping the hierarchical identifier to the radius of a concentric circle, the intra-layer spatial position to the circumferential angle or offset, and the interaction density value to the symbol rendering intensity; and generating concentric circle rendering parameters for each candidate core node, including: radius, angle, rendering symbol, and symbol rendering intensity.

2. The virtual-real fusion interactive control method based on five-dimensional dynamic topology as described in claim 1, characterized in that: The generation of the local rendering instruction includes: Iterate through the concentric circle rendering parameters of each candidate core node and calculate the corresponding coordinates on the actual display device; Map the radius to the display layer position, the angle to the relative position within the layer, and the rendering symbol and symbol rendering intensity to the spot and brightness control of the device rendering command; Linked mapping of concentric circle rendering parameters for candidate core nodes within the same sub-topology ensures continuous concentric circle hierarchy and consistent relative positions between candidate core nodes, generating a complete local rendering instruction set. The local rendering instruction set includes the output commands of each candidate core node on the display device.

3. The virtual-real fusion interactive control method based on five-dimensional dynamic topology as described in claim 2, characterized in that: The generation of the synchronization compensation amount includes: For each candidate core node, calculate the time difference between the local time stamp and the unified reference time of the central control unit; The time difference is adjusted according to the allocation ratio of different levels based on the level of the candidate core node; Based on the radial position of the candidate core node in the concentric circle level, the time difference is multiplied by the radius scaling factor to obtain the corrected time deviation of the candidate core node. The synchronization compensation amount is generated by averaging the correction time deviations of all candidate core nodes within the same sub-topology.

4. The virtual-real fusion interactive control method based on five-dimensional dynamic topology as described in claim 3, characterized in that: The adjustment of the local rendering instruction execution timing based on the synchronization compensation amount includes: Iterate through the local rendering instructions of all candidate core nodes within the sub-topology unit, and linearly offset the execution time of the local rendering instructions according to the synchronization compensation amount: If the synchronization compensation amount is positive, then the execution instruction will be delayed for the time corresponding to the synchronization compensation amount. If the synchronization compensation amount is negative, then the time corresponding to the absolute value of the synchronization compensation amount is executed in advance; Maintain the hierarchical order of candidate core nodes within the sub-topology and the hierarchical position of concentric circles unchanged; The adjusted rendering instruction set is output to the on-site display and broadcasting system to achieve synchronous rendering across multiple terminals.

5. A virtual-real fusion interactive control system based on five-dimensional dynamic topology, based on the virtual-real fusion interactive control method based on five-dimensional dynamic topology as described in any one of claims 1 to 4, characterized in that: Also includes: The sub-topology generation module is used by edge nodes to process the collected five-dimensional topology data and divide it into multiple sub-topologies based on node interaction density. Cooperative coding information is generated for each sub-topology on the edge side. The weight allocation module is used by the central control unit to receive the co-coding information, allocate neighborhood weights in combination with historical states, and send them to the corresponding edge nodes; the edge nodes correct the sub-topology to generate updated co-coding information. The rendering mapping module is used by the central control unit to map the updated co-coding information into concentric circle rendering parameters based on the cultural symbol dictionary, and distribute them to the edge nodes. The edge nodes perform linkage mapping based on the rendering parameters and sub-topology to generate local rendering instructions. The synchronization compensation module is used by the central control unit to calculate the synchronization deviation based on the time stamp information of each edge node, and to send the synchronization compensation amount to the edge node. The edge node adjusts the execution timing of local rendering instructions according to the synchronization compensation amount, and outputs the rendering results to the on-site display terminal and the broadcasting system. The processing of the collected five-dimensional topology data includes: edge nodes receiving five-dimensional topology data from the central controller and performing initial layering according to the ground layer, facade layer, space layer, audience layer, and virtual layer to form a layered topology input set; the division into multiple sub-topologies based on node interaction density includes: in the layered topology input set, edge nodes perform local clustering based on node interaction density, dividing high-density interaction areas in the same layer into sub-topology units; the generation of collaborative coding information includes: after forming sub-topology units, edge nodes assign a layer identifier and a location identifier to each node according to its topology layer and spatial position in the sub-topology; edge nodes combine the layer identifier, intra-layer spatial position, and inter-node interaction density of each node in the sub-topology to form collaborative coding information; The local clustering based on node interaction density includes: statistically analyzing the communication frequency, data exchange count, or operation trigger count between each node and its neighboring nodes, and calculating the average interaction value with all neighboring nodes, using the average interaction value as the node's interaction density value; after obtaining the interaction density values ​​of all nodes within the topology layer, setting the density threshold of the topology layer based on the average interaction density and fluctuation amplitude of each node; when the interaction density value of a node is higher than the density threshold, the node is marked as a candidate core node; otherwise, it is considered an ordinary node; for each candidate core node, the neighborhood radius is increased layer by layer along the concentric circle hierarchy until the average interaction density of the new extended layer is lower than the density threshold, forming a sub-topology unit; The method of allocating neighborhood weights based on historical states includes: the central control unit receiving co-coding information uploaded by each edge node, including the hierarchical identifier, concentric circle expansion layer number, and interaction density of the sub-topology unit where each candidate core node is located, and obtaining the historical interaction density record of the sub-topology unit; for each candidate core node, calculating the difference between the current interaction density and the historical interaction density as the real-time deviation; the neighborhood weight is composed of the candidate core node's own interaction density contribution and the interaction strength contribution between sub-topology units through weighting, wherein the own interaction density contribution is the current candidate core node's interaction density divided by the sum of the interaction densities of candidate core nodes within the sub-topology unit; the neighborhood interaction contribution is the sum of the interaction densities of the current sub-topology unit and its neighboring sub-topology units divided by the sum of all neighborhood interaction densities; The edge node correction of the sub-topology includes: sorting the neighborhood weights from high to low; wherein, high-weight neighborhood nodes are distributed in the inner layer closer to the center of the sub-topology unit, and low-weight neighborhood nodes are distributed in the outer layer; the relative distance between candidate core nodes within the same layer is linearly adjusted according to the weights, while maintaining the hierarchical order; and the radius position of each candidate core node is adjusted by combining historical interaction density and real-time deviation. If the real-time deviation is positive and the neighborhood weight is higher than the average neighborhood weight, the radius is reduced by the product of the scaling factor and the real-time deviation; if the real-time deviation is negative and the neighborhood weight is lower than the average neighborhood weight, the radius is increased by the product of the scaling factor and the absolute value of the real-time deviation; if the real-time deviation is 0, the radius remains unchanged; the hierarchical identifier of each candidate core node, the adjusted intra-layer spatial position, and the original or real-time interaction density are combined to form the updated co-coding information. The step of mapping the updated co-coding information to concentric circle rendering parameters includes: dividing the sub-topology units and reading the hierarchical identifier and intra-layer spatial position of each candidate core node; searching for the symbol set corresponding to the candidate core node hierarchy from the cultural symbol dictionary; mapping the hierarchical identifier to the radius of a concentric circle, the intra-layer spatial position to the circumferential angle or offset, and the interaction density value to the symbol rendering intensity; and generating concentric circle rendering parameters for each candidate core node, including: radius, angle, rendering symbol, and symbol rendering intensity.

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