Intelligent virtual interaction method based on digital twinning

Abstract

The invention discloses an intelligent virtual interaction method based on digital twinning, and particularly relates to the technical field of digital twinning. A virtual object difference mapping data set is constructed by collecting virtual object identifiers, semantic attributes and topological relation data before and after digital twin dynamic reconstruction, and interaction state changes are analyzed by combining virtual interaction semantic continuity and operation logic mobility. Semantic continuity influence data and operation logic migration evaluation data are formed; respectively constructing semantic mapping adjustment data and operation logic migration path data through a virtual object semantic matching method and an interaction state machine migration method, and carrying out fusion analysis to determine interaction semantic and operation logic migration strategy data; finally, according to interactive semantics and operation logic migration strategy data, interactive semantics updating and interactive logic state smooth migration are executed, and therefore virtual interactive semantics coherence and smooth migration in the digital twinning dynamic reconstruction process are achieved.

Description

Technical Field

[0001] This invention relates to the field of digital twin technology, and more specifically, to an intelligent virtual interaction method based on digital twins. Background Technology

[0002] Existing digital twin virtual interactions typically require continuous dynamic reconstruction to adapt to changes in physical entities. In this process, the identifiers, semantic attributes, and topological relationships of virtual interactive objects change frequently.

[0003] Existing digital twin technologies lack effective mechanisms for handling semantic breaks and operational logic discontinuities caused by changes in virtual object identification, semantic attributes, and topological relationships during the dynamic reconstruction of virtual interactions. This results in insufficient continuity of the user's virtual interaction experience and affects the interaction accuracy and stability of the digital twin system. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide an intelligent virtual interaction method based on digital twins to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A digital twin-based intelligent virtual interaction method includes the following steps: S1: Collect virtual object identifiers, semantic attributes, and topological relationship data before and after dynamic reconstruction of the digital twin, and construct a set of virtual object difference mapping data; S2: Based on the semantic continuity of virtual interaction and the transferability of interactive operation logic, conduct an impact analysis on the interaction state change of the virtual object difference mapping data set to form semantic continuity impact data and operation logic transfer evaluation data; S3: Based on the semantic continuity of the data, a semantic matching method for virtual objects is used to establish the semantic correspondence between virtual objects before and after reconstruction, forming semantic mapping adjustment data; S4: Based on the operation logic migration evaluation data, the interactive state machine migration method is used to analyze the state differences of interactive operations before and after reconstruction, and to form operation logic migration path data. S5: Perform fusion analysis on semantic mapping adjustment data and operational logic migration path data to determine the interactive semantics and operational logic migration strategy data applicable to the dynamic reconstruction of the digital twin; S6: Based on the interaction semantics and operation logic migration strategy data, perform interaction semantic updates and smooth migration of interaction logic states.

[0006] In a preferred embodiment, S1 specifically refers to: Collect virtual object identification data, virtual object semantic attribute data, and virtual object topological relationship data before the dynamic reconstruction of the digital twin; Collect virtual object identification data, virtual object semantic attribute data, and virtual object topological relationship data after dynamic reconstruction of the digital twin; Based on the differences between the virtual object identification data, virtual object semantic attribute data and virtual object topological relationship data before and after the dynamic reconstruction of the digital twin, a set of virtual object difference mapping data is generated.

[0007] In a preferred embodiment, S2 specifically refers to: Based on the virtual object difference mapping dataset, we conduct interactive semantic continuity correlation analysis on the differences in the semantic attribute data of virtual objects to generate semantic continuity impact data. Based on the virtual object difference mapping dataset, the feasibility of interactive state migration is assessed for the differences in virtual object topological relationship data, and operational logic migration assessment data is generated.

[0008] In a preferred embodiment, S3 specifically refers to: Candidate virtual object identifier data pairs are determined based on the virtual object difference mapping data set; Based on the semantic continuity impact data, extract the difference items of candidate virtual object identifier data and corresponding virtual object semantic attribute data; Calculate the name similarity and value consistency between the semantic attribute data of virtual objects before and after reconstruction; By combining the adjacency constraints of the virtual object topology data, conflicting matching pairs are eliminated, and semantic mapping adjustment data is output.

[0009] In a preferred embodiment, S4 specifically refers to: Based on the operation logic migration evaluation data, user virtual interaction operation sequences and corresponding virtual object identification data are extracted, and the interaction state machine before reconstruction is constructed according to the interaction triggering conditions and state transition relationships. Based on the virtual object difference mapping data set, the virtual object identification data is replaced and the transition constraints are updated synchronously to construct the reconstructed interactive state machine; By comparing the reachable state set and transition edge set of the interaction state machine before and after reconstruction, operation logic migration path data is generated.

[0010] In a preferred embodiment, S5 specifically refers to: Based on the semantic mapping adjustment data, the consistency of the virtual object identification data in the operation logic migration path data is checked, and the virtual object identification data that cannot be covered by the semantic mapping adjustment data is marked. Based on the marking results, generate virtual object identifier data replacement rules and transfer constraint revision rules; Based on the virtual object identifier data replacement rules and transfer constraint revision rules, the operation logic migration path data is merged and conflict resolved to obtain interaction semantics and operation logic migration strategy data.

[0011] In a preferred embodiment, S6 specifically refers to: Based on the interaction semantics and operation logic migration strategy, update the binding relationship between the virtual object identification data and the virtual object semantic attribute data in the user's virtual interaction operation sequence; The current state and the state to be executed of the reconstructed interactive state machine are updated based on the transition constraint revision rules; Based on the updated binding relationship and the updated current state, generate interaction semantic update records and interaction logic state smooth transition records, and write them into the user's virtual interaction operation sequence.

[0012] The technical effects and advantages of the intelligent virtual interaction method based on digital twins in this invention are as follows: By collecting virtual object identifiers, semantic attributes, and topological relationship data before and after dynamic reconstruction of a digital twin, and constructing a set of virtual object difference mapping data, object changes during the dynamic reconstruction process of the digital twin can be structurally expressed and used as a unified input for subsequent processing. Based on the semantic continuity of virtual interactions and the transferability of interactive operation logic, an impact analysis of interaction state changes is conducted, forming semantic continuity impact data and operation logic transfer evaluation data, providing quantifiable criteria for judging semantic and operational changes. Furthermore, a virtual object semantic matching method is used to establish the semantic correspondence between virtual objects before and after reconstruction and generate semantic mapping adjustment data, ensuring that the semantics of objects interacting before reconstruction are consistently mapped after reconstruction. Simultaneously, the interaction state machine transition method is used to analyze the state differences of the interaction operations before and after reconstruction and generate operation logic transition path data, so that the interaction process has a reusable transition path after model evolution; the semantic mapping adjustment data and operation logic transition path data are fused and analyzed to determine the interaction semantics and operation logic transition strategy data, so that semantic updates and state transitions have unified strategy constraints; finally, the interaction semantics update and interaction logic state smooth transition are executed according to the interaction semantics and operation logic transition strategy data, thereby maintaining the semantic coherence and logical continuity of virtual interaction operations during the dynamic reconstruction of the digital twin, reducing the probability of interaction mismatch and process interruption, and improving the stability and consistency of the virtual interaction process. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of an intelligent virtual interaction method based on digital twins according to the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0015] Example: Figure 1 This invention presents an intelligent virtual interaction method based on digital twins, which includes the following steps: S1: Collect virtual object identifiers, semantic attributes, and topological relationship data before and after dynamic reconstruction of the digital twin, and construct a set of virtual object difference mapping data; S2: Based on the semantic continuity of virtual interaction and the transferability of interactive operation logic, conduct an impact analysis on the interaction state change of the virtual object difference mapping data set to form semantic continuity impact data and operation logic transfer evaluation data; S3: Based on the semantic continuity of the data, a semantic matching method for virtual objects is used to establish the semantic correspondence between virtual objects before and after reconstruction, forming semantic mapping adjustment data; S4: Based on the operation logic migration evaluation data, the interactive state machine migration method is used to analyze the state differences of interactive operations before and after reconstruction, and to form operation logic migration path data. S5: Perform fusion analysis on semantic mapping adjustment data and operational logic migration path data to determine the interactive semantics and operational logic migration strategy data applicable to the dynamic reconstruction of the digital twin; S6: Based on the interaction semantics and operation logic migration strategy data, perform interaction semantic updates and smooth migration of interaction logic states.

[0016] S1: Collect virtual object identifiers, semantic attributes, and topological relationship data before and after dynamic reconstruction of the digital twin, and construct a virtual object difference mapping data set, including: Collect virtual object identification data, virtual object semantic attribute data, and virtual object topological relationship data before the dynamic reconstruction of the digital twin; Specifically, the virtual object identification data before dynamic reconstruction of the digital twin refers to the set of unique identification data corresponding to each virtual object within the digital twin before the reconstruction process occurs. Each virtual object identification data is expressed as a unique alphanumeric string to ensure a one-to-one correspondence between the virtual object identification data and the virtual object. For example, the virtual object identification data can be set as a 32-bit alphanumeric string.

[0017] The semantic attribute data of virtual objects before dynamic reconstruction of the digital twin refers to the set of attribute data that corresponds one-to-one with the identification data of virtual objects before dynamic reconstruction of the digital twin. This data expresses the actual meaning and functional characteristics of the virtual objects, including but not limited to the type, name, functional description, and parameter value range of the virtual objects. The semantic attribute data of virtual objects is stored in a key-value pair structure, where the key is the attribute name of the virtual object, and the value is the corresponding attribute parameter or meaning description. For example, the semantic attribute data of virtual objects includes, but is not limited to, the attribute name "temperature sensor," the attribute parameter "measurement range 0-150 degrees Celsius," the attribute description "used to monitor changes in ambient temperature," and the definition of all operation types supported by the virtual object.

[0018] The topological relationship data of virtual objects before dynamic reconstruction of a digital twin refers to the data set representing the spatial location or logical connection relationship between virtual objects. This topological relationship data is expressed as an undirected graph, where each node corresponds to a virtual object identifier, and each edge describes the spatial adjacency, data interaction, or logical dependency relationship between two virtual objects. The virtual object topological relationship data is recorded in the form of an adjacency matrix or adjacency list. For example, when using an adjacency matrix, the element values ​​are 0 or 1, where an element value of 1 indicates that there is a direct adjacency or logical connection relationship between the corresponding virtual objects.

[0019] Collect virtual object identification data, virtual object semantic attribute data, and virtual object topological relationship data after dynamic reconstruction of the digital twin; Specifically, the virtual object identification data after dynamic reconstruction of the digital twin refers to the new set of virtual object identification data generated after the dynamic reconstruction operation of the digital twin is completed. The data structure and expression method are consistent with the virtual object identification data before dynamic reconstruction of the digital twin.

[0020] The semantic attribute data of the virtual object after dynamic reconstruction of the digital twin also refers to the set of attribute data corresponding to the virtual object's identifier data after reconstruction. This includes the virtual object type, name, functional description, and specific parameter value range, expressed and stored in key-value pairs to ensure consistency with the structure of the virtual object's semantic attribute data before reconstruction. For example, the semantic attribute data of the virtual object after dynamic reconstruction of the digital twin includes, but is not limited to, the attribute name "pressure sensor", the attribute parameter "measurement range of 0-300 kPa", the attribute description "used to monitor changes in environmental pressure", and the definition of the operation types supported by the virtual object.

[0021] The topological relationship data of virtual objects after dynamic reconstruction of the digital twin also refers to the data set describing the spatial location or logical connection relationship between virtual objects after the reconstruction operation. It is expressed in an undirected graph, and each node corresponds to the virtual object identification data after dynamic reconstruction of the digital twin. The definition and storage structure of adjacency relationships are consistent with those before reconstruction, using an adjacency matrix or adjacency list. The definition and value rules of elements in the adjacency matrix are consistent with those before reconstruction, where an element value of 1 indicates that there is an adjacency or logical connection relationship between the corresponding virtual objects.

[0022] Based on the differences in virtual object identification data, virtual object semantic attribute data and virtual object topological relationship data before and after dynamic reconstruction of the digital twin, a set of virtual object difference mapping data is generated. Specifically, the difference comparison includes the comparison of virtual object identification data, the comparison of virtual object semantic attribute data, and the comparison of virtual object topological relationship data.

[0023] The comparison of virtual object identification data specifically involves establishing a mapping table for virtual object identification data. The starting data is the virtual object identification data before the dynamic reconstruction of the digital twin, and the target data is the virtual object identification data after the dynamic reconstruction. A comparison is then performed. If the starting data has an exact match in the target data, the identification data is confirmed to be unchanged; if the starting data does not have an exact match in the target data, the virtual object identification data is marked as changed or deleted; if the target data contains entirely new data that is not present in the starting data, the data is marked as newly added virtual object identification data.

[0024] Specifically, the comparison of semantic attribute data differences for virtual objects involves comparing the name and value of each attribute in the semantic attribute data of each virtual object with the mapping table after the comparison of virtual object identification data differences. It then marks the changed attributes and details of these changes, including but not limited to attribute additions, deletions, or modifications, thus forming information on the differences in the semantic attribute data of virtual objects. For example, if the measurement range of an attribute parameter in the semantic attribute data of a virtual object identification changes from 0-150 degrees Celsius to 0-200 degrees Celsius, the change process is recorded, along with the parameters before and after the change.

[0025] Specifically, the comparison of virtual object topological relationship data involves marking virtual object nodes whose adjacency relationships in the topological structure have changed, along with the details of these changes. This includes, but is not limited to, the addition or deletion of adjacency relationships, as well as changes in the nodes connecting these adjacency relationships. For example, it records the topological relationship between two virtual object identifiers: before reconstruction, they were adjacent; after reconstruction, the adjacency relationship disappeared, and the corresponding virtual object identifier data is recorded.

[0026] After the above comparison is completed, the obtained virtual object identification data difference information, virtual object semantic attribute data difference information, and virtual object topological relationship data difference information will be integrated to form a virtual object difference mapping data set.

[0027] S2: Based on the semantic continuity of virtual interaction and the transferability of interactive operation logic, an impact analysis of interaction state changes is performed on the virtual object difference mapping dataset, forming semantic continuity impact data and operation logic transfer evaluation data, including: Based on the virtual object difference mapping dataset, we conduct interactive semantic continuity correlation analysis on the differences in the semantic attribute data of virtual objects to generate semantic continuity impact data. Specifically, the semantic continuity correlation analysis refers to clarifying the impact of differences in the semantic attribute data of virtual objects on the semantic continuity of virtual interactions. This involves: extracting the names and parameter values ​​of changed attributes from the semantic attribute data difference information of virtual objects in the virtual object difference mapping dataset; evaluating the correlation between each difference item in the semantic attribute data of a virtual object and the sequence of user virtual interaction operations formed by the virtual interaction operations before the dynamic reconstruction of the digital twin, including but not limited to the type of interaction action, the conditions for triggering the action, the frequency of use of semantic attribute data, and the virtual interaction scenario in which the interaction operation takes place; calculating the degree of influence of the correlation on the semantic continuity of virtual interactions, and using a weighted scoring mechanism for quantitative evaluation. The weighting parameters are determined based on the magnitude of change in the semantic attribute data of virtual objects and the degree of dependence of the virtual interaction operation sequence on the corresponding semantic attribute data. For example, the weight of the magnitude of attribute change is set to a real number between 0 and 1. At the same time, the degree of dependence of the virtual interaction operation sequence on the attribute data is determined based on the frequency of attribute data being called in historical interaction records. For example, the weight of attribute data called more than 80% of the time is set to 0.9, and the weight of attribute data called less than 20% of the time is set to 0.2. Finally, based on the comprehensive score of each difference item in the semantic attribute data of virtual objects, the difference items with a comprehensive score greater than or equal to 0.6 are judged to have a significant impact on the semantic continuity of the interaction, generating semantic continuity impact data, and recording each difference item and its corresponding comprehensive score.

[0028] Based on the virtual object difference mapping dataset, the feasibility assessment of interactive state migration is performed on the differences in virtual object topological relationship data, and operation logic migration assessment data is generated. Specifically, the implementation methods for the feasibility assessment of interactive state migration include, but are not limited to, the following: First, based on the virtual object difference mapping data set, extract the virtual object identifier data pairs that have changed in the virtual object topology relationship data difference information. These virtual object identifier data pairs record the connection relationships and change methods between virtual objects whose adjacency relationships have changed, such as adding adjacency relationships, deleting adjacency relationships, or changes in the virtual object identifier data involved in adjacency relationships. Based on the virtual object identifier data corresponding to each step of the user's virtual interaction operation sequence recorded before the dynamic reconstruction of the digital twin, identify whether the virtual object identifier data pairs involved in the virtual object topology relationship data difference items are included in the virtual object identifier data set involved in the user's virtual interaction operation sequence. If the virtual object identifier data set involved in the user's virtual interaction operation sequence contains virtual object identifier data pairs from the virtual object topology relationship data difference items, then the difference items are considered to have a potential impact on the virtual interaction operation logic migration. For each virtual object topology relationship data difference item with potential impact, conduct interactive state migration path analysis, including but not limited to constructing a path reachability matrix for analysis. The reachability matrix is ​​constructed by using virtual object identifiers in the virtual interaction sequence as matrix nodes. Each matrix node represents the interaction state involved in the corresponding virtual interaction operation. Matrix elements record the reachability relationship between interaction states; for example, a matrix element of 1 indicates that two interaction states are reachable, and a matrix element of 0 indicates that they are not reachable. The path reachability matrix is ​​used to analyze the impact of changes in virtual object topology data on the logical migration of virtual interaction operations. This analysis includes, but is not limited to, changes in topology leading to the breaking of existing paths, the generation of new paths, or changes in path length between virtual interaction states. Based on the analysis results, a scoring mechanism is used to quantitatively evaluate the impact of these changes on the logical migration of virtual interaction operations. The weight parameters of the scoring mechanism are determined based on path changes; for example, the weight for path breaking is set to 0.9, the weight for new path generation is 0.5, and the weight for path length changes is 0.3. Finally, based on the evaluation results, the impact of each virtual object topology data difference item on the logical migration of interaction operations is determined. Difference items with a comprehensive score greater than or equal to 0.5 are marked as having a significant impact, forming the operation logic migration evaluation data. The content of each difference item and its corresponding score value are recorded.

[0029] S3: Based on the semantic continuity impact data, a virtual object semantic matching method is used to establish the semantic correspondence between virtual objects before and after reconstruction, forming semantic mapping adjustment data, including: Candidate virtual object identifier data pairs are determined based on the virtual object difference mapping data set; Specifically, the virtual object difference mapping dataset is a dataset formed after comparing the differences in virtual object identifier data, virtual object semantic attribute data, and virtual object topological relationship data before and after the dynamic reconstruction of the digital twin. Based on the virtual object difference mapping dataset, the virtual object identifier datasets before and after the dynamic reconstruction of the digital twin are extracted. Using each virtual object identifier data in the dataset before the dynamic reconstruction as a matching starting point, potential corresponding virtual object identifier data is filtered in the dataset after the dynamic reconstruction. The filtering rules are limited based on the change types of the virtual object identifier data recorded in the virtual object difference mapping dataset, including unchanged, modified, deleted, and newly added virtual object identifier data. For virtual object identifier data that has not changed, candidate virtual object identifier data pairs are directly set as matching pairs between virtual object identifier data before and after the dynamic reconstruction of the digital twin. For virtual object identifier data that has changed, candidate virtual object identifier data pairs are defined as data pairs consisting of the starting data and the target data recorded in the virtual object identifier data mapping relationship table in the virtual object difference mapping data set. For virtual object identifier data that has been deleted, the selection of candidate virtual object identifier data pairs is based on the set of adjacent nodes of the virtual object topology relationship data as the basis for determining the association relationship. Virtual object identifier data that has changed and whose adjacent node set overlap ratio is greater than or equal to a preset adjacent overlap threshold is included in the candidate range. The preset adjacent overlap threshold is determined based on the size distribution of the adjacent node set of the virtual object topology relationship data before the dynamic reconstruction of the digital twin. For example, the preset adjacent overlap threshold is set to 0.5. For newly added virtual object identifier data, the selection of candidate virtual object identifier data pairs is based on the similarity of virtual object semantic attribute data. The similarity of virtual object semantic attribute data is obtained by weighting attribute name similarity and attribute parameter value consistency. Attribute name similarity is calculated by the proportion of common characters in the attribute name strings, and attribute parameter value consistency is calculated by the proportion of overlap in numerical intervals or the proportion of intersection of enumerated sets. Newly added virtual object identifier data with a similarity of virtual object semantic attribute data greater than or equal to a preset semantic similarity threshold is included in the candidate range. The preset semantic similarity threshold is determined based on the distribution of the comprehensive score value of the data influenced by semantic continuity; for example, the preset semantic similarity threshold is set to 0.7. Through selection, a set of candidate virtual object identifier data pairs is formed, consisting of virtual object identifier data before dynamic reconstruction of the digital twin and virtual object identifier data after dynamic reconstruction of the digital twin.

[0030] Based on the semantic continuity impact data, extract the difference items of candidate virtual object identifier data and corresponding virtual object semantic attribute data; Specifically, the semantic continuity impact data is a dataset generated after performing interactive semantic continuity correlation analysis on the differences in the semantic attribute data of virtual objects. It records the comprehensive score value and source of each difference in the semantic attribute data of a virtual object. Based on the semantic continuity impact data, candidate virtual object identifier data pairs are processed to extract the semantic attribute data difference information of the virtual objects corresponding to the candidate virtual object identifier data pairs in the virtual object difference mapping dataset. The semantic attribute data difference information of virtual objects includes changes in attribute names, changes in attribute parameter values, and changes in attribute set structure. For each candidate virtual object identifier data pair, the changed attribute names and corresponding attribute parameter values ​​are extracted from the semantic attribute data of the virtual objects before and after dynamic reconstruction of the digital twin. Simultaneously, the comprehensive score value recorded in the semantic continuity impact data is correlated to form a set of semantic attribute data difference items corresponding to the candidate virtual object identifier data pair. Only the semantic attribute data difference items of virtual objects whose comprehensive score value reaches a preset impact threshold are retained. The preset impact threshold is set based on historical comprehensive score values.

[0031] Calculate the name similarity and value consistency between the semantic attribute data of virtual objects before and after reconstruction; Specifically, for each set of candidate virtual object identifier data and its corresponding set of differences in virtual object semantic attribute data, the similarity of attribute names and the consistency of attribute parameter values ​​are calculated. Attribute name similarity measures the semantic closeness between the attribute names in the virtual object's semantic attribute data before and after dynamic reconstruction of the digital twin. The calculation method for attribute name similarity combines character-level matching and semantic-level matching. Character-level matching determines the basic similarity by comparing the proportion of common characters in the attribute name strings, while semantic-level matching corrects this by comparing the consistency of the attribute names' semantic categories in a predefined semantic lexicon. Attribute name similarity is ultimately normalized to a real number between 0 and 1. Attribute parameter value consistency measures the consistency between the attribute parameter values ​​in the virtual object's semantic attribute data before and after dynamic reconstruction of the digital twin in terms of numerical range or enumerated set. For numerical attribute parameters, consistency is calculated by comparing the overlap ratio of numerical intervals. For enumerated attribute parameters, consistency is calculated by comparing the intersection ratio of enumeration sets. Attribute parameter consistency is also normalized to the real number range between 0 and 1. For each difference in the semantic attribute data of a virtual object, a corresponding attribute name similarity and attribute parameter value consistency result is generated, and these results are correlated and recorded with the comprehensive score in the semantic continuity impact data.

[0032] By combining the adjacency constraints of the virtual object topology data, conflicting matching pairs are eliminated, and semantic mapping adjustment data is output. Specifically, the virtual object topology relationship data represents the spatial location or logical connection relationship between virtual objects in the form of an undirected graph. Based on the virtual object topology relationship data, the adjacency consistency of candidate virtual object identifier data pairs is checked. For each candidate virtual object identifier data pair, the set of adjacent nodes corresponding to the virtual object identifier data in the virtual object topology relationship data before dynamic reconstruction of the digital twin, and the set of adjacent nodes corresponding to the virtual object identifier data in the virtual object topology relationship data after dynamic reconstruction of the digital twin are extracted. By comparing the degree of overlap between the adjacent node sets, the consistency of the candidate virtual object identifier data pair in the topological structure is determined. If the adjacent node sets of the candidate virtual object identifier data pair remain consistent before and after reconstruction, the candidate virtual object identifier data pair is determined to satisfy the topological relationship constraint; if the adjacent node sets differ significantly and cannot be reasonably explained by the topological change records in the virtual object difference mapping data set, the candidate virtual object identifier data pair is determined to have a topological conflict. Candidate virtual object identifier data pairs with topological conflicts are removed from the candidate set. For candidate virtual object identifier data pairs that simultaneously satisfy attribute name similarity, attribute parameter value consistency, and topological relationship constraints, a valid semantic correspondence of virtual objects is confirmed. Finally, the confirmed semantic correspondences of virtual objects are output in structured data form, forming semantic mapping adjustment data. This semantic mapping adjustment data records the virtual object identification data before and after the dynamic reconstruction of the digital twin, the corresponding semantic attribute data matching relationships of the virtual objects, and the matching basis parameters.

[0033] S4: Based on the operation logic migration evaluation data, the interactive state machine migration method is used to analyze the state differences of interactive operations before and after reconstruction, forming operation logic migration path data, including: Based on the operation logic migration evaluation data, user virtual interaction operation sequences and corresponding virtual object identification data are extracted, and the interaction state machine before reconstruction is constructed according to the interaction triggering conditions and state transition relationships. Specifically, a user virtual interaction sequence refers to the historical record of user interactions with virtual object identifier data before the dynamic reconstruction of the digital twin. Each user virtual interaction sequence defines the interaction action type, interaction triggering condition, involved virtual object identifier data, and the chronological order of the interaction actions. Based on operation logic migration evaluation data, all relevant user virtual interaction sequences are extracted. Each user virtual interaction sequence is timestamped to mark the moment the interaction action occurred, with the timestamp precision limited, for example, to the millisecond level. Each user virtual interaction sequence is parsed to extract the interaction action type, interaction triggering condition, and corresponding virtual object identifier data. The interaction action type includes, but is not limited to, clicking, dragging, swiping, selecting, and inputting text on virtual objects. The interaction triggering condition refers to the logical constraints that cause the interaction action to be executed, including but not limited to a user click event, a swipe reaching a predetermined distance, or virtual object attribute parameters reaching a preset threshold. The corresponding virtual object identifier data is the virtual object identifier data involved in each interaction action recorded in the user virtual interaction sequence. Based on the extracted information, a pre-reconstruction interaction state machine is constructed, using virtual object identifier data as nodes and the interaction action types and triggering conditions of the user's virtual interaction operation sequence as transition edges. The pre-reconstruction interaction state machine describes the transition rules between user interaction states, that is, how each user interaction action before the dynamic reconstruction of the digital twin causes a transition in the virtual interaction state. The pre-reconstruction interaction state machine is described using a directed graph data structure, where each node represents the virtual interaction state corresponding to the interaction action, and each transition edge is defined as the combination of the interaction triggering condition and the type of interaction action executed from the starting node to the target node. For example, a transition edge might be recorded as "Clicking virtual object identifier data A and satisfying the attribute parameter temperature greater than 30 degrees Celsius, transitioning from virtual interaction state X to virtual interaction state Y." This ensures that the transition relationship of each virtual interaction state, along with the corresponding virtual object identifier data and triggering conditions, are recorded in detail, thus forming the pre-reconstruction interaction state machine.

[0034] Based on the virtual object difference mapping data set, the virtual object identification data is replaced and the transition constraints are updated synchronously to construct the reconstructed interactive state machine; Specifically, the virtual object difference mapping data set records the changes in virtual object identifier data before and after the dynamic reconstruction of the digital twin, including four types of changes: unchanged, altered, deleted, and added. Based on the virtual object difference mapping data set, the virtual object identifier data involved in each interaction action in the pre-reconstruction interaction state machine is replaced. If the virtual object identifier data recorded in the virtual object difference mapping data set has not changed, the original virtual object identifier data is retained. If it has changed, the corresponding virtual object identifier data recorded in the virtual object difference mapping data set is used for replacement. If virtual object identifier data is deleted, the most similar or functionally close virtual object identifier data needs to be determined for replacement based on the association rules recorded in the virtual object difference mapping data set, such as selection based on the similarity of virtual object semantic attribute data. For newly added virtual object identifier data, it needs to be determined whether it affects the existing virtual interaction state transition relationship. If it does, the newly added virtual object identifier data is added to the corresponding virtual interaction state node. After completing the virtual object identifier data replacement, the interaction state transition constraints are updated synchronously. The specific update of the interaction state transition constraints is as follows: For all interaction trigger conditions in the pre-reconstruction interaction state machine, it is determined whether the virtual object identification data involved in the interaction trigger conditions has changed. If the virtual object identification data has changed, the interaction trigger conditions are updated according to the changes recorded in the virtual object difference mapping data set. For example, when the range of attribute parameter values ​​changes, the corresponding interaction trigger condition threshold is modified synchronously. If the virtual object identification data has not changed, the original interaction trigger conditions are retained. Through the above method, the synchronous update of virtual object identification data and interaction trigger conditions is completed, and finally, a reconstructed interaction state machine consistent with the virtual object identification data set after the dynamic reconstruction of the digital twin is obtained. It is also stored using a directed graph structure, and the definition method of each node and transition edge is consistent with the pre-reconstruction interaction state machine.

[0035] By comparing the reachable state set and transition edge set of the interaction state machine before and after reconstruction, operation logic migration path data is generated. Specifically, the reachable state sets of the pre-reconstruction and post-reconstruction interactive state machines are extracted separately. The reachable state set refers to the set of all virtual interactive state nodes that can be reached from any initial state of the interactive state machine via state transition relationships. Elements in the set are defined and recorded as virtual interactive state nodes. The transition edge sets of the pre-reconstruction and post-reconstruction interactive state machines are also extracted separately. These transition edge sets are the set of all interactive state transition relationships defined in the interactive state machine, with each transition edge recording the interaction action type and triggering condition. The reachable state sets of the pre-reconstruction and post-reconstruction interactive state machines are compared to identify newly added or disappeared virtual interactive state nodes after the dynamic reconstruction of the digital twin. The transition edge sets of the pre-reconstruction and post-reconstruction interactive state machines are also compared to identify newly added state transition relationships, the disappearance of existing state transition relationships, and changes in the triggering conditions of state transition relationships. For example, the triggering condition threshold of state transition relationships changes after reconstruction. Based on the comparison results, operational logic migration path data is constructed. This data describes how the user's virtual interaction operation sequence migrates from the pre-reconstruction interaction state machine path to the post-reconstruction interaction state machine path after the dynamic reconstruction of the digital twin. The path data is stored in the form of path migration rules. Each rule records the original state node, the new state node, the original transition condition, the new transition condition, the changes in the virtual object identifier data involved, and the corresponding semantic attribute data changes. The path migration rules are generated by establishing a pre- and post-transition relationship between the identified new, deleted, and changed state nodes and transition edges to form path change logic. For example, it might be recorded as "From the original state node A to the original state node B via the original transition condition 1, after the dynamic reconstruction of the digital twin, it transforms into "From the new state node C to the new state node D via the new transition condition 2, where the virtual object identifier data X is replaced with the virtual object identifier data Y, and the attribute parameter threshold is adjusted from 30 degrees Celsius to 45 degrees Celsius." Finally, the operational logic migration path data is formed.

[0036] S5: Perform fusion analysis on semantic mapping adjustment data and operational logic migration path data to determine data suitable for the interactive semantics and operational logic migration strategies after the dynamic reconstruction of the digital twin, including: Based on the semantic mapping adjustment data, the consistency of the virtual object identification data in the operation logic migration path data is checked, and the virtual object identification data that cannot be covered by the semantic mapping adjustment data is marked. Specifically, the operational logic migration path data is a dataset formed after comparing and analyzing the interaction state machine before and after reconstruction. Each operational logic migration path records the virtual interaction state nodes before and after reconstruction, the original transition conditions, the new transition conditions, and the changes in the virtual object identifier data involved. The semantic mapping adjustment data is a dataset formed after completing the virtual object semantic matching process. It records the confirmed semantic correspondence between the virtual object identifier data before and after the dynamic reconstruction of the digital twin. Based on the semantic mapping adjustment data, the operational logic migration path data is processed to extract all virtual object identifier data involved in each path and verify whether the virtual object identifier data exists in the semantic correspondence recorded in the semantic mapping adjustment data. If the virtual object identifier data has a corresponding relationship in the semantic mapping adjustment data, it is determined that the virtual object identifier data passes the consistency check; if the virtual object identifier data does not have a corresponding record in the semantic mapping adjustment data, it is determined that the virtual object identifier data cannot be overwritten by the semantic mapping adjustment data, and the virtual object identifier data is marked. The marking content includes the source state node, target state node, and corresponding operation logic migration path marking information of the virtual object identification data, thus forming a set of marked virtual object identification data.

[0037] Based on the marking results, generate virtual object identifier data replacement rules and transfer constraint revision rules; Specifically, for the tagged virtual object identifier data set, the usage of each tagged virtual object identifier data in the operation logic migration path data is analyzed, including the binding relationship of virtual object identifier data in interaction state nodes and the constraint relationship of virtual object identifier data in state transition conditions. Virtual object identifier data replacement rules are used to replace virtual object identifier data that cannot be covered by semantic mapping adjustment data in the operation logic migration path data. The generation of virtual object identifier data replacement rules is based on the virtual object identifier data change relationships recorded in the virtual object difference mapping data set and the virtual object semantic attribute data difference information. The generation method is as follows: For the tagged virtual object identifier data, the virtual object difference mapping data set is searched to see if there is any virtual object identifier data of a changed type associated with the virtual object identifier data. If there is, the virtual object identifier data of the changed type associated with the virtual object identifier data is selected as the replacement target. If there is no virtual object identifier data of the changed type, the virtual object identifier data of new virtual object identifier data with a semantic attribute data similarity reaching a preset similarity threshold is searched in the virtual object difference mapping data set. For example, new virtual object identifier data with a comprehensive score of semantic attribute data name similarity and value consistency greater than or equal to 0.7 is searched. If there is still no virtual object identifier data that meets the conditions, the virtual object identifier data is marked as an irreplaceable type. Through the above search and judgment, a set of virtual object identifier data replacement rules is formed. Each virtual object identifier data replacement rule records the original virtual object identifier data, the replacement target virtual object identifier data, and the type of replacement basis.

[0038] The transfer constraint revision rules are used to synchronously revise the interaction state transfer conditions in the operation logic migration path data after the virtual object identifier data replacement is completed. The generation of transfer constraint revision rules is based on the original transfer conditions, new transfer conditions, and differences in virtual object semantic attribute data recorded in the operation logic migration path data. For transfer conditions involving the tagged virtual object identifier data, it is analyzed whether the transfer conditions contain parameter constraints directly related to the virtual object semantic attribute data, such as parameter value ranges, threshold judgment conditions, or enumeration state restrictions. If the transfer conditions contain parameter constraints directly related to the virtual object semantic attribute data, the transfer condition parameters are revised according to the differences in virtual object semantic attribute data. For example, when the attribute parameter value range changes, the parameter value range in the original transfer conditions is synchronously adjusted to be consistent with the parameter range of the reconstructed virtual object semantic attribute data. If the transfer conditions do not contain parameter constraints directly related to the virtual object semantic attribute data, the original transfer condition structure is retained, and only the virtual object identifier data involved is replaced. Through the above method, a set of transfer constraint revision rules is formed, and each transfer constraint revision rule records the original transfer conditions, new transfer conditions, and the corresponding virtual object identifier data replacement relationship.

[0039] Based on the virtual object identifier data replacement rules and the transfer constraint revision rules, the operation logic migration path data is merged and conflict resolved to obtain the interaction semantics and operation logic migration strategy data. Specifically, path merging and conflict resolution use operational logic migration path data as the processing object and the set of rules for replacing virtual object identifier data and revising transfer constraints as the processing basis. Multiple paths in the operational logic migration path data involving the same pre-reconstruction virtual interaction state node and the same post-reconstruction virtual interaction state node are merged. If multiple paths have consistent state transition results after completing the replacement of virtual object identifier data and revision of transfer constraints, the multiple paths are merged into one path, and the path identifier information before merging is recorded. Path conflicts in the operational logic migration path data are resolved. Path conflicts refer to multiple paths pointing to the same post-reconstruction virtual interaction state node after completing the replacement of virtual object identifier data and revision of transfer constraints, but with contradictory transfer conditions or constraint parameters. For path conflicts, priority is determined based on the scoring results recorded in the semantic continuity impact data and the operational logic migration evaluation data. Paths with higher comprehensive scores are retained first, while paths with lower comprehensive scores are marked as secondary paths or eliminated. For example, when the comprehensive score of the semantic attribute data difference between the virtual objects corresponding to two paths is 0.8 and 0.4 respectively, the path with a comprehensive score of 0.8 is retained first. If the comprehensive scores of the paths are the same, the path with smaller changes in path length is retained first. Through path merging and conflict resolution, the final operational logic migration path data is formed.

[0040] After completing path merging and conflict resolution, the retained operation logic migration path data is integrated with the corresponding virtual object identifier data replacement rules and transfer constraint revision rules to form interaction semantics and operation logic migration strategy data.

[0041] S6: Based on the interaction semantics and operation logic migration strategy data, perform interaction semantic updates and smooth transitions of interaction logic states, including: Based on the interaction semantics and operation logic migration strategy, update the binding relationship between the virtual object identification data and the virtual object semantic attribute data in the user's virtual interaction operation sequence; Specifically, the interaction semantics and operation logic migration strategy data is structured data processed by virtual object identifier data replacement rules and transfer constraint revision rules. It records the binding relationship between each virtual interaction state node and the corresponding virtual object identifier data, the replacement rules, and the corresponding virtual object semantic attribute data adjustment scheme. The user virtual interaction operation sequence is historical sequence data recording the user's interactions with virtual objects before the dynamic reconstruction of the digital twin. It includes the interaction action type, triggering condition, action occurrence timestamp, and the corresponding virtual object identifier data and virtual object semantic attribute data. In order to update the binding relationship between virtual object identifier data and virtual object semantic attribute data, the virtual object identifier data involved in each interaction action in the user virtual interaction operation sequence is analyzed based on the interaction semantics and operation logic migration strategy data. If the virtual object identifier data in the user virtual interaction operation sequence has a replacement target in the interaction semantics and operation logic migration strategy data, the corresponding virtual object identifier data in the user virtual interaction operation sequence is replaced with the replacement virtual object identifier data specified in the interaction semantics and operation logic migration strategy data, and the virtual object semantic attribute data bound to the virtual object identifier data is updated synchronously. The updating of virtual object semantic attribute data includes: adjusting the value range, parameter settings, or functional descriptions of the attribute data bound to the virtual object identifier data in the user's virtual interaction operation sequence based on the attribute data difference information recorded in the interaction semantics and operation logic migration strategy data. For example, when the attribute parameter value range changes, the original attribute parameter value range is replaced with the new parameter value range. When the virtual object identifier data in the user's virtual interaction operation sequence does not find a corresponding replacement target in the interaction semantics and operation logic migration strategy data, a secondary screening of replacement targets is performed based on the similarity of virtual object semantic attribute data. The similarity calculation method is as follows: comparing the attribute name similarity and parameter value consistency of the virtual object semantic attribute data before and after the dynamic reconstruction of the digital twin, setting the attribute name similarity weight and parameter value consistency weight as the basis for comprehensive evaluation. For example, the attribute name similarity weight is set to 0.6, the parameter value consistency weight is set to 0.4, and a comprehensive similarity score greater than or equal to 0.75 is determined as a replacement target. After the update process is completed, a new set of binding relationship data is formed for all virtual object identification data and virtual object semantic attribute data involved in the user's virtual interaction operation sequence.

[0042] The current state and the state to be executed of the reconstructed interactive state machine are updated based on the transition constraint revision rules; Specifically, the reconstructed interactive state machine is a directed graph data structure generated after the dynamic reconstruction of the digital twin. It represents the user's virtual interaction operation sequence and allows for state transitions. Nodes in the state machine represent the virtual interaction states the user may be in, and transition edges represent the transition relationships between states and their corresponding triggering conditions. The transition constraint revision rules record the content that needs to be updated due to changes in the semantic attribute data of virtual objects, including the triggering conditions for interactive state transitions and the replacement of corresponding virtual object identifier data. To update the reconstructed interactive state machine, the state transition triggering conditions and corresponding virtual object identifier data defined for each transition edge are analyzed one by one based on the transition constraint revision rules. If the virtual object identifier data or attribute parameters involved in the state transition triggering conditions are recorded as requiring adjustment in the transition constraint revision rules, the triggering condition constraints of the corresponding transition edge are updated according to the content recorded in the rules. For example, if the original triggering condition constraint is "temperature parameter greater than 40 degrees Celsius," and the transition constraint revision rules record a change in the temperature parameter's value range as "measurement range changed to 0-50 degrees Celsius," then the corresponding triggering condition needs to be revised to "temperature parameter greater than 45 degrees Celsius." After completing the update of all transition conditions and constraints, record the current virtual interaction state node of the user, as well as the executable state transition paths starting from the current state node. Each path fully records the triggering conditions and the corresponding virtual object identification data and semantic attribute data.

[0043] Based on the updated binding relationship and the updated current state, generate interaction semantic update records and interaction logic state smooth transition records, and write them into the user's virtual interaction operation sequence; Specifically, the interaction semantic update record records the details of changes in the semantic attribute data of virtual objects involved in each interaction action, including changes in attribute names, adjustments to value ranges, and revisions to function descriptions. The interaction logic state smooth transition record records the smooth transition scheme from the pre-reconstruction interaction state machine to the post-reconstruction interaction state machine in the user's virtual interaction operation sequence, including the original virtual interaction state nodes, new virtual interaction state nodes, changes in trigger conditions, and replacement schemes for virtual object identifier data. The method for generating the interaction semantic update record is as follows: compare the semantic attribute data of virtual objects before and after reconstruction for each step of the user's virtual interaction operation sequence, extract the differences, and record them to form a semantic update record. The method for generating the interaction logic state smooth transition record is as follows: based on the updated current state, according to the updated binding relationship, analyze the changes in virtual object identifier data and trigger conditions involved in the state transition process for each step of the user's virtual interaction operation sequence, record the original state, new state, changes in transition trigger conditions, and path changes during the state transition process, ensuring the continuity of the transition path for each virtual interaction state node. For example, the record could be: "From virtual interaction state node X before reconstruction, it reaches node Y through the original trigger condition (temperature greater than 40 degrees Celsius). After the update, it changes to from virtual interaction state node X1 to node Y1 through the new trigger condition (temperature greater than 45 degrees Celsius)," ensuring that the user's virtual interaction operation sequence can smoothly migrate according to the recorded content. After generating the above records, the interaction semantic update record and the interaction logic state smooth migration record are completely written into the user's virtual interaction operation sequence, and a timestamp is added to each record.

[0044] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0045] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design 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 implementation should not be considered beyond the scope of this application.

[0046] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0047] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0048] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0049] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0050] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion 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, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0051] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0052] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent virtual interaction based on digital twins, characterized in that, Includes the following steps: S1: Collect virtual object identifiers, semantic attributes, and topological relationship data before and after dynamic reconstruction of the digital twin, and construct a set of virtual object difference mapping data; S2: Based on the semantic continuity of virtual interaction and the transferability of interactive operation logic, conduct an impact analysis on the interaction state change of the virtual object difference mapping data set to form semantic continuity impact data and operation logic transfer evaluation data; S3: Based on the semantic continuity of the data, a semantic matching method for virtual objects is used to establish the semantic correspondence between virtual objects before and after reconstruction, forming semantic mapping adjustment data; S4: Based on the operation logic migration evaluation data, the interactive state machine migration method is used to analyze the state differences of interactive operations before and after reconstruction, and to form operation logic migration path data. S5: Perform fusion analysis on semantic mapping adjustment data and operational logic migration path data to determine the interactive semantics and operational logic migration strategy data applicable to the dynamic reconstruction of the digital twin; S6: Based on the interaction semantics and operation logic migration strategy data, perform interaction semantic updates and smooth migration of interaction logic states.

2. The intelligent virtual interaction method based on digital twins according to claim 1, characterized in that, S1, specifically: Collect virtual object identification data, virtual object semantic attribute data, and virtual object topological relationship data before the dynamic reconstruction of the digital twin; Collect virtual object identification data, virtual object semantic attribute data, and virtual object topological relationship data after dynamic reconstruction of the digital twin; Based on the differences between the virtual object identification data, virtual object semantic attribute data and virtual object topological relationship data before and after the dynamic reconstruction of the digital twin, a set of virtual object difference mapping data is generated.

3. The intelligent virtual interaction method based on digital twins according to claim 2, characterized in that, S2, specifically: Based on the virtual object difference mapping dataset, we conduct interactive semantic continuity correlation analysis on the differences in the semantic attribute data of virtual objects to generate semantic continuity impact data. Based on the virtual object difference mapping dataset, the feasibility of interactive state migration is assessed for the differences in virtual object topological relationship data, and operational logic migration assessment data is generated.

4. The intelligent virtual interaction method based on digital twins according to claim 3, characterized in that, S3, specifically: Candidate virtual object identifier data pairs are determined based on the virtual object difference mapping data set; Based on the semantic continuity impact data, extract the difference items of candidate virtual object identifier data and corresponding virtual object semantic attribute data; Calculate the name similarity and value consistency between the semantic attribute data of virtual objects before and after reconstruction; By combining the adjacency constraints of the virtual object topology data, conflicting matching pairs are eliminated, and semantic mapping adjustment data is output.

5. The intelligent virtual interaction method based on digital twins according to claim 4, characterized in that, S4, specifically: Based on the operation logic migration evaluation data, user virtual interaction operation sequences and corresponding virtual object identification data are extracted, and the interaction state machine before reconstruction is constructed according to the interaction triggering conditions and state transition relationships. Based on the virtual object difference mapping data set, the virtual object identification data is replaced and the transition constraints are updated synchronously to construct the reconstructed interactive state machine; By comparing the reachable state set and transition edge set of the interaction state machine before and after reconstruction, operation logic migration path data is generated.

6. The intelligent virtual interaction method based on digital twins according to claim 5, characterized in that, S5, specifically: Based on the semantic mapping adjustment data, the consistency of the virtual object identification data in the operation logic migration path data is checked, and the virtual object identification data that cannot be covered by the semantic mapping adjustment data is marked. Based on the marking results, generate virtual object identifier data replacement rules and transfer constraint revision rules; Based on the virtual object identifier data replacement rules and transfer constraint revision rules, the operation logic migration path data is merged and conflict resolved to obtain interaction semantics and operation logic migration strategy data.

7. The intelligent virtual interaction method based on digital twins according to claim 6, characterized in that, S6, specifically: Based on the interaction semantics and operation logic migration strategy, update the binding relationship between the virtual object identification data and the virtual object semantic attribute data in the user's virtual interaction operation sequence; The current state and the state to be executed of the reconstructed interactive state machine are updated based on the transition constraint revision rules; Based on the updated binding relationship and the updated current state, generate interaction semantic update records and interaction logic state smooth transition records, and write them into the user's virtual interaction operation sequence.

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