347results about How to "Improve collaboration efficiency" patented technology

The invention relates to an industrial robot cooperative control method, system and device and a storage medium. The method comprises the following steps: acquiring machine system information, working environment conditions, task demand contents and cooperative mode information of a plurality of industrial robots; performing spatial analysis on the working environment condition to obtain environment structure characteristics; performing task decomposition on the task demand content according to the cooperation mode information to obtain a sub-task list; mapping the machine system information into the environment structure features to obtain a corresponding mapping relationship, and performing association analysis on the mapping relationship to obtain a task allocation scheme; performing individual optimization on the comprehensive control parameters based on a task allocation scheme to obtain robot control parameters; and performing cooperative strategy analysis according to the sub-task list and the robot control parameters to obtain robot cooperative strategies, and performing comprehensive analysis on all the robot cooperative strategies to obtain an overall cooperative control strategy. According to the invention, the whole industrial robot system can be more suitable for complex and changeable actual production scenes.

The invention discloses a multi-terminal vehicle management system based on an intelligent algorithm, relates to the technical field of vehicle management, and is used for solving the problem of insufficient real-time performance and cooperative efficiency of vehicle management. According to the method, a multi-modal sensor fusion technology is combined with Gaussian process regression, complex environment data is modeled in real time, dynamic target and static background features are accurately extracted, environment changes are analyzed and predicted in combination with a time sequence, accurate input is provided for path planning and task allocation, a path is dynamically adjusted through an incremental optimization algorithm, emergencies are coped, and the path planning and task allocation efficiency is improved. According to a distributed path optimization mechanism, multi-vehicle task path conflicts are eliminated, the cooperation efficiency is improved, a priority model is constructed based on the task emergency degree, the time constraint and the resource matching degree, the weight is dynamically adjusted, vehicle and task matching is optimized in combination with reinforcement learning, the task execution efficiency is ensured, resource competition and path conflicts are solved, and the task execution efficiency is improved. Efficient cooperation in a complex dynamic environment is realized, and the real-time performance and management efficiency of vehicle management are improved.

The invention provides an unmanned aerial vehicle multi-target tracking method and system based on visual and millimeter-wave radar information fusion, and the method comprises the steps: obtaining an association result through employing a space-time consistency model, constructing a self-adaptive joint probability data association frame according to the association result, so as to obtain an initial target state estimation value, and carrying out the recognition of the initial target state estimation value. A prospective path planning algorithm is adopted to obtain an optimal observation angle flight path, a Bayesian network is utilized to obtain initial observation data, based on the initial observation data, an optimal target state estimation value is generated, a distributed cooperative sensing mechanism is used to generate an initial tracking task allocation scheme, and an intelligent resource allocation strategy is implemented. Generating an initial resource allocation scheme, starting a quick response protocol to obtain an optimal tracking task allocation scheme, and generating an optimal resource allocation scheme based on the optimal tracking task allocation scheme; according to the technical scheme provided by the invention, the accuracy of target identification is improved, the environmental adaptability is enhanced, the tracking efficiency is improved, and the working time is prolonged.

The invention discloses a multi-agent robot cooperative control method based on distributed reinforcement learning, and the method comprises the steps: building a multi-agent reinforcement learning algorithm environment, and defining a state space, an action space and a reward function; constructing a distributed reinforcement learning training framework which comprises a sampling module, a training module and a scheduling management and storage module; based on an actor-commentator architecture, constructing an independent actor network and a commentator network for each robot agent; through a distributed training framework, sample data sharing of the sampling module and neural network parameter sharing and cooperative training of the training module are realized; and finally, loading the trained neural network into a multi-agent robot system, and carrying out cooperative control according to environment changes and task requirements. Therefore, the robot intelligent body of each node can share experience, and cooperative training is shared through neural network parameters, so that a cooperative control strategy is realized, and the overall performance and robustness of the system are improved.

The invention, which relates to the technical field of supply chain information, discloses a comprehensive supply chain control system comprising a transaction and collaborative service module, an order management and decision support module and a data interaction and integration module. The transaction and cooperation service module is used for processing transaction information of supply chain participants, ensuring information safety and accuracy, managing the full life cycle of a contract and performing real-time monitoring, establishing a real-time communication and cooperation project management channel, and improving cooperation efficiency; according to the invention, the transaction and collaborative service module has a significant effect, encryption processing ensures the security of transaction information, leakage and tampering are prevented, contract management is efficient and flexible, a multi-parameter evaluation optimization template reduces the default risk, a collaborative mechanism improves the collaborative efficiency of all parties, and the response speed of a supply chain is enhanced.

The invention discloses a civil heterogeneous unmanned cluster path coordination method and system based on unmanned-unmanned cooperation, and belongs to the field of civil unmanned aerial vehicle path coordination, and the method comprises the steps: obtaining an unmanned aerial vehicle cooperative flight task, carrying out the analysis of the unmanned aerial vehicle cooperative flight task, and building a subtask monomer; idle unmanned aerial vehicle self-inspection is executed, a feature set of idle unmanned aerial vehicles is established, feature matching is performed, and unmanned aerial vehicle-subtask mapping is established; establishing a search cluster and a following cluster; according to the pre-flight trajectory, executing real-time environmental data acquisition by using the search cluster; and pre-flight trajectory adjustment is carried out to complete path coordination of the unmanned aerial vehicle cooperative flight task. The technical problems that in the prior art, the environment adaptability of civil unmanned aerial vehicle cluster path planning is insufficient, and the heterogeneous cluster cooperation efficiency is not high are solved, and the technical effects that environment perception and trajectory optimization are carried out through cooperation of the search cluster and the follow-up cluster, and the environment adaptability and cooperation efficiency of the heterogeneous unmanned aerial vehicle cluster are improved are achieved.

The invention relates to the technical field of mixed reality, in particular to a mixed reality multi-user interaction large-space positioning, aligning and collaborating system and method, and aims to solve the problems that in the prior art, the user interaction experience is improved only by collecting multi-aspect data for processing, efficient collaboration work of multiple users in a large space cannot be achieved, and the user experience is poor. Information sharing, task distribution and real-time interaction among users cannot be realized; information sharing, task distribution and real-time interaction among users are realized through the multi-user cooperation module, cross-device operation consistency is ensured through a multi-device sharing coordinate system, configuration is simplified, cooperation efficiency is improved, real-time data transmission is realized through multi-device network synchronization, delay is reduced, cooperation fluency is enhanced, and user experience is improved. The interaction reality sense is enhanced through physical interaction logic synchronization, the working process is optimized, and the cooperation experience is improved.

The invention provides a multi-agent cooperation system, which comprises a multi-agent cooperation engine module, a task decomposition and distribution module and a tool calling normal form module, and is characterized in that the task decomposition and distribution module is used for decomposing tasks and distributing decomposed sub-tasks to agents; the multi-agent cooperation engine module is used for managing cooperation and communication between agents; and the tool calling module enables the intelligent agent to dynamically call different tools. According to the multi-agent collaboration system, the collaboration efficiency among the agents, the flexibility of task decomposition, the adaptivity of tool calling and the intelligent level of user interaction are remarkably improved, and remarkable technical advantages and effects are shown in complex task processing and dynamic environment processing.

The invention relates to the technical field of digital information processing, and provides a photovoltaic power station data operation and maintenance management system, and a data exchange network service management system comprises a server, a cloud management module, an edge calculation module, a data exchange module, a performance evaluation module, an intelligent routing module and a self-adaptive data synchronization module. The performance evaluation module is used for monitoring key performance indexes of the network state of the whole system, evaluating the current running states of the cloud, the edge nodes and the network state through the key performance indexes to form an evaluation result, and feeding back the result to the cloud management module, the edge calculation module, the self-adaptive data synchronization module and the intelligent routing module; and the data exchange module is responsible for data synchronization and exchange between the cloud and the edge nodes, so that the data consistency of the edge nodes in the system is ensured.

The invention discloses a multi-agent collaborative scheduling method and system based on maximum entropy reinforcement learning, and the method comprises the steps: generating an environment state vector according to the first environment data of a production line; generating an initial production task according to the environment state vector; performing task scheduling operation on the initial production task, and generating a path plan; storing the environment state vector, the initial production task and the path planning to obtain empirical data; according to the empirical data, training an initial strategy model through a maximum entropy reinforcement learning algorithm to obtain a target strategy model; and obtaining a multi-agent collaborative target scheduling strategy according to the target strategy model. The multi-agent cooperation efficiency can be improved, so that the production efficiency is improved, and the method can be widely applied to the technical field of agent scheduling.

The invention relates to the technical field of data distributed storage, and discloses a distributed storage method and system for clinical test data, and the method comprises the steps: carrying out the ring signature encryption processing of the patient test data of a plurality of data centers, and obtaining a patient anonymization identifier and standardized clinical data; performing two-stage random storage node configuration to obtain an optimal storage node configuration scheme; constructing an LPPMM-DA data aggregation model based on the optimal storage node configuration scheme, and performing fragmentation processing on the patient test data to obtain a plurality of target data fragments; performing dynamic operation envelope analysis and alliance graph game calculation on the multiple target data fragments to obtain a storage resource scheduling scheme; according to the storage resource scheduling scheme and the anonymization identifier, distributed data block storage and access authentication are executed on the multiple target data fragments, data block storage distribution information is generated, a complete data access control system is constructed, and safe and reliable storage of clinical test data is ensured.

The invention belongs to the technical field of intelligent weighing, and more particularly relates to an intelligent self-adaptive electronic scale system based on machine learning and a data processing method, and the system comprises a composite sensor module which is used for collecting gravity, volume and shape information; the automatic calibration module is connected with the composite sensor module and is used for carrying out regular calibration and calibration according to the data of the composite sensor module; the wireless networking module is connected with the automatic calibration module and is used for wirelessly transmitting and interacting the calibrated data; the intelligent operation and maintenance module is connected with the wireless networking module and is used for receiving the transmitted data and realizing equipment state monitoring and anomaly detection; the environment adaptation module is connected with the intelligent operation and maintenance module and is used for realizing adaptive compensation in a severe environment according to a detection result; and the man-machine interaction module is connected with the environment adaptation module and is used for displaying a compensated result and realizing a user-friendly operation interface, so that high-precision and all-around weighing perception is realized.

The invention provides a large model interaction method and system based on multi-model collaborative dialogue, and relates to the technical field of artificial intelligence, and the method comprises the steps: dividing multi-modal data into a pixel block matrix and extracting feature vectors, constructing a hexagonal honeycomb-shaped coding matrix to store data information, and generating an attention score matrix by adopting a multi-head attention mechanism; constructing a model communication network based on the transmission data unit, and calculating a professional degree score through graph convolution; according to the method, performance data is collected to generate an evaluation graph, and an optimal node cooperation strategy is output in combination with dominant learning, so that the efficiency and accuracy of multi-model cooperation dialogue are improved, and the robustness and expandability of the system are enhanced.

The invention relates to the technical field of long and short term memory and natural language processing, and discloses a session processing method and device based on long and short term memory, equipment and a medium. Using the updated large language model to respond to the input verbal skill based on the stored and downloaded long-term memory data to form interactive session information, and storing the interactive session information as short-term memory data in real time; wherein the large language model is updated through federal learning according to the short-term memory data; determining a theme according to the short-term memory data, screening important memory data in the short-term memory data based on a preset priority, and incrementally storing the important memory data as long-term memory data of the corresponding theme; and releasing the long-term memory data subjected to incremental storage to the message queue middleware according to the theme, so that other service line servers subscribing to the theme download the long-term memory data. The problems of memory decline, poor memory consistency and poor integration of a session system are solved.

The invention provides a high-efficiency intelligent teaching resource scheduling algorithm and an implementation method thereof, and the method comprises the steps: constructing a judgment matrix according to a learner capability difference evaluation result, cooperation efficiency analysis data, knowledge graph coverage rate statistics and learning style matching degree score, carrying out the calculation to obtain a group heterogeneity index, solving the weight of each index through a feature value method, and carrying out the calculation of the group heterogeneity index. Carrying out weighted summation to obtain a group complementarity comprehensive index; acquiring a historical learning data sequence of a learner, extracting time sequence features, combining a current individual progress deviation monitoring result, individual resource demand evaluation and individual learning content suitability analysis, constructing an individual development trajectory prediction model, and predicting a future individual learning performance curve; and aiming at the group complementarity comprehensive index and a future individual learning performance prediction result, constructing a multi-objective optimization model of resource allocation, setting a group complementarity objective function and an individual satisfaction objective function, and solving to obtain a resource allocation scheme for balancing group and individual benefits.

The invention relates to the technical field of copper wire manufacturing control, in particular to a copper wire multi-pass rolling and annealing cooperative control method and system based on an intelligent network, and the method comprises the steps: setting a process control node according to an industrial control process, building a cooperative communication network based on the process control node, and collecting a multi-mode industrial control signal; setting a data transmission processing protocol, establishing an industrial control sensing platform, integrating multi-mode industrial control signals, and converting the multi-mode industrial control signals according to process positions to generate process operation parameters; analyzing non-linear correlation between process steps, and calculating process adjustment parameters by combining the copper wire performance indexes; according to the data transmission processing protocol, the process operation parameters are transmitted to a cooperative control center and compared with the process adjustment parameters for analysis, and a parameter cooperative control instruction is generated; and the parameter cooperative control instruction is fed back to the rolling control node and the annealing temperature control node based on the cooperative communication network for parameter correction. According to the invention, the problems of low process synergy efficiency and insufficient signal processing capability in copper wire manufacturing are effectively solved.

The invention provides a digital office data synchronization and sharing method and system based on cloud computing, and relates to the technical field of cloud computing, and the method comprises the steps: building a distributed data synchronization system on a cloud computing platform, and detecting the change of digital office data on each terminal device through a real-time monitoring mechanism; when data change is detected, triggering an incremental synchronization algorithm, and only synchronizing the changed data part; historical version information of each data change is recorded by using a block chain-based distributed account book technology, and data version tracking and backtracking are realized; constructing a role-based access control system, and allocating data access permissions to different users; a real-time collaborative editing function is realized, and multiple users are allowed to edit the same digital office data at the same time; establishing a data sharing log system, and recording data access and operation behaviors of each user; and a machine learning algorithm is utilized to analyze a user behavior mode, and related digital office data is automatically recommended.

The invention relates to the field of legal service management, and discloses a legal service management system based on a block chain, and the system comprises the following modules: a block chain network, an intelligent contract module, a data storage module, a user interface module, a feedback and monitoring module and a user management module, the non-tampering property and the transparency are ensured; the intelligent contract module automatically executes contract terms and supports intelligent management; the data storage module adopts a hierarchical structure, and on-chain data and off-chain data are stored in a distinguished manner, so that the storage and access efficiency is optimized; and the user interface module provides user-friendly operation experience through a visual tool. By using the block chain technology, all contract execution and compliance audit data are encrypted and stored in a distributed mode, it is ensured that tampering is avoided and whole-course traceability is achieved, and a user and related mechanisms can verify the authenticity and integrity of the contract data at any time.

The invention relates to the technical field of equipment management, in particular to a medical beauty equipment cloud management system and management method. The method comprises the following steps: acquiring a medical beauty equipment number and medical beauty equipment parameters; carrying out cloud platform data uploading on the medical beauty equipment parameters based on the medical beauty equipment number, and generating medical beauty equipment monitoring data; consumable information digital registration is carried out on the medical beauty equipment monitoring data, and a beauty equipment consumable digital registry is generated; the method comprises the following steps: acquiring beauty equipment consumable data through a beauty equipment consumable digital registry to obtain beauty equipment consumable sensing data; consumable loss influence analysis is carried out on the beauty equipment consumable sensing data, and a consumable state monitoring data set is generated; and performing consumable service life prediction on the consumable state monitoring data set, thereby generating consumable service life early warning data. According to the invention, through real-time monitoring, intelligent analysis and dynamic adjustment of the cloud platform, the accuracy and comprehensiveness of cloud management of the medical beauty equipment are improved.

The invention relates to the technical field of robot control, particularly discloses a path planning and dynamic obstacle avoidance control method for multi-task collaborative operation of an industrial robot, and aims to solve the problems of task scheduling conflict, dynamic obstacle response lag and low collaborative efficiency in a multi-robot system. The method comprises the following steps: constructing a task-resource joint scheduling model and generating initial task allocation; planning a conflict-free collaborative path based on an improved space-time A star algorithm; predicting a dynamic obstacle trajectory by using an LSTM network and generating a space-time envelope; constructing a second-order safety barrier function fusing task priorities; local obstacle avoidance re-planning is realized through rolling horizon model predictive control; and the global rescheduling is triggered when the task delay exceeds the limit or the deadlock risk occurs. According to the technical scheme, closed-loop linkage of global task collaboration and local dynamic obstacle avoidance is realized, and the system collaboration efficiency, the obstacle avoidance success rate and the operation robustness are remarkably improved.

The invention relates to the technical field of enterprise data management, in particular to a distributed collaborative office data processing method and system, and the method comprises the following steps: based on employee task completion records, evaluating various capability processing capabilities of employees through extracting and analyzing the project completion data, feedback frequency and interaction data of the employees, and calculating the task completion data of the employees; the task process of the current project is analyzed, the requirements of the target project for various skills are identified, and a capability and requirement data set is formed; according to the invention, through real-time monitoring and analysis of interaction data and feedback frequency of employees, capability of the employees is accurately assessed and project requirements are matched, reasonable human resource configuration is realized and flexibility of project management is improved, and through dynamic adjustment of data access authority, information security is ensured and a data leakage risk is reduced. Real-time data synchronization and consistency verification guarantee that data is accurate among multiple nodes, the team is helped to identify the reason of low efficiency in combination with analysis of cooperation efficiency, and the cooperation efficiency among team members is enhanced.

The invention discloses a product process route generation method and device based on a bill of materials, a medium and equipment, and belongs to the technical field of computer intelligence. The method comprises the following steps: acquiring an engineering drawing of a to-be-processed product; extracting a bill of material of the to-be-processed product according to the engineering drawing of the to-be-processed product; according to the bill of material of the to-be-processed product, establishing association relationship data between parts related to the to-be-processed product; and according to the incidence relation data among the parts related to the to-be-processed product and the existing process database, a preliminary process route of the to-be-processed product is generated through operation. The device, the medium and the equipment can be used for realizing the method. By integrating the functions of engineering drawing analysis, BOM automatic generation, process database matching, process route intelligent planning and optimization and the like, full-automatic conversion from a product design drawing to a production process route is realized, and powerful support is provided for digital transformation of enterprises in the manufacturing industry.

The invention discloses an MBSE-based air inlet test control device modeling method. The method comprises the following steps: S1, carrying out operation analysis; s2, system design; s3, component design; s4, constructing a Refine traceability matrix from the component demand to the system layer design and a Derive-Request traceability matrix from the component demand to the system demand, and constructing a Refine traceability matrix from the system demand to the operation analysis layer design and a Derive-Request traceability matrix from the system demand to the user demand; and S5, constructing a demand meta-model and an interface meta-model, and carrying out meta-model replacement according to an actual interface of the system. According to the method, the defects caused by a document-based system design method in the previous design process are effectively overcome, and tight combination of system design and requirements is ensured. According to the method, the readability of the model is greatly enhanced, the ambiguity problem caused by numerous elements is avoided, the repetitive work is reduced, the system iteration process is simplified, and the development period of the system is shortened.

The invention provides a smart city traffic information system based on a 5G network, and relates to the technical field of data processing, and the system comprises a digital traffic processing module which is used for collecting and analyzing the operation data of various traffic facilities and vehicles in real time so as to recognize a traffic flow mode, predict a traffic state, obtain an analysis result, and according to the analysis result, determine the traffic flow mode; traffic signals are automatically adjusted, and traffic flow is optimized; and the digital government affair cooperation module is used for automatically acquiring and distributing update information of traffic policies and laws and regulations, automatically processing traffic violation behaviors, and collecting and analyzing feedback information of the public for the traffic policies to obtain an analysis report. According to the system, a plurality of digital modules are integrated, real-time collection, intelligent analysis and efficient management of traffic information are realized, the traffic operation efficiency and safety are improved, the public participation degree and satisfaction degree are enhanced, and intelligent, collaborative and sustainable development of urban traffic is effectively promoted.

The invention discloses a code version management method based on multi-person collaboration, belongs to the technical field of software development, and in the code version management method based on the GIT distributed version control system, efficient work is guaranteed through modes of code submission, combined submission, code combination and the like. According to an existing cooperation mode, in the development process of one iteration cycle, developers can submit codes for multiple times, and after iteration development is completed through cooperation of multiple persons, many submission records appear, and therefore the code submission records are disordered. Through the technology, after each developer completes the respective task, the submission records are combined into one, so that the readability of submitted information is greatly improved. By means of code submission, merging submission, code merging and the like, high efficiency of work is guaranteed, the code submission management process is standardized, many benefits are brought to software development teams, and the method is an important means for improving software development efficiency and quality.

The invention discloses a building construction site arrangement optimization method and system and a storage medium. According to the main scheme, the method comprises the steps that topographic data, building layout data and equipment layout data of a building construction site are acquired; drawing a construction site rough arrangement diagram according to the collected building layout data and equipment layout data by using CAD software, and importing the rough arrangement diagram into BIM modeling software to generate a construction site basic model; analyzing the construction site basic model of the BIM technology, and marking a problem area of the basic model; an optimization model is formed by changing the layout of a problem area of the basic model; and analyzing the optimization model to judge whether the optimization model meets the standard or not. According to the technical scheme, intelligent optimization and real-time monitoring of construction site arrangement can be realized, the construction efficiency is improved, the cost is reduced, and the construction safety is enhanced.

The invention relates to the technical field of underwater static target object detection and processing, in particular to an unmanned cross-domain positioning and acoustic fingerprint processing method and system for an underwater static target. Comprising the following steps: performing wide-area scanning on a task sea area, and scheduling an AUV and unmanned aerial vehicle cluster to a target area after discovering a suspicious target; the unmanned aerial vehicle cluster receives an acoustic signal of the AUV and transmits the acoustic signal to the cooperative resolving center in combination with self-positioning data so as to provide accurate coordinate guidance for the AUV; the AUV sails to a target area, parallel processing map construction and accurate positioning, target identification and dual-mode fingerprint generation are carried out, and a target task package is packaged; the ROV receives and analyzes the task packet, autonomously plans a path and sails to a target area, a sonar is started to collect data and generate real-time feature fingerprints, and the real-time feature fingerprints are matched with fingerprints in the task packet; and after matching succeeds, a specific job task is autonomously executed. According to the invention, a complete automatic solution is provided for scenes such as deep and far sea detection, emergency salvage, pipeline maintenance and the like.

The present invention proposes a communication-sensitive multi-agent collaboration method, which is applied to the field of vehicle network communication technology. The method of the present invention includes: the agent uses an information filtering module to encode the locally observed message into a hidden state vector, that is, a compressed filtered message, and before sending the message, the shared medium access control module is used to score the message, and the edge computing node sorts the message value according to the score, and sends a confirmation message to the agent with the topK message value. After the agent receives the confirmation, it sends the message; the edge computing node receives all messages, uses the message distillation module to extract valid information, and summarizes and distributes it to each agent; in the process of summarizing the agent messages, the graph convolution aggregation method based on the graph information bottleneck is used to retain the agent topology structure information, and the summarized message is distilled. The present invention reduces the transmission of redundant and invalid information between agents, saves communication resources, and improves the decision-making ability and collaboration efficiency of multiple agents.

The invention discloses an intelligent monitoring platform and method based on AI vision, and relates to the technical field of security monitoring, the intelligent monitoring platform comprises a video acquisition module, an intelligent calculation module, an AI vision analysis module, an alarm module and a comprehensive management platform, the video acquisition module is used for acquiring video data of a monitoring area in real time; the intelligent calculation module comprises intelligent equipment deployed in a monitoring area, and the intelligent equipment is responsible for performing feature extraction and preliminary analysis on the video data; the AI visual analysis module is used for using a cloud server and is responsible for further performing feature extraction and analysis classification on the video data processed by the intelligent calculation module, and the alarm module is used for triggering an alarm when the intelligent calculation module and the AI visual analysis module cooperatively detect abnormal behaviors of the video data. According to the invention, the real-time performance and the accuracy of monitoring are improved, and the false alarm rate and the missing report rate are reduced; and the specific environment is monitored in a customized manner, so that the pertinence and effectiveness of monitoring are improved.

The invention discloses an underground space layout scheme VR visual interaction device and interaction method. The interaction device comprises a three-dimensional graphic processing unit, a virtual reality interaction terminal, a design software synchronization interface and a collaborative design communication module, wherein the virtual reality interaction terminal, the design software synchronization interface and the collaborative design communication module interact with the three-dimensional graphic processing unit. The three-dimensional graphic processing unit adopts a high-performance graphic processor and a special graphic acceleration chip, converts two-dimensional plane layout data into a three-dimensional space model and performs real-time rendering; the virtual reality interaction terminal serves as a direct interface for user experience and is integrated with the three-dimensional graphic processing unit through a low-delay wireless transmission module. The design software synchronization interface realizes data exchange with external design software and synchronizes modification to the three-dimensional graphic processing unit; and the collaborative design communication module is used for supporting real-time collaboration and communication of multiple users in the virtual environment. According to the method, high-performance hardware and special software are combined, so that rapid visualization and real-time interaction of underground space layout are realized.