A multi-player online system

Abstract

The application discloses a multi-person online system, solves the problem that the existing simulation training system cannot realize comprehensive multi-person online training situation information and multi-person online target movement dynamic information data by completing the starting and presenting of corresponding virtual training modules through a PC, and comprises a student end, an online management module, and an electronic sand table module; the student end is used for displaying a three-dimensional scene of a training area; the online management module is used for acquiring student motion trajectory data, analyzing and calculating the student motion trajectory based on a preset dynamic motion model; and the electronic sand table module acquires the analysis result of the student motion trajectory of the online management module and projects and presents the analysis result; the embodiment of the application is provided with the online management module, the online management module can acquire the student motion trajectory data, analyze and calculate the student motion trajectory based on the preset dynamic motion model, and comprehensively present the multi-person online training situation information and the multi-person online target movement dynamic information data.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of teaching training, and particularly relates to a multi-user online system. BACKGROUND

[0002] In recent years, human-computer interaction technology has been successfully applied to entertainment, medical treatment, smart home, automobile, education and many other fields, and has also begun to gradually integrate into everyone's life. With the continuous improvement and perfection of technology, human-computer interaction technology can effectively increase the number of simulation training entities in a virtual training environment, and can also improve the complexity and variability of the virtual training environment, thereby enhancing the perception ability of the trainees and effectively reducing the cost of the training.

[0003] Chinese patent CN108961893A discloses a virtual reality interactive simulation training system based on a VR device. The system includes a VR interactive device, a PC machine for constructing a simulation training module, and a host body for data conversion and transmission. The VR interactive device includes a head-mounted device and a sensor module. The training method is as follows: the construction of a virtual training module is completed by the PC machine combined with the three-dimensional interactive function in the VR technology, the trainee selects a virtual training module corresponding to the simulation training required; the trainee wears the VR interactive device, and the PC machine starts the corresponding virtual training module; the trainee obtains the position and situation in the virtual application scene through the head-mounted device, and completes the corresponding operation through the sensor module according to the training operation steps. However, the existing simulation training system cannot comprehensively integrate multi-user online training situation information and dynamic information data of multi-user online target movement, because it completes the starting and presentation of the corresponding virtual training module through the PC machine, resulting in poor multi-user online interaction. Therefore, we propose a multi-user online system. SUMMARY

[0004] The present application aims at the deficiencies of the prior art, and provides a multi-user online system, which solves the problem that the existing simulation training system cannot comprehensively integrate multi-user online training situation information and dynamic information data of multi-user online target movement, because it completes the starting and presentation of the corresponding virtual training module through the PC machine.

[0005] The existing simulation training system starts and presents the corresponding virtual training module through a PC, cannot achieve comprehensive multi-online training situation information and multi-online target movement dynamic information data, and leads to poor multi-online interaction. Based on this, a multi-online system is provided. Briefly, the system comprises a student end, an online management module and an electronic sand table module. The online management module is in communication connection with the student end, is used for acquiring student movement trajectory data, and is used for transcoding the student movement trajectory data and analyzing and calculating the student movement trajectory based on a preset dynamic movement model. When multi-online teaching training is performed, multiple groups of students perform synchronous training in a training area. The student end displays a three-dimensional scene of the training area, and can also acquire student movement trajectory data. The online management module is used for acquiring the student movement trajectory data, transcoding the student movement trajectory data, analyzing and calculating the student movement trajectory based on a preset dynamic movement model, and finally the electronic sand table module acquires the analysis result of the student movement trajectory of the online management module and projects and presents the analysis result. The online management module can acquire student movement trajectory data, analyze and calculate the student movement trajectory based on a preset dynamic movement model, and comprehensively present multi-online training situation information and multi-online target movement dynamic information data, thereby improving the collaboration and interaction of multi-online training.

[0006] The present application is implemented as follows. A multi-online system comprises:

[0007] A student end is used for displaying a three-dimensional scene of a training area and assisting in acquiring student movement trajectory data.

[0008] An online management module is in communication connection with the student end, is used for acquiring student movement trajectory data, transcoding the student movement trajectory data, analyzing and calculating the student movement trajectory based on a preset dynamic movement model, and finally the electronic sand table module acquires the analysis result of the student movement trajectory of the online management module and projects and presents the analysis result.

[0009] An electronic sand table module is in communication connection with the online management module, and acquires the analysis result of the student movement trajectory of the online management module and projects and presents the analysis result.

[0010] Preferably, the student end comprises:

[0011] A VR headgear is used for receiving three-dimensional map data imported by the electronic sand table module and presenting the three-dimensional map data.

[0012] A student interaction unit is used for acquiring and collecting student operation instructions and uploading the operation instructions to the online management module.

[0013] Preferably, the online management module comprises:

[0014] a trajectory preprocessing unit for obtaining student motion trajectory data and preprocessing the student motion trajectory data;

[0015] a trajectory transcoding unit electrically connected with the trajectory preprocessing unit and configured to perform uniform transcoding processing on the student motion trajectory data based on a preset transcoding rule to obtain standardized trajectory motion data;

[0016] a model construction unit for constructing a dynamic motion model.

[0017] Preferably, the online management module further comprises:

[0018] a trajectory analysis unit for analyzing and calculating student motion trajectory.

[0019] Preferably, the method for constructing the dynamic motion model specifically comprises:

[0020] obtaining model construction sample data and dividing the sample data into a training set and a validation set;

[0021] loading an initial grabbing model in the dynamic motion model and grabbing sample motion features based on the initial grabbing model;

[0022] setting motion weights of each group of features in N motion features by an iterative optimization and a stochastic gradient method, respectively, to construct a weighted learning model;

[0023] optimizing the weighted learning model based on the stochastic gradient method to construct the dynamic motion model.

[0024] Preferably, the method for constructing the dynamic motion model specifically further comprises:

[0025] loading the validation set, verifying the weighted learning model by the validation set to obtain a recognition result, judging whether the recognition result meets an expectation, and if so, completing the construction of the dynamic motion model.

[0026] Preferably, the method for analyzing and calculating student motion trajectory by the trajectory analysis unit specifically comprises:

[0027] obtaining the standardized trajectory motion data, analyzing motion feature vectors of the standardized trajectory motion data based on the dynamic motion model by the trajectory analysis unit, and performing state decomposition on the motion feature vectors based on a decomposer in the dynamic motion model to obtain a plurality of motion components;

[0028] Load a plurality of motion components, traverse the plurality of motion components based on a dynamic motion model, and analyze and calculate attribute key vectors and attribute value vectors of the motion components in a three-dimensional scene of the training area.

[0029] Preferably, the trajectory analysis unit analyzes and calculates the method of the student motion trajectory, and specifically further comprises:

[0030] The trajectory analysis unit analyzes the attribute key vector and the attribute value vector of the standardized trajectory motion data to obtain the student motion trajectory situation point.

[0031] Preferably, the electronic sand table module comprises:

[0032] The map data processing unit is used for collecting the training area terrain data, and performing noise filtering, data fusion and data decoding processing on the shaped data;

[0033] The terrain construction unit is used for loading the training area terrain data, and constructing a three-dimensional virtual map based on a preset three-dimensional modeling model;

[0034] The teaching linkage sand table is in communication connection with the map data processing unit, receives three-dimensional virtual map data, and presents the three-dimensional virtual map.

[0035] Preferably, the electronic sand table module further comprises:

[0036] The trajectory projection unit is used for acquiring the motion trajectory data and the student motion trajectory situation point, and projecting the motion trajectory data and the student motion trajectory situation point to the teaching linkage sand table based on a preset adjustment rule.

[0037] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0038] The online management module can acquire the student motion trajectory data, analyze and calculate the student motion trajectory based on the preset dynamic motion model, thereby comprehensively presenting the multi-player online training situation information and the dynamic information data of the multi-player online target movement, and improving the collaboration and interactivity of the multi-player online training.

[0039] The embodiments of the present application construct and train the dynamic motion model, thereby realizing accurate analysis of the trajectory motion data and rapid prediction of the student motion trajectory situation point, thereby facilitating the multi-player online training and teaching guidance. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 It is a structure schematic diagram of the multi-player online system provided by the present application.

[0041] Figure 2 is a structural schematic diagram of a student end provided by the present application.

[0042] Figure 3 is an operation interface schematic diagram when a VR helmet performs virtual simulation display provided by the present application.

[0043] Figure 4 is an operation display interface diagram when a VR helmet is worn to perform a local calibration map training provided by the present application.

[0044] Figure 5 is a structural schematic diagram of an online management module provided by the present application.

[0045] Figure 6 is an implementation flow schematic diagram of a dynamic motion model construction method provided by the present application.

[0046] Figure 7 is an implementation flow schematic diagram of a method for analyzing and calculating a student motion trajectory by a trajectory analysis unit provided by the present application.

[0047] Figure 8 is a structural schematic diagram of an electronic sand table module provided by the present application.

[0048] Figure 9 is an implementation flow schematic diagram of a multi-player online method provided by the present application.

[0049] In the figure: 100-student end, 110-VR helmet, 120-student interaction unit, 200-online management module, 210-trajectory preprocessing unit, 220-trajectory transcoding unit, 230-model construction unit, 240-trajectory analysis unit, 300-electronic sand table module, 310-map data processing unit, 320-terrain construction unit, 330-teaching linkage sand table, 340-trajectory projection unit. DETAILED DESCRIPTION

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the description and claims of this application as well as the above abstract are intended to cover all alternatives, modifications, and equivalents. The terms "comprising", "having", "including", and "containing" used herein are meant to be open-ended and non-limiting.

[0051] Reference to an“embodiment” herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. As will be apparent to those of ordinary skill in the art, embodiments described herein can be combined with other embodiments.

[0052] The existing simulation training system completes the starting and presentation of the corresponding virtual training module through the PC machine, and cannot achieve the comprehensive multi-online training situation information and the dynamic information data of multi-online target movement, resulting in poor multi-online interaction. Based on this, a multi-online system is proposed. In short, the system comprises a student end 100, an online management module 200 and an electronic sand table module 300. The online management module 200 is in communication connection with the student end 100, and the online management module 200 is used for acquiring student motion trajectory data, and transcoding the student motion trajectory data, and analyzing and calculating the student motion trajectory based on a preset dynamic motion model. When multi-online teaching training is carried out, a plurality of groups of students carry out synchronous training in a training area. The student end 100 displays a three-dimensional scene of the training area. The student end 100 can also collect student motion trajectory data. The online management module 200 is used for acquiring student motion trajectory data, and transcoding the student motion trajectory data, and analyzing and calculating the student motion trajectory based on a preset dynamic motion model. Finally, the electronic sand table module 300 acquires the student motion trajectory analysis result of the online management module 200, and projects and presents the analysis result. The embodiment of the application is provided with the online management module 200. The online management module 200 can acquire student motion trajectory data, and analyze and calculate the student motion trajectory based on a preset dynamic motion model, so as to comprehensively present multi-online training situation information and dynamic information data of multi-online target movement, and improve the collaboration and interaction of multi-online training.

[0053] The embodiment of the application provides a multi-online system, Figure 1 The structure diagram of the multi-online system is shown. The multi-online system specifically comprises:

[0054] The student end 100 is used for displaying a three-dimensional scene of a training area, and assisting in collecting student motion trajectory data.

[0055] The online management module 200 is in communication connection with the student end 100, and the online management module 200 is used for acquiring student motion trajectory data, and transcoding the student motion trajectory data, and analyzing and calculating the student motion trajectory based on a preset dynamic motion model.

[0056] An electronic sand table module 300 is in communication connection with the online management module 200, and the electronic sand table module 300 obtains the analysis result of the student motion trajectory of the online management module 200 and projects and presents the analysis result.

[0057] It should be noted that the online management module 200, the student end 100 and the electronic sand table module 300 can realize the interaction of data through the communication connection mode of SCK, MOSI, MISO and SS lines, the online management module 200 can serve the student end 100 in a one-to-n group of student end 100 mode, and it is ensured that multiple people and multiple groups of students can perform multi-person online training in the training area.

[0058] In the embodiment, when multi-person online teaching training is performed, multiple groups of students perform synchronous training in the training area, the student end 100 displays the three-dimensional scene of the training area, and the student end 100 can also collect student motion trajectory data, the online management module 200 is used for obtaining the student motion trajectory data, and the student motion trajectory data is transcoded, the student motion trajectory is analyzed and calculated based on a preset dynamic motion model, and finally the electronic sand table module 300 obtains the analysis result of the student motion trajectory of the online management module 200 and projects and presents the analysis result.

[0059] The embodiment of the application is provided with the online management module 200, the online management module 200 can obtain student motion trajectory data, and analyze and calculate the student motion trajectory based on a preset dynamic motion model, so as to comprehensively present multi-person online training situation information and dynamic information data of multi-person online target movement, and improve the collaboration and interaction of multi-person online training.

[0060] The embodiment of the application provides a student end 100, Figure 2 The structure diagram of the student end 100 is shown, and the student end 100 specifically includes:

[0061] The VR helmet 110 is used for receiving three-dimensional map data introduced by the electronic sand table module 300 and presenting the three-dimensional map data, as shown in Figure 3 As shown in the figure, the operation interface schematic diagram when the VR helmet 110 performs virtual simulation display is shown.

[0062] The student interaction unit 120 is used for obtaining and collecting student operation instructions and uploading the operation instructions to the online management module 200.

[0063] It should be noted that the VR helmet 110 presents a three-dimensional map in a manner combining VR technology, and the student can be taught to read a map, identify terrain and objects, and perform real scene synthesis in a VR environment by wearing the VR helmet 110. Meanwhile, when the student wears the VR helmet 110 for training, the student can perform on-site orientation, on-site map calibration, on-site map comparison, on-site point determination, and distance calculation learning and training tasks, such as Figure 4 As shown in the figure, an operation display interface diagram is shown when the VR helmet 110 is used for on-site map calibration training.

[0064] In this embodiment, the student interaction unit 120 can be used in combination with a professional virtual reality hardware platform, and the student interaction unit 120 can support all mobile virtual reality devices of the VR platform, as well as professional 3D projectors or naked-eye 3D display devices. At the same time, the three-dimensional map data imported into the VR helmet 110 supports the use of a local area network or offline.

[0065] Meanwhile, in this embodiment, the VR helmet 110 is built-in with multiple API interfaces, including but not limited to a reserved interface 1 (future import, 2D / 3D map conforming to software standards), a network interface, a WEB permission control interface, a user login interface, a user management interface, a user department management interface, a server configuration information interface, a version information acquisition interface, a log service interface, a server information acquisition interface, a statistics interface, and a user behavior recording interface.

[0066] The embodiment of the present application provides an online management module 200, Figure 5 The structure diagram of the online management module 200 is shown, and the online management module 200 specifically includes:

[0067] A trajectory preprocessing unit 210 is configured to obtain student motion trajectory data and preprocess the student motion trajectory data.

[0068] It should be noted that the preprocessing of the student motion trajectory data includes but is not limited to noise filtering, data fusion, and data decoding, and the student motion trajectory data is obtained through multiple sensors installed on the VR helmet 110.

[0069] A trajectory transcoding unit 220 is electrically connected with the trajectory preprocessing unit 210, and the trajectory transcoding unit 220 uniformly transcodes the student motion trajectory data based on a preset transcoding rule to obtain standardized trajectory motion data.

[0070] A model construction unit 230 is configured to construct a dynamic motion model.

[0071] a trajectory analysis unit 240 configured to analyze and calculate the trajectory of the student.

[0072] In this embodiment, the model construction unit 230 and the trajectory analysis unit 240 can communicate through a Wi-Fi, Bluetooth, or wired (such as Ethernet) network.

[0073] The embodiment of the present application provides a dynamic motion model construction method, Figure 6 The embodiment of the present application provides a dynamic motion model construction method,

[0074] In step S101, model construction sample data is obtained, and the sample data is divided into a training set and a validation set.

[0075] In this embodiment, the model construction sample data can be obtained from a historical database, and the sample ratio of the training set and the validation set can be 3:1.

[0076] In step S102, an initial grabbing model in the dynamic motion model is loaded, and sample motion features are grabbed based on the initial grabbing model.

[0077] The initial grabbing model is specifically a neural network model based on deep learning, and the initial grabbing model includes a grabbing module, a convolution module, and an LSTM module, and the convolution module is provided with three convolution sections, each of which includes a convolution layer, a ReLu activation layer, and a pooling layer.

[0078] In step S103, the motion weight of each group of features in N motion features is set through an iterative optimization and a stochastic gradient method, and a weighted learning model is constructed.

[0079] In this embodiment, the motion weight of each group of features in N motion features is set through an iterative optimization and a stochastic gradient method, and the number of iterations can be 100 times.

[0080] In step S104, the weighted learning model is optimized based on the stochastic gradient method, and a dynamic motion model is constructed.

[0081] In step S105, the validation set is loaded, the weighted learning model is verified through the validation set, and a recognition result is obtained.

[0082] In step S106, it is determined whether the recognition result meets the expectation, and in this embodiment, the preset expectation of the recognition result can be that the recognition accuracy is greater than 95%.

[0083] In step S107, if the recognition result meets the expectation, the construction of the dynamic motion model is completed, and if the recognition result does not meet the expectation, step S102 is re-executed to re-train and verify the model.

[0084] The embodiment of the present application realizes accurate analysis on trajectory motion data and rapid prediction of the motion trajectory trend point of the trainee by constructing and training a dynamic motion model, thereby facilitating the multi-player online training and teaching guidance of the teacher.

[0085] The embodiment of the present application provides a method for analyzing and calculating the motion trajectory of the trainee by the trajectory analysis unit 240, Figure 7 The implementation flowchart of the method for analyzing and calculating the motion trajectory of the trainee by the trajectory analysis unit 240 is shown, and the method for analyzing and calculating the motion trajectory of the trainee by the trajectory analysis unit 240 specifically comprises:

[0086] In step S201, the standardized trajectory motion data is obtained, the trajectory analysis unit 240 analyzes the motion feature vector of the standardized trajectory motion data based on the dynamic motion model, and the state decomposition of the motion feature vector is performed based on the decomposer in the dynamic motion model, thereby obtaining a plurality of motion components;

[0087] In step S202, the plurality of motion components are loaded, the plurality of motion components are traversed based on the dynamic motion model, and the attribute key vector and the attribute value vector of the motion component in the three-dimensional scene of the training area are obtained.

[0088] In step S203, the trajectory analysis unit 240 analyzes the attribute key vector and the attribute value vector of the standardized trajectory motion data to obtain the motion trajectory trend point of the trainee.

[0089] The embodiment of the present application provides an electronic sand table module 300, Figure 8 The structure diagram of the electronic sand table module 300 is shown, and the electronic sand table module 300 specifically comprises:

[0090] The map data processing unit 310 is used to collect the training area terrain data, and perform noise filtering, data fusion and data decoding processing on the shaped data;

[0091] The terrain construction unit 320 is used to load the training area terrain data, and construct a three-dimensional virtual map based on a preset three-dimensional modeling model;

[0092] In the embodiment, the preset three-dimensional modeling model can be Blender V2.9, and the terrain is modeled by using the Blender V2.9 modeling tool with the imported terrain data. This may include the drawing of topography features such as terrain undulations, mountains, rivers, etc. The powerful modeling tool of Blender can be used to create realistic terrain models.

[0093] And the three-dimensional modeling model in modeling, mountains, rivers, roads, contour lines and other features in the three-dimensional environment 1:1 construction, in the construction of 3D map can be in which the present site fixed point, calculation and other teaching.

[0094] Teaching interactive sand table 330, the teaching interactive sand table 330 is connected with the map data processing unit 310 and receives three-dimensional virtual map data, and presents three-dimensional virtual map.

[0095] In this embodiment, the student logs in to the online management module 200 through the teaching interactive sand table 330 device. The student can adjust the observation angle according to the position, dynamically zoom in and out the map, and view the details or overview of the map. Support multiple students to use at the same time, can be calculated, determine the target point, identify the map in the small screen 3D sand table, the teaching interactive sand table 330 requires that the house model precision reaches the II level standard, the building scale conforms to the real situation, which is manifested as a cuboid shape, which can be basically identified through the feature without texture mapping; The structure of the terrain model conforms to the real situation, which shows the basic shape, and the topographic features can be obviously identified through the model. The texture mapping is collected on site, and the texture performance should conform to the real situation; Each small land block has less than 5000 faces. At the same time, the teaching interactive sand table 330 supports multiple display modes, the 3D map can be freely zoomed in and out, the observation angle can be switched, and the student can also freely move in the scene in the first person mode (the simulation interaction mode is WASD).

[0096] The trajectory projection unit 340 is used for acquiring motion trajectory data and student motion trajectory situation points, and projecting the motion trajectory data and student motion trajectory situation points to the teaching interactive sand table 330 based on a preset adjustment rule.

[0097] On the other hand, the embodiment of the present application also provides a multi-player online method, Figure 9 The implementation flowchart of the multi-player online method is shown, and the multi-player online method specifically includes:

[0098] Step S10, collecting student motion trajectory data;

[0099] Step S20, acquiring student motion trajectory data, and transcoding the student motion trajectory data, analyzing and calculating the student motion trajectory based on a preset dynamic motion model;

[0100] Step S30, acquiring the analysis result of the student motion trajectory of the online management module 200, and projecting and presenting the analysis result.

[0101] The embodiment of the present application also provides a structural diagram of a computer device, which comprises a display screen, a memory, a processor and a computer program, wherein the memory stores the computer program, and the computer program is executed by the processor to enable the processor to execute the steps of the multi-player online method.

[0102] It can be understood that, in the preferred embodiment provided by the present application, the computer device can also be a notebook computer, a personal digital assistant (PDA), a mobile phone or other communication device.

[0103] For example, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the terminal device. For example, the computer program can be divided into the units or modules of the multi-player online system provided by the above-mentioned various system embodiments.

[0104] Those skilled in the art can understand that the description of the terminal device is only an example and does not constitute a limitation on the terminal device, and the terminal device can include more or less components than the above description, or combine certain components or different components, for example, can include an input / output device, a network access device, a bus and the like.

[0105] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or can also be any conventional processor. The above processor is the control center of the terminal device, and is connected with various parts of the terminal device through various interfaces and lines.

[0106] The memory can be used to store computer programs and / or modules, and the processor realizes various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area. In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0107] In summary, the application provides a multi-user online system. When multi-user online teaching training is performed, multiple groups of trainees perform synchronous training in a training area. A trainee terminal 100 displays a three-dimensional scene of the training area. The trainee terminal 100 can also collect trainee motion trajectory data. An online management module 200 is configured to acquire the trainee motion trajectory data, transcode the trainee motion trajectory data, analyze and calculate the trainee motion trajectory based on a preset dynamic motion model, and finally an electronic sand table module 300 acquires the analysis result of the trainee motion trajectory of the online management module 200 and projects and presents the analysis result.

[0108] The online management module 200 can acquire the trainee motion trajectory data, analyze and calculate the trainee motion trajectory based on a preset dynamic motion model, and comprehensively present multi-user online training situation information and dynamic information data of multi-user online target movement, thereby improving the collaboration and interactivity of multi-user online training.

[0109] It should be noted that, for the foregoing embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the application is not limited by the action sequence described, because according to the application, some steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the application.

[0110] In several embodiments provided by the present application, it should be understood that the disclosed apparatus can be implemented in other manners. For example, the division of the apparatus embodiments described above is merely illustrative, and the division of the units can be changed according to actual needs. For example, two or more units can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0111] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0112] The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the protection scope of the application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on these embodiments, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art can still make some modifications or adjustments to the features of the embodiments of the present application according to the actual situation without conflict and without creative labor, so as to obtain different, but essentially not deviating from the concept of the present application. Other technical solutions, which also belong to the scope of protection of the present application.

Claims

1. A multiplayer online system, characterized in that, The multi-user online system includes: The student terminal is used to display the three-dimensional scene of the training area and assist in collecting student movement trajectory data; The online management module is connected to the student's terminal for communication. The online management module is used to acquire the student's movement trajectory data, transcode the student's movement trajectory data, and analyze and calculate the student's movement trajectory based on a preset dynamic motion model. An electronic sand table module is connected to an online management module, and the electronic sand table module obtains the student movement trajectory analysis results from the online management module and projects the analysis results. The online management module also includes: A trajectory analysis unit, which is used to analyze and calculate the student's movement trajectory; The method by which the trajectory analysis unit analyzes and calculates the student's movement trajectory specifically includes: Standardized trajectory motion data is acquired, and the trajectory analysis unit analyzes the motion feature vectors extracted from the standardized trajectory motion data based on the dynamic motion model. The motion feature vectors are then decomposed into several motion components based on the decomposer in the dynamic motion model. Load several motion components, traverse several motion components based on the dynamic motion model, and assign attribute key vectors and attribute value vectors to the motion components in the 3D scene of the training area. The method for the trajectory analysis unit to analyze and calculate the student's movement trajectory specifically includes: The trajectory analysis unit analyzes the attribute key vector and attribute value vector of the standardized trajectory motion data to obtain the student's motion trajectory status points.

2. The multiplayer online system as described in claim 1, characterized in that: The student terminal includes: VR headset, the VR headset is used to receive three-dimensional map data imported by the electronic sand table module and to present the three-dimensional map data; The student interaction unit is used to acquire and collect student operation instructions and upload the operation instructions to the online management module.

3. A multiplayer online system as described in claim 1, characterized in that: The online management module includes: A trajectory preprocessing unit is used to acquire student movement trajectory data and preprocess the student movement trajectory data. The trajectory transcoding unit is electrically connected to the trajectory preprocessing unit, and the trajectory transcoding unit performs unified transcoding processing on the student's motion trajectory data based on preset transcoding rules to obtain standardized trajectory motion data. A model building unit is used to build a dynamic motion model.

4. A multiplayer online system as described in claim 3, characterized in that: The method for constructing the dynamic motion model specifically includes: Obtain sample data for model building and divide the sample data into training set and validation set; Load the initial grasping model in the dynamic motion model, and extract the motion features of the grasped samples based on the initial grasping model; A weighted learning model is constructed by setting the motion weights of each group of features in N motion features using iterative optimization and stochastic gradient methods. The weighted learning model is optimized using the stochastic gradient method to construct a dynamic motion model.

5. A multiplayer online system as described in claim 4, characterized in that: The method for constructing the dynamic motion model further includes: Load the validation set, validate the weighted learning model using the validation set, obtain the recognition results, and determine whether the recognition results meet the expectations. If they do, the construction of the dynamic motion model is complete.

6. A multiplayer online system as described in claim 5, characterized in that: The electronic sand table module includes: A map data processing unit is used to collect terrain data of the training area and perform noise filtering, data fusion, and data decoding on the terrain data. A terrain construction unit is used to load terrain data of the training area and construct a three-dimensional virtual map based on a preset three-dimensional modeling model. The teaching-linked sand table is connected to the map data processing unit and receives three-dimensional virtual map data to present a three-dimensional virtual map.

7. A multiplayer online system as described in claim 6, characterized in that: The electronic sand table module also includes: The trajectory projection unit is used to acquire motion trajectory data and student motion trajectory status points, and project the motion trajectory data and student motion trajectory status points onto the teaching linkage sand table based on preset adjustment rules.

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