VR multi-user interaction flexible space system

Abstract

The invention discloses a VR multi-user interaction flexible space system, and relates to the technical field of multi-user VR interaction, teaching course arrangement is obtained from a management manual of a specified campus, the accuracy and practicability of a virtual environment are ensured, and the environment requirement information is set in a VR platform by a worker, so that the user experience is improved. The virtual teaching environment is customized and optimized in a personalized manner, the VR platform accurately optimizes the internal space according to the teaching environment type, the number of people needing to be accommodated in the space and the space layout, the practicability of the environment and the comfort level of students are improved, VR equipment is used for collecting the face information of the students, an exclusive VR image is generated, the immersion and the reality are enhanced, and in the interaction evaluation stage, the interaction evaluation efficiency is improved. Through guidance of the conflict processing module, optimization of resource allocation and interaction experience is facilitated, the conflict processing module evaluates interaction conflicts of students in a VR environment in real time, virtual experiment apparatuses are intelligently allocated according to priority information, and fairness and efficiency of resource allocation are ensured.

Description

Technical Field

[0001] The present invention relates to the field of multi-person VR interaction technology, and in particular to a VR multi-person interactive flexible space system. Background Art

[0002] With the rapid development of virtual reality (VR) technology and the continuous improvement of educational needs, VR is seen as an emerging tool that can revolutionize traditional teaching models. The potential of VR education lies in its ability to create an immersive learning environment for students, allowing them to practice and explore in a safe and interactive environment. In order to fully tap the educational value of VR, it is imperative to develop an efficient VR multiplayer interactive flexible space system.

[0003] Prior art, such as the invention patent application with announcement number CN116679834A, discloses a large-space multi-person VR interactive experience system and method, in which the interactive action delay of the interactive handle is small, the simulation accuracy is high, and the interaction of multiple users will not cause interference. The specific positioning of the user in the experience space is convenient and accurate, reducing positioning deviation, improving the accuracy of interaction, and there is no blocking between users or handles. There is no need for a large number of high-difficulty algorithms to cooperate with positioning, which reduces the difficulty of developing VR interaction and the load on system operation, making it convenient for more people to participate at the same time and improving the user's VR experience, making various actions and interactions in the experience space more accurate, allowing multiple users to interact with each other to increase the fun of VR interaction, and allowing users to have a more immersive VR experience.

[0004] There are at least the following technical problems with the above scheme: 1. The above scheme lacks a description of the evaluation of positioning accuracy and interaction stability in a multi-user environment, which may lead to positioning errors and untimely interactions in the VR experience. Although it mentions that the interactive action delay of the interactive handle is small and the simulation accuracy is high, it does not provide detailed instructions on how to achieve positioning accuracy and interaction stability. In addition, it does not include details such as how to deal with interference and mutual blocking between multiple users. As a result, in actual applications, when the number of users increases, the system cannot effectively guarantee the stability of positioning and interaction, thus affecting the experience effect.

[0005] 2. The above scheme lacks a sustainable development evaluation mechanism for the VR teaching environment, which will make it impossible to scientifically judge the effectiveness of the teaching environment. Although it mentions improving the user's immersive experience, it does not include how to evaluate the sustainable development capabilities of the environment, which will make it impossible to monitor and optimize the teaching environment in the long term, and unable to ensure that VR teaching remains competitive and adaptable in the evolving educational technology. Summary of the invention

[0006] The purpose of the present invention is to provide a VR multi-person interactive flexible space system to solve the problems existing in the background technology.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a VR multi-person interactive flexible space system, including: a VR environment creation module, which is used to obtain the teaching course schedule of a specified campus under a specified teaching background, and then create various VR teaching environments that meet multi-person interaction.

[0008] The VR environment control unit is used to evaluate the interaction process of each student in each VR teaching environment.

[0009] The display terminal is used to display the interaction of each student in the VR teaching environment.

[0010] The beneficial effects of the present invention are: 1. A VR multi-person interactive flexible space system provided by the present invention can ensure the accuracy and practicality of the virtual environment by obtaining the teaching course schedule from the management manual of the designated campus. The staff can set the environmental demand information in the VR platform, which is conducive to personalized customization and optimization of the virtual teaching environment. According to the type of teaching environment, the number of people to be accommodated in the space and the spatial layout, the VR platform can accurately optimize the internal space, improve the practicality of the environment and the comfort of students, use VR equipment to collect students' facial information, generate exclusive VR images, enhance immersion and reality, and present the real image of the students in the virtual environment, which greatly improves their presence and participation in the virtual environment.

[0011] 2. In the interactive evaluation stage, the embodiment of the present invention is conducive to optimizing resource allocation and interactive experience through the guidance of the conflict handling module. The conflict handling module evaluates the interactive conflicts that occur among students in the VR environment in real time, and intelligently allocates virtual experimental equipment according to priority information, thereby ensuring the fairness and efficiency of resource allocation and reducing unnecessary disputes caused by resource competition. Through reasonable guidance and management, students can complete teaching tasks in a good interactive atmosphere and improve the overall learning experience.

[0012] 3. The embodiments of the present invention obtain the adaptability parameters of students in various VR teaching environments, which is conducive to comprehensively evaluating the sustainable development of the teaching environment. The collection and analysis of adaptability parameters provides multi-dimensional data on students' interest, participation and satisfaction, which is helpful to evaluate and improve the teaching environment, objectively evaluate whether the teaching environment meets the requirements of long-term development, and ensure the continuous updating and optimization of teaching content. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] See also Figure 1 As shown, the present invention provides a VR multi-person interactive flexible space system, which includes: a VR environment creation module, a VR environment control unit, a conflict handling module, a sustainable development assessment module, an early warning terminal and a database.

[0017] The VR environment creation module is connected to the VR environment control unit, the VR environment control unit includes a conflict handling module and a sustainable development assessment module, the conflict handling module is connected to the sustainable development assessment module, and the VR environment control unit is respectively connected to the early warning terminal and the database.

[0018] The VR environment creation module is used to obtain the teaching course schedule of a specified campus under a specified teaching background, and then create various VR teaching environments that meet the needs of multi-person interaction.

[0019] In a specific embodiment, the specific process of creating each VR teaching environment that satisfies multi-person interaction is as follows: S1. Obtain the teaching course schedule of the designated campus from the campus management manual of the designated campus, divide the process of each VR teaching environment into preliminary environment creation and student image creation, and create each VR teaching environment in the VR platform of the Web.

[0020] S2. According to the teaching course arrangement of the designated campus, the staff sets the environmental demand information of each VR teaching environment in the VR platform. The environmental demand information includes the type of teaching environment, the number of people that the space needs to accommodate, and the spatial layout. According to the type of each teaching environment, the VR platform displays each VR teaching environment corresponding to the type of teaching environment. According to the teaching course arrangement of the designated campus, the VR teaching environments that meet the teaching course arrangement of the designated campus are selected and recorded as each VR teaching environment to be optimized. According to the number of people that the space needs to accommodate and the spatial layout set by the staff, the VR platform optimizes the internal space of each VR teaching environment to be optimized, thereby realizing the preliminary environment creation of each VR teaching environment.

[0021] S3. Through VR teaching simulation training, VR equipment is used to collect the corresponding facial information of each student during the VR teaching simulation training. According to the facial information of each student, the VR platform generates an exclusive VR image corresponding to each student, thereby realizing the creation of each student's image, thereby completing the creation of various VR teaching environments for multi-person interaction.

[0022] It should be noted that the VR teaching environments include VR laboratories, VR libraries, VR outdoor parks, VR museums and VR virtual conference rooms, etc. The VR equipment contains head-mounted displays and limb tracking sensors, and the head-mounted displays contain cameras and audio equipment, etc. The "teaching course arrangement" mainly refers to the specific content, class schedule, lecturers, teaching objectives and classroom activities of each course in the designated campus. The "Web" in the "Web-based VR platform" refers to an online platform realized by Internet technology. "Web" allows users to access the VR environment through a browser without the need to install special software. The spatial layout refers to the internal dimensions of the VR teaching environment and the arrangement of desks and chairs inside. Optimizing the internal space of each VR teaching environment to be optimized refers to expanding or reducing the internal space of each VR teaching environment.

[0023] The VR environment control unit is used to evaluate the interaction process of each student in each VR teaching environment, and specifically includes: a conflict handling module and a sustainable development evaluation module.

[0024] The conflict handling module is used to evaluate the conflicts among students in the VR teaching environment.

[0025] In a specific embodiment, the analysis of conflicts among students in a VR teaching environment is performed as follows:

[0026] When each student wears a VR device to conduct VR experiment interaction in a VR laboratory, if the number of students who take the same virtual experiment equipment in the VR laboratory at time point b is greater than or equal to 2, the students who take the same virtual experiment equipment at time point b are recorded as conflicting students, and the priority information corresponding to each conflicting student is obtained. The priority information includes the comprehensive learning score, the experiment completion progress and the visual locking time. The conflict priority coefficient corresponding to each conflicting student is calculated, and then the conflict priority level corresponding to each conflicting student is obtained. When each conflicting student takes the virtual experiment equipment at time point b, according to the conflict priority level of each conflicting student, the virtual experiment equipment is preferentially allocated to the conflicting student with the first conflict priority level. When the conflicting student with the first conflict priority level has used up the virtual experiment equipment, a pop-up window is displayed to prompt the conflicting student with the second conflict priority level, so as to complete the allocation of virtual experiment equipment.

[0027] It should be noted that b is an arbitrary set time point, and the conflict that occurs among students in the VR teaching environment refers to multiple students taking the same object in the VR teaching environment at the same time point, and the objects include but are not limited to virtual experimental equipment, virtual books and virtual stationery.

[0028] In a specific embodiment, the conflict priority coefficient corresponding to each conflicting student is calculated, and the specific calculation process is as follows: the standard control priority information corresponding to the student in the VR teaching environment is obtained from the database, and the standard control priority information includes the standard control comprehensive learning score, the standard control experiment completion progress and the standard control visual locking time.

[0029] By calculating the formula Get the conflict priority coefficient VR corresponding to each conflicting student i , i is the number of each conflicting student, i=1, 2,..., n, n is the total number of conflicting students, n is a positive integer, where Pi, Hi, Ti represent the comprehensive learning score, experiment completion progress, and visual lock duration corresponding to the i-th conflicting student, respectively; P′, H′, T′ represent the standard control comprehensive learning score, standard control experiment completion progress, and standard control visual lock duration, respectively; ι1, ι2, ι3 are the weight factors corresponding to the set comprehensive learning score, the weight factor corresponding to the experiment completion progress, and the weight factor corresponding to the visual lock duration, respectively.

[0030] It should be noted that the values ​​of ι1, ι2, and ι3 are all greater than 0 and less than 1, and ι1+ι2+ι3=1.

[0031] It should also be noted that the importance of each factor is determined through expert evaluation and historical conflict priority coefficient. For example, if a VR teaching course emphasizes practicality, the weight of the experiment completion progress is set to 0.5, and the comprehensive learning score and visual lock time are each 0.25. In the specific setting, the comprehensive learning score reflects the overall mastery of the students, the experiment completion progress reflects the practical application ability, and the visual lock time measures the students' concentration on specific content. For example, if recent data shows that students are generally lagging behind in completing the experiment progress, the weight of the experiment completion progress can be appropriately increased to 0.6, and the weight factor corresponding to the experiment completion progress and the weight factor corresponding to the visual lock time are each 0.2.

[0032] In a specific embodiment, the conflict priority level corresponding to each conflicting student is obtained, and the specific analysis process is as follows: each conflict priority coefficient interval is obtained from the database, each conflict priority coefficient interval corresponds to each conflict priority level, and the conflict priority coefficient corresponding to each conflicting student is compared with each conflict priority coefficient interval respectively. If the conflict priority coefficient corresponding to the i-th conflicting student belongs to a certain conflict priority coefficient interval, it indicates that the conflict priority level corresponding to the i-th conflicting student is the conflict priority level corresponding to the conflict priority coefficient interval, so as to obtain the conflict priority level corresponding to each conflicting student.

[0033] In a specific embodiment, the priority information corresponding to each conflicting student is obtained by the following specific acquisition process: the number of times each conflicting student actively answers questions and helps classmates solve problems in the VR teaching environment is obtained from the database, and the number of times each conflicting student actively answers questions and helps classmates solve problems is calculated by the formula P i =c i *κ1+d i *κ2, and the comprehensive learning score Pi corresponding to each conflicting student is obtained. ci and di respectively represent the number of times the i-th conflicting student actively answers questions and helps classmates solve problems in the VR teaching environment. κ1 and κ2 are the weight factors of the number of times the i-th conflicting student actively answers questions and helps classmates solve problems, respectively.

[0034] The experimental completion progress corresponding to the VR experimental interaction of each conflicting student in the VR laboratory is obtained from the database, and the corresponding time point when each conflicting student visually locks on the virtual experimental equipment and the corresponding time point when the visual leaves the virtual experimental equipment are obtained through the pupil tracking function in the VR device. By performing a difference calculation, the visual locking time corresponding to the VR experimental interaction of each conflicting student in the VR laboratory is obtained.

[0035] It should be noted that the values ​​of κ1 and κ2 are both greater than 0 and less than 1, κ1+κ2=1, and the setting process of κ1 and κ2 is the same as the setting process of ι1, ι2, and ι3, which will not be repeated here.

[0036] In the interactive evaluation stage, the embodiment of the present invention is conducive to optimizing resource allocation and interactive experience through the guidance of the conflict handling module. The conflict handling module evaluates the interactive conflicts that occur among students in the VR environment in real time, and intelligently allocates virtual experimental equipment according to priority information, thereby ensuring the fairness and efficiency of resource allocation and reducing unnecessary disputes caused by resource competition. Through reasonable guidance and management, students can complete teaching tasks in a good interactive atmosphere and improve the overall learning experience.

[0037] The sustainable development evaluation module is used to obtain the corresponding adaptability parameters of each student in each VR teaching environment, and then calculate the comprehensive interest coefficient of each student in each VR teaching environment, thereby analyzing whether each VR teaching environment meets the sustainable development requirements of VR teaching.

[0038] In a specific embodiment, the adaptability parameters corresponding to each student in each VR teaching environment are obtained, and the specific acquisition process is as follows: the adaptability parameters include facial information scores, average number of interactions, and average number of completed tasks. The facial expression images corresponding to each student in each VR teaching environment are obtained through the camera set in the VR device worn by each student. The scores of the facial expression images corresponding to each student are obtained through image recognition technology and deep learning algorithms. Facial expressions are divided into positive facial expressions and negative facial expressions. The scores are calculated by formula M x =JJ x *μ1+XJ x *μ2, get the facial information score M of each student in each VR teaching environment x , x is the number of each student, x = 1, 2, ..., y, y is the total number of students, y is a positive integer, JJ x and XJ x They are respectively represented as the positive facial expression score and negative facial expression score corresponding to the x-th student, μ1 and μ2 are the set positive facial expression score weight factors and negative facial expression score weight factors respectively.

[0039] The number of interactions and the number of completed tasks of each student in each VR teaching environment are obtained from the database, and the number of interactions and the number of completed tasks of each student in each VR teaching environment are accumulated respectively to obtain the total number of interactions and the total number of completed tasks of each student in each VR teaching environment. The total number of interactions and the total number of completed tasks of each student in each VR teaching environment are divided by the number of VR teaching environments respectively, and the result obtained is the average number of interactions and the average number of completed tasks of each student in each VR teaching environment.

[0040] It should be noted that the values ​​of μ1 and μ2 are both greater than 0 and less than 1, μ1+μ2=1, and the setting process of μ1 and μ2 is the same as the setting process of ι1, ι2, and ι3, which will not be elaborated here. The facial information scoring standard is set in advance, for example: the positive facial expression score is 0 to 20, and the negative facial expression score is -10 to 0. The facial expression image of a student is analyzed by image recognition technology and deep learning algorithm. Assuming that the student shows a smile and eye concentration during the VR teaching process, the student's expression is first determined to be a positive facial expression, and the positive facial expression is identified and analyzed with the positive facial expression large model to obtain the student's positive facial expression score, so as to analyze the corresponding facial expression score of each student.

[0041] It should also be noted that image recognition technology and deep learning algorithms are existing technologies and will not be elaborated on here. The number of interactions includes but is not limited to the number of conversations students have with other students, the number of operations students have on virtual experimental equipment, tools or interfaces, and the number of questions students ask teachers or the system in a VR teaching environment. The number of completed tasks includes but is not limited to the number of tasks students have completed independently and the number of tasks students have completed at different stages of the course.

[0042] In a specific embodiment, the comprehensive interest coefficient of each student in each VR teaching environment is calculated, and the specific calculation process is as follows: the standard control adaptability parameters corresponding to the students in the VR teaching environment are obtained from the database, and the standard control adaptability parameters include the standard control facial information score, the standard control average number of interactions and the standard control average number of completed tasks.

[0043] By calculating the formula Get the comprehensive interest coefficient of each student in each VR teaching environment j is the number of each VR teaching environment, j=1, 2,..., m, m is the total number of VR teaching environments, m is a positive integer, where Mxj, Wxj, and Dxj respectively represent the facial information score, average number of interactions, and average number of completed tasks of the xth student in the jth VR teaching environment, M′, W′, and D′ respectively represent the facial information score of the standard control, the average number of interactions of the standard control, and the average number of completed tasks of the standard control, ν1, ν2, and ν3 respectively represent the weight factors corresponding to the set facial information score, the average number of interactions, and the average number of completed tasks.

[0044] It should be noted that the values ​​of ν1, ν2, and ν3 are all greater than 0 and less than 1, ν1+ν2+ν3=1, and the setting process of ν1, ν2, and ν3 is the same as the setting process of ι1, ι2, and ι3, which will not be elaborated here.

[0045] In a specific embodiment, the analysis of whether each VR teaching environment meets the requirements of sustainable development of VR teaching is as follows: the comprehensive interest coefficient of each student in each VR teaching environment is accumulated to obtain the total comprehensive interest coefficient corresponding to each VR teaching environment, the comprehensive interest coefficient threshold corresponding to each VR teaching environment is obtained from the database, and the total comprehensive interest coefficient corresponding to each VR teaching environment is compared with the comprehensive interest coefficient threshold. If the total comprehensive interest coefficient corresponding to a VR teaching environment is greater than or equal to the comprehensive interest coefficient threshold, it indicates that the VR teaching environment meets the requirements of sustainable development of VR teaching, otherwise it indicates that the VR teaching environment does not meet the requirements of sustainable development of VR teaching, so as to analyze whether each VR teaching environment meets the requirements of sustainable development of VR teaching.

[0046] It should be noted that, by conducting spatial layout and teaching content analysis and student questionnaire surveys on various VR teaching environments that do not meet the requirements for the sustainable development of VR teaching, the specific reasons for the low comprehensive interest coefficient were obtained. The specific reasons include but are not limited to unattractive content, insufficient interactivity and technical problems. According to the specific reasons, each VR teaching environment was adjusted and optimized, for example, updating teaching content, strengthening interactive design, modifying layout, adding interactive games to attract students' attention, conducting teacher training, environmental optimization, technology upgrades and a circular evaluation mechanism.

[0047] The embodiments of the present invention obtain the adaptability parameters of students in various VR teaching environments, which is conducive to comprehensively evaluating the sustainable development of the teaching environment. The collection and analysis of adaptability parameters provides multi-dimensional data on students' interest, participation and satisfaction, which is helpful to evaluate and improve the teaching environment, objectively evaluate whether the teaching environment meets the requirements of long-term development, and ensure the continuous updating and optimization of teaching content.

[0048] The display terminal is used to display the interaction status of each student in the VR teaching environment. The specific display content includes: when the conflict priority level corresponding to each conflicting student is obtained or a VR teaching environment does not meet the requirements of sustainable development of VR teaching, a prompt is displayed.

[0049] The database is used to store the standard control priority information corresponding to the students in the VR teaching environment, the standard control priority information includes the standard control comprehensive learning score, the standard control experiment completion progress and the standard control visual lock time, and also stores each conflict priority coefficient interval, each conflict priority coefficient interval corresponds to each conflict priority level, and also stores the number of active answers to questions and the number of times the students help classmates solve problems in the VR teaching environment, and also stores the experiment completion progress corresponding to the VR experiment interaction conducted by the i students in the VR laboratory, and also stores the number of interactions and the number of completed tasks corresponding to each student in each VR teaching environment. It also stores the standard control adaptability parameters corresponding to the students in the VR teaching environment, and the standard control adaptability parameters include the standard control facial information score, the standard control average number of interactions and the standard control average number of completed tasks, and also stores the comprehensive interest coefficient threshold corresponding to each VR teaching environment.

[0050] A VR multi-person interactive flexible space system provided by the present invention can ensure the accuracy and practicality of the virtual environment by obtaining the teaching course schedule from the management manual of the designated campus. The staff can set the environmental demand information in the VR platform, which is conducive to personalized customization and optimization of the virtual teaching environment. According to the type of teaching environment, the number of people to be accommodated in the space and the spatial layout, the VR platform can accurately optimize the internal space, improve the practicality of the environment and the comfort of students, use VR equipment to collect students' facial information, generate exclusive VR images, enhance immersion and reality, and present the real image of the students in the virtual environment, which greatly improves their presence and participation in the virtual environment.

[0051] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they shall all fall within the protection scope of the present invention.

Claims

1. A VR multi-person interactive flexible space system, characterized in that: include: The VR environment creation module is used to obtain the teaching course schedule of a specified campus under a specified teaching background, and then create various VR teaching environments that meet the needs of multi-person interaction; A VR environment control unit is used to evaluate the interaction process of each student in each VR teaching environment; The display terminal is used to display the interaction of each student in the VR teaching environment.

2. A VR multi-person interactive flexible space system according to claim 1, characterized in that: The specific process of creating various VR teaching environments that meet multi-person interaction is as follows: S1. Obtain the teaching course schedule of the designated campus from the campus management manual of the designated campus, divide the process of each VR teaching environment into preliminary environment creation and student image creation, and create each VR teaching environment in the VR platform of the Web; S2. According to the teaching course arrangement of the designated campus, the staff sets the environmental demand information of each VR teaching environment in the VR platform. The environmental demand information includes the teaching environment type, the number of people that the space needs to accommodate, and the spatial layout. According to the teaching environment type, the VR platform displays each VR teaching environment corresponding to the teaching environment type. According to the teaching course arrangement of the designated campus, each VR teaching environment that meets the teaching course arrangement of the designated campus is selected and recorded as each VR teaching environment to be optimized. According to the number of people that the space needs to accommodate and the spatial layout set by the staff, the VR platform optimizes the internal space of each VR teaching environment to be optimized, thereby realizing the preliminary environment creation of each VR teaching environment; S3. Through VR teaching simulation training, VR equipment is used to collect the corresponding facial information of each student during the VR teaching simulation training. According to the facial information of each student, the VR platform generates an exclusive VR image corresponding to each student, thereby realizing the creation of each student's image, thereby completing the creation of various VR teaching environments for multi-person interaction.

3. A VR multi-person interactive flexible space system according to claim 1, characterized in that: The VR environment control unit is used to evaluate the interaction process of each student in each VR teaching environment, including: The conflict handling module is used to evaluate the conflicts among students in the VR teaching environment; The sustainable development evaluation module is used to obtain the corresponding adaptability parameters of each student in each VR teaching environment, and then calculate the comprehensive interest coefficient of each student in each VR teaching environment, thereby analyzing whether each VR teaching environment meets the sustainable development requirements of VR teaching.

4. A VR multi-person interactive flexible space system according to claim 3, characterized in that: The specific analysis process of analyzing the conflicts among students in the VR teaching environment is as follows: When each student wears a VR device to conduct VR experiment interaction in a VR laboratory, if the number of students who take the same virtual experiment equipment in the VR laboratory at time point b is greater than or equal to 2, the students who take the same virtual experiment equipment at time point b are recorded as conflicting students, and the priority information corresponding to each conflicting student is obtained. The priority information includes the comprehensive learning score, the experiment completion progress and the visual locking time. The conflict priority coefficient corresponding to each conflicting student is calculated, and then the conflict priority level corresponding to each conflicting student is obtained. When each conflicting student takes the virtual experiment equipment at time point b, according to the conflict priority level of each conflicting student, the virtual experiment equipment is preferentially allocated to the conflicting student with the first conflict priority level. When the conflicting student with the first conflict priority level has used up the virtual experiment equipment, a pop-up window is displayed to prompt the conflicting student with the second conflict priority level, so as to complete the allocation of virtual experiment equipment.

5. A VR multi-person interactive flexible space system according to claim 4, characterized in that: The specific calculation process of calculating the conflict priority coefficient corresponding to each conflicting student is as follows: Obtaining the standard control priority information corresponding to the students in the VR teaching environment from the database, the standard control priority information including the standard control comprehensive learning score, the standard control experiment completion progress and the standard control visual locking time; By calculating the formula Get the conflict priority coefficient VR corresponding to each conflicting student i , i is the number of each conflicting student, i = 1, 2, ..., n, n is the total number of conflicting students, n is a positive integer, where P i , H i , T i They respectively represent the comprehensive learning score, experiment completion progress, and visual lock duration corresponding to the i-th conflicting student. P′, H′, and T′ represent the standard control comprehensive learning score, standard control experiment completion progress, and standard control visual lock duration, respectively. ι1, ι2, and ι3 are the weight factors corresponding to the set comprehensive learning score, the weight factor corresponding to the experiment completion progress, and the weight factor corresponding to the visual lock duration, respectively.

6. A VR multi-person interactive flexible space system according to claim 5, characterized in that: The conflict priority level corresponding to each conflicting student is obtained, and the specific analysis process is as follows: Obtain each conflict priority coefficient interval from the database, each conflict priority coefficient interval corresponds to each conflict priority level, compare the conflict priority coefficient corresponding to each conflict student with each conflict priority coefficient interval, if the conflict priority coefficient corresponding to the i-th conflict student belongs to a certain conflict priority coefficient interval, then it means that the conflict priority level corresponding to the i-th conflict student is the conflict priority level corresponding to the conflict priority coefficient interval, so as to obtain the conflict priority level corresponding to each conflict student.

7. The VR multi-person interactive flexible space system according to claim 4, characterized in that: The priority information corresponding to each conflicting student is obtained, and the specific acquisition process is as follows: The number of times each conflicting student actively answered questions and helped classmates solve problems in the VR teaching environment was obtained from the database, and the formula P was used to calculate the number of times each conflicting student actively answered questions and helped classmates solve problems in the VR teaching environment. i =c i *κ1+d i *κ2, and obtain the comprehensive learning score P corresponding to each conflicting student i , c i and d i They are respectively represented by the number of times the i-th conflict student actively answers questions and helps classmates solve problems in the VR teaching environment, κ1 and κ2 are the weight factors of the number of times the i-th conflict student actively answers questions and helps classmates solve problems, respectively; The experimental completion progress corresponding to the VR experimental interaction of each conflicting student in the VR laboratory is obtained from the database, and the corresponding time point when each conflicting student visually locks on the virtual experimental equipment and the corresponding time point when the visual leaves the virtual experimental equipment are obtained through the pupil tracking function in the VR device. By performing a difference calculation, the visual locking time corresponding to the VR experimental interaction of each conflicting student in the VR laboratory is obtained.

8. The VR multi-person interactive flexible space system according to claim 3, characterized in that: The specific acquisition process of obtaining the adaptability parameters corresponding to each student in each VR teaching environment is as follows: Adaptability parameters include facial information score, average number of interactions and average number of completed tasks. The facial expression images of each student in each VR teaching environment are obtained through the camera set in the VR device worn by each student. The scores of the facial expression images of each student are obtained through image recognition technology and deep learning algorithms. Facial expressions are divided into positive facial expressions and negative facial expressions. The score is calculated by formula M x =JJ x *μ1+XJ x *μ2, get the facial information score M of each student in each VR teaching environment x , x is the number of each student, x = 1, 2, ..., y, y is the total number of students, y is a positive integer, JJ x and XJ x They are respectively represented as the positive facial expression score and negative facial expression score corresponding to the x-th student, μ1 and μ2 are the set positive facial expression score weight factor and negative facial expression score weight factor respectively; The number of interactions and the number of completed tasks of each student in each VR teaching environment are obtained from the database, and the number of interactions and the number of completed tasks of each student in each VR teaching environment are accumulated respectively to obtain the total number of interactions and the total number of completed tasks of each student in each VR teaching environment. The total number of interactions and the total number of completed tasks of each student in each VR teaching environment are divided by the number of VR teaching environments respectively, and the result obtained is the average number of interactions and the average number of completed tasks of each student in each VR teaching environment.

9. The VR multi-person interactive flexible space system according to claim 8, characterized in that: The specific calculation process of calculating the comprehensive interest coefficient of each student in each VR teaching environment is as follows: Obtain the corresponding standard control adaptability parameters of students in the VR teaching environment from the database. The standard control adaptability parameters include the standard control facial information score, the standard control average number of interactions, and the standard control average number of completed tasks; By calculating the formula Get the comprehensive interest coefficient of each student in each VR teaching environment j is the number of each VR teaching environment, j = 1, 2, ..., m, m is the total number of VR teaching environments, m is a positive integer, where Mx j 、Wx j 、Dx j They respectively represent the facial information score, average number of interactions, and average number of completed tasks of the x-th student in the j-th VR teaching environment. M′, W′, and D′ represent the facial information score of the standard control, the average number of interactions of the standard control, and the average number of completed tasks of the standard control. ν1, ν2, and ν3 are the weight factors corresponding to the set facial information score, the average number of interactions, and the average number of completed tasks, respectively.

10. A VR multi-person interactive flexible space system according to claim 9, characterized in that: The analysis of whether each VR teaching environment meets the requirements for the sustainable development of VR teaching is as follows: The comprehensive interest coefficients of each student in each VR teaching environment are accumulated to obtain the total comprehensive interest coefficient corresponding to each VR teaching environment. The comprehensive interest coefficient threshold corresponding to each VR teaching environment is obtained from the database, and the total comprehensive interest coefficient corresponding to each VR teaching environment is compared with the comprehensive interest coefficient threshold. If the total comprehensive interest coefficient corresponding to a VR teaching environment is greater than or equal to the comprehensive interest coefficient threshold, it indicates that the VR teaching environment meets the requirements of the sustainable development of VR teaching. Otherwise, it indicates that the VR teaching environment does not meet the requirements of the sustainable development of VR teaching. In this way, whether each VR teaching environment meets the requirements of the sustainable development of VR teaching is analyzed.

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