Immersive collaborative parachuting training method and system

Abstract

The present invention discloses an immersive collaborative skydiving training method and system, and specifically relates to the technical field of multi-person formation collaborative skydiving training. The present invention includes: step one, pre-training pre-processing, step two, generating a guiding motion trajectory, step three, monitoring the physiological state of each trainee, step four, evaluating the training effect of each trainee, step five, evaluating the training compliance level of the target project, and step six, generating a training plan for each trainee. The present invention adopts a combination of VR virtual technology and an outdoor wind tunnel to form an immersive virtual skydiving training environment. The present invention analyzes the collected training data of each trainee, evaluates the training effect of each trainee, obtains the training compliance level of the target project, and proposes a training plan for each trainee accordingly, which can effectively improve the skydiving skills of each trainee and improve the skydiving training method.

Description

Technical Field

[0001] The present invention relates to the technical field of coordinated skydiving training, and in particular to an immersive coordinated skydiving training method and system. Background Art

[0002] Collaborative skydiving is a parachuting activity that performs various formations and actions in the air. With the advancement of skydiving technology and the improvement of skydiving equipment, it has gradually developed from a leisure activity to a competitive sport. Collaborative skydiving has become a common event in international skydiving competitions. However, for novice or less experienced skydivers, there is a great risk in actual skydiving training without proficient flying skills. Therefore, it is necessary to study the collaborative skydiving training method in an immersive virtual safety environment.

[0003] Prior art includes a virtual reality-based parachute simulation training method and system disclosed in an invention patent application published as CN117173950A, wherein the method comprises: if it is detected that the trainee is located in a truss body and has worn a harness system and a virtual reality display device, then, according to the type of parachute training for the trainee, the suspension moving component and the vibration lifting component detachably installed in the truss body are controlled to operate so that the trainee can enter the parachute simulation training in a simulated off-plane posture, and the virtual reality display device is controlled to display the virtual reality image of the parachuting training, and the posture data and operation data of the trainee are collected in real time during the parachute simulation training to control the suspension moving component to change the operating state so that the trainee can move in the truss body.

[0004] The prior art, such as the invention patent application disclosed in the announcement CN107807735A, discloses a method and system for collaborative parachuting training, wherein the method includes: the collaborative parachuting training system includes multiple sets of simulated parachuting training subsystems, each trainee uses a set of simulated parachuting training subsystems for training, the spatial attitude sensing sensor collects the movement information of the trainee's head, and obtains the trainee's control information on the parachute rope, and sends the collected data to the graphics server, the graphics server generates its own current spatial position and attitude in real time according to the data collected by the spatial attitude sensing sensor of the simulated parachuting training subsystem, combines the current spatial position and attitude information of other simulated parachuting training subsystems, generates a three-dimensional scene and sends the three-dimensional scene to the visual simulation helmet of the simulated parachuting training subsystem for display. In this way, each visual simulation helmet displays all parachutists, that is, the three-dimensional scene displayed by each visual simulation helmet is the parachuting process of a parachuting formation, and the simulation training of multi-person collaborative parachuting is completed.

[0005] It can be seen from the above scheme that the current immersive skydiving training method uses physical structures and virtual equipment to simulate the skydiving environment. However, this skydiving simulation method mainly relies on virtual equipment to bring immersion, which is mainly reflected in the visual experience of the skydiving simulation environment. It lacks the tactile feeling of the body during the real skydiving process, resulting in limited simulated skydiving effects. At the same time, the commonly used truss physical structure is mostly used for single or double person simulation training, resulting in the inability to realize multi-person formation collaborative skydiving simulation training. There are great limitations on the scalability of skydiving training, and it cannot meet the actual application scenario requirements of multi-person collaborative skydiving training.

[0006] On the other hand, the existing technology for multi-person collaborative training usually considers how to achieve the sharing of parachuting control positions, ignoring the in-depth analysis of parachuting training results. Common analysis techniques are to process the video footage of each parachuting trainee and analyze the movements and postures of each parachutist. This is limited to two-dimensional analysis, which makes it difficult to make a reasonable evaluation of the three-dimensional spatial training motion trajectory of each parachutist, and it is impossible to evaluate the parachuting training effect through quantitative data, and it is impossible to effectively propose a reasonable training plan for the training effect to improve the parachuting training effect. Summary of the invention

[0007] The purpose of the present invention is to provide an immersive collaborative skydiving training method and system to solve the problems existing in the background technology.

[0008] A first aspect of the present invention provides an immersive collaborative skydiving training method, comprising: an immersive collaborative skydiving training method, characterized in that the method comprises: step one, pre-training pre-processing, constructing an immersive skydiving training scene based on an outdoor wind tunnel and VR virtual technology, checking the equipment worn by each trainee, obtaining environmental data and the training years of each trainee, and calculating the project difficulty tolerance coefficient based on the project difficulty tolerance coefficient, selecting a training project based on the project difficulty tolerance coefficient and recording it as a target project.

[0009] Step 2: Generate a guidance motion trajectory. Extract the position and direction information of each trainee under different instructions required by the target project from the database to generate a guidance motion trajectory for each trainee.

[0010] Step 3: Monitor the physiological status of each trainee, collect various physiological data of each trainee, and calculate the physiological compliance coefficient of each trainee.

[0011] Step 4. Evaluate the training effect of each trainee, obtain the actual motion trajectory slices, guided motion trajectory slices and the distance between each trainee and the adjacent personnel in each execution time period under the descending action instruction, and calculate the descending motion quality coefficient of each trainee based on this; obtain the actual motion trajectory slices, guided motion trajectory slices and turning speed of each trainee in each execution time period under the turning action instruction, and calculate the turning motion quality coefficient of each trainee based on this; based on the descending motion quality coefficient and turning motion quality coefficient of each trainee, calculate the training coordination compliance coefficient of the target project.

[0012] Step 5: Evaluate the training compliance level of the target project. Based on the physiological compliance coefficient of each trainee and the training synergy compliance coefficient of the target project, calculate the training compliance coefficient of the target project and evaluate the training compliance level of the target project.

[0013] Step 6: Generate a training plan for each trainee and implement response measures corresponding to the training compliance level of the target project.

[0014] The second aspect of the present invention provides a system for executing an immersive collaborative skydiving training method, comprising: a device wearable end collaborative unit, including a position acquisition module, a training data acquisition module, a motion trajectory synchronization module, a VR virtual module, a training control center unit, including a motion trajectory generation module, a physiological data analysis module, a collaborative compliance coefficient analysis module, a training compliance coefficient evaluation module, a training compliance level response module, a database, a network communication module and an intelligent display module.

[0015] The location acquisition module is used to obtain the location information of each training personnel.

[0016] The physiological data collection module is used to collect the physiological data of each training personnel.

[0017] The motion trajectory synchronization module is used to receive the guidance motion trajectory sent by the training control center.

[0018] VR virtual module is used to display three-dimensional motion trajectory and simulate the actual skydiving environment.

[0019] The motion trajectory generation module is used to generate the guiding motion trajectory of each trainee according to the initial position information of each trainee and the position direction information of each trainee under different instructions required by the target project.

[0020] The physiological data analysis module calculates the physiological compliance coefficient of each trainee according to the physiological data of each trainee.

[0021] The coordination compliance coefficient analysis module is used to calculate the descending motion quality coefficient and the turning motion quality coefficient of each trainee, and calculate the coordination compliance coefficient of each trainee accordingly.

[0022] The training compliance coefficient evaluation module is used to evaluate the training compliance level of the target project based on the physiological compliance coefficient of each trainee and the training coordination compliance coefficient of the target project.

[0023] The training compliance level response module is used to make response measures corresponding to the training compliance level according to the training compliance level of the target project.

[0024] The network communication module is used for network connection between the collaborative unit of the wearable device and the training control center unit to realize information interaction.

[0025] The intelligent display module is used for information exchange between training personnel and the training control center.

[0026] The database is used to store the difficulty coefficient ranges of each training project, store the position and direction information of each trainee under different instructions required by each target project, store the normal heart rate range and normal breathing rate range of the trainees, store the training years of each trainee, and store the training level ranges of the target project.

[0027] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: First, the present invention utilizes an outdoor wind tunnel and VR virtual equipment to construct an immersive skydiving environment. The outdoor wind tunnel can simulate the free fall stage in skydiving. Combined with the VR virtual equipment, it can bring an immersive skydiving training effect to each trainee. In addition, the outdoor wind tunnel has a large space for accommodating personnel, which can meet the needs of multi-person collaborative skydiving training.

[0028] 2. The present invention generates a guiding three-dimensional motion trajectory through three-dimensional simulation technology according to the initial position and target position of the parachuting trainees, and can guide the parachuting trainees in real time to master a fast and safe parachuting motion trajectory, ensuring that each trainee can find his or her position in time during the coordinated parachuting process and complete the requirements of coordinated parachuting.

[0029] 3. The present invention analyzes the spatial three-dimensional motion trajectory of each trainee. According to the analysis of the actual operation trajectory and important parameters under different instructions, it can accurately determine the parachuting coordination compliance coefficient of each trainee, realize in-depth analysis of the parachuting training results of each trainee, and help each trainee find the shortcomings in parachuting training.

[0030] 4. The present invention collects various physiological data of each trainee through sensors integrated in wearable devices, analyzes the physiological compliance coefficient of each trainee, and judges the training compliance degree of the target item in combination with the collaborative compliance coefficient of each trainee. It can timely discover whether the target item is suitable for each trainee, so as to make adjustments and ensure the safety of each trainee during the training process. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] 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.

[0032] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0033] Figure 2 It is a system structure connection diagram of the present invention.

[0034] Figure 3 This is a system network topology diagram of the present invention. DETAILED DESCRIPTION

[0035] 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.

[0036] For easier understanding, some terms of the present invention are explained below.

[0037] An outdoor wind tunnel refers to a system that artificially creates and controls airflow to form strong winds in a specific space, allowing trainees to fly in the air and pose in various shapes and perform various movements. During this process, trainees need to use aerodynamics to rise and fall, turn, and complete technical moves.

[0038] VR virtual technology refers to a technology that can generate a simulated environment through computer technology, which makes users feel as if they are in a three-dimensional space.

[0039] Embodiment 1

[0040] Reference Figure 1 As shown, the first aspect of the present invention provides an immersive collaborative skydiving training method, including: step one, pre-training preprocessing, building an immersive skydiving training scene based on an outdoor wind tunnel and VR virtual technology, checking the equipment worn by each trainee, obtaining environmental data and the training years of each trainee, and calculating the project difficulty tolerance coefficient based on the project difficulty tolerance coefficient, selecting a training project based on the project difficulty tolerance coefficient and recording it as a target project.

[0041] Step 2: Generate a guidance motion trajectory. Extract the position and direction information of each trainee under different instructions required by the target project from the database to generate a guidance motion trajectory for each trainee.

[0042] Step 3: Monitor the physiological status of each trainee, collect various physiological data of each trainee, and calculate the physiological compliance coefficient of each trainee.

[0043] Step 4. Evaluate the training effect of each trainee, obtain the actual motion trajectory slices, guided motion trajectory slices and the distance between each trainee and the adjacent personnel in each execution time period under the descending action instruction, and calculate the descending motion quality coefficient of each trainee based on this; obtain the actual motion trajectory slices, guided motion trajectory slices and turning speed of each trainee in each execution time period under the turning action instruction, and calculate the turning motion quality coefficient of each trainee based on this; based on the descending motion quality coefficient and turning motion quality coefficient of each trainee, calculate the training coordination compliance coefficient of the target project.

[0044] Step 5: Evaluate the training compliance level of the target project. Based on the physiological compliance coefficient of each trainee and the training synergy compliance coefficient of the target project, calculate the training compliance coefficient of the target project and evaluate the training compliance level of the target project.

[0045] Step 6: Generate a training plan for each trainee and implement response measures corresponding to the training compliance level of the target project.

[0046] In a specific embodiment of the present invention, the pre-training pre-processing method is as follows: each trainee wears the numbered parachuting equipment in turn, and sends a correct wearing signal and the parachuting equipment number to the training control center through the induction sensor integrated in the parachuting equipment. After receiving the correct wearing signal, the training control center records the parachuting equipment number as the number of each trainee. ,in Indicates the number of each trainer, Indicates the total number of trainees.

[0047] Obtain ambient wind speed through wind speed sensor , extract the training years of each trainee from the database , through the formula: , calculate the project difficulty tolerance coefficient.

[0048] The difficulty coefficient range of each training item is extracted from the database and matched with the item difficulty tolerance coefficient to obtain the training item to be selected. After confirmation by the training personnel, the training item to be selected is recorded as the target item.

[0049] The present invention utilizes an outdoor wind tunnel and VR virtual equipment to construct an immersive skydiving environment. The outdoor wind tunnel can simulate the free fall stage in skydiving. Combined with the VR virtual equipment, it can bring an immersive skydiving training effect to each trainee. In addition, the outdoor wind tunnel has a large space for accommodating personnel, which can meet the needs of multi-person collaborative skydiving training.

[0050] In a specific embodiment of the present invention, the position and direction information of each trainee under different instructions required by the target project is extracted from the database to generate the guided motion trajectory of each trainee. The specific method is: obtaining the initial position information of each trainee, extracting the position and direction information of each trainee under different instructions required by the target project from the database, and the training control center generates the guided motion trajectory of each trainee through computer three-dimensional simulation software based on this.

[0051] The training control center uses the network to synchronize the guided motion trajectory to the VR virtual devices worn by each trainee. At the same time, it updates the guided motion trajectory according to the actual position of each trainee, and reminds each trainee to execute the command action through voice broadcast.

[0052] The present invention generates a guiding three-dimensional motion trajectory through three-dimensional simulation technology according to the initial position and target position of the parachuting trainees, and can guide the parachuting trainees in real time to master a fast and safe parachuting motion trajectory, ensuring that each trainee can find his or her position in time during the coordinated parachuting process and complete the requirements of the coordinated parachuting.

[0053] In a specific embodiment of the present invention, the physiological data of each trainee is collected and the physiological compliance coefficient of each trainee is calculated. The specific method is: the heart rate of each trainee at each collection time point during the monitoring period is obtained through the electrocardiogram sensor and the resistance strain gauge sensor integrated in the wearable device. , respiratory rate , , Indicates the subscript of each acquisition time point within the monitoring period, Indicates the total number of acquisition time points within the monitoring period.

[0054] Based on the heart rate of each trainee during the monitoring period , respiratory rate , through the formula: , , , calculate the physiological compliance coefficient of each trainee ,in Indicates the number of The first collection The heart rate of the trainees meets the judgment value. Indicates the number of The first collection The breathing rate of the trainees meets the judgment value. Indicates the normal heart rate range of the trainee. Indicates the normal breathing rate range of the trainee.

[0055] It should be noted that, in a specific embodiment, for example, the first The total number of times collected by the training personnel is 5, and the collected heart rate is , , , , The respiratory rate collected is , , , , , where the normal heart rate range of the trainee is , Normal breathing rate range , heart rate and respiratory rate are measured in beats per minute.

[0056] By formula: , , Calculate the first Physiological compliance coefficient of trainees .

[0057] In a specific embodiment of the present invention, the actual motion trajectory slices, guide motion trajectory slices and the distance between each trainee and the adjacent personnel in each execution time period under the descending action instruction are obtained, and the descending motion quality coefficient of each trainee is calculated based on this. The specific method is as follows: after the training is completed, the training control center slices and classifies the actual motion trajectory of each trainee according to the execution time period of the descending action instruction, and obtains the actual running trajectory slices of each execution time period of the descending action instruction of each trainee, which are recorded as ,in , Indicates the number of each execution time period of the descending action instruction. Indicates the total number of execution time periods of the descending action instructions. Similarly, the training control center obtains the guiding operation trajectory slices of each execution time period of the descending action instructions of each trainee .

[0058] The training control center obtains the actual distance between each trainee and the adjacent trainee during each execution period of the trainee's descent action instruction based on the actual running trajectory slice of each trainee's descent action instruction during each execution period. Similarly, obtain the standard spacing between each execution time period of the descending action instruction of each trainee and the adjacent trainees .

[0059] It should be noted that, in a specific embodiment, the actual distance between each execution time period of the descending action instruction of each trainee and the adjacent trainee is the actual distance between the current trainee and the adjacent trainee in the clockwise direction.

[0060] Through computer image processing technology, the actual running trajectory of each trainee's descending action instruction in each execution time period is sliced Slice the track with guidance Perform overlap comparison to obtain the running trajectory overlap index of the descending action instructions of each trainee .

[0061] By formula: Calculate the descent operation quality coefficient of each trainee .

[0062] In a specific embodiment of the present invention, the actual motion trajectory slices, guided motion trajectory slices and steering speed of each trainee in each execution time period under the steering action instruction are obtained, and the steering motion quality coefficient of each trainee is calculated based on the obtained actual motion trajectory slices, guided motion trajectory slices and steering speed of each trainee in each execution time period under the steering action instruction are calculated based on the obtained actual motion trajectory slices, guided motion trajectory slices and steering speed of each trainee in each execution time period under the steering action instruction are obtained. ,in , Indicates the number of each execution time period of the steering action instruction. Indicates the total number of steering action instructions in each execution time period. Similarly, obtain the guiding operation trajectory slices of each training personnel's steering action instructions in each execution time period , through computer image recognition technology, the actual running trajectory of each trainee's steering action instruction in each execution time period is sliced , guide the running track slice Perform overlap comparison to obtain the running trajectory overlap index of the steering action instructions of each trainee .

[0063] The training control center obtains the actual steering speed of each trainee's steering action instruction in each execution time period based on the actual running trajectory slice of each trainee's steering action instruction in each execution time period. .

[0064] The training control center obtains the standard steering speed of each training personnel's steering action instruction in each execution time period based on the guidance operation trajectory slice of each training personnel's steering action instruction in each execution time period. .

[0065] It should be noted that, in a specific embodiment, the training control center obtains the steering angles based on the guiding operation trajectory slices of each training personnel's steering action instructions in each execution time period. and turn time , through the formula , calculate the standard turning speed of each training personnel's turning action instruction in each execution time period .

[0066] By formula: , calculate the steering operation quality coefficient of each trainee .

[0067] The present invention analyzes the spatial three-dimensional motion trajectory of each trainee, and according to the analysis of the actual operation trajectory and important parameters under different instructions, can accurately judge the parachuting coordination compliance coefficient of each trainee, realizes in-depth analysis of the parachuting training results of each trainee, and helps each trainee to technically find the shortcomings in parachuting training.

[0068] In a specific embodiment of the present invention, the training coordination compliance coefficient of the target project is calculated by: based on the descending operation quality coefficient of each trainee , Steering operation quality coefficient , through the formula: , and obtain the training synergy coefficient of the target project, where For the descending trajectory to meet the weight factor, , The steering trajectory meets the weight factor, .

[0069] In a specific embodiment of the present invention, the specific method for evaluating the training compliance level of the target project is: based on the training synergy compliance coefficient of the target project , Physiological compliance coefficient of each trainee , through the formula: , calculate the training compliance coefficient of the target project .

[0070] Training compliance coefficient based on target items ,like Belongs to the first interval , then the training compliance level of the target item is judged to be high compliance.

[0071] like Belongs to the second interval , then the training compliance level of the target item is judged to be generally compliant.

[0072] like Belongs to the third interval , then the training compliance level of the target item is judged to be low compliance.

[0073] Through the above analysis, the training compliance level of the target project is obtained.

[0074] It should be noted that, in a specific embodiment, the first interval, the second interval, and the third interval only represent the division of the training compliance level intervals of the target project, and do not specifically refer to the priority in level. The training compliance level intervals of the target project are determined based on the competitive scores of the actual coordinated parachuting of the target project of each trainee and the corresponding training compliance coefficients of each target project. If the competitive scores of the actual coordinated parachuting of the target project of the trainee are excellent, the minimum and maximum values ​​of the training compliance coefficients of each target project of the trainee are taken as the interval dividing boundaries for the target project compliance level of the high compliance level. Similarly, the interval dividing boundaries for the target project compliance level of the general compliance level and the low compliance level are obtained.

[0075] In a specific embodiment of the present invention, the implementation of the response measures corresponding to the training compliance level of the target project is specifically as follows: based on the training compliance level of the target project, if the training compliance level of the target project is a low compliance level, then obtaining the difficulty coefficient interval of the target project , match the difficulty coefficient interval of the target project from the database The training items are recorded as training items to be changed and displayed through the smart display terminal for the trainees to select independently.

[0076] If the training compliance level of the target project is a general compliance level, the training compliance level of the target project of each trainee can be improved by increasing the frequency of each trainee's theoretical learning and practical learning of the target project.

[0077] If the training compliance level of the target project is high compliance level, then obtain the difficulty coefficient range of the target project , match the difficulty coefficient interval of the target project from the database The training items are recorded as training items to be changed and displayed through the smart display terminal for the trainees to select independently.

[0078] It should be noted that, in a specific embodiment, the training compliance level of the target project is a high compliance level, the training project with a higher difficulty coefficient range is changed, and the frequency of theoretical learning is reduced to twice a week.

[0079] Generally, for those who meet the required level, the frequency of theoretical learning for each trainee will be increased to three times a week, and the frequency of practical learning for target projects will be increased to three times a week.

[0080] For low compliance levels, change to training items with lower difficulty levels, increase the frequency of theoretical learning to four times a week, and match response measures according to the training compliance level of the target items.

[0081] The present invention collects various physiological data of each trainee through sensors integrated in wearable devices, analyzes the physiological compliance coefficient of each trainee, and judges the training compliance degree of the target item in combination with the collaborative compliance coefficient of each trainee. It can timely discover whether the target item is suitable for each trainee, so as to make adjustments and ensure the safety of each trainee during the training process.

[0082] Embodiment 2

[0083] Reference Figure 2 As shown, the second aspect of the present invention provides a system for executing an immersive collaborative skydiving training method, comprising: a device wearable end collaborative unit, including a position acquisition module, a training data acquisition module, a motion trajectory synchronization module, a VR virtual module, a training control center unit, including a motion trajectory generation module, a physiological data analysis module, a collaborative compliance coefficient analysis module, a training compliance coefficient evaluation module, a training compliance level response module, a database, a network communication module and an intelligent display module.

[0084] The location acquisition module is used to obtain the location information of each training personnel.

[0085] The physiological data collection module is used to collect the physiological data of each training personnel.

[0086] The motion trajectory synchronization module is used to receive the guidance motion trajectory sent by the training control center.

[0087] VR virtual module is used to display three-dimensional motion trajectory and simulate the actual skydiving environment.

[0088] The motion trajectory generation module is used to generate the guiding motion trajectory of each trainee according to the initial position information of each trainee and the position direction information of each trainee under different instructions required by the target project.

[0089] The physiological data analysis module calculates the physiological compliance coefficient of each trainee according to the physiological data of each trainee.

[0090] The coordination compliance coefficient analysis module is used to calculate the descending motion quality coefficient and the turning motion quality coefficient of each trainee, and calculate the coordination compliance coefficient of each trainee accordingly.

[0091] The training compliance coefficient evaluation module is used to evaluate the training compliance level of the target project based on the physiological compliance coefficient of each trainee and the training coordination compliance coefficient of the target project.

[0092] The training compliance level response module is used to make response measures corresponding to the training compliance level according to the training compliance level of the target project.

[0093] The network communication module is used for network connection between the collaborative unit of the wearable device and the training control center unit to realize information interaction.

[0094] The intelligent display module is used for information exchange between training personnel and the training control center.

[0095] The database is used to store the difficulty coefficient ranges of each training project, store the position and direction information of each trainee under different instructions required by each target project, store the normal heart rate range and normal breathing rate range of the trainees, store the training years of each trainee, and store the training level ranges of the target project.

[0096] It should be noted that, in a specific embodiment, the collaborative center unit of the wearable device and the training control center unit are connected to the network communication module; in the collaborative center unit of the wearable device, the position acquisition module is connected to the physiological data acquisition module, the physiological data acquisition module is connected to the motion trajectory synchronization module, the motion trajectory synchronization module is connected to the VR simulation module; in the training control center unit, the motion trajectory generation module is connected to the physiological data analysis module, the physiological data analysis module is connected to the collaborative compliance coefficient analysis module, the collaborative compliance coefficient analysis module is connected to the training compliance coefficient evaluation module, the training compliance coefficient evaluation module is connected to the training compliance level response module, the database is connected to the collaborative center unit of the wearable device and the training control center unit, and the smart display module is connected to the training control center unit.

[0097] Embodiment 3

[0098] Reference Figure 3 As shown, the present invention provides a scalable system network structure, in which the wearable device collaboration center units with different numbers are connected to the training control center through a network communication module.

[0099] The device wearable collaborative center unit on the parachuting equipment serves as a device node, allowing the device wearable collaborative center unit network on one or more parachuting devices to easily access the training control center through the network communication module. The training control center receives signals and data from the device wearable collaborative center unit to provide training guidance and training evaluation for training personnel wearing the equipment.

[0100] The scalable system structure provided by the present invention can provide a complete system structure for collaborative skydiving training while meeting the needs of single-person skydiving training, thereby achieving guidance, evaluation and improvement plans for collaborative skydiving training.

[0101] 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 by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. An immersive collaborative skydiving training method, characterized in that: The method comprises: Step 1: Pre-training pre-processing: build an immersive skydiving training scene based on outdoor wind tunnel and VR virtual technology, check the equipment worn by each trainee, obtain environmental data and the training years of each trainee, and calculate the project difficulty tolerance coefficient based on the project difficulty tolerance coefficient. Select the training project based on the project difficulty tolerance coefficient and record it as the target project; Step 2: Generate a guidance motion trajectory, extract the position and direction information of each trainee under different instructions required by the target project from the database, and generate a guidance motion trajectory for each trainee; Step 3: monitor the physiological state of each trainee, collect various physiological data of each trainee, and calculate the physiological compliance coefficient of each trainee; Step 4: Evaluate the training effect of each trainee, obtain the actual motion trajectory slices, guided motion trajectory slices and the distance between each trainee and the adjacent personnel in each execution time period under the descending action instruction, and calculate the descending motion quality coefficient of each trainee based on this, obtain the actual motion trajectory slices, guided motion trajectory slices and turning speed of each trainee in each execution time period under the turning action instruction, and calculate the turning motion quality coefficient of each trainee based on this, and calculate the training coordination compliance coefficient of the target project based on the descending motion quality coefficient and the turning motion quality coefficient of each trainee; Step 5: Evaluate the training compliance level of the target project. Based on the physiological compliance coefficient of each trainee and the training synergy compliance coefficient of the target project, calculate the training compliance coefficient of the target project and evaluate the training compliance level of the target project. Step 6: Generate a training plan for each trainee and implement response measures corresponding to the training compliance level of the target project.

2. An immersive collaborative skydiving training method according to claim 1, characterized in that: The specific method of the pre-training pre-processing is as follows: Each trainee wears the numbered parachuting equipment in turn, and sends the correct wearing signal and the parachuting equipment number to the training control center through the induction sensor integrated in the parachuting equipment. After receiving the correct wearing signal, the training control center records the parachuting equipment number as the number of each trainee. ,in Indicates the number of each trainer, Indicates the total number of trainees; Obtain ambient wind speed through wind speed sensor , extract the training years of each trainee from the database , through the formula: , calculate the project difficulty tolerance coefficient; The difficulty coefficient range of each training item is extracted from the database and matched with the item difficulty tolerance coefficient to obtain the training item to be selected. After confirmation by the training personnel, the training item to be selected is recorded as the target item.

3. An immersive collaborative skydiving training method according to claim 2, characterized in that: The specific method of extracting the position and direction information of each trainee under different instructions required by the target project from the database and generating the guiding motion trajectory of each trainee is as follows: Obtain the initial position information of each trainee, extract the position and direction information of each trainee under different instructions required by the target project from the database, and the training control center generates the guidance motion trajectory of each trainee through computer three-dimensional simulation software; The training control center uses the network to synchronize the guided motion trajectory to the VR virtual devices worn by each trainee. At the same time, it updates the guided motion trajectory according to the actual position of each trainee, and reminds each trainee to execute the command action through voice broadcast.

4. The immersive collaborative skydiving training method according to claim 3, characterized in that: The specific method of collecting various physiological data of each trainee and calculating the physiological compliance coefficient of each trainee is as follows: The heart rate of each trainee at each collection time point during the monitoring period is obtained through the integrated ECG sensor and resistance strain gauge sensor on the wearable device. , respiratory rate , , Indicates the subscript of each acquisition time point in the monitoring period, Indicates the total number of acquisition time points within the monitoring period; Based on the heart rate of each trainee during the monitoring period , respiratory rate , through the formula: , , , calculate the physiological compliance coefficient of each trainee ,in Indicates the number of The first collection The heart rate of the trainees meets the judgment value. Indicates the number of The first collection The breathing rate of the trainees meets the judgment value. Indicates the normal heart rate range of the trainee. Indicates the normal breathing rate range of the trainee.

5. The immersive collaborative skydiving training method according to claim 4, characterized in that: The actual motion trajectory slices, guided motion trajectory slices and the distance between each trainee and the adjacent personnel in each execution time period under the descending action instruction are obtained, and the descending motion quality coefficient of each trainee is calculated based on the obtained actual motion trajectory slices, guided motion trajectory slices and the distance between each trainee and the adjacent personnel in each execution time period under the descending action instruction, and the specific method is as follows: After the training, the training control center slices and classifies the actual motion trajectory of each trainee according to the execution time period of the descending action instruction, and obtains the actual running trajectory slices of each trainee's descending action instruction execution time period, which are recorded as ,in , Indicates the number of each execution time period of the descending action instruction. Indicates the total number of execution time periods of the descending action instructions. Similarly, the training control center obtains the guiding operation trajectory slices of each execution time period of the descending action instructions of each trainee ; The training control center obtains the actual distance between each trainee and the adjacent trainee during each execution period of the trainee's descent action instruction based on the actual running trajectory slice of each trainee's descent action instruction during each execution period. Similarly, obtain the standard spacing between each execution time period of the descending action instruction of each trainee and the adjacent trainees ; Through computer image processing technology, the actual running trajectory of each trainee's descending action instruction in each execution time period is sliced Slice the track with guidance Perform overlap comparison to obtain the running trajectory overlap index of the descending action instructions of each trainee ; By formula: Calculate the descent operation quality coefficient of each trainee .

6. The immersive collaborative skydiving training method according to claim 5, characterized in that: The actual motion trajectory slices, guided motion trajectory slices and steering speed of each trainee in each execution time period under the steering action instruction are obtained, and the steering motion quality coefficient of each trainee is calculated based on the obtained actual motion trajectory slices, guided motion trajectory slices and steering speed of each trainee in each execution time period under the steering action instruction, and the specific method is as follows: The training control center slices and classifies the actual motion trajectory of each trainee according to the execution time period of the steering action instruction, and obtains the actual running trajectory slices of each trainee's steering action instruction in each execution time period. ,in , Indicates the number of each execution time period of the steering action instruction. Indicates the total number of steering action instructions in each execution time period. Similarly, obtain the guiding operation trajectory slices of each training personnel's steering action instructions in each execution time period , through computer image recognition technology, the actual running trajectory of each trainee's steering action instruction in each execution time period is sliced , guide the running track slice Perform overlap comparison to obtain the running trajectory overlap index of the steering action instructions of each trainee ; The training control center obtains the actual steering speed of each trainee's steering action instruction in each execution time period based on the actual running trajectory slice of each trainee's steering action instruction in each execution time period. ; The training control center obtains the standard steering speed of each training personnel's steering action instruction in each execution time period based on the guidance operation trajectory slice of each training personnel's steering action instruction in each execution time period. ; By formula: , calculate the steering operation quality coefficient of each trainee .

7. An immersive collaborative skydiving training method according to claim 6, characterized in that: The specific method of calculating the training synergy compliance coefficient of the target project is as follows: Descent operation quality factor based on each training personnel , Steering operation quality coefficient , through the formula: , and obtain the training synergy coefficient of the target project, where For the descending trajectory to meet the weight factor, , The steering trajectory meets the weight factor, .

8. The immersive collaborative skydiving training method according to claim 7, characterized in that: The specific method for evaluating the training compliance level of the target item is as follows: Training synergy compliance coefficient based on target items , Physiological compliance coefficient of each trainee , through the formula: , calculate the training compliance coefficient of the target project ; Training compliance coefficient based on target items ,like Belongs to the first interval , then the training compliance level of the target project is judged to be high compliance; like Belongs to the second interval , then the training compliance level of the target item is judged to be generally compliant; like Belongs to the third interval , then the training compliance level of the target item is judged to be low compliance; Through the above analysis, the training compliance level of the target project is obtained.

9. The immersive collaborative skydiving training method according to claim 8, characterized in that: The specific method of implementing the response measures corresponding to the training compliance level of the target project is as follows: Based on the training compliance level of the target project, if the training compliance level of the target project is a low compliance level, obtain the difficulty coefficient range of the target project , match the difficulty coefficient interval of the target project from the database The training items are recorded as the training items to be changed, which are displayed through the smart display terminal and selected by the training personnel themselves; If the training compliance level of the target project is a general compliance level, the training compliance level of the target project of each trainee is improved by increasing the frequency of theoretical learning and practical learning of the target project for each trainee; If the training compliance level of the target project is high compliance level, then obtain the difficulty coefficient range of the target project , match the difficulty coefficient interval of the target project from the database The training items are recorded as training items to be changed and displayed through the smart display terminal for the trainees to select independently.

10. A system for executing the immersive collaborative skydiving training method according to any one of claims 1 to 9, characterized in that: include: The wearable device collaborative unit includes a location acquisition module, a training data acquisition module, a motion trajectory synchronization module, and a VR virtual module; the training control center unit includes a motion trajectory generation module, a physiological data analysis module, a collaborative compliance coefficient analysis module, a training compliance coefficient evaluation module, a training compliance level response module, a database, a network communication module, and an intelligent display module; A location acquisition module is used to obtain the location information of each training personnel; Physiological data collection module, used to collect physiological data of each trainee; The motion trajectory synchronization module is used to receive the guidance motion trajectory sent by the training control center; VR virtual module, used to display three-dimensional motion trajectory and simulate the actual skydiving environment; The motion trajectory generation module is used to generate the guidance motion trajectory of each trainee according to the initial position information of each trainee and the position direction information of each trainee under different instructions required by the target project; The physiological data analysis module calculates the physiological compliance coefficient of each trainee according to the physiological data of each trainee; The coordination compliance coefficient analysis module is used to calculate the descending motion quality coefficient and the turning motion quality coefficient of each trainee, and calculate the coordination compliance coefficient of each trainee accordingly; A training compliance coefficient evaluation module is used to evaluate the training compliance level of the target project based on the physiological compliance coefficient of each trainee and the training coordination compliance coefficient of the target project; A training compliance level response module is used to make response measures corresponding to the training compliance level according to the training compliance level of the target project; Network communication module, used for network connection between the wearable device collaborative unit and the training control center unit to achieve information interaction; Smart display module, used for information exchange between training personnel and the training control center; The database is used to store the difficulty coefficient ranges of each training project, store the position and direction information of each trainee under different instructions required by each target project, store the normal heart rate range and normal breathing rate range of the trainees, store the training years of each trainee, and store the training level ranges of the target project.

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