CN-122006219-A - Golf lower skill simulation training method and system

CN122006219ACN 122006219 ACN122006219 ACN 122006219ACN-122006219-A

Abstract

The invention discloses a golf lower skill simulation training method and a system, which relate to the technical field of computer aided training, and comprise the steps of responding to a training mode selected by a user, generating training conditions comprising different ball positions, gradients and wind direction combinations through a scene simulation module; when a user swings, multisource motion data are collected and swing characteristic data are extracted, the swing characteristic data are input into an AI analysis module to generate action deviation analysis results, a feedback output module generates correction guide information according to the deviation analysis results, a scene simulation module simulates the flight track and landing points of a ball based on the ball hitting moment data, an evaluation module evaluates the ball hitting effect, generates performance analysis data and correction suggestions and carries out visual presentation, and difficulty parameters of a follow-up training scene are dynamically adjusted according to the current ball hitting performance to form a personalized training path. The invention realizes the fine analysis of the swing action and the immersive simulation of the actual combat scene, and effectively improves the actual combat capability of users in the field.

Inventors

LIU LONGJI
WEI LINSEN

Assignees

深圳市如歌科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260403

Claims (10)

1. A golf lower skill simulation training method, which is characterized by comprising the following steps: Responding to a training mode selected by a user, and generating training conditions comprising different ball positions, gradients and wind direction combinations through a scene simulation module; When the swing of the user is detected, acquiring multi-source motion data generated in the swing process of the user through a motion capture module, and extracting swing characteristic data; Inputting the swing characteristic data to an AI analysis module, decomposing the swing action into a plurality of stages by the AI analysis module, comparing the swing action with standard actions in an expert knowledge base, generating an action deviation analysis result, and sending the action deviation analysis result to a feedback output module; the feedback output module generates correction guidance information according to the action deviation analysis result and feeds back the correction guidance information to a user in real time through display equipment or voice broadcasting equipment; after the batting happens, the scene simulation module simulates the flight track and the drop point of the ball based on the batting moment data; The batting effect is evaluated through the evaluation module, performance analysis data and correction advice are generated, and the batting simulation animation and feedback information are visually presented through the display equipment so as to be used for a user to refer to and correct the swing action; And dynamically adjusting difficulty parameters of a subsequent training scene through a difficulty adjusting module according to the batting performance, and forming a personalized training path to simulate real scene difficulty change.
2. The golf lower skill simulation training method of claim 1, wherein the training conditions include a slope condition that a ball is above both feet and a ball is below both feet, and a virtual obstacle is provided at a target area.
3. The golf lower skill simulation training method of claim 1, wherein the specific step of decomposing the swing into a plurality of stages and comparing the swing with the standard motions in the expert knowledge base comprises decomposing the swing into upper top, lower start, moment of striking, delivering and receiving action nodes, and vector comparing the body joint angle and the club head position parameters extracted from each node with the standard model.
4. The golf lower skill simulation training method of claim 1, wherein the correction advice is natural language descriptive information associated with specific motion phases and quantified deviation data, and wherein the visual presentation comprises a skeletal animation overlay of a user swing with a standard three-dimensional model.
5. A golf lower skill simulation training system, comprising: The data acquisition module is used for acquiring multisource motion data in the swing process of a user through a multi-mode sensor and extracting swing characteristic data; The data processing module is connected with the data acquisition module and used for carrying out fusion processing on the multi-source motion data; The AI analysis module is connected with the data processing module, is internally provided with an expert knowledge base and is used for decomposing the swing action into a plurality of stages according to the characteristic data and comparing the stages with the expert knowledge base to generate an action deviation analysis result; the scene simulation module is used for loading corresponding virtual training scenes according to the training mode selected by the user, generating training conditions comprising different ball positions, gradients and wind direction combinations, and simulating the flight track and landing points of the golf based on the ball striking moment data; The feedback output module is connected with the AI analysis module and the scene simulation module and is used for generating correction guidance information according to the action deviation analysis result and feeding back the correction guidance information to a user in real time through display equipment or voice broadcasting equipment; the evaluation module is used for evaluating the batting effect to generate performance analysis data and correction advice and visually presenting batting simulation animation and feedback information through the display equipment; the difficulty adjusting module is used for dynamically adjusting difficulty parameters of the subsequent training scene according to the batting performance to form a personalized training path.
6. The golf lower skill simulation training system of claim 5, wherein the data acquisition module comprises a high-speed camera unit and an inertial sensor, and wherein the multi-source motion data comprises at least body joint angle, club head trajectory, club head speed, face angle, angular velocity, and linear acceleration.
7. The golf lower skill simulation training system of claim 5, wherein the AI analysis module decomposes the swing into upper swing top, lower swing start, moment of impact, swing and swing back, and extracts body joint angle and club head position parameters corresponding to each node for vector comparison with a standard model.
8. The golf lower skill simulation training system of claim 5, wherein the training patterns comprise four sub-patterns, and the AI analysis modules in different sub-patterns are respectively configured to analyze key technical indicators in corresponding sub-patterns, wherein the key technical indicators comprise a launch performance parameter, a green drop point control parameter, a tee drop control parameter, and a putter line and speed matching correlation parameter.
9. The golf lower skill simulation training system of claim 5, wherein the scene simulation module further comprises a training condition generation unit for generating a simulation scene containing different combinations of ball position, gradient, wind direction according to the selected training pattern randomly or in a preset sequence.
10. The golf lower skill simulation training system of claim 5, wherein the visual presentation comprises virtual batting trajectories, updated data panels, and a skeletal animation overlay of a user swing versus a standard three-dimensional model, wherein the correction advice is natural language descriptive information associated with specific motion phases and quantized bias data.

Description

Golf lower skill simulation training method and system Technical Field The invention relates to the technical field of computer aided training, in particular to a golf lower skill simulation training method and a golf lower skill simulation training system. Background The golf sport has extremely high requirements on technical precision and environment adaptability, and players in actual combat on the field need to deal with complex and changeable court conditions, including factors such as different ball positions, gradient, wind direction, change of green speed and the like. However, the existing golf training devices mainly have the following technical drawbacks: First, conventional swing analyzers or simulators are mostly limited to single data source collection, such as relying only on high-speed imaging or relying only on inertial sensors, and are difficult to achieve multi-dimensional synchronous analysis of body gestures and club head motion parameters, resulting in a lack of comprehensiveness and accuracy in swing motion analysis. Second, existing devices typically provide only an overall swing assessment, such as "swing irregularities", lack the ability to resolve and compare minute phases of a swing, and fail to precisely locate deviations in the swing to specific phases such as backswing, downswing, instant of impact, or hand-off, and it is difficult for a user to obtain operational corrective instruction. More critical, existing training equipment generally lacks immersive simulation of a real lower field environment. The user trains under the ideal conditions of flat ball position and constant wind speed for a long time, and cannot adapt to complex terrains such as ball positions higher than two feet, lower than two feet, upward slopes and downward slopes, long grass areas and the like and gradient changes of the green in actual combat, so that a significant gap exists between training effect and actual combat capability. In addition, most of the existing devices are static difficulty setting, training difficulty cannot be dynamically adjusted according to real-time performance of users, and personalized and progressive training path planning is lacked. Disclosure of Invention The invention mainly aims to provide a golf lower-field skill simulation training method and a golf lower-field skill simulation training system, and aims to solve the technical problems that the existing golf training equipment lacks of real lower-field environment simulation, cannot conduct multi-dimensional real-time analysis and staged accurate guidance on swing motions, and therefore a user is difficult to convert training effects into actual combat capability. In order to achieve the above object, the present invention provides a golf lower skill simulation training method, comprising the following steps: Responding to a training mode selected by a user, and generating training conditions comprising different ball positions, gradients and wind direction combinations through a scene simulation module; When the swing of the user is detected, acquiring multi-source motion data generated in the swing process of the user through a motion capture module, and extracting swing characteristic data; Inputting the swing characteristic data to an AI analysis module, decomposing the swing action into a plurality of stages by the AI analysis module, comparing the swing action with standard actions in an expert knowledge base, generating an action deviation analysis result, and sending the action deviation analysis result to a feedback output module; the feedback output module generates correction guidance information according to the action deviation analysis result and feeds back the correction guidance information to a user in real time through display equipment or voice broadcasting equipment; after the batting happens, the scene simulation module simulates the flight track and the drop point of the ball based on the batting moment data; The batting effect is evaluated through the evaluation module, performance analysis data and correction advice are generated, and the batting simulation animation and feedback information are visually presented through the display equipment so as to be used for a user to refer to and correct the swing action; And dynamically adjusting difficulty parameters of a subsequent training scene through a difficulty adjusting module according to the batting performance, and forming a personalized training path to simulate real scene difficulty change. Further, the training conditions include a slope condition that the ball is above both feet and the ball is below both feet, and a virtual obstacle is set in the target area. Further, the specific steps of decomposing the swing motion into a plurality of stages and comparing with the standard motion in the expert knowledge base include decomposing the swing motion into upper swing top points, lower swing start, striking moments, swing delivering and swin