A gaming chair control system

Abstract

The present application provides a gaming chair control system, which relates to the field of gaming chair control technology. The data acquisition module is used to acquire dynamic yaw data of the gaming chair during movement. The adaptation compensation module is used to detect the player's body posture changes in real time and adjust the perspective situation data in the game. The adaptation compensation interval of the gaming chair in response to the player's posture changes is determined according to the motion change command and the dynamic yaw data. The cooperative actuation module is used to perform multi-degree-of-freedom matching on the pivoting interaction nodes to obtain the linkage posture interpolation of the gaming chair during multi-axis motion cooperative control, and then determine the cooperative actuation cycle of the gaming chair during cooperative interaction. The status warning module is used to perform status warning on the posture adjustment of the gaming chair in complex movements according to the control feedback mark. The present application can accurately synchronize the player's posture changes with the dynamic yaw of the chair movement during the dynamic interaction process to improve the response accuracy of the gaming chair.

Description

Technical Field

[0001] The present application relates to the technical field of game chair control, and more specifically, to a game chair control system. Background Art

[0002] Gaming chair control refers to adjusting the posture, angle, tilt, vibration feedback and other parameters of the gaming chair through electric or mechanical systems to improve the user's immersion and comfort. With the development of virtual reality (VR) and augmented reality (AR) technology, gaming chairs have become an important part of the player's interactive experience. Through intelligent control systems, gaming chairs can automatically adjust the seat position or provide vibration feedback according to the user's body movements, game scenes and environmental changes, simulating a more realistic interactive experience.

[0003] However, in the existing gaming chair control methods, there is a problem that the relationship between the player's posture and the dynamic changes of the chair cannot be accurately identified in real time, and there is a lack of effective control mechanism for posture adjustment and feedback synchronization in complex motion scenes, which makes the gaming chair's response lag or over-react, resulting in a non-smooth or uncomfortable experience for players, thus affecting the immersion and safety of the interaction. Therefore, how to accurately synchronize the player's posture changes with the dynamic yaw of the chair's movement during dynamic interaction to improve the response accuracy of the gaming chair is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a gaming chair control system that can accurately synchronize a player's posture changes with the dynamic yaw of the chair movement during dynamic interaction to improve the response accuracy of the gaming chair.

[0005] In a first aspect, the present application provides a gaming chair control system, the control system comprising:

[0006] A data acquisition module, used to identify the player's motion posture information and the dynamic yaw data of the gaming chair during movement through the sensing head of the gaming chair controller;

[0007] An adaptation compensation module is used to detect the player's body posture changes in real time and adjust the perspective situation data in the game, extract the movement direction change instruction of the gaming chair during dynamic movement from the perspective situation data, and determine the adaptation compensation interval of the gaming chair when responding to the player's posture changes according to the movement direction change instruction and the dynamic yaw data;

[0008] A collaborative actuation module is used to obtain the pivot interaction nodes at the rotating joints of the gaming chair during dynamic interaction, perform multi-degree-of-freedom matching on the pivot interaction nodes, obtain the linkage posture interpolation of the gaming chair during multi-axis motion collaborative control, and then determine the collaborative actuation cycle of the gaming chair during collaborative interaction based on the linkage posture interpolation and the action posture information;

[0009] The status warning module is used to determine the control feedback mark of the gaming chair during dynamic range motion synchronization through the adaptation compensation interval and the coordinated actuation cycle, and to provide status warning for the posture adjustment of the gaming chair in complex movements according to the control feedback mark.

[0010] In this embodiment, real-time detection of changes in the player's body posture and adjustment of the perspective situation data in the game specifically includes:

[0011] Detect the player's body posture changes in real time to obtain synchronous posture information when the player's body posture changes;

[0012] The perspective situation data in the game is generated according to the synchronous posture information, and the perspective in the game is adjusted according to the perspective situation data feedback.

[0013] In this embodiment, extracting the movement direction change instruction of the gaming chair during dynamic movement from the viewing angle situation data specifically includes:

[0014] Determining the movement direction change characteristics of the gaming chair during dynamic movement according to the viewing angle situation data;

[0015] Determining the motion direction-changing property of the gaming chair during dynamic motion by using the motion direction-changing feature;

[0016] A movement direction changing instruction of the gaming chair during dynamic movement is determined according to the movement direction changing attribute.

[0017] In this embodiment, performing multi-degree-of-freedom matching on the pivot interaction node to obtain the linkage posture interpolation of the gaming chair during multi-axis motion coordinated control specifically includes:

[0018] Determining a matching attenuation amount of the gaming chair under multi-axis motion according to the pivot interaction node;

[0019] Determine linkage attenuation characteristics through matching attenuation of the gaming chair under multi-axis motion;

[0020] The linkage attenuation feature is loaded into the degree of freedom control process of the gaming chair to obtain the posture response vector of the gaming chair during the multi-axis motion coordinated control;

[0021] The linkage posture interpolation of the gaming chair during multi-axis motion coordinated control is determined according to the posture response vector.

[0022] In this embodiment, determining the coordinated actuation cycle of the gaming chairs during the coordinated interaction by the linkage posture interpolation and the action posture information specifically includes:

[0023] Determining posture feedback characteristics when the viewing angle changes in the game according to the linkage posture interpolation;

[0024] Determine the state response node of the gaming chair when responding to dynamic interaction through the action posture information;

[0025] The collaborative actuation period of the gaming chairs during collaborative interaction is determined according to the posture feedback feature and the state response node.

[0026] In this embodiment, determining the control feedback identifier of the gaming chair during dynamic range motion synchronization through the adaptation compensation interval and the coordinated actuation cycle specifically includes:

[0027] Extracting the situation awareness feedback amount when the gaming chair is adjusted from the adaptation compensation interval;

[0028] Determining, according to the coordinated actuation cycle, an actuation control property of the gaming chair in response to a viewing angle switch;

[0029] The control feedback identifier of the gaming chair during dynamic range motion synchronization is determined by the situation awareness feedback amount and the actuation control attribute.

[0030] In this embodiment, the control feedback identifier represents an identification signal for guiding multi-axis synchronous control and error compensation in the dynamic range movement of the gaming chair.

[0031] In this embodiment, the pivot interaction node represents a key point where the gaming chair plays a role in core rotation and power transmission in multi-axis motion.

[0032] In this embodiment, the dynamic yaw data refers to the angle information of the gaming chair deviating from the reference direction during the rotational motion.

[0033] In this embodiment, the motion posture information represents the spatial position and direction data of the player's body in the gaming chair.

[0034] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0035] The data acquisition module is used to identify the player's action posture information and the dynamic yaw data of the gaming chair during movement; the adaptation compensation module is used to detect the player's body posture changes in real time and adjust the perspective situation data in the game, and the movement change direction instruction of the gaming chair during dynamic movement is extracted from the perspective situation data, and the adaptation compensation interval of the gaming chair in response to the player's posture changes is determined according to the movement change direction instruction and the dynamic yaw data; the cooperative actuation module is used to obtain the pivot interaction nodes at the rotating joints of the gaming chair during dynamic interaction, and the pivot interaction nodes are matched with multiple degrees of freedom to obtain the linkage posture interpolation of the gaming chair during multi-axis motion cooperative control, and then the cooperative actuation cycle of the gaming chair during cooperative interaction is determined according to the linkage posture interpolation and the action posture information; the status warning module is used to determine the control feedback mark of the gaming chair during dynamic range motion synchronization according to the adaptation compensation interval and the cooperative actuation cycle, and the status warning of the posture adjustment of the gaming chair in complex movements is performed according to the control feedback mark.

[0036] It can be seen that in the present application, the player's posture changes and the dynamic yaw of the chair movement can be accurately matched during the dynamic interaction process; wherein, the relationship between the player's movements and the dynamic changes of the chair is accurately captured, and the player's posture and the chair movement state can be synchronized in real time; through the comprehensive analysis of posture changes and dynamic yaw data, the adaptive compensation interval of posture adjustment can be calculated in real time to ensure that the gaming chair can be accurately adjusted according to the player's posture changes to avoid excessive or delayed motion response; through multi-degree-of-freedom matching and posture interpolation, the collaborative actuation cycle under multi-axis linkage is accurately calculated, so that the gaming chair can be smoothly and collaboratively controlled in complex motion scenes, ensuring multi-axis motion synchronization and enhancing the player's comfort and immersion; through the control feedback mark and status warning mechanism, the posture deviation and motion anomaly can be detected and adjusted in time to ensure the stability and safety of the gaming chair in complex movements and improve the fluency and reliability of the gaming experience.

[0037] In summary, the technical solution adopted in the present application can accurately synchronize the player's posture changes with the dynamic yaw of the chair movement during dynamic interaction, so as to improve the response accuracy of the gaming chair. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application 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 the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0039] Figure 1 is a module structure diagram of a gaming chair control system provided in accordance with the present application;

[0040] Figure 2 is a schematic diagram of a flow chart for determining an adaptation compensation interval according to the present application;

[0041] Figure 3 It is a schematic diagram of the process of determining linkage posture interpolation provided by this application. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0043] The embodiment of the present application provides a gaming chair control system, the core of which is to identify the player's action posture information and the dynamic yaw data of the gaming chair during movement through a data acquisition module; to detect the player's body posture changes in real time and adjust the perspective situation data in the game through an adaptation compensation module, to extract the movement change command of the gaming chair during dynamic movement from the perspective situation data, and to determine the adaptation compensation interval of the gaming chair in response to the player's posture changes according to the movement change command and the dynamic yaw data; to obtain the pivot interaction node at the rotating joint of the gaming chair during dynamic interaction through a collaborative actuation module, to perform multi-degree-of-freedom matching on the pivot interaction node, to obtain the linkage posture interpolation of the gaming chair during multi-axis motion collaborative control, and then to determine the collaborative actuation cycle of the gaming chair during collaborative interaction according to the linkage posture interpolation and the action posture information; to determine the control feedback mark of the gaming chair during dynamic range motion synchronization according to the adaptation compensation interval and the collaborative actuation cycle through a status warning module, and to perform status warning on the posture adjustment of the gaming chair in complex movements according to the control feedback mark. The above scheme can accurately synchronize the player's posture changes with the dynamic yaw of the chair movement during dynamic interaction to improve the response accuracy of the gaming chair.

[0044] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown, this figure is a module structure diagram of a gaming chair control system according to this embodiment of the present application. The control system includes: a data acquisition module 100, an adaptation compensation module 200, a coordinated actuation module 300 and a status warning module 400, which are described as follows:

[0045] The data acquisition module 100 is used to identify the player's motion posture information and the dynamic yaw data of the gaming chair during movement through the sensor head of the gaming chair controller.

[0046] In this embodiment, the sensor head of the gaming chair controller identifies the player's motion posture information and the dynamic yaw data of the gaming chair during movement. In specific implementation, a multi-axis sensor head is arranged on the top of the backrest, the left side, the right side and the footrest of the gaming chair. The sensor head collects the following data in real time at a fixed frequency (such as 100Hz): acceleration data, angular velocity data and pressure data, and the collected acceleration data, angular velocity data and pressure data are used as the player's motion posture information. Then, the gaming chair base is equipped with a high-resolution rotary encoder or laser gyroscope to measure the chair body yaw angle and rotation rate in real time, and the chair body yaw angle and rotation rate are used as dynamic yaw data.

[0047] It should be noted that, in the present application, the action posture information represents the spatial position and direction data of the player's body in the gaming chair, and the dynamic yaw data refers to the angle information of the gaming chair deviating from the reference direction during the rotational motion.

[0048] The adaptation compensation module 200 is used to detect the player's body posture changes in real time and adjust the perspective situation data in the game, extract the movement change direction instruction of the gaming chair during dynamic movement from the perspective situation data, and determine the adaptation compensation interval of the gaming chair when responding to the player's posture changes based on the movement change direction instruction and the dynamic yaw data.

[0049] In this embodiment, the following methods can be used to detect the player's body posture changes in real time and adjust the perspective situation data in the game, namely:

[0050] Detect the player's body posture changes in real time to obtain synchronous posture information when the player's body posture changes;

[0051] The perspective situation data in the game is generated according to the synchronous posture information, and the perspective in the game is adjusted according to the perspective situation data feedback.

[0052] In the specific implementation, first, based on the IMU and camera sensors, data sampling is performed at a refresh rate of 50Hz, and the multi-sensor data is synchronized through timestamps, that is, the synchronous posture information when the player's body posture changes is obtained; then, the quaternion rotation transformation is used to map the synchronous posture information to the camera perspective in the game, that is, the perspective situation data in the game is generated, and the PID controller is used to adjust the game perspective according to the deviation between the player's perspective and the target perspective.

[0053] It should be noted that, in the present application, the synchronous posture information refers to the spatial position information that is synchronized with the system time when the player's body posture changes, and the perspective situation data refers to the perspective and environmental status data of the camera in the game.

[0054] In this embodiment, the movement direction change instruction of the gaming chair during dynamic movement is extracted from the viewing angle situation data by the following steps, namely:

[0055] Determining the movement direction change characteristics of the gaming chair during dynamic movement according to the viewing angle situation data;

[0056] Determining the motion direction-changing property of the gaming chair during dynamic motion by using the motion direction-changing feature;

[0057] A movement direction changing instruction of the gaming chair during dynamic movement is determined according to the movement direction changing attribute.

[0058] In the specific implementation, first, obtain the camera position information in the game (position, orientation, pitch angle, yaw angle and other time series data) from the perspective situation data, calculate the angular velocity change through the perspective data of consecutive frames, and identify the turning behavior. The calculation formula is: ,in, represents the angular velocity, Indicates the yaw angle of the previous moment, Indicates the yaw angle of the viewing angle at the next moment, Represents the time interval. Perform the second-order differential of the camera position information, extract the acceleration feature, detect the rapid turning or emergency stop operation, and obtain the motion change feature; then, based on the extracted motion change feature, use the pattern recognition algorithm to classify it. Common methods include: Threshold judgment method: set the angular velocity and acceleration thresholds, map them to attributes such as "left turn", "right turn", "acceleration", etc., then input the feature vector, output the motion change label, and use the motion change label as the motion change attribute, where the motion change attribute includes direction attribute, amplitude attribute and timing attribute. Finally, establish an attribute-action mapping table (rule base or decision tree). For example, if the direction attribute is left turn, the amplitude attribute is violent, and the timing attribute is sudden change, then the output instruction is to trigger "sharp left turn", and the output instruction is used as the motion change instruction. If a rule-based controller is used, the motion change instruction is output according to the preset mapping rule.

[0059] It should be noted that, in the present application, the motion change feature refers to a set of data features of the player's motion trends (such as turning, speed change, emergency stop, etc.), the motion change attribute refers to a set of categories of the changing states of the gaming chair, and the motion change instruction refers to a standardized control signal that controls the motion behavior of the gaming chair.

[0060] Preferably, in this embodiment, the adaptation compensation interval of the gaming chair in response to the player's posture change is determined according to the motion change instruction and the dynamic yaw data, referring to Figure 2As described above, the figure is a schematic diagram of a process for determining an adaptation compensation interval in some embodiments of the present application. In this embodiment, determining the adaptation compensation interval can be implemented by the following steps:

[0061] In step S21, the movement type identification of the gaming chair during movement is obtained;

[0062] In step S22, determining the switching adaptation amount of the gaming chair in response to the player's posture change based on the movement type identifier;

[0063] In step S23, determining the posture delay amount of the gaming chair when adjusting the posture according to the movement change instruction;

[0064] In step S24, hysteresis compensation information of the gaming chair when adjusting the posture is determined according to the dynamic yaw data and the switching adaptation amount;

[0065] In step S25, an adaptation compensation interval of the gaming chair when responding to a change in the player's posture is determined according to the switching adaptation amount and the hysteresis compensation information.

[0066] In the specific implementation, first, according to the motion data stream (such as accelerometer, gyroscope signal), use the machine learning model (such as random forest classifier) ​​or threshold judgment algorithm to identify the current motion type (such as steering, drifting, acceleration) of the gaming chair, that is, to obtain the motion type identification. Then, based on the motion type identification, consult the mapping table (such as rule base or neural network mapping) and output the corresponding switching adaptation amount, that is, the transition parameter required for posture adjustment; again, according to the motion change instruction, calculate the system response delay (such as PID controller delay term) through the signal response model, including: establish the transfer function model of the system, and consider the relationship between the input signal and the output response. For the PID controller, the delay term is usually caused by factors such as the inertia of the system, the sensor sampling time and the communication delay. By analyzing the step response or frequency response of the system, the delay time can be identified. By incorporating the delay term into the transfer function of the PID controller, the control parameters can be optimized to compensate for the delay and improve the stability and response speed of the system. Then, according to the dynamic yaw data and the switching adaptation amount, the hysteresis model (such as the Preisach model) is used to calculate the compensation value to correct the nonlinear hysteresis effect, that is, the dynamic yaw data (such as yaw angle, angular velocity and angular acceleration) and the switching adaptation amount (such as motion range, speed limit) are collected. The Preisach model describes the nonlinear hysteresis characteristics of the system by decomposing and superimposing a series of basic hysteresis operators. By inputting the dynamic yaw data, the model calculates the hysteresis response of the system and generates the corresponding compensation value. The compensation value is used to adjust the control command to offset the nonlinear hysteresis effect, thereby improving the response accuracy and stability of the system. Finally, the switching adaptation amount and hysteresis compensation information are integrated, and the interval estimation model or fuzzy control algorithm is used to determine the adaptation compensation interval (i.e., the upper and lower bounds of attitude adjustment), including: performing interval analysis on the adaptation amount and hysteresis compensation information, and calculating the estimated interval in combination with historical data, so as to obtain reasonable upper and lower bounds of attitude adjustment. The fuzzy control algorithm converts the adaptation amount and hysteresis compensation information into fuzzy variables by fuzzifying the input, performs fuzzy reasoning according to the preset fuzzy rule base, and then outputs the upper and lower bounds of attitude adjustment by defuzzification.

[0067] It should be noted that, in the present application, the motion type identifier represents a label describing the current motion mode of the gaming chair; the switching adaptation amount represents; the posture delay amount represents the transition correction value when adjusting the posture; the hysteresis compensation information represents the set of compensation parameters required for the delay caused by the mechanical lag of the gaming chair; the adaptation compensation interval represents the adjustment range in response to changes in the player's posture.

[0068] The collaborative actuation module 300 is used to obtain the pivot interaction nodes at the rotating joints of the gaming chair during dynamic interaction, perform multi-degree-of-freedom matching on the pivot interaction nodes, obtain the linkage posture interpolation of the gaming chair during multi-axis motion collaborative control, and then determine the collaborative actuation cycle of the gaming chair during collaborative interaction based on the linkage posture interpolation and the action posture information.

[0069] In this embodiment, the following method can be used to obtain the pivoting interaction nodes at the rotating joints of the gaming chair during dynamic interaction, namely, an inertial measurement unit (IMU) or an angle encoder is arranged in the multi-axis rotating joints of the gaming chair to collect joint position information and rotation angles in real time. The pivoting node position is identified by a three-dimensional space analysis algorithm (such as vector cross product to solve the joint rotation axis). Subsequently, a multi-rigid body dynamics algorithm based on skeleton modeling is used to determine the motion association relationship of each joint in the multi-axis linkage, and mark the pivoting interaction nodes.

[0070] It should be noted that, in the present application, the pivot interaction node represents the key point of the gaming chair that plays a role in core rotation and power transmission in multi-axis motion.

[0071] Preferably, in this embodiment, the pivot interaction nodes are matched with multiple degrees of freedom to obtain the linkage posture interpolation of the gaming chair during multi-axis motion coordinated control. Figure 3 The figure is a schematic diagram of a process for determining linkage posture interpolation in some embodiments of the present application. In this embodiment, the linkage posture interpolation can be implemented by the following steps:

[0072] In step S31, a matching attenuation of the gaming chair under multi-axis motion is determined according to the pivot interaction node;

[0073] In step S32, the linkage attenuation characteristic is determined by the matching attenuation of the gaming chair under multi-axis motion;

[0074] In step S33, the linkage attenuation feature is loaded into the degree of freedom control process of the gaming chair to obtain a posture response vector of the gaming chair during multi-axis motion coordinated control;

[0075] In step S34, the linkage posture interpolation of the gaming chair during multi-axis motion coordinated control is determined according to the posture response vector.

[0076] In the specific implementation, first, according to the identified pivot interaction nodes, the displacement, angle and force data in the multi-axis motion are collected, and the joint response amplitude is calculated using the multi-degree-of-freedom motion modeling algorithm (such as the inverse kinematics IK model). At the same time, the matching attenuation during multi-axis linkage is measured by the exponential decay model or the Gaussian weighted algorithm. Then, based on the matching attenuation, the multi-axis response frequency band is decomposed by wavelet transform or Fourier analysis, the main linkage mode and resonance characteristics are extracted, and the linkage attenuation feature matrix is ​​constructed. Then, the linkage attenuation characteristics are input into the multi-degree-of-freedom control model (such as LSTM neural network or fuzzy controller), and the posture response vector in the multi-axis collaborative control is derived by combining the real-time motion data, that is, the linkage attenuation characteristics (such as motion attenuation coefficient, energy dissipation rate) and real-time motion data (such as yaw, roll, pitch angle) are collected. The LSTM neural network predicts the dynamic response of the system by learning time series data; the fuzzy controller processes nonlinear relationships through the rule base. The linkage attenuation characteristics are fused with the real-time motion data to generate multi-axis collaborative control instructions. Finally, the posture response vector (such as angle, angular velocity) is derived for precise adjustment of the motion state of the gaming chair. Finally, based on the attitude response vector, an interpolation algorithm (such as cubic spline interpolation or B-spline interpolation) is used to fit the attitude trajectory in multi-axis collaborative control, and the linkage attitude interpolation sequence under multi-axis motion is calculated, that is, the linkage attitude interpolation is obtained. Among them, the cubic spline interpolation or B-spline interpolation algorithm is used to fit the attitude trajectory in multi-axis collaborative control. Cubic spline interpolation constructs a piecewise cubic polynomial and solves the tridiagonal matrix equation to ensure the continuity of the function and derivative at the interpolation point; B-spline interpolation uses a linear combination of basis functions to establish a polynomial curve, and calculates the interpolation sequence corresponding to the control point through a recursive formula. According to the known attitude data points, the time parameters are input, the interpolation function is evaluated, and the linkage attitude interpolation sequence under multi-axis motion is obtained.

[0077] It should be noted that in the present application, the matching attenuation amount represents the attenuation coefficient of the response amplitude of each joint in multi-axis collaborative motion; the linkage attenuation characteristic represents; the posture response vector represents a multidimensional vector set of posture change trends of each degree of freedom in multi-axis collaborative control; the linkage posture interpolation represents a set of continuous posture trajectory points generated under multi-axis collaborative control.

[0078] In this embodiment, the coordinated actuation period of the game chairs during the coordinated interaction can be determined by the linkage posture interpolation and the action posture information in the following manner, namely:

[0079] Determining posture feedback characteristics when the viewing angle changes in the game according to the linkage posture interpolation;

[0080] Determine the state response node of the gaming chair when responding to dynamic interaction through the action posture information;

[0081] The collaborative actuation period of the gaming chairs during collaborative interaction is determined according to the posture feedback feature and the state response node.

[0082] In the specific implementation, first, according to the linkage posture interpolation, a timing analysis algorithm (such as DTW dynamic time warping) or a convolutional neural network (CNN) is used to extract features of the viewing angle change trend, obtain a feedback feature set reflecting the posture response of the gaming chair, and obtain the posture feedback feature from the feedback feature set; then, according to the action posture information, a motion detection algorithm (such as Kalman filtering or LSTM prediction model) is used to calibrate the key posture switching points of the gaming chair when responding to player interaction, that is, the state response nodes, including: Kalman filtering is based on the system state space model, and uses the prediction-update mechanism to suppress noise in real-time posture data, and determines the switching points such as response acceleration, deceleration or sudden change of direction through continuous multi-frame state estimation. The LSTM prediction model extracts the time series features between the player's action and the posture response of the gaming chair through time series learning, predicts the future state change trend based on the input historical posture data, and calibrates the key response nodes at the state mutation point; finally, the posture feedback features and the state response nodes are input into the collaborative control model (such as the fuzzy neural network optimized by the genetic algorithm), the phase difference and synchronization between the two are calculated, and the collaborative actuation cycle, that is, the collaborative actuation cycle of multi-axis linkage, is derived, including: the fuzzy neural network (FNN) models the input-output relationship through fuzzy rules and neural network structure, and the genetic algorithm globally optimizes the fuzzy rule parameters and neuron weights to improve the modeling accuracy. The model aligns the posture feedback features with the state response nodes in time series, and calculates the corresponding phase difference (that is, the time offset of the state changes of the two in the same cycle) and synchronization (a numerical indicator of the consistency of multi-axis response). Subsequently, based on the periodic collaborative relationship between the multiple axes, the actuation cycle interval with the highest repeatability and the best synchronization is extracted, which is the collaborative actuation cycle of multi-axis linkage.

[0083] It should be noted that in the present application, the posture feedback feature represents a set of time series features that reflect the impact of changes in the posture of the gaming chair on the viewing angle; the state response node represents a set of key time points that mark the changes in player movements that trigger system responses; and the collaborative actuation cycle represents the cycle time required to complete a coordinated movement in multi-axis collaborative control.

[0084] The status warning module 400 is used to determine the control feedback mark of the gaming chair during dynamic range motion synchronization through the adaptation compensation interval and the coordinated actuation cycle, and to perform status warning for the posture adjustment of the gaming chair in complex movements according to the control feedback mark.

[0085] In this embodiment, the control feedback identifier of the gaming chair during dynamic range motion synchronization is determined by the adaptation compensation interval and the coordinated actuation cycle in the following manner, namely:

[0086] Extracting the situation awareness feedback amount when the gaming chair is adjusted from the adaptation compensation interval;

[0087] Determining, according to the coordinated actuation cycle, an actuation control property of the gaming chair in response to a viewing angle switch;

[0088] The control feedback identifier of the gaming chair during dynamic range motion synchronization is determined by the situation awareness feedback amount and the actuation control attribute.

[0089] In the specific implementation, first, according to the adaptive compensation interval, the sensor data fusion algorithm (such as Kalman filter or particle filter) is used to perform multi-dimensional analysis on the real-time motion data, and the attitude offset value, velocity change rate and other situational awareness feedback quantities are extracted. Among them, according to the adaptive compensation interval, the sensor data fusion algorithm (such as Kalman filter or particle filter) is used to perform multi-dimensional analysis on the real-time motion data, and the attitude offset value, velocity change rate and other situational awareness feedback quantities are extracted. Kalman filter predicts the system state by taking the sensor data such as accelerometer and gyroscope as input, and corrects the error through the update step, and estimates the attitude offset value (angle change) and velocity change rate (integral of acceleration) in real time. Particle filter uses particle sets to simulate complex systems, and obtains state estimation through resampling and weight update for the uncertainty of sensor data, and extracts the attitude offset value and velocity change rate. Then, according to the cooperative actuation cycle, the response delay and action cycle characteristics are analyzed through time series analysis (such as Fourier transform or autoregressive model), and the actuation control properties when the response perspective is switched are calibrated, including response delay, acceleration threshold and periodic characteristics. According to the cooperative actuation cycle, the response delay and action cycle characteristics are analyzed through time series analysis (such as Fourier transform or autoregressive model). For example, the response data is analyzed in the frequency domain using Fourier transform to extract the periodic components and calibrate the acceleration threshold in the action cycle (such as the acceleration point exceeding a certain threshold is the start of the action). At the same time, the response delay is analyzed by the autoregressive model, the temporal relationship between the action and the feedback is identified, and the delay time is determined. Finally, the situation awareness feedback amount and the actuation control property are input into the neural network model or fuzzy control algorithm, and multi-dimensional feature matching and correlation analysis are performed to output the control feedback identifier. For example, the Pearson correlation coefficient is used to calculate the relationship between the velocity change rate and the acceleration. If the correlation coefficient between the two is close to 1, it means that the velocity change and the acceleration change are synchronized, which may mean that the system needs to adjust the actuation control property in a fast response state. Similarly, through fuzzy control rules, if the acceleration threshold is greater than the set value and the velocity change rate is high, the control system can output a stronger feedback flag for real-time attitude adjustment and error compensation in dynamic range motion.

[0090] It should be noted that in the present application, the situation awareness feedback quantity represents a set of feedback parameters that describe the multi-dimensional state changes of the gaming chair during motion adjustment; the actuation control attribute represents a set of dynamic control parameters corresponding to the response cycle in multi-axis collaborative control; and the control feedback identifier represents an identification signal that guides multi-axis synchronous control and error compensation in the dynamic range movement of the gaming chair.

[0091] In this embodiment, the state warning of the posture adjustment of the gaming chair in complex movements according to the control feedback mark can be specifically determined and implemented in the following manner: first, the gaming chair is equipped with a variety of sensors (such as accelerometers, gyroscopes, etc.) to collect real-time posture, acceleration, velocity change rate and other data, and uses sensor data fusion algorithms (such as Kalman filtering or particle filtering) for data processing and accurate estimation. The control feedback mark indicates whether the current system state is normal. Considering key indicators such as acceleration, velocity change rate, posture offset and other parameters, it is determined whether the abnormal threshold is reached. When the control feedback mark shows an abnormality (such as excessive velocity change rate, acceleration exceeding the limit, etc.), the abnormality of the control feedback mark can be determined based on expert experience and gaming chair debugging experiments, and the system automatically triggers a state warning. At this time, the warning mechanism will analyze the degree of deviation between the current motion state and the preset safety range or expected trajectory. If the deviation is large, the system will issue a warning and make corresponding adjustments. After the warning system is triggered, the control system will make real-time adjustments according to the feedback mark. For example, slow down the posture change speed, adjust the acceleration threshold, etc., to ensure that the gaming chair movement is always within a safe and comfortable range, and avoid excessively violent movements that cause discomfort or safety risks to players.

[0092] It can be seen that in the present application, the player's posture changes and the dynamic yaw of the chair movement can be accurately matched during the dynamic interaction process; wherein, the relationship between the player's movements and the dynamic changes of the chair is accurately captured, and the player's posture and the chair movement state can be synchronized in real time; through the comprehensive analysis of posture changes and dynamic yaw data, the adaptive compensation interval of posture adjustment can be calculated in real time to ensure that the gaming chair can be accurately adjusted according to the player's posture changes to avoid excessive or delayed motion response; through multi-degree-of-freedom matching and posture interpolation, the collaborative actuation cycle under multi-axis linkage is accurately calculated, so that the gaming chair can be smoothly and collaboratively controlled in complex motion scenes, ensuring multi-axis motion synchronization and enhancing the player's comfort and immersion; through the control feedback mark and status warning mechanism, the posture deviation and motion anomaly can be detected and adjusted in time to ensure the stability and safety of the gaming chair in complex movements and improve the fluency and reliability of the gaming experience.

[0093] In summary, the technical solution adopted in the present application can accurately synchronize the player's posture changes with the dynamic yaw of the chair movement during dynamic interaction, so as to improve the response accuracy of the gaming chair.

[0094] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0095] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, the storage medium including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically-erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0096] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A gaming chair control system, characterized in that: The control system comprises: A data acquisition module, used to identify the player's motion posture information and the dynamic yaw data of the gaming chair during movement through the sensing head of the gaming chair controller; An adaptation compensation module is used to detect the player's body posture changes in real time and adjust the perspective situation data in the game, extract the movement direction change instruction of the gaming chair during dynamic movement from the perspective situation data, and determine the adaptation compensation interval of the gaming chair when responding to the player's posture changes according to the movement direction change instruction and the dynamic yaw data; A collaborative actuation module is used to obtain the pivot interaction nodes at the rotating joints of the gaming chair during dynamic interaction, perform multi-degree-of-freedom matching on the pivot interaction nodes, obtain the linkage posture interpolation of the gaming chair during multi-axis motion collaborative control, and then determine the collaborative actuation cycle of the gaming chair during collaborative interaction based on the linkage posture interpolation and the action posture information; A status warning module, used to determine the control feedback mark of the gaming chair during dynamic range motion synchronization through the adaptation compensation interval and the coordinated actuation cycle, and to perform status warning for the posture adjustment of the gaming chair in complex movements according to the control feedback mark; Among them, real-time detection of player's body posture changes and adjustment of the perspective situation data in the game specifically include: Real-time detection of player's body posture changes to obtain synchronous posture information when the player's body posture changes; Generating viewing angle situation data in the game according to the synchronous posture information, and adjusting the viewing angle in the game according to the viewing angle situation data feedback; The step of extracting the movement direction change instruction of the gaming chair during dynamic movement from the viewing angle situation data specifically includes: Determining the movement direction change characteristics of the gaming chair during dynamic movement according to the viewing angle situation data; Determining the motion direction-changing property of the gaming chair during dynamic motion by using the motion direction-changing feature; Determining a movement direction change instruction of the gaming chair during dynamic movement according to the movement direction change attribute; Wherein, determining the adaptation compensation interval of the gaming chair in response to the player's posture change according to the motion change instruction and the dynamic yaw data specifically includes: Get the motion type identifier of the gaming chair when it is in motion; Determining, based on the movement type identifier, a switching adaptation amount of the gaming chair in response to a change in the player's posture; Determining the posture delay amount of the gaming chair when adjusting the posture according to the movement change direction instruction; Determining hysteresis compensation information of the gaming chair when adjusting the posture according to the dynamic yaw data and the switching adaptation amount; An adaptation compensation interval of the gaming chair when responding to a change in a player's posture is determined according to the switching adaptation amount and the hysteresis compensation information.

2. A gaming chair control system as claimed in claim 1, characterized in that: The multi-degree-of-freedom matching of the pivot interaction node is performed to obtain the linkage posture interpolation of the gaming chair during the multi-axis motion coordinated control, specifically including: Determining a matching attenuation amount of the gaming chair under multi-axis motion according to the pivot interaction node; Determine linkage attenuation characteristics through matching attenuation of the gaming chair under multi-axis motion; The linkage attenuation feature is loaded into the degree of freedom control process of the gaming chair to obtain the posture response vector of the gaming chair during the multi-axis motion coordinated control; The linkage posture interpolation of the gaming chair during multi-axis motion coordinated control is determined according to the posture response vector.

3. A gaming chair control system as claimed in claim 1, characterized in that: Determining the coordinated actuation cycle of the gaming chairs during the coordinated interaction by the linkage posture interpolation and the action posture information specifically includes: Determining posture feedback characteristics when the viewing angle changes in the game according to the linkage posture interpolation; Determine the state response node of the gaming chair when responding to dynamic interaction through the action posture information; The collaborative actuation period of the gaming chairs during collaborative interaction is determined according to the posture feedback feature and the state response node.

4. A gaming chair control system as claimed in claim 1, characterized in that: Determining the control feedback identifier of the gaming chair during dynamic range motion synchronization through the adaptation compensation interval and the coordinated actuation cycle specifically includes: Extracting the situation awareness feedback amount when the gaming chair is adjusted from the adaptation compensation interval; Determining, according to the coordinated actuation cycle, an actuation control property of the gaming chair in response to a viewing angle switch; The control feedback identifier of the gaming chair during dynamic range motion synchronization is determined by the situation awareness feedback amount and the actuation control attribute.

5. A gaming chair control system as claimed in claim 1, characterized in that: The control feedback mark represents an identification signal for guiding the multi-axis synchronous control and error compensation in the dynamic range movement of the gaming chair.

6. A gaming chair control system as claimed in claim 1, characterized in that: The pivot interaction nodes represent the key points where the gaming chair plays a role in core rotation and power transmission in multi-axis motion.

7. A gaming chair control system as claimed in claim 1, characterized in that: The dynamic yaw data refers to the angle information of the gaming chair deviating from the reference direction during the rotational motion.

8. A gaming chair control system as claimed in claim 1, characterized in that: The motion posture information represents the spatial position and direction data of the player's body in the gaming chair.

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