Motor simulation counterweight reality enhancement method and system

Abstract

The application relates to the technical field of artificial intelligence, and discloses a motor simulation counterweight sense reality improvement method and system, which comprises the following steps: calculating inertia force and centrifugal force of a user operation device by using a dynamic load model; outputting compensation torque of the user operation device, and decomposing the compensation torque into a low-frequency steady-state component and a high-frequency transient component; determining output steady-state torque of the low-frequency steady-state component, defining a vibration waveform of the high-frequency transient component, and combining the output steady-state torque and the vibration waveform to analyze potential transformation characteristics of a load of the user operation device; generating adaptive counterweight of the user operation device, analyzing a palm contact force distribution diagram of a target user; calculating an adaptation coefficient of the palm contact force distribution diagram; and when an adaptation threshold value meets preset adaptation threshold value standards, taking the adaptive counterweight as target simulation counterweight of the target user. The application can improve the sense reality of the motor simulation counterweight.

Description

Technical Field

[0001] This invention relates to a method and system for improving the realism of simulated counterweight in motors, belonging to the field of artificial intelligence technology. Background Technology

[0002] Motor-simulated counterweight enhancement refers to using motor drive, sensor feedback, and control algorithms to simulate the tactile effects of real physical counterweights (such as gravity, inertia, and impact force) in a virtual or remote operating environment, providing users with a force feedback experience close to real physical interaction. Its core objective is to address the shortcomings of traditional fixed counterweights or simple force feedback systems in terms of dynamic response, tactile delicacy, and environmental adaptability.

[0003] Traditional techniques for improving the realism of simulated counterweight motion using motors mainly rely on open-loop or simplified closed-loop force feedback control. The core of this approach is to pre-set a series of torque-time or torque-position curves. When a user triggers a specific virtual interaction (such as "picking up a hammer"), the motor strictly outputs the corresponding resistance or force according to the preset curve. It cannot perceive the user's unique operational dynamics, such as subtle changes in swing speed, acceleration, and posture. Therefore, the simulated inertial force and centrifugal force are fixed and distorted, lacking the physical response that a real object should have, making it difficult to achieve a highly immersive and realistic motion sensation. Summary of the Invention

[0004] This invention provides a method and system for improving the realism of the simulated counterweight in a motor, the main purpose of which is to improve the realism of the simulated counterweight in a motor.

[0005] To achieve the above objectives, the present invention provides a method for improving the realism of the simulated counterweight in a motor, comprising:

[0006] Collect the spatial acceleration and angular velocity of the target user on the user operating device, establish a dynamic load model of the user operating device, and calculate the inertial force and centrifugal force of the user operating device based on the spatial acceleration and angular velocity using the dynamic load model.

[0007] Based on the inertial force and centrifugal force, the compensation torque of the user operating device is output, and the compensation torque is decomposed into a low-frequency steady-state component and a high-frequency transient component.

[0008] Determine the output steady-state torque of the low-frequency steady-state component, define the vibration waveform of the high-frequency transient component, and combine the output steady-state torque and the vibration waveform to analyze the potential load transformation characteristics of the user operating equipment.

[0009] Based on the potential load transformation characteristics, an adaptive counterweight for the user's operating device is generated, and the palm contact force distribution map of the target user is analyzed.

[0010] Based on the adaptive weight, the adaptation coefficient of the palm contact force distribution map is calculated. When the adaptation coefficient meets the preset adaptation threshold standard, the adaptive weight is used as the target simulated weight for the target user.

[0011] Optionally, the step of outputting the compensation torque of the user operating device based on the inertial force and centrifugal force includes:

[0012] The inertial force and centrifugal force are vectored together to obtain the total feedback force;

[0013] Define the virtual load application point of the user operating device;

[0014] Calculate the lever arm vector at the point of application of the virtual load;

[0015] Based on the total feedback force and the lever arm vector, the compensation torque of the user operating device is calculated.

[0016] Optionally, calculating the compensation torque of the user operating device based on the total feedback force and the lever arm vector includes:

[0017] Analyze the load inertia tensor and damping matrix of the user operating device;

[0018] Based on the load inertia tensor, the damping matrix, the total feedback force, and the lever arm vector, the compensation torque of the user-operated device is calculated using the following formula:

[0019]

[0020] in, This indicates the compensation torque for user-operated equipment. This represents the lever arm vector of the user operating the device. Indicates the total feedback force. Indicates the dynamic compensation coefficient. Represents the load inertia tensor. This represents the angular acceleration of the user operating the device. This represents the angular acceleration of the user operating the device. This represents the damping matrix.

[0021] Optionally, establishing the dynamic load model of the user operating device includes:

[0022] Establish the rotation matrix between the user operating device and the preset world coordinate system;

[0023] Define the virtual load parameters of the user operating device, wherein the virtual load parameters include virtual mass and moment of inertia tensor;

[0024] Based on the virtual load parameters, a dynamic load equation for the user operating device is constructed, wherein the dynamic load equation includes translational dynamics equations and rotational dynamics equations;

[0025] Based on the rotation matrix and the dynamic load equation, a dynamic load model of the user operating device is established.

[0026] Optionally, the step of decomposing the compensated torque into low-frequency steady-state components and high-frequency transient components includes:

[0027] The compensation torque is preprocessed to obtain the processed compensation torque;

[0028] Perform a Fourier transform on the converted compensation torque to obtain the converted compensation torque;

[0029] Extract the low-frequency and high-frequency components of the transformed compensation torque;

[0030] The low-frequency component and the high-frequency component are reconstructed respectively to obtain the low-frequency steady-state component and the high-frequency transient component.

[0031] Optionally, the definition of the vibration waveform of the high-frequency transient component includes:

[0032] Identify the spectral peak of the high-frequency transient component to calculate the total energy of the high-frequency transient component;

[0033] Construct the basic waveform of the high-frequency transient component;

[0034] The non-periodic transient effect and natural decay of the high-frequency transient component are analyzed to increase the high-frequency noise of the base waveform, thereby obtaining the noise high-frequency transient component;

[0035] The vibration waveform of the basic waveform is determined based on the natural attenuation and the total energy of the high-frequency components.

[0036] Optionally, the step of combining the output steady-state torque and the vibration waveform to analyze the potential load transformation characteristics of the user operating equipment includes:

[0037] The output steady-state torque and the vibration waveform are synchronized to obtain synchronized output steady-state torque and synchronized vibration waveform;

[0038] Generate the composite torque signal of the synchronous output steady-state torque and the synchronous vibration waveform;

[0039] Analyze the time spectrum and load steady-state coefficient of the composite torque signal;

[0040] Calculate the high-frequency energy difference of the time spectrum;

[0041] Based on the high-frequency energy differential and the load steady-state coefficient, the potential load transformation characteristics of the user operating equipment are determined.

[0042] Optionally, generating the adaptive weight of the user operating device based on the potential load transformation characteristics includes:

[0043] Construct a six-dimensional vector of the potential transformation features of the load;

[0044] The six-dimensional vector is normalized to obtain a normalized six-dimensional vector;

[0045] Based on the normalized six-dimensional vector, the virtual mass adjustment, moment of inertia adjustment, and vibration gain adjustment of the user operating device are analyzed.

[0046] By combining the virtual mass adjustment, rotational inertia adjustment, and vibration gain adjustment, an adaptive counterweight for the user operating device is generated.

[0047] Optionally, the analysis of the palm contact force distribution map of the target user includes:

[0048] Collect the palm contact force data of the target user;

[0049] Construct a two-dimensional matrix of the palm contact force data to calculate the normal contact force of the palm sensor corresponding to the target user;

[0050] Define the biomechanical region of the target user;

[0051] Based on the normal contact force, the regional force ratio of the biomechanical region is calculated using the following formula:

[0052]

[0053] in, Indicates the first The proportion of regional forces in each biomechanical region Indicates the first A biomechanical region, Indicates the first Location index of the palm sensor in the biomechanical region. Indicates the first The biomechanical regions are located in The normal contact force of the palm sensor Indicates the first The biomechanical regions are located in The weighting coefficients of the palm sensor, Indicates the first The sum of contact forces of the palm sensors in each biomechanical region;

[0054] The palm contact force distribution map of the target user is determined by the force ratio of the area.

[0055] To address the aforementioned problems, the present invention also provides a system for improving the realism of simulated counterweight motion in motor operation, the system comprising:

[0056] The dynamic load analysis module is used to collect the spatial acceleration and angular velocity of the target user on the user operating device, establish a dynamic load model of the user operating device, and calculate the inertial force and centrifugal force of the user operating device based on the spatial acceleration and angular velocity using the dynamic load model.

[0057] The compensation torque analysis module is used to output the compensation torque of the user operating device based on the inertial force and centrifugal force, and decompose the compensation torque into low-frequency steady-state components and high-frequency transient components.

[0058] The load potential analysis module is used to determine the output steady-state torque of the low-frequency steady-state component, define the vibration waveform of the high-frequency transient component, and analyze the load potential transformation characteristics of the user operating equipment by combining the output steady-state torque and the vibration waveform.

[0059] The contact force distribution analysis module is used to generate an adaptive counterweight for the user's operating device based on the potential load transformation characteristics, and to analyze the palm contact force distribution map of the target user.

[0060] The target simulated weight module is used to calculate the adaptation coefficient of the palm contact force distribution map based on the adaptive weight. When the adaptation coefficient meets the preset adaptation threshold standard, the adaptive weight is used as the target simulated weight of the target user.

[0061] By collecting the spatial acceleration and angular velocity of the target user during equipment operation, a dynamic load model is established. This model accurately calculates the inertial and centrifugal forces acting on the equipment. Based on real-time analysis of these forces, the system outputs a compensating torque and decomposes it into low-frequency steady-state components and high-frequency transient components. This effectively distinguishes between the long-term load trend and instantaneous disturbance characteristics of the equipment. This process not only accurately identifies potential load transformation characteristics but also provides a scientific basis for generating adaptive counterweight schemes. During the adaptive counterweight generation process, by combining low-frequency steady-state torque and high-frequency vibration waveforms, the system can dynamically adjust the equipment's counterweight structure, optimize the center of gravity distribution and inertia matching, and significantly improve the operational stability and user comfort of the equipment. Simultaneously, by analyzing the target user's hand contact force distribution diagram and calculating the adaptation coefficient, the compatibility between the counterweight scheme and the user's physiological characteristics can be further evaluated. When the adaptation coefficient meets a preset threshold, the adaptive counterweight becomes the target user's exclusive simulated counterweight, achieving highly personalized equipment calibration. Overall, this technology significantly improves the comprehensive performance and user satisfaction of operating the equipment, and has broad application prospects and market value. Therefore, this invention can improve the realism of the simulated counterweight's tactile feedback. Attached Figure Description

[0062] Figure 1 This is a flowchart illustrating a method for improving the realism of simulated counterweight in motors according to an embodiment of the present invention.

[0063] Figure 2 This is a schematic diagram of a module for a motor simulation counterweight system to improve the realism of body feeling, provided in an embodiment of the present invention.

[0064] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0065] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0066] This application provides a method for improving the realism of simulated counterweight motion in motor-driven systems. The execution entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for improving the realism of simulated counterweight motion in motor-driven systems can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0067] Reference Figure 1The diagram shown is a flowchart illustrating a method for improving the realism of simulated counterweight motion in a motor according to an embodiment of the present invention. In this embodiment, the method for improving the realism of simulated counterweight motion in a motor includes:

[0068] S1. Collect the spatial acceleration and angular velocity of the target user on the user operating device, establish a dynamic load model of the user operating device, and calculate the inertial force and centrifugal force of the user operating device based on the spatial acceleration and angular velocity using the dynamic load model.

[0069] It should be explained that the target user refers to an individual who uses a motion-sensing interaction device to perform virtual operations, experience force feedback, or simulate counterweight scenarios. For example, a user operating a controller, force feedback glove, or joystick in virtual reality (VR) training, game simulation, or industrial simulation. The user operating device refers to the input / output interaction device held or worn by the target user, such as a VR controller, force feedback glove, joystick, motion controller, etc. The spatial acceleration refers to the linear acceleration change of the user operating device in three-dimensional space along various directions (such as the X, Y, and Z axes), which is usually measured by the accelerometer built into the device. The angular velocity refers to the rate at which the user operating device rotates around one or more axes, which is usually measured by a gyroscope.

[0070] The present invention establishes a dynamic load model of the user-operated device, which can accurately calculate the inertial force and centrifugal force generated by the device during movement.

[0071] Specifically, establishing the dynamic load model of the user operating device includes:

[0072] Establish the rotation matrix between the user operating device and the preset world coordinate system;

[0073] Define the virtual load parameters of the user operating device, wherein the virtual load parameters include virtual mass and moment of inertia tensor;

[0074] Based on the virtual load parameters, a dynamic load equation for the user operating device is constructed, wherein the dynamic load equation includes translational dynamics equations and rotational dynamics equations;

[0075] Based on the rotation matrix and the dynamic load equation, a dynamic load model of the user operating device is established.

[0076] Wherein, the world coordinate system refers to a fixed global reference system used to describe the absolute position and attitude of the user-operated device in physical space; the rotation matrix refers to a 3×3 orthogonal matrix used to transform vectors in the device coordinate system to the world coordinate system; the virtual mass refers to the mass of the virtual object that the user-operated device needs to simulate; the rotational inertia tensor refers to the inertial characteristics describing the rotation of the virtual load around each axis of the device coordinate system; the translational dynamics equation refers to the linear motion law of the virtual mass under the action of external forces; the rotational dynamics equation refers to the rotational motion of the virtual load under the action of torque; and the dynamic load model refers to the system model that integrates the translational and rotational dynamics equations, used to calculate the force and torque that the motor needs to output.

[0077] Optionally, the dynamic load equation of the user operating device is constructed based on the virtual load parameters, wherein the dynamic load equation includes translational dynamics equation and rotational dynamics equation, wherein the translational dynamics equation is constructed using Newton's second law; and the rotational dynamics equation is constructed using Euler's equation.

[0078] This invention, based on the aforementioned spatial acceleration and angular velocity, utilizes the dynamic load model to calculate the inertial force and centrifugal force of the user-operated device, achieving real-time dynamic perception of user operation behavior. Here, the inertial force refers to the "virtual reaction force" exhibited by the virtual mass when the user-operated device accelerates, and the centrifugal force refers to the radial virtual force generated by the virtual mass due to the device's rotational motion.

[0079] S2. Based on the inertial force and centrifugal force, output the compensation torque of the user operating device, and decompose the compensation torque into a low-frequency steady-state component and a high-frequency transient component.

[0080] Based on the inertial force and centrifugal force, the present invention outputs the compensation torque of the user operating device, laying a solid physical foundation for subsequent force feedback compensation and simulated counterweight optimization.

[0081] Specifically, the step of outputting the compensation torque for the user operating device based on the inertial force and centrifugal force includes:

[0082] The inertial force and centrifugal force are vectored together to obtain the total feedback force;

[0083] Define the virtual load application point of the user operating device;

[0084] Calculate the lever arm vector at the point of application of the virtual load;

[0085] Based on the total feedback force and the lever arm vector, the compensation torque of the user operating device is calculated.

[0086] Wherein, the total feedback force refers to the total virtual force synthesized by the vectors of inertial force and centrifugal force; the virtual load application point refers to the centroid of the virtual load, representing the offset from the device gripping center to the virtual force application position; the lever arm vector refers to the vector from the motor rotation center to the virtual load application point; and the compensation torque refers to the theoretical torque that the motor needs to output.

[0087] Optionally, the virtual load application point of the user operating device can be defined by CAD model calibration.

[0088] Further, calculating the compensation torque of the user operating device based on the total feedback force and the lever arm vector includes:

[0089] Analyze the load inertia tensor and damping matrix of the user operating device;

[0090] The compensation torque of the user operating device is calculated based on the load inertia tensor, the damping matrix, the total feedback force, and the lever arm vector.

[0091] Furthermore, as another embodiment of the present invention, the compensation torque is calculated using the following formula:

[0092]

[0093] in, This indicates the compensation torque for user-operated equipment. This represents the lever arm vector of the user operating the device. Indicates the total feedback force. Indicates the dynamic compensation coefficient. Represents the load inertia tensor. This represents the angular acceleration of the user operating the device. This represents the angular acceleration of the user operating the device. This represents the damping matrix.

[0094] Wherein, the load inertia tensor is a physical quantity that describes the inertial distribution of the user-operated device when it rotates around different axes in three-dimensional space; the damping matrix dynamic compensation coefficient is a dimensionless adjustment parameter used to balance the weight between feedback force and inertia and damping effects; the angular acceleration is the rate of change of angular velocity over time, describing the acceleration or deceleration process of the device's rotational motion; and the damping matrix is ​​a physical quantity that describes the damping effect experienced by the device during rotation.

[0095] This invention decomposes the compensation torque into low-frequency steady-state components and high-frequency transient components, which can comprehensively grasp the potential load transformation characteristics of the user's operating equipment, thereby providing data support and theoretical basis for subsequent adaptive counterweight strategies.

[0096] Specifically, the process of decomposing the compensated torque into low-frequency steady-state components and high-frequency transient components includes:

[0097] The compensation torque is preprocessed to obtain the processed compensation torque;

[0098] Perform a Fourier transform on the converted compensation torque to obtain the converted compensation torque;

[0099] Extract the low-frequency and high-frequency components of the transformed compensation torque;

[0100] The low-frequency component and the high-frequency component are reconstructed respectively to obtain the low-frequency steady-state component and the high-frequency transient component.

[0101] Wherein, the processed compensation torque refers to the preprocessed signal after discretization sampling and windowing of the original time-domain compensation torque signal; the transformed compensation torque refers to the complex spectrum after the time-domain signal is transformed to the frequency domain by Fourier transform (FFT); the low-frequency component refers to the spectral part of the transformed compensation torque with a frequency below a threshold; the high-frequency component refers to the spectral part of the transformed compensation torque with a frequency above a threshold; the low-frequency steady-state component refers to the time-domain signal reconstructed by inverse Fourier transform (IFFT) of the low-frequency component; and the high-frequency transient component refers to the time-domain signal reconstructed by inverse Fourier transform of the high-frequency component.

[0102] Optionally, the preprocessing of the compensation torque to obtain the processed compensation torque can be performed on a preprocessed signal after discretization sampling and windowing.

[0103] S3. Determine the output steady-state torque of the low-frequency steady-state component, define the vibration waveform of the high-frequency transient component, and analyze the potential load transformation characteristics of the user operating equipment by combining the output steady-state torque and the vibration waveform.

[0104] This invention determines that the output steady-state torque of the low-frequency steady-state component provides a clean underlying signal for high-frequency vibration feedback, ensuring the synergy of multi-frequency force feedback. The output steady-state torque refers to the torque output corresponding to the low-frequency steady-state component, used to simulate the continuous mechanical action of a virtual load (such as gravity or inertial drag), typically in the frequency range of 0–10 Hz. Its characteristics include stable amplitude and no high-frequency fluctuations, providing users with basic force feedback.

[0105] The present invention defines that the vibration waveform of the high-frequency transient component can generate a high-frequency vibration waveform that combines physical accuracy and tactile richness, significantly improving the realism of transient interaction.

[0106] Specifically, the definition of the vibration waveform of the high-frequency transient component includes:

[0107] Identify the spectral peak of the high-frequency transient component to calculate the total energy of the high-frequency transient component;

[0108] Construct the basic waveform of the high-frequency transient component;

[0109] The non-periodic transient effect and natural decay of the high-frequency transient component are analyzed to increase the high-frequency noise of the base waveform, thereby obtaining the noise high-frequency transient component;

[0110] The vibration waveform of the basic waveform is determined based on the natural attenuation and the total energy of the high-frequency components.

[0111] Wherein, the spectral peak value refers to the local maximum value in the spectrum of the high-frequency transient component whose amplitude is significantly higher than that of the adjacent frequency point; the total energy of the high-frequency component refers to the sum of the energy of all spectral components in the high-frequency band; the basic waveform refers to the periodic sinusoidal signal generated by the main resonant frequency; the non-periodic transient effect refers to the random or abrupt components in the vibration that cannot be described by a single frequency (such as collision and breakage, friction and scraping); the natural decay refers to the characteristic that the vibration amplitude gradually weakens over time; the high-frequency noise refers to the random signal superimposed on the basic waveform; the noise high-frequency transient component refers to the mixed signal after the basic waveform and high-frequency noise are superimposed, which has both periodicity and randomness; and the vibration waveform refers to the time-domain signal that is finally output to the motor.

[0112] Optionally, the high-frequency noise added to the basic waveform can be obtained by extracting the energy distribution from the non-peak region of the high-frequency spectrum.

[0113] Optionally, the analysis of the non-periodic transient effects of the high-frequency transient components can be simulated using band-limited white noise.

[0114] This invention combines the output steady-state torque and the vibration waveform to analyze the potential load transformation characteristics of the user-operated device, enabling end-to-end analysis from the original torque signal to higher-order load semantics, and providing core decision-making basis for adaptive haptic feedback.

[0115] In detail, the analysis of the potential load transformation characteristics of the user operating equipment by combining the output steady-state torque and the vibration waveform includes:

[0116] The output steady-state torque and the vibration waveform are synchronized to obtain synchronized output steady-state torque and synchronized vibration waveform;

[0117] Generate the composite torque signal of the synchronous output steady-state torque and the synchronous vibration waveform;

[0118] Analyze the time spectrum and load steady-state coefficient of the composite torque signal;

[0119] Calculate the high-frequency energy difference of the time spectrum;

[0120] Based on the high-frequency energy differential and the load steady-state coefficient, the potential load transformation characteristics of the user operating equipment are determined.

[0121] The synchronous output steady-state torque refers to the low-frequency (0~10Hz) steady-state torque signal output by the system after frequency domain decomposition. The synchronous vibration waveform refers to the time-domain vibration signal generated by the high-frequency transient component (>10Hz). The composite torque signal refers to the time-domain superposition result of the steady-state torque and the vibration waveform, which is the final control signal output to the motor. The time spectrum refers to the time-frequency joint distribution obtained by STFT, which reflects the frequency components of the composite signal at different times. The load steady-state coefficient refers to the index that quantifies the load stability. The high-frequency energy difference refers to the rate of change of high-frequency energy between adjacent time frames. The load potential transformation characteristics refer to the user operation intentions identified by fusing the steady-state coefficient and the high-frequency difference, such as characteristics like increased load mass or sudden collision.

[0122] Optionally, the composite torque signal that generates the synchronous output steady-state torque and synchronous vibration waveform utilizes a double-buffering technique, with buffer A processing the steady-state torque and buffer B processing the vibration waveform, and is synthesized and output at a frequency of 1kHz.

[0123] S4. Based on the potential load transformation characteristics, generate an adaptive counterweight for the user's operating device and analyze the palm contact force distribution map of the target user.

[0124] Based on the potential load transformation characteristics, the present invention generates an adaptive weight for the user operation device, which can achieve millisecond-level adaptive weight adjustment and accurately match virtual physical rules with user operation intentions.

[0125] Specifically, generating the adaptive weight of the user operating device based on the potential load transformation characteristics includes:

[0126] Construct a six-dimensional vector of the potential transformation features of the load;

[0127] The six-dimensional vector is normalized to obtain a normalized six-dimensional vector;

[0128] Based on the normalized six-dimensional vector, the virtual mass adjustment, moment of inertia adjustment, and vibration gain adjustment of the user operating device are analyzed.

[0129] By combining the virtual mass adjustment, rotational inertia adjustment, and vibration gain adjustment, an adaptive counterweight for the user operating device is generated.

[0130] The six-dimensional vector refers to the original six-dimensional vector formed by extracting six core features from the composite torque signal. The normalized six-dimensional vector refers to the six-dimensional vector after each feature is independently normalized to the range of [0,1]. The virtual mass adjustment amount refers to the set of virtual mechanical parameters that are dynamically adjusted according to real-time operation. The moment of inertia adjustment amount refers to the correction value of the moment of inertia tensor of the virtual load. The vibration gain adjustment amount refers to the dynamic scaling factor of the amplitude of the high-frequency vibration waveform. The adaptive counterweight refers to the set of virtual mechanical parameters that are dynamically adjusted according to real-time operation.

[0131] Optionally, the analysis of the virtual mass adjustment, moment of inertia adjustment, and vibration gain adjustment of the user-operated device based on the normalized six-dimensional vector can be performed using a trained LSTM model.

[0132] This invention analyzes the palm contact force distribution map of the target user to achieve an intelligent closed loop from "pressure perception" to "weight optimization", which significantly improves the realism and security of virtual interaction.

[0133] In detail, the analysis of the palm contact force distribution map of the target user includes:

[0134] Collect the palm contact force data of the target user;

[0135] Construct a two-dimensional matrix of the palm contact force data to calculate the normal contact force of the palm sensor corresponding to the target user;

[0136] Define the biomechanical region of the target user;

[0137] Based on the normal contact force, the regional force ratio of the biomechanical region is calculated using the following formula;

[0138] The palm contact force distribution map of the target user is determined by the force ratio of the area.

[0139] Furthermore, as another embodiment of the present invention, the regional force ratio is calculated using the following formula:

[0140]

[0141] in, Indicates the first The proportion of regional forces in each biomechanical region Indicates the first A biomechanical region, Indicates the first Location index of the palm sensor in the biomechanical region. Indicates the first The biomechanical regions are located in The normal contact force of the palm sensor Indicates the first The biomechanical regions are located in The weighting coefficients of the palm sensor, Indicates the first The sum of contact forces of the palm sensors in each biomechanical region.

[0142] The palm contact force data refers to the set of raw signals collected by a pressure sensor array that reflects the interaction force between the user's palm and the contact surface of the device. The two-dimensional matrix refers to the matrix formed by arranging the pressure sensor data according to the physical layout. The normal contact force refers to the force component of the sensor surface perpendicular to the contact surface. The biomechanical region refers to the mechanical sub-regions divided according to the anatomy and function of the hand, including the palm area, thumb area, and hypothenar eminence area. The regional force ratio refers to the ratio of the weighted force of a certain biomechanical region to the total grip force, reflecting the load contribution of that region. The weighted coefficient palm contact force distribution map refers to the priority coefficients assigned according to the functional importance of the regions. The palm contact force distribution map refers to the visualization result of the force ratio of each region in the form of a heat map.

[0143] Optionally, the calculation of the normal contact force of the palm sensor corresponding to the target user can be achieved by multiplying the pressure of the palm sensor and the effective sensing area.

[0144] Optionally, an example of the weighting coefficient of the palm sensor is: the weighting coefficient of the palm area can be 1.2, and the weighting coefficient of the thumb area can be 0.7.

[0145] S5. Based on the adaptive weight, calculate the adaptation coefficient of the palm contact force distribution map. When the adaptation coefficient meets the preset adaptation threshold standard, use the adaptive weight as the target simulated weight of the target user.

[0146] Based on the adaptive weight, calculating the adaptation coefficient of the palm contact force distribution map can accurately analyze whether the configuration meets user needs, thereby improving the realism of the weight distribution for the user. The adaptation threshold is an index that quantifies the degree of matching between the actual palm contact force distribution and the expected ideal distribution, with a value range of [0, 1].

[0147] Finally, when the adaptation coefficient meets the preset adaptation threshold standard, the present invention uses the adaptive weight as the target simulated weight for the target user, thus achieving a closed loop from real-time adaptation to persistent configuration and significantly improving user experience consistency. The adaptation threshold standard refers to the critical similarity value used to determine whether the current adaptive weight parameters reach the user's ideal state, and the target simulated weight refers to the optimal force feedback parameter set finally determined by the system when the adaptation coefficient meets the threshold.

[0148] By collecting the spatial acceleration and angular velocity of the target user during equipment operation, a dynamic load model is established. This model accurately calculates the inertial and centrifugal forces acting on the equipment. Based on real-time analysis of these forces, the system outputs a compensating torque and decomposes it into low-frequency steady-state components and high-frequency transient components. This effectively distinguishes between the long-term load trend and instantaneous disturbance characteristics of the equipment. This process not only accurately identifies potential load transformation characteristics but also provides a scientific basis for generating adaptive counterweight schemes. During the adaptive counterweight generation process, by combining low-frequency steady-state torque and high-frequency vibration waveforms, the system can dynamically adjust the equipment's counterweight structure, optimize the center of gravity distribution and inertia matching, and significantly improve the operational stability and user comfort of the equipment. Simultaneously, by analyzing the target user's hand contact force distribution diagram and calculating the adaptation coefficient, the compatibility between the counterweight scheme and the user's physiological characteristics can be further evaluated. When the adaptation coefficient meets a preset threshold, the adaptive counterweight becomes the target user's exclusive simulated counterweight, achieving highly personalized equipment calibration. Overall, this technology significantly improves the comprehensive performance and user satisfaction of operating the equipment, and has broad application prospects and market value. Therefore, this invention can improve the realism of the simulated counterweight's tactile feedback.

[0149] like Figure 2 The diagram shown is a schematic of a module of a motor simulation counterweight system for improving the realism of body sensation according to an embodiment of the present invention.

[0150] The motor-simulated counterweight motion simulation enhancement system 200 described in this invention can be installed in an electronic device. Depending on the functions implemented, the system may include a dynamic load analysis module 201, a compensation torque analysis module 202, a load potential analysis module 203, a contact force distribution analysis module 204, and a target simulated counterweight module 205. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0151] In this embodiment of the invention, the functions of each module / unit are as follows:

[0152] The dynamic load analysis module 201 is used to collect the spatial acceleration and angular velocity of the target user on the user operating device, establish a dynamic load model of the user operating device, and calculate the inertial force and centrifugal force of the user operating device based on the spatial acceleration and angular velocity using the dynamic load model.

[0153] The compensation torque analysis module 202 is used to output the compensation torque of the user operating device based on the inertial force and centrifugal force, and decompose the compensation torque into low-frequency steady-state components and high-frequency transient components.

[0154] The load potential analysis module 203 is used to determine the output steady-state torque of the low-frequency steady-state component, define the vibration waveform of the high-frequency transient component, and analyze the load potential transformation characteristics of the user operating device by combining the output steady-state torque and the vibration waveform.

[0155] The contact force distribution analysis module 204 is used to generate an adaptive counterweight for the user operating device based on the potential load transformation characteristics, and to analyze the palm contact force distribution map of the target user.

[0156] The target simulation weight module 205 is used to calculate the adaptation coefficient of the palm contact force distribution map based on the adaptive weight. When the adaptation coefficient meets the preset adaptation threshold standard, the adaptive weight is used as the target simulation weight of the target user.

[0157] In detail, the modules in the motor-simulated counterweight motion simulation enhancement system 200 described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method described above uses the same technique to improve the realism of the simulated counterweight in motor simulation and can produce the same technical effect, so it will not be elaborated here.

[0158] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0159] Finally, it should be noted that in the above embodiments, each embodiment can be combined with each other or independent. Deleting any one of them will not affect the technical implementation of other embodiments. The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for improving the realism of simulated counterweight in motor operation, characterized in that, The method includes: Collect the spatial acceleration and angular velocity of the target user on the user operating device, establish a dynamic load model of the user operating device, and calculate the inertial force and centrifugal force of the user operating device based on the spatial acceleration and angular velocity using the dynamic load model; Based on the inertial force and centrifugal force, the compensation torque of the user operating device is output, and the compensation torque is decomposed into a low-frequency steady-state component and a high-frequency transient component. Determine the output steady-state torque of the low-frequency steady-state component, define the vibration waveform of the high-frequency transient component, and combine the output steady-state torque and the vibration waveform to analyze the potential load transformation characteristics of the user operating equipment. Based on the potential load transformation characteristics, an adaptive counterweight for the user's operating device is generated, and the palm contact force distribution map of the target user is analyzed. Based on the adaptive weight, the adaptation coefficient of the palm contact force distribution map is calculated. When the adaptation coefficient meets the preset adaptation threshold standard, the adaptive weight is used as the target simulated weight for the target user.

2. The method for improving the realism of motor-simulated counterweight as described in claim 1, characterized in that, The step of outputting the compensation torque for the user operating device based on the inertial force and centrifugal force includes: The inertial force and centrifugal force are vectored together to obtain the total feedback force; Define the virtual load application point of the user operating device; Calculate the lever arm vector at the point of application of the virtual load; Based on the total feedback force and the lever arm vector, the compensation torque of the user operating device is calculated.

3. The method for improving the realism of motor-simulated counterweight as described in claim 2, characterized in that, The calculation of the compensation torque for the user-operated device based on the total feedback force and the lever arm vector includes: Analyze the load inertia tensor and damping matrix of the user operating device; Based on the load inertia tensor, the damping matrix, the total feedback force, and the lever arm vector, the compensation torque of the user-operated device is calculated using the following formula: in, This indicates the compensation torque for user-operated equipment. This represents the lever arm vector of the user operating the device. Indicates the total feedback force. Indicates the dynamic compensation coefficient. Represents the load inertia tensor. This represents the angular acceleration of the user operating the device. This represents the angular acceleration of the user operating the device. This represents the damping matrix.

4. The method for improving the realism of motor-simulated counterweight as described in claim 1, characterized in that, The establishment of the dynamic load model for the user operating device includes: Establish the rotation matrix between the user operating device and the preset world coordinate system; Define the virtual load parameters of the user operating device, wherein the virtual load parameters include virtual mass and moment of inertia tensor; Based on the virtual load parameters, a dynamic load equation for the user operating device is constructed, wherein the dynamic load equation includes translational dynamics equations and rotational dynamics equations; Based on the rotation matrix and the dynamic load equation, a dynamic load model of the user operating device is established.

5. The method for improving the realism of motor-simulated counterweight as described in claim 1, characterized in that, The step of decomposing the compensated torque into low-frequency steady-state components and high-frequency transient components includes: The compensation torque is preprocessed to obtain the processed compensation torque; Perform a Fourier transform on the converted compensation torque to obtain the converted compensation torque; Extract the low-frequency and high-frequency components of the transformed compensation torque; The low-frequency component and the high-frequency component are reconstructed respectively to obtain the low-frequency steady-state component and the high-frequency transient component.

6. The method for improving the realism of the simulated counterweight in a motor as described in claim 1, characterized in that, The vibration waveform defining the high-frequency transient component includes: Identify the spectral peak of the high-frequency transient component to calculate the total energy of the high-frequency transient component; Construct the basic waveform of the high-frequency transient component; The non-periodic transient effect and natural decay of the high-frequency transient component are analyzed to increase the high-frequency noise of the base waveform, thereby obtaining the noise high-frequency transient component; The vibration waveform of the basic waveform is determined based on the natural attenuation and the total energy of the high-frequency components.

7. The method for improving the realism of motor-simulated counterweight as described in claim 1, characterized in that, The analysis of the potential load transformation characteristics of the user operating equipment by combining the output steady-state torque and the vibration waveform includes: The output steady-state torque and the vibration waveform are synchronized to obtain synchronized output steady-state torque and synchronized vibration waveform; Generate the composite torque signal of the synchronous output steady-state torque and the synchronous vibration waveform; Analyze the time spectrum and load steady-state coefficient of the composite torque signal; Calculate the high-frequency energy difference of the time spectrum; Based on the high-frequency energy differential and the load steady-state coefficient, the potential load transformation characteristics of the user operating equipment are determined.

8. The method for improving the realism of motor-simulated counterweight as described in claim 1, characterized in that, The step of generating adaptive weights for the user operating device based on the potential load transformation characteristics includes: Construct a six-dimensional vector of the potential transformation features of the load; The six-dimensional vector is normalized to obtain a normalized six-dimensional vector; Based on the normalized six-dimensional vector, the virtual mass adjustment, moment of inertia adjustment, and vibration gain adjustment of the user operating device are analyzed. By combining the virtual mass adjustment, rotational inertia adjustment, and vibration gain adjustment, an adaptive counterweight for the user operating device is generated.

9. The method for improving the realism of the simulated counterweight in a motor as described in claim 1, characterized in that, The analysis of the target user's palm contact force distribution includes: Collect the palm contact force data of the target user; Construct a two-dimensional matrix of the palm contact force data to calculate the normal contact force of the palm sensor corresponding to the target user; Define the biomechanical region of the target user; Based on the normal contact force, the regional force ratio of the biomechanical region is calculated using the following formula: in, Indicates the first The proportion of regional forces in each biomechanical region Indicates the first A biomechanical region, Indicates the first Location index of the palm sensor in the biomechanical region. Indicates the first The biomechanical regions are located in The normal contact force of the palm sensor Indicates the first The biomechanical regions are located in The weighting coefficients of the palm sensor, Indicates the first The sum of contact forces of the palm sensors in each biomechanical region; The palm contact force distribution map of the target user is determined by the force ratio of the area.

10. A system for improving the realism of simulated counterweight using a motor, characterized in that, The system includes: The dynamic load analysis module is used to collect the spatial acceleration and angular velocity of the target user on the user operating device, establish a dynamic load model of the user operating device, and calculate the inertial force and centrifugal force of the user operating device based on the spatial acceleration and angular velocity using the dynamic load model. The compensation torque analysis module is used to output the compensation torque of the user operating device based on the inertial force and centrifugal force, and decompose the compensation torque into low-frequency steady-state components and high-frequency transient components. The load potential analysis module is used to determine the output steady-state torque of the low-frequency steady-state component, define the vibration waveform of the high-frequency transient component, and analyze the load potential transformation characteristics of the user operating equipment by combining the output steady-state torque and the vibration waveform. The contact force distribution analysis module is used to generate an adaptive counterweight for the user's operating device based on the potential load transformation characteristics, and to analyze the palm contact force distribution map of the target user. The target simulated weight module is used to calculate the adaptation coefficient of the palm contact force distribution map based on the adaptive weight. When the adaptation coefficient meets the preset adaptation threshold standard, the adaptive weight is used as the target simulated weight of the target user.

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