Personalized texture touch rendering method and system based on electro-vibration friction physical model

Abstract

The invention provides a personalized texture touch rendering method and system based on an electro-vibration friction physical model, and the method comprises the steps: constructing a personalized sliding friction physical model fusing texture geometry, fingertip physiological parameters, positive pressure and sliding speed, and achieving the quantitative mapping from texture features to tangential friction force; establishing an equivalent relationship between the friction behavior and the electro-vibration, and analyzing a corresponding driving voltage time domain code through an electrostatic pressure integral discretization model based on an effective contact area; and finally, the coded signal is applied to an electro-vibration device, and surface friction is modulated to reproduce the target texture touch feeling. According to the method, the whole-course physical mapping model from the texture features to the driving signals is constructed, and the user personalized parameters are introduced, so that a personalized and customized touch rendering scheme can be provided for different textures, different users and different touch interaction scenes, and the reality and accuracy of texture touch reproduction experience are remarkably improved.

Description

Technical Field

[0001] This invention relates to tactile re-presentation technology, and in particular to a personalized texture tactile rendering method and system based on an electro-vibration friction physical model. Background Technology

[0002] Haptic rendering technology in virtual environments plays a crucial role in enhancing the immersive experience of metaverse scenes. However, existing technologies still have significant shortcomings in reproducing detailed textures. Due to the complexity of tactile perception mechanisms and the interdisciplinary nature of tactile research, current texture rendering methods still suffer from a lack of theoretical basis, limited realism and richness, and significant limitations in application scenarios. Existing technologies mainly face the following challenges: First, the lack of a complete and interpretable physical mapping from texture geometry features to tactile perception signals leads to a reliance on empirical "black box" models in the rendering process, limiting realism and generalization ability. Second, the inability to dynamically and personally adapt tactile parameters for different users (e.g., physiological differences in fingertips), different interaction behaviors (e.g., pressure, swiping speed), and different texture surfaces (e.g., regular and random textures) makes it difficult to meet the customized needs of diverse scenarios. Third, existing electro-vibration tactile reproduction schemes often have high driving voltages and low energy efficiency, restricting their safe integration and application expansion in mobile devices and consumer electronics. These shortcomings collectively limit the in-depth application and development of texture tactile reproduction technology in cutting-edge interactive scenarios such as metaverse and AR / VR.

[0003] It should be noted that the information disclosed in the background section above is only for understanding the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The main objective of this invention is to overcome the deficiencies in the aforementioned background technology and provide a personalized texture tactile rendering method and system based on an electro-vibration friction physical model.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A personalized texture tactile rendering method based on an electro-vibration friction physical model includes the following steps: S1. Construction of a personalized sliding friction physical model: Construct a multi-layered heterogeneous two-dimensional finger linear elastic body model and a two-dimensional texture model. Analyze the sliding process of the finger on the texture surface through finite element simulation. Establish a personalized sliding friction physical model that integrates texture geometric features, fingertip physiological parameters, normal pressure and sliding speed to achieve a quantitative mapping from texture geometric features to tangential friction force. S2. Solving the electro-vibration driving signal: Establish the mapping relationship between the personalized sliding friction physical model and the electro-vibration electrostatic force; based on the effective contact area of ​​the fingertip, construct a discretized model of electrostatic pressure integral to quantify the electrostatic force generated by the electro-vibration device; input the contact spatiotemporal information extracted by finite element simulation and the parameters of the electro-vibration device into the discretized model to calculate the temporal coding information of the driving voltage required for texture tactile rendering; S3. Tactile Reproduction: The driving voltage time-domain encoded information obtained in step S2 is applied to the electro-vibration device to drive it to work and modulate the friction between the fingertip and the device surface, thereby reproducing the tactile perception of the target texture.

[0006] Further, in step S1, the personalized sliding friction physical model is constructed in the following way: an equivalent mapping relationship of friction behavior under two contact scenarios, namely, a real textured surface and a tactile screen surface, is established so that the tangential friction force is equal in the two scenarios; the mapping relationship is realized by associating the time-varying friction coefficient and normal force of the textured surface with the electrostatic force, normal force and fixed friction coefficient of the tactile screen surface, wherein the time-varying friction coefficient is a function of the finger sliding path and sliding speed.

[0007] Furthermore, in step S2, the discretization model of the electrostatic pressure integral is constructed and processed in the following manner: The time-varying effective contact area between the fingertip and the surface of the tactile screen is divided into multiple discrete micro-elements in the spatiotemporal domain. The electrostatic pressure calculation model for each micro-element correlates the applied voltage, the area facing the micro-element, and the equivalent capacitance distance composed of the thickness and dielectric constant of the fingertip cuticle, air gap, and tactile screen dielectric layer. By summing the electrostatic pressure contributions of all infinitesimal elements at discrete moments, the macroscopic electrostatic force acting on the fingertip at that moment can be calculated.

[0008] Furthermore, the method also includes a step S0: personalized parameter input, which involves measuring the two-dimensional geometric dimensions of the user's fingertip and the width of the fingerprint ridge through image processing, and obtaining frictional behavior parameters related to the sliding speed through a passive touch tactile measurement experiment, and inputting the parameters into the personalized sliding friction physical model in step S1.

[0009] Furthermore, the method is applicable to the tactile reproduction of periodic regular textures and non-periodic complex textures, wherein the geometric features of the complex textures are acquired by a surface topography measuring instrument and converted into a two-dimensional texture profile model based on the tactile interaction sliding trajectory.

[0010] Furthermore, the solution of the driving voltage time-domain encoded information in step S2 is specifically as follows: The electrostatic force that needs to be introduced on the surface of the touch screen to achieve the target tangential friction force, as determined by the equivalent mapping relationship in step S1, is used as the target output of the electrostatic pressure integral discretization model. Based on the discretized model, combined with the information on the area of ​​each micro-element facing each other, the thickness of the fingertip keratin layer and air layer that vary with time extracted from the finite element simulation, and the fixed structural parameters of the electro-vibrating device, the driving voltage signal that can generate the target electrostatic force is solved in reverse as it varies with time.

[0011] A personalized texture tactile reproduction system implementing the method includes: The personalized model parameter calculation module is used to obtain the user's personalized physiological parameters and friction behavior parameters of the fingertips; The texture rendering calculation module is connected to the personalized model parameter calculation module and is used to receive the personalized parameters and perform the construction of the personalized sliding friction physical model, finite element simulation and the calculation of the driving voltage time domain encoding information. The tactile reproduction interaction module, connected to the texture rendering calculation module, includes a host computer, a signal generator, a voltage amplifier, and an electro-vibrating tactile screen connected in sequence, used to receive the driving voltage time-domain encoded information and generate corresponding tactile stimuli.

[0012] Furthermore, the personalized model parameter calculation module includes: An electronic 3D microscope under-microscopic measurement system is used to acquire fingertip images and obtain fingertip geometric parameters through image processing algorithms; A force-based passive touch tactile measurement system is used to measure the tangential frictional force between the fingertip and a textured sample under controlled positive pressure and sliding speed in order to obtain frictional behavior parameters.

[0013] Furthermore, the texture rendering calculation module includes: The simulation unit is used to perform finite element mechanical simulation of the multilayer heterogeneous finger model and texture model during the sliding process; The data extraction unit is used to automatically extract spatiotemporal information of the contact area and pressure distribution from the simulation results; The algorithm solution unit is used to run the electrostatic pressure integral discretization model, receive the spatiotemporal domain information and device parameters, and execute the reverse solution algorithm for the driving voltage time-domain encoded information.

[0014] Furthermore, the electro-vibrating tactile screen comprises, from bottom to top, a substrate layer, an electrode layer, and a dielectric layer; wherein the dielectric layer is a dielectric material layer with a thickness of 100-1000 nm, and the electrode layer is a conductive material layer with a thickness of 100-500 nm.

[0015] The present invention has the following beneficial effects: This invention provides a personalized texture tactile rendering method and system based on an electro-vibration friction physical model, effectively solving the problems of insufficient realism and richness in existing texture tactile rendering methods and limited application scenarios. The core of this invention lies in constructing a complete, quantitative mapping chain from physical perception to electrical signal drive. By establishing a multi-layered heterogeneous two-dimensional finger linear elastic body model and a two-dimensional texture model, and using finite element simulation, a personalized sliding friction physical model integrating multiple variables such as texture geometric features, fingertip physiological parameters, normal pressure, and sliding speed is constructed, thereby achieving a precise mapping from texture geometric features to tangential friction force. By establishing an equivalent relationship of frictional behavior between the real texture surface and the tactile screen surface, and innovatively proposing a discretized model of electrostatic pressure integral based on the effective contact area of ​​the fingertip, the electrostatic force generated by electro-vibration is precisely quantified, and the corresponding driving voltage time-domain encoding is finally calculated. This end-to-end physical modeling method avoids the limitations of traditional "black box" mapping, giving the rendering results clear physical meaning and interpretability, and significantly enhancing the robustness and generalization ability of the system. By incorporating personalized physiological parameters (such as fingertip size and fingerprint ridge width) and interaction parameters (such as pressing pressure and swiping speed) and configuring the model accordingly, this invention can provide customized tactile rendering solutions for different users, textures, and interaction scenarios, thereby effectively improving the accuracy and realism of tactile reproduction. Furthermore, based on the established physical model, the dielectric layer configuration of the electro-vibrating device was optimized, significantly reducing the system driving voltage amplitude and tactile perception threshold. This ensures rendering quality while significantly improving the device's safety, energy efficiency, and integration feasibility.

[0016] This invention is not only applicable to periodic, regular textures, but can also be extended to non-periodic, complex textures such as fabrics, demonstrating excellent versatility and scalability. It provides a highly realistic tactile reproduction solution for diverse scenarios such as virtual reality, augmented reality, mobile interaction, and assistive technologies. Experimental verification shows that the average accuracy of tactile matching for various complex textures exceeds 80%, and under personalized rendering schemes, the tactile matching accuracy can be further improved by more than 20%, confirming its effectiveness and advancement in improving the realism of texture tactile reproduction and user experience.

[0017] Other beneficial effects of the embodiments of the present invention will be further described below. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the composition of the tactile reproduction system based on the electro-vibration tactile screen according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a two-dimensional multilayer heterogeneous linear elastomer fingertip model in an embodiment of the present invention; Figure 3 This is a schematic diagram simulating the finger sliding process in an embodiment of the present invention; Figure 4 This refers to the structural composition of each micro-element in the electrostatic pressure integral model in this embodiment of the invention; Figure 5 These are the electro-vibrating haptic screen driving voltage information corresponding to the five different period textures in the embodiments of the present invention after haptic rendering; Figure 6 This is a schematic diagram of the composition of the passive touch tactile measurement system in an embodiment of the present invention.

[0019] Figure 7 These are the model calculation and experimental measurement results of the electrostatic force output by the electro-vibrating tactile screen in the embodiments of the present invention; Figure 8 This is a two-dimensional texture profile information extracted along a specified sliding trajectory for the texture of a specific commercial fabric in an embodiment of the present invention; Figure 9 This is the electro-vibrating haptic screen driving voltage encoding information obtained after performing tactile rendering on a specific commercial fabric in an embodiment of the present invention.

[0020] Figure 10 This is the overall flowchart of the personalized texture tactile rendering method based on the electro-vibration friction physical model of the present invention. Detailed Implementation

[0021] The embodiments of the present invention will be described in detail below. It should be emphasized that the following description is merely exemplary and not intended to limit the scope and application of the present invention.

[0022] This invention aims to address the shortcomings of existing texture tactile rendering methods, such as a lack of realism, richness, physical meaning, interpretability, and generalization ability. It proposes a personalized texture tactile rendering method and system based on an electro-vibration friction physical model. By constructing a physical mapping model from texture features to driving signals and introducing user-personalized parameters, it can provide personalized tactile rendering solutions for different textures, different users, and different tactile interaction scenarios, significantly improving the realism and accuracy of texture tactile reproduction experience.

[0023] See Figure 10 This invention provides a personalized texture tactile rendering method based on an electro-vibration tribology physical model, comprising the following steps: Step S1. Construction of a personalized sliding friction physical model: Construct a multi-layered heterogeneous two-dimensional finger linear elastic body model and a two-dimensional texture model. Analyze the sliding process of the finger on the texture surface through finite element simulation. Establish a personalized sliding friction physical model that integrates texture geometric features, fingertip physiological parameters, normal pressure, and sliding speed to achieve a quantitative mapping from texture geometric features to tangential friction force.

[0024] In some embodiments, in step S1, the personalized sliding friction physical model is constructed in the following way: establishing an equivalent mapping relationship of friction behavior under two contact scenarios, namely, a real textured surface and a tactile screen surface, so that the tangential friction force is equal in the two scenarios; the mapping relationship is realized by associating the time-varying friction coefficient and normal force of the textured surface with the electrostatic force, normal force and fixed friction coefficient of the tactile screen surface, wherein the time-varying friction coefficient is a function of the finger sliding path and sliding speed.

[0025] Step S2. Solving for the electro-vibration driving signal: Establish the mapping relationship between the personalized sliding friction physical model and the electro-vibration electrostatic force; based on the effective contact area of ​​the fingertip, construct a discretized model of the electrostatic pressure integral to quantify the electrostatic force generated by the electro-vibration device; input the contact spatiotemporal information extracted by finite element simulation and the parameters of the electro-vibration device into the discretized model to calculate the temporal coding information of the driving voltage required for texture tactile rendering; In some embodiments, in step S2, the discretization model of the electrostatic pressure integral is constructed and processed as follows: the time-varying effective contact area between the fingertip and the haptic screen surface is divided into multiple discrete micro-elements in the spatiotemporal domain; the electrostatic pressure calculation model of each micro-element correlates the applied voltage, the area facing the micro-element, and the equivalent capacitance distance composed of the thickness and dielectric constant of the fingertip keratin layer, air gap, and haptic screen dielectric layer; by summing the electrostatic pressure contributions of all micro-elements at discrete times, the macroscopic electrostatic force acting on the fingertip at that time is calculated.

[0026] In some embodiments, the solution of the time-domain encoded information of the driving voltage in step S2 is specifically as follows: the electrostatic force that needs to be introduced on the surface of the touch screen to achieve the target tangential friction force, which is determined by the equivalent mapping relationship in step S1, is used as the target output of the electrostatic pressure integral discretization model; based on the discretization model, combined with the information on the facing area of ​​each micro-element, the thickness of the fingertip keratin layer and the air layer that vary with time extracted from the finite element simulation, and the fixed structural parameters of the electro-vibration device, the signal of the driving voltage that can generate the target electrostatic force is solved in reverse as it varies with time.

[0027] Step S3. Tactile Reproduction: The driving voltage time-domain encoded information obtained in step S2 is applied to the electro-vibration device to drive it to work and modulate the friction between the fingertip and the device surface, thereby reproducing the tactile perception of the target texture.

[0028] In some embodiments, the method further includes a step S0: personalized parameter input, which involves measuring the two-dimensional geometric dimensions of the user's fingertip and the width of the fingerprint ridge through image processing, obtaining frictional behavior parameters related to the sliding speed through a passive touch tactile measurement experiment, and inputting the parameters into the personalized sliding friction physical model in step S1.

[0029] In some embodiments, the method is applicable to the tactile reproduction of periodic regular textures and non-periodic complex textures, wherein the geometric features of the complex textures are acquired by a surface topography measuring instrument and converted into a two-dimensional texture profile model based on the tactile interaction sliding trajectory.

[0030] This invention also provides a personalized texture tactile reproduction system for implementing the method, including a personalized model parameter calculation module, a texture rendering calculation module, and a tactile reproduction interaction module: the personalized model parameter calculation module is used to acquire personalized physiological parameters and friction behavior parameters of the user's fingertips; the texture rendering calculation module is connected to the personalized model parameter calculation module and is used to receive the personalized parameters, perform the construction of the personalized sliding friction physical model, finite element simulation, and solve the driving voltage time-domain encoding information; the tactile reproduction interaction module is connected to the texture rendering calculation module and includes a host computer, a signal generator, a voltage amplifier, and an electro-vibrating tactile screen connected in sequence, used to receive the driving voltage time-domain encoding information and generate corresponding tactile stimuli.

[0031] In some embodiments, the personalized model parameter calculation module includes: an electron 3D microscope under-microscope measurement system for acquiring fingertip images and obtaining fingertip geometric parameters through image processing algorithms; and a force-based passive touch tactile measurement system for measuring the tangential frictional force between the fingertip and the texture sample under controllable positive pressure and sliding speed to obtain frictional behavior parameters.

[0032] In some embodiments, the texture rendering calculation module includes: a simulation unit for performing finite element mechanical simulation of the multilayer heterogeneous finger model and texture model during the sliding process; a data extraction unit for automatically extracting spatiotemporal information of the contact area and pressure distribution from the simulation results; and an algorithm solution unit for running the electrostatic pressure integral discretization model, receiving the spatiotemporal information and device parameters, and executing the reverse solution algorithm for the driving voltage time-domain encoded information.

[0033] In some embodiments, the electro-vibrating haptic screen comprises, from bottom to top, a substrate layer, an electrode layer, and a dielectric layer; wherein the dielectric layer is a dielectric material layer with a thickness of 100-1000 nm, preferably such as a 400 nm thick SiO2 dielectric layer, and the electrode layer is a conductive material layer with a thickness of 100-500 nm, preferably such as a 220 nm thick indium tin oxide electrode layer. Through optimized design, the dielectric layer generates sufficient electrostatic force at a relatively low driving voltage amplitude, thereby reducing the tactile sensing threshold and operating voltage of the system.

[0034] This invention provides a personalized texture tactile rendering method and system based on an electro-induced vibration friction physical model. By constructing a complete and quantified physical mapping chain from physical perception to electrical signal drive, it establishes a personalized sliding friction physical model integrating multiple variables such as texture geometry, fingertip physiological parameters, normal pressure, and sliding speed, achieving precise mapping from texture features to tangential friction force. By establishing equivalent relationships of frictional behavior and innovatively proposing a discretized model of electrostatic pressure integral based on effective contact area, it accurately quantifies electrostatic force and calculates the driving voltage code, giving the rendering process clear physical meaning and interpretability, significantly enhancing the system's robustness and generalization ability. Simultaneously, by introducing user-personalized physiological and interaction parameters, it provides customized rendering solutions for different users, textures, and interaction scenarios, effectively improving the realism and accuracy of tactile reproduction. This invention is not only applicable to periodic textures but can also be extended to non-periodic complex textures such as fabrics, demonstrating good versatility and scalability, providing a highly realistic tactile solution for diverse interaction scenarios. The following further describes specific embodiments of the present invention, algorithm examples, and experimental verification.

[0035] A texture tactile rendering method based on an electro-vibration friction physical model includes the following steps: Step S1, Construction of Personalized Sliding Friction Physical Model: Construct a multi-layered heterogeneous two-dimensional finger linear elastic body model and a two-dimensional texture model. Analyze the sliding process of the finger on the texture surface through finite element simulation. Establish a personalized sliding friction physical model that integrates multiple variables such as texture profile, fingertip size, normal pressure and sliding speed to achieve quantitative mapping from texture geometric features to tangential friction force. Step S2, Solving the electro-vibration driving signal: Establish the mapping relationship between the personalized sliding friction physical model described in step S1 and the electro-vibration electrostatic force; Based on the effective contact area of ​​the human fingertip, construct a discretized model of the electrostatic pressure integral to quantify the electrostatic force generated by the electro-vibration device; Using the contact spatiotemporal information extracted by the finite element simulation and the parameters of the electro-vibration device as input, calculate the driving voltage temporal coding information required for texture tactile rendering through the discretized model; Step S3, tactile reproduction: The driving voltage time-domain encoded information obtained in step S2 is input into the tactile reproduction system with the electro-vibrating device as the core, driving the electro-vibrating device to work, thereby reproducing the tactile perception of the target texture.

[0036] Furthermore, in step S1, the personalized sliding friction physical model is constructed based on the classical Coulomb friction model, by incorporating the influence of texture space structure, interactive sliding trajectory, and spatiotemporal dynamic changes of sliding velocity on the friction coefficient. Specifically, it includes: The friction mapping relationship in the two tactile interaction scenarios (real texture, touch screen) involved in tactile rendering is shown in the following equation (1): (1) in, It is the path of a finger sliding on a textured surface. It is the finger swiping speed. This represents the three-dimensional topographic distribution of a real textured surface. In the superscript and subscript, "rs" represents the real textured surface, and "hd" represents the haptic display surface. It is the normal force, which is expressed mathematically as a function of time. The function form. Let $\mathbf$ represent the tangential sliding friction, electrostatic attraction, and coefficient of friction, respectively. Mathematically, they are all expressed as a function of time. Finger swipe path Finger swipe speed The function form. In mathematical formulas, it is represented as and With respect to time in two mutually perpendicular directions and texture space distribution The function form.

[0037] Furthermore, in step S2, the electrostatic pressure integral model employs discretized infinitesimal elements to specifically consider the influence of the fingerprint microstructure, fingertip curvature, and air gap at the contact interface on the effective contact area and electrostatic attraction during actual contact. Specifically, this includes: Based on the electrostatic pressure integral model based on the effective contact area of ​​the fingertip, at discrete time... The macroscopic electrostatic force at the fingertip is: (2) in, For a moment The corresponding voltage value, For a moment The corresponding electrostatic force value, and They are the first The thickness of the stratum corneum and air layer in a micro-element of the finger. and These are the dielectric constants of the keratin layer and the air layer of the finger, respectively. and They are the first The thickness and dielectric constant of the insulating layer in each micro-element. It is the first Each infinitesimal element at discrete time The area directly opposite below.

[0038] Therefore, the time-domain encoding of the driving voltage based on tribomodulation is as follows:

[0039] in, This represents the time-domain signal of the driving voltage applied to the electrode layer of the touchscreen. and They are the first The thickness of the stratum corneum and air layer of the finger changes over time in a micro-element. and These are the dielectric constants of the keratin layer and the air layer of the finger, respectively. and They are the first The thickness and dielectric constant of the insulating layer in each micro-element. It is the first The change of the area of ​​a micro-element over time. This indicates the change in the boundary of the effective contact area between the finger and the tactile screen surface over time.

[0040] The method further includes: step S0, personalized input of model parameters: through contact force measurement experiments, obtain personalized contact mechanics parameters and friction parameters of the user, and calculate and input the parameters in the personalized sliding friction physical model.

[0041] The method can be applied to the tactile reproduction of different types of textures, including but not limited to periodic regular textures and general complex textures.

[0042] A texture tactile reproduction system for implementing the method includes: The personalized model parameter calculation module includes an electron 3D microscope under-microscope measurement system and a force-based passive touch tactile measurement system. The electron 3D microscope under-microscope measurement system consists of an electron 3D microscope and a host computer. It uses image algorithms to process and calculate fingertip images to obtain personalized parameters such as the fingertip's two-dimensional geometric dimensions, fingerprint ridge width, and Young's modulus. The force-based passive touch tactile measurement system consists of a finger support and fixation structure, a texture tangential displacement mechanism, a finger positive pressure adjustment mechanism, a three-dimensional force sensor, and a tactile interaction surface. It uses passive touch tactile measurement experiments to obtain frictional behavior parameters between the fingertip and texture, related to sliding speed.

[0043] The texture rendering algorithm module consists of ABAQUS sliding friction mechanics simulation, Python data automatic extraction program and Python driving voltage tactile rendering algorithm. It is used to execute the personalized sliding friction physical model construction and electro-vibration driving signal solution steps, and output driving voltage time-domain encoded information. The tactile interaction module includes a host computer, a signal generator, a voltage amplifier, and an electro-vibrating tactile screen connected in sequence, which are used to receive the time-domain encoded information of the driving voltage and generate corresponding tactile stimuli.

[0044] The driving voltage amplitude of the dielectric layer of the electro-vibrating tactile screen is less than 50V, and the tactile perception threshold is less than 30V.

[0045] The system operates based on a triboelectric modulation texture tactile rendering algorithm. As a texture tactile rendering method based on an electro-vibration triboelectric physical model, its key lies in establishing a quantitative mapping model across the entire link from texture physical features to electro-vibration driving signals. Specifically, this mapping model can be achieved through the following three core components: 1. Construction of a personalized sliding friction physical model: First, a multi-layered heterogeneous two-dimensional linear elastic body model of the fingertip is constructed. This model not only simulates the multi-layered structure of human fingertip skin and the different mechanical properties of different layers, but also incorporates fingerprint ridges, an important feature affecting tactile sensation. Simultaneously, a two-dimensional texture profile model is established based on the three-dimensional distribution of the target's real texture and the two-dimensional sliding trajectory of tactile interaction.

[0046] Secondly, finite element analysis software (such as ABAQUS) was used to perform mechanical simulations of the sliding process of a fingertip on a textured surface and an electro-vibration haptic display screen. Based on this, the classic Coulomb friction model was extended to establish a personalized sliding friction physical model that integrates multiple parameters such as texture profile, fingertip size, normal force, and sliding speed. This model achieves a precise and quantitative mapping from texture geometry to the tangential friction force perceived by the user.

[0047] 2. Electro-induced vibration driven voltage triboelectric modulation encoding: This step aims to map the aforementioned friction into a voltage signal that can drive an electro-vibrating device.

[0048] a) Friction-electrostatic force mapping: Establish the equivalent relationship of friction behavior under two contact scenarios: real textured surface and electro-vibration tactile reproduction interactive screen surface. Derive the electrostatic force required to achieve a specific tangential friction force, see Equation (1) for details.

[0049] b) Precise Electrostatic Force Modeling: Based on the classical electro-vibration electrostatic force model, an innovative discretized model of electrostatic pressure integration based on the effective contact area of ​​the fingertip is proposed. This model fully considers the influence of fingerprint microstructure, fingertip curvature, and interfacial air gap on the effective contact area and electric field distribution in actual contact. By dividing the contact area in the personalized sliding friction physical model of step 1 into a mesh in the spatiotemporal domain and integrating (or discretizing and summing) the electrostatic pressure on each micro-element, the total electrostatic force is accurately quantified. At discrete time... For the specific calculation of the macroscopic electrostatic force at the fingertip, please refer to equation (2).

[0050] c) Driving signal calculation: Input the contact spatiotemporal information (such as contact area and pressure distribution) extracted from the finite element simulation in step 1 and the electro-vibration device parameters (such as dielectric constant and thickness) into the discretized model, and reverse calculate the driving voltage time-domain encoding information that can generate the target electrostatic force, see equation (3) for details.

[0051] 3. Tactile reproduction: The driving voltage time-domain encoded information, obtained by solving the above-mentioned triboelectric modulation texture haptic rendering method in the host computer, is sent to an arbitrary waveform generator via a network cable, and then applied to the electro-vibrating haptic screen via a voltage amplifier. When the user's finger slides on the screen, the modulated electrostatic force will change the friction between the fingertip and the screen surface, thereby allowing the user to perceive a haptic effect consistent with the real texture, thus realizing the reproduction of the real texture on the electro-vibrating haptic interactive screen.

[0052] This invention is based on a personalized two-dimensional texture tactile rendering model of triboelectric modulation, and transmits and reproduces realistic texture tactile information through the electro-vibration tactile reproduction system.

[0053] Example (I) System Composition The texture tactile reproduction system that implements this method mainly consists of three modules: (1) Calculation and rendering module: This is the host computer, which is equipped with ABAQUS finite element analysis software and texture tactile rendering algorithm based on Python. It is responsible for the construction, simulation and calculation of personalized sliding friction physical model and driving voltage signal.

[0054] (2) Signal generation and amplification module: including RIGOL DG1062Z function / arbitrary waveform generator and Agilent ATA-2082 voltage amplifier, used to receive and amplify the voltage time-domain encoded signal sent by the calculation module.

[0055] (3) Tactile interaction and perception module: such as Figure 1 As shown, the core of the tactile interaction and sensing module is the electro-vibrating tactile screen 1, whose structure, from bottom to top, typically consists of: a glass substrate layer, an ITO electrode layer, and a SiO2 dielectric layer. An amplified driving signal is applied between the upper and lower electrodes to generate a controllable electrostatic force. Other components include a tachymeter display 2, a slider 4 guiding finger movement, and a realistic texture sample 3.

[0056] (II) Personalized parameter measurement and model input To improve the experience for specific users, personalized parameter measurements can be performed: (1) Finger tip geometric parameters: can be obtained by observing images under an electron 3D microscope and using image processing algorithms.

[0057] (2) Biomechanical parameters: The elastic modulus and other parameters of the heterogeneous structures in each layer of the finger model can be calculated by fingertip indentation test.

[0058] (3) Friction parameter calibration: Using a passive touch tactile measurement system experimental platform, the variation of tangential friction force with sliding speed under different normal pressures was measured to calculate the friction coefficient model parameters in the sliding friction physical model. For example... Figure 6 As shown, the passive touch tactile measurement system includes a finger support and fixing structure 11, a texture tangential displacement mechanism 12, a finger positive pressure adjustment mechanism 13, a tactile interactive surface 14, and a three-dimensional force sensor 15.

[0059] (III) Driving signal generation and tactile reproduction process (1) In the calculation module, input the three-dimensional distribution of the target's real texture, the tactile interaction sliding trajectory, and the user's personalized parameters.

[0060] (2) Run the finite element simulation and rendering algorithm, and finally output a driving voltage signal file (.RAF format) corresponding to the texture and interaction conditions.

[0061] (3) Send the file to the waveform generator, set the amplifier gain, amplify the signal to the target rendering amplitude, and connect it to the electrode of the electro-vibrating screen.

[0062] (4) The user's wrist is grounded, and the user places their finger on the powered electro-vibrating haptic screen and slides it to perceive the realistic texture of the reproduced target.

[0063] Example 1: Personalized tactile reproduction and performance verification of five different periodic artificial textures This example details how to apply the method of the present invention to a group of... Defined, under five different periods ( Personalized tactile rendering and effect evaluation are performed on realistic tactile scenes where the 3D texture slides in a straight line along the texture periodic direction.

[0064]

[0065] In the above formula, Represents the three-dimensional topographic distribution of a realistic textured surface. For texture element units along The number of axes distributed, For texture element units along The number of axes distributed, The sliding distance is the distance along the finger sliding trajectory defined by formula (2-2). For texture period, The height of the textured substrate is used to support the microstructures on the textured surface. The height of the textured surface containing microstructures.

[0066]

[0067] In the above formula, The planar sliding trajectory of a finger on a textured surface is mathematically represented as: and With respect to time in two mutually perpendicular directions The parametric equation form. It refers to the finger swiping speed.

[0068] 1. Model building and simulation 1) Finger Model: Based on the fingertip parameters of the subjects in the personalized parameter measurement experiment, a multi-layered heterogeneous two-dimensional planar linear elastic body model was established, including the stratum corneum (5), epidermis (6), dermis (7), subcutaneous tissue (8), bone (9), and nail (10). Figure 2 As shown.

[0069] 2) Texture Model: Create two-dimensional texture profile models based on tactile interaction sliding trajectories under five different cycles.

[0070] 3) Electro-vibration tactile screen model: Create a two-dimensional cross-sectional model composed of different materials for the base layer, electrode layer, and dielectric layer.

[0071] 4) Simulation settings: Use ABAQUS finite element simulation (e.g., Figure 3 As shown) simulates a finger applying positive pressure with classic sliding contact (as shown). ) and different sliding speeds ( , , , , , , The normal and tangential contact force distributions at each moment are extracted by traversing various textured surfaces and electro-vibrating haptic screen surfaces.

[0072] 2. Drive signal calculation The spatiotemporal contact force data obtained from the simulation are input into an electrostatic pressure integral discretization model written in Python. Each integral element is as follows: Figure 4 As shown, it consists of conductive tissue of human fingertip, keratin layer of human fingertip, air layer, dielectric layer of electro-vibrating tactile screen, and electrode layer of electro-vibrating tactile screen.

[0073] Model electrical parameter settings: The dielectric layer of the electro-vibrating haptic screen is an optimized high-k material (thickness is...). The SiO2 layer); the electrode layer is The ITO layer.

[0074] After the algorithm runs, it outputs five sets of time-domain signals of the driving voltage corresponding to different periodic textures in the described tactile scenario. Figure 5 Five cyclical textures were demonstrated under normal pressure. Sliding speed is The interactive scenarios and the surface friction coefficient of the electro-vibrating tactile screen are The coefficient of friction of a real textured surface is The encoded information of the driving voltage waveform under friction conditions.

[0075] 3. System Setup and Experiment 1) Device fabrication: Based on the optimization results, a layer with a thickness of [thickness missing] was deposited on the glass substrate by magnetron sputtering. Indium tin oxide (ITO) is used as the electrode layer; then a layer with a thickness of [missing information] is deposited by electron beam evaporation. Silicon dioxide (SiO2) is used as the dielectric layer to complete the fabrication of the electro-vibrating tactile screen.

[0076] 2) Preparation of realistic texture samples: To reduce interference from other irrelevant factors, realistic texture samples are designed to be unidirectionally periodic, consistent with the two-dimensional profile of the texture model. The lattice-like morphology was fabricated using digital light processing (DLP) photopolymerization 3D printing (Mofang nanoArch S140), and the material was... Light yellow HTL resin for curing wavelengths.

[0077] 3) Experimental Design: a) Rendering scheme determination: Ten subjects were recruited to conduct a tactile perception threshold experiment to determine the optimal sliding speed for tactile perception of five rendered textures under the conditions of tactile reproduction on the electro-vibrating screen. Based on the experimental results, the optimal sliding speed was selected. This serves as a unified temporal reference frequency for haptic rendering of the five textures. Regarding amplitude parameter settings, the textures are configured according to this reference speed ( ) absolute threshold of tactile perception Adjustments were made to unify the tactile perception intensity of the five textures after tactile rendering.

[0078] b) Tactile reproduction performance test: Real texture tactile matching experiment and rendered texture tactile matching experiment were conducted on all subjects respectively.

[0079] c) Personalized haptic rendering test: Two subjects were selected, and the five textures mentioned above were used as experimental subjects. The test was conducted based on their fingertip information (fingert width). fingertip thickness fingerprint ridge width Personalized and non-personalized texture tactile rendering were performed, and the driving signals under the personalized and non-personalized rendering were used to conduct texture tactile matching experiments.

[0080] 4. Experimental Results 1) Objective performance of the device: such as Figure 7 As shown, the tactile perception threshold of electro-vibration significantly decreased after the dielectric layer optimization design, from Descending to The performance level is significantly lower than that of traditional designs. This result demonstrates the effectiveness of the established model and its guiding significance for the optimized design of dielectric layers.

[0081] 2) Tactile reproduction performance: The average tactile matching accuracy between the five rendered textures and the real textures reaches 83%, and the texture tactile reproduction effect is excellent.

[0082] 3) Personalized haptic rendering performance: For subjects using the personalized approach, the average haptic matching accuracy was improved by 20% to 30% compared to the non-personalized approach.

[0083] Example 2: Tactile Reproduction of General Realistic Complex Textures This example details the process and effect of applying the method of this invention to perform personalized texture tactile rendering for specific users and specific general complex realistic textures.

[0084] A commercial fabric was selected as an example of a general textured surface application.

[0085] 1. Model building and simulation 1) Finger Model: Based on the fingertip parameters of the subjects in the personalized parameter measurement experiment, a multi-layered heterogeneous two-dimensional planar linear elastic body model containing the stratum corneum, epidermis, dermis, subcutaneous tissue, bone, and nail was built in ABAQUS.

[0086] 2) Texture Model: The MN-1 surface topography analyzer was used to analyze the texture of a given square area ( The texture gradient curve of the fabric surface was measured. The tactile interaction sliding trajectory was chosen as a straight line parallel to the side length of the square. Finally, a two-dimensional texture profile model based on the tactile interaction sliding trajectory was obtained, as shown below. Figure 8 As shown.

[0087] 3) Electro-vibration tactile screen model: Create a two-dimensional cross-sectional model composed of different materials for the base layer, electrode layer, and dielectric layer.

[0088] 4) Simulation settings: Simulate a finger making a fixed sliding contact with a normal force ( ) and sliding speed ( The normal and tangential contact force distributions at each moment are extracted by traversing the textured surface and the electro-vibrating haptic screen surface.

[0089] 2. Drive signal calculation The spatiotemporal contact force data obtained from the simulation were input into an electrostatic pressure integral discretization model written in Python.

[0090] Model electrical parameter settings: The dielectric layer of the electro-vibrating haptic screen is an optimized high-k material (thickness is...). The SiO2 layer); the electrode layer is The ITO layer.

[0091] After the algorithm runs, it outputs the time-domain signal of the driving voltage corresponding to the texture in the tactile scenario described above. Figure 9 It shows that the positive pressure is Sliding speed is The interactive scenarios and the surface friction coefficient of the electro-vibrating tactile screen are The coefficient of friction of a real textured surface is The encoded information of the driving voltage waveform under friction conditions.

[0092] 3. System Setup and Experiment 1) Device fabrication: Based on the optimization results, a layer with a thickness of [thickness missing] was deposited on the glass substrate by magnetron sputtering. Indium tin oxide (ITO) is used as the electrode layer; then a layer with a thickness of [missing information] is deposited by electron beam evaporation. Silicon dioxide (SiO2) is used as the dielectric layer to complete the fabrication of the electro-vibrating tactile screen.

[0093] 2) Preparation of Realistic Texture Samples: To minimize interference from other irrelevant factors, realistic texture samples were designed with a grid-like morphology consistent with the two-dimensional cross-section of the texture model. They were prepared using digital light processing (DLP) photopolymerization 3D printing (Mofang nanoArch S140), and the material was... Light yellow HTL resin for curing wavelengths.

[0094] 3) Experimental Design: Ten volunteers were recruited to conduct a subjective evaluation of the tactile reproduction similarity of the general texture using a Likert scale.

[0095] 4. Experimental Results The average similarity between the general texture tactile rendering and the real texture sample is 75%. These experimental results demonstrate that the texture tactile rendering method proposed in this invention has excellent extension capabilities for general textures and a realistic tactile reproduction effect.

[0096] In summary, this invention provides a personalized texture tactile rendering method and system based on an electro-vibration friction physical model. Its core lies in constructing a complete, quantitative mapping chain from texture physical features to electrical signal drive: firstly, by establishing a personalized sliding friction physical model that integrates multiple variables, a precise mapping from texture geometry to tangential force is achieved; then, through an innovative electrostatic pressure integral discretization model, the corresponding driving voltage time-domain encoding is accurately solved. This end-to-end physical modeling fundamentally overcomes the limitations of traditional empirical "black box" mapping, enabling tactile reproduction to possess clear physical consistency and good interpretability. Based on this, this invention exhibits several significant advantages. By introducing personalized physiological and interaction parameters of the user, the system can provide customized rendering schemes for different users, different textures, and interaction scenarios, greatly improving the accuracy and realism of tactile reproduction. Simultaneously, the optimized design of key components (such as the dielectric layer) based on the physical model significantly reduces the system driving voltage and perception threshold, balancing high performance with low power consumption and high security. This method is not only applicable to periodic regular textures but can also be effectively extended to various complex random textures, exhibiting excellent versatility and scalability. Experimental results show that the average accuracy of this solution in tactile matching of various complex textures exceeds 80%, and the personalized solution can further improve this by more than 20%, which strongly demonstrates its effectiveness and advanced nature in improving the realism of texture tactile reproduction and user experience.

[0097] The main advantages of the embodiments of the present invention compared with the traditional technology are specifically reflected in the following aspects: 1. Traditional texture tactile rendering methods mostly rely on empirical mapping relationships, while this invention establishes and verifies for the first time a complete physical mapping chain from texture geometric features to electro-vibration driving signals. By constructing a personalized sliding friction physical model and an electrostatic pressure integral discretization model, the physical mechanism of the tactile reproduction process is restored, breaking through the limitations of existing technologies that rely on "black box" mapping.

[0098] 2. Significantly improved rendering realism. Experimental data shows that the average tactile matching accuracy of this invention for complex textures exceeds 80%. Especially in the reproduction of fine textures (period <1mm), by accurately simulating the vibration perception characteristics of fingerprints and the mechanical properties of skin, a tactile experience highly similar to that of real textures is achieved.

[0099] 3. Outstanding Personalization and Adaptation Capabilities. By incorporating user finger geometry parameters, biomechanical characteristics, and interactive behavior features, personalized customization of haptic rendering is achieved. Verification experiments show that the personalized approach can further improve the accuracy of haptic matching by 20%, effectively solving the user experience differences caused by the "one-size-fits-all" approach of traditional methods.

[0100] 4. Significant system performance optimization. Based on the guidance of the physical model, the dielectric layer of the electro-vibration device was optimized, reducing the driving voltage from the traditional 200V to below 50V and the sensing threshold to below 30V, which greatly improves the safety and energy efficiency of the device and creates conditions for integration into mobile devices.

[0101] 5. The algorithm has good versatility. The physical modeling framework proposed in this invention is not only applicable to periodic regular textures, but also, as verified by experiments, can be effectively extended to the tactile reproduction of random textures such as fabrics, demonstrating good versatility and extensibility.

[0102] The solution of this invention has good environmental adaptability and easy integration characteristics, and can be widely used in many fields: 1. Consumer electronics sector Suitable for consumer electronics products such as smartphones, tablets, and wearable devices, it can provide users with an enhanced interactive experience, such as realistic virtual keyboard tactile feedback, game vibration feedback, and haptic prompts for icon boundaries.

[0103] 2. Virtual Reality / Augmented Reality This technology enables the reproduction of tactile textures in virtual objects within VR / AR systems, allowing users to distinguish between different materials through touch and significantly enhancing immersion. It is particularly suitable for scenarios requiring material identification, such as virtual shopping and digital museums.

[0104] 3. Application of auxiliary technologies It provides visually impaired individuals with tactile representations of graphics and text, enabling tactile information transmission as a substitute for vision. It can be applied to assistive devices such as Braille displays and graphic tactile navigation devices.

[0105] 4. Industrial Design and Simulation In industrial design fields such as automotive interiors and home appliances, virtual evaluation of material effects can be achieved, reducing the cost of producing physical prototypes and accelerating the product development process.

[0106] 5. Remote operation and training It is applied to scenarios requiring precise tactile feedback, such as remote medical surgical robots and robots operating in hazardous environments, providing operators with a realistic sense of touch in the remote environment.

[0107] This invention demonstrates significant application value in industries such as robot grasping and recognition, automation, tactile reproduction, and virtual reality. By establishing a physical mechanism model, it fills a technological gap in the field of electro-vibration tactile rendering, creating a technological leap from traditional methods. It combines low voltage and high realism, particularly meeting the dual demands of safety and user experience in consumer electronics, and has broad application prospects. Its application in assistive technology also helps improve the information acquisition capabilities of visually impaired individuals, while its application in industrial design helps reduce the consumption of physical samples, aligning with the trend of green manufacturing.

[0108] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various equivalent substitutions or obvious modifications can be made without departing from the concept of the present invention, and all such modifications, achieving the same performance or application, should be considered within the scope of protection of the present invention.

Claims

1. A personalized texture tactile rendering method based on an electro-vibration tribology physical model, characterized in that, Includes the following steps: S1. Construction of a personalized sliding friction physical model: Construct a multi-layered heterogeneous two-dimensional finger linear elastic body model and a two-dimensional texture model. Analyze the sliding process of the finger on the texture surface through finite element simulation. Establish a personalized sliding friction physical model that integrates texture geometric features, fingertip physiological parameters, normal pressure and sliding speed to achieve a quantitative mapping from texture geometric features to tangential friction force. S2. Solving the electro-vibration driving signal: Establish the mapping relationship between the personalized sliding friction physical model and the electro-vibration electrostatic force; based on the effective contact area of ​​the fingertip, construct a discretized model of electrostatic pressure integral to quantify the electrostatic force generated by the electro-vibration device; input the contact spatiotemporal information extracted by finite element simulation and the parameters of the electro-vibration device into the discretized model to calculate the temporal coding information of the driving voltage required for texture tactile rendering; S3. Tactile Reproduction: The driving voltage time-domain encoded information obtained in step S2 is applied to the electro-vibration device to drive it to work and modulate the friction between the fingertip and the device surface, thereby reproducing the tactile perception of the target texture.

2. The method according to claim 1, characterized in that, In step S1, the personalized sliding friction physical model is constructed in the following way: an equivalent mapping relationship of friction behavior under two contact scenarios, namely, a real textured surface and a tactile screen surface, is established so that the tangential friction force is equal in the two scenarios; the mapping relationship is realized by associating the time-varying friction coefficient and normal force of the textured surface with the electrostatic force, normal force and fixed friction coefficient of the tactile screen surface, wherein the time-varying friction coefficient is a function of the finger sliding path and sliding speed.

3. The method according to claim 1, characterized in that, In step S2, the discretization model of the electrostatic pressure integral is constructed and processed in the following manner: The time-varying effective contact area between the fingertip and the surface of the tactile screen is divided into multiple discrete micro-elements in the spatiotemporal domain. The electrostatic pressure calculation model for each micro-element correlates the applied voltage, the area facing the micro-element, and the equivalent capacitance distance composed of the thickness and dielectric constant of the fingertip cuticle, air gap, and tactile screen dielectric layer. By summing the electrostatic pressure contributions of all infinitesimal elements at discrete moments, the macroscopic electrostatic force acting on the fingertip at that moment can be calculated.

4. The method according to claim 1, characterized in that, The method further includes a step S0: personalized parameter input, which involves measuring the two-dimensional geometric dimensions of the user's fingertip and the width of the fingerprint ridge through image processing, and obtaining frictional behavior parameters related to the sliding speed through a passive touch tactile measurement experiment, and inputting the parameters into the personalized sliding friction physical model in step S1.

5. The method according to claim 1, characterized in that, The method is applicable to the tactile reproduction of periodic regular textures and non-periodic complex textures, wherein the geometric features of the complex textures are acquired by a surface topography measuring instrument and converted into a two-dimensional texture profile model based on the tactile interaction sliding trajectory.

6. The method according to claim 2 or 3, characterized in that, The specific steps for solving the time-domain encoded information of the driving voltage in step S2 are as follows: The electrostatic force that needs to be introduced on the surface of the touch screen to achieve the target tangential friction force, as determined by the equivalent mapping relationship in step S1, is used as the target output of the electrostatic pressure integral discretization model. Based on the discretized model, combined with the information on the facing area of ​​each micro-element, the thickness of the fingertip keratin layer and air layer, which vary with time and are extracted from the finite element simulation, and the fixed structural parameters of the electro-vibrating device, the driving voltage signal that can generate the target electrostatic force is solved in reverse as it varies with time.

7. A personalized texture tactile reproduction system implementing the method as described in any one of claims 1-6, characterized in that, include: The personalized model parameter calculation module is used to obtain the user's personalized physiological parameters and friction behavior parameters of the fingertips; The texture rendering calculation module is connected to the personalized model parameter calculation module and is used to receive the personalized parameters and perform the construction of the personalized sliding friction physical model, finite element simulation and the calculation of the driving voltage time domain encoding information. The tactile reproduction interaction module, connected to the texture rendering calculation module, includes a host computer, a signal generator, a voltage amplifier, and an electro-vibrating tactile screen connected in sequence, used to receive the driving voltage time-domain encoded information and generate corresponding tactile stimuli.

8. The system according to claim 7, characterized in that, The personalized model parameter calculation module includes: An electronic 3D microscope under-microscopic measurement system is used to acquire fingertip images and obtain fingertip geometric parameters through image processing algorithms; A force-based passive touch tactile measurement system is used to measure the tangential frictional force between the fingertip and a textured sample under controlled positive pressure and sliding speed in order to obtain frictional behavior parameters.

9. The system according to claim 7, characterized in that, The texture rendering calculation module includes: The simulation unit is used to perform finite element mechanical simulation of the multilayer heterogeneous finger model and texture model during the sliding process; The data extraction unit is used to automatically extract spatiotemporal information of the contact area and pressure distribution from the simulation results; The algorithm solution unit is used to run the electrostatic pressure integral discretization model, receive the spatiotemporal domain information and device parameters, and execute the reverse solution algorithm for the driving voltage time-domain encoded information.

10. The system according to claim 7, characterized in that, The electro-vibrating tactile screen comprises, from bottom to top, a substrate layer, an electrode layer, and a dielectric layer; wherein the dielectric layer is a dielectric material layer with a thickness of 100-1000 nm, and the electrode layer is a conductive material layer with a thickness of 100-500 nm.

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