Multi-modal high-precision terrain interaction system based on tactile feedback and fuzzy logic

Abstract

The invention provides a multi-mode high-precision terrain interaction system based on tactile feedback and fuzzy logic, when a user touches the surface of a sensor by fingers, a piezoresistive sensor records pressure position and intensity information in real time, and an upper computer adopts a super-resolution algorithm to filter and compensate original data. And after two-dimensional funnel effect and fuzzy logic calculation, the platform adjusts feedback amplitudes and frequencies of the LRA at four corners in real time, and accurately simulates topographic features at a touch position. A two-dimensional interface on the upper computer displays touch points and corresponding tactile feedback parameters in real time, a user can adjust touch actions in real time according to feedback, and the accurate and efficient multi-mode terrain interaction effect is experienced.

Description

Technical Field

[0001] The present invention belongs to the fields of human-computer interaction technology and virtual reality technology, and specifically relates to a multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic. Background Art

[0002] Currently, traditional visual mapping technology is widely used in fields such as navigation, planning, and education. However, with the rapid development of remote sensing technology and the rapid increase in terrain data, traditional two-dimensional visual maps have shown significant shortcomings when processing high-precision three-dimensional terrain data. Due to data simplification, visual maps struggle to accurately capture the details of complex terrain, resulting in significant spatial distortion, which makes it difficult for users to analyze and utilize high-precision geographic data. Furthermore, traditional maps are primarily visual, neglecting the interactive experience of other senses. This limits users' ability to understand complex terrain features or in scenarios requiring high precision. Although multimodal mapping technology, particularly tactile mapping, has been gradually applied to geographic information systems in recent years, traditional tactile feedback technology often faces challenges such as high hardware complexity, insufficient feedback accuracy, and poor real-time performance. These issues make tactile feedback ineffective in practical applications, preventing users from quickly and accurately perceiving complex terrain details and meeting the requirements for high-precision geographic information interaction. Furthermore, existing tactile mapping technologies generally lack intelligent feedback mechanisms and are unable to dynamically customize the tactile experience based on different terrain characteristics, limiting their practical application in a wider range of fields. Summary of the Invention

[0003] The purpose of the present invention is to provide a high-precision terrain interaction system based on tactile feedback and fuzzy logic algorithm to solve the problems of spatial distortion and information simplification when traditional visual maps display high-precision terrain data, and to make up for the shortcomings of traditional tactile feedback technology in accuracy and interactivity.

[0004] The present invention discloses a multi-modal high-precision terrain interaction system based on tactile feedback and fuzzy logic, which includes a 16×16 piezoresistive array flexible thin film pressure sensor, a linear resonant actuator, and a host computer;

[0005] The 16×16 piezoresistive array flexible thin film pressure sensor is used to collect pressure distribution and position data when the user touches the sensor in real time;

[0006] The host computer has a two-dimensional terrain visualization interface, which combines the synchronously loaded digital elevation model data to extract multi-dimensional terrain features such as altitude, slope, and roughness under the contact point; based on the fuzzy logic algorithm, it makes rule judgments on the multi-dimensional terrain features and calculates the feedback amplitude of the linear resonant actuator;

[0007] The linear resonant actuators are arranged at four corners of the system to provide haptic feedback according to feedback amplitude.

[0008] Further, the 16x16 array sensor captures the pressure distribution on the touch surface, and then reconstructs the original data by using a super-resolution method combining interpolation and adaptive filtering:

[0009] Linear interpolation is performed on the values of the two horizontal lines in the x direction, and on the y=y1 horizontal line, there is:

[0010]

[0011] R1 represents the result of linear interpolation in the y=y1 direction, x2 represents the x-axis coordinate of the right known point, x1 represents the x-axis coordinate of the left known point, x represents the x-axis coordinate of the target point to be interpolated, Q 11 represents the sampling value of the coordinate (x1, y1), Q 21 represents the sampling value of the coordinate (x2, y1);

[0012] On the y=y2 horizontal line, there is:

[0013]

[0014] R2 represents the result of linear interpolation in the y=y2 direction, Q 12 represents the sampling value of the coordinate (x1, y2), Q 22 represents the sampling value of the coordinate (x2, y2);

[0015] Linear interpolation is performed again on the above two intermediate values R1 and R2 in the y direction, and the interpolation result W mn is finally obtained at any m, n:

[0016]

[0017] y2 represents the y-axis coordinate of the upper known point, y1 represents the y-axis coordinate of the lower known point, and y represents the y-axis coordinate of the target point to be interpolated; x m represents the x-coordinate of the sensor contact point after two interpolations, y n represents the y-coordinate of the sensor contact point after two interpolations;

[0018] The high-resolution pressure field P SR obtained after reconstruction is:

[0019]

[0020] P(m, n) is a 16x16 array sensor capturing the pressure distribution on the touch surface, where m = 1, 2, …, 16; n = 1, 2, …, 16.

[0021] Further, the host computer calculates the pressure center of the contact area:

[0022]

[0023] where C(t) = (x c ,y c ) represents the pressure center of the contact area, the positions x c and y c are obtained by weighted average of each coordinate on the sensor grid, respectively;

[0024] By smoothing the change of the pressure center in consecutive frames, and using the adjacent time interval to calculate its motion speed:

[0025]

[0026] v(t) represents the motion speed, and Δt represents the adjacent time interval.

[0027] Further, the host computer can accurately position and modulate each vibration touch point in the array sensor through the two-dimensional funnel illusion, and by adjusting the vibration amplitude, the vibration is concentrated to a highly concentrated virtual vibration point. The output of the linear resonant actuator is:

[0028]

[0029] A represents the target intensity of the virtual actuator, D x and D y are the maximum horizontal and vertical distances between multiple linear resonant actuators, and are the horizontal and vertical distances from the actuator A k to the target position A, A k (k = 1, 2, 3, 4) represents the feedback of the kth linear resonant actuator.

[0030] Further, the target intensity of the virtual actuator uses Perlin Noise as a modulation means, and introduces an internal noise modulation factor α to quantitatively describe the influence of noise on the final vibration signal. The entire feedback function is as follows:

[0031] A(i, j) = A2(i, j) · [1 + αN(x, y)]

[0032] A(i,j) represents the target strength of the virtual actuator, A2(i,j) represents the compensation altitude function, N(x,y) represents the Perlin noise function, and α represents the internal noise modulation factor.

[0033] Furthermore, the host computer implements dynamic weight allocation through a fuzzy rule base based on T-norm aggregation operation, performs multi-dimensional reasoning based on roughness r, terrain slope s, and real-time speed v, and uses the center method to defuzzify the combined reasoning results to generate the noise modulation factor α:

[0034] α=w r r(i,j)+w s s(i,j)+w v v(i,j)

[0035] r(i,j) is the roughness of coordinate i,j, s(i,j) is the slope of terrain at coordinate i,j, v(i,j) is the real-time speed at coordinate i,j, w r Represents the weight of roughness, w s Represents the weight of terrain slope, w v Indicates the coordinate real-time speed weight.

[0036] Furthermore, to address the issue of the logarithmic curve changing too slowly at high altitudes, a smooth transition strategy based on linear growth is introduced at high altitudes. This allows the system to provide clearer representation when dealing with medium-height hills and towering mountains, resulting in the compensated altitude function A2(i,j):

[0037] A2(i,j)=A1(i,j)+λ[h(i,j)-h th ]

[0038] A1(i,j)=log(1+h(i,j))

[0039] A1(i,j) represents the elevation function, h(i,j) represents the basic altitude information, h th High altitude benchmark value;

[0040] λ represents the altitude judgment function, when h th >h(i,j) when λ=0, if h th <h(i,j)时λ=1。

[0041] The beneficial effects achieved by the present invention are:

[0042] In response to the complex structure and high hardware stacking of traditional terrain tactile systems, the present invention achieves a simplified design and low-cost deployment. Traditional tactile mapping systems typically rely on large-scale actuator arrays and dedicated hardware platforms, resulting in bulky equipment, complex wiring, high assembly and maintenance costs, and difficulty in adapting to portable or embedded scenarios. Through a modular design, the present invention relies only on a 16×16 flexible pressure array and four LRA actuators, combined with lightweight host computer control logic, to achieve high-precision restoration of complex terrain. This structure not only significantly reduces the number of physical components and reduces system complexity, but also facilitates rapid deployment, expansion, and maintenance, making it suitable for diverse application needs such as education, science popularization, and field demonstrations.

[0043] In response to the need to add a large number of actuators to improve resolution in traditional systems, the present invention uses two-dimensional funnel illusion technology to efficiently achieve fine spatial tactile feedback. In order to improve spatial resolution, most terrain tactile simulation platforms need to deploy a large number of physical tactile output units in a limited area, resulting in system congestion and dense wiring. The present invention innovatively introduces a two-dimensional funnel illusion mechanism. By coordinating and controlling a small number of LRA amplitudes and phases, multiple virtual tactile points are synthesized between the actuators, significantly improving spatial resolution while reducing hardware requirements. This method not only achieves precise positioning and continuously changing vibration simulation, but also enhances the user's directional perception and tactile immersion experience.

[0044] In view of the fact that traditional feedback systems have delayed responses and are unable to reflect subtle terrain differences, the present invention has high real-time performance and fine amplitude control capabilities. Traditional systems generally have problems with processing delays and slow feedback when facing large-area terrain or high-frequency interactions, and are particularly weak in expressing complex terrain details. The present invention uses a highly sensitive flexible sensor array for multi-point parallel acquisition, and combines a fuzzy logic judgment mechanism with Perlin noise modulation to achieve dynamic and progressive amplitude output. The system has a short response time and a natural tactile transition. It can capture and feedback tiny differences in terrain undulations, greatly enhancing the immediacy of interaction and the natural perception experience.

[0045] This invention addresses the limitations of traditional terrain feedback devices, which are often limited to static models or standard interfaces, lack flexible interactive feedback mechanisms, and require users to rely on specialized knowledge for operation. This invention integrates a visual map with a tactile feedback interface, providing a touch-to-response experience and allowing users to adjust feedback intensity and terrain analysis mode based on their preferences. The entire system offers a user-friendly interface and simple operation, requiring no specialized knowledge for quick learning. It is particularly suitable for applications such as education, assisted perception, and virtual navigation, providing a natural and intuitive interaction experience for diverse user groups. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 For: system structure diagram;

[0047] Figure 2Fig. 1 is a schematic diagram of a system tactile simulation map;

[0048] Figure 3 Fig. 2 is a schematic diagram of a system array sensor interpolation;

[0049] Figure 4 Fig. 3 is a schematic diagram of a system array sensor;

[0050] Figure 5 Fig. 4 is a schematic diagram of a system dynamic noise composition;

[0051] Figure 6 Fig. 5 is a schematic diagram of a system feedback. DETAILED DESCRIPTION

[0052] The present application will be further described below in conjunction with specific embodiments, and the advantages and features of the present application will become more apparent as the description proceeds. However, these embodiments are merely exemplary, and do not constitute any limitation on the scope of the present application. Those skilled in the art should understand that modifications or substitutions can be made to the details and forms of the technical solutions of the present application without departing from the spirit and scope of the present application, and such modifications and substitutions all fall within the protection scope of the present application.

[0053] As Figure 1 described above, the present application provides a multi-modal high-precision terrain interaction system based on tactile feedback and fuzzy logic, which comprises a 16x16 piezoresistive array flexible film pressure sensor, an upper computer and a linear resonant actuator.

[0054] As Figure 2-3 described above, the 16x16 piezoresistive array flexible film pressure sensor can collect pressure distribution and position data in real time when a user touches, and realize high-precision tactile information collection. The 16x16 array sensor captures the pressure distribution P(m, n) (wherein m=1, 2, …, 16; n=1, 2, …, 16) on the touch surface, and then uses an interpolation combined with adaptive filtering super-resolution method to reconstruct the original data, thereby significantly improving the system's ability to capture dynamic motion and ensuring real-time response.

[0055] According to the four reference points (x1, y1), (x1, y2), (x2, y1), (x2, y2) sampled, linear interpolation is performed on the values of the two horizontal lines in the x direction, and on the y=y1 horizontal line, there is:

[0056]

[0057] R1 represents the result of linear interpolation in the y=y1 direction, x2 represents the x-axis coordinate of the right known point, x1 represents the x-axis coordinate of the left known point, x represents the x-axis coordinate of the target point to be interpolated, Q 11Represents the sampling value of the coordinate (x1, y1), Q 21 Represents the sample value of coordinate (x2, y1);

[0058] On the horizontal line y=y2, we have:

[0059]

[0060] R2 represents the result of linear interpolation in the y=y2 direction, Q 12 Represents the sampling value of the coordinate (x1, y2), Q 22 Represents the sampling value with coordinates (x2, y2);

[0061] Perform another linear interpolation on the two intermediate values ​​R1 and R2 along the y direction, and finally obtain the interpolation result W at any m and n. mn :

[0062]

[0063] y2 represents the y-axis coordinate of the known point above, y1 represents the y-axis coordinate of the known point below, and y represents the y-axis coordinate of the target point that needs to be interpolated; x m Indicates the x coordinate and y coordinate of the sensor contact point after two interpolations n Indicates the y coordinate of the sensor contact point after two interpolations;

[0064] The high-resolution pressure field P obtained after reconstruction SR (x,y) can more accurately reflect subtle changes during touch.

[0065]

[0066] P(m,n) is a 16×16 array sensor that captures the pressure distribution on the touch surface, where m=1, 2, …, 16 and n=1, 2, …, 16.

[0067] The host computer has a two-dimensional terrain visualization interface that can display the user's touch location and pressure intensity in real time; at the same time, the host computer is responsible for data reception and processing, using a super-resolution algorithm to filter and compensate tactile data, improving the real-time and accuracy of tactile feedback, and collaborating with Arduino to achieve precise control and synchronous output of tactile feedback signals.

[0068] The 16×16 piezoresistive array flexible thin film pressure sensor and the linear resonant actuator communicate with the host computer in real time through a serial interface.

[0069] like Figure 4 In order to further track the touch trajectory, the host computer calculates the pressure center C(t) of the contact area = (x c ,yc )(where position x c and y c are obtained by the weighted average of each coordinate on the sensor grid).

[0070]

[0071] By smoothing the changes in the center of pressure in consecutive frames and calculating its movement speed v(t) using the adjacent time interval Δt, the platform achieves accurate tracking of fast movements and thus perceives more subtle tactile changes.

[0072]

[0073] With the help of this data processing process, the sensor grid with originally limited resolution can output high-resolution tactile feedback, allowing users to clearly perceive detailed features such as tiny bumps and slope differences on the surface.

[0074] The host computer combines the synchronously loaded digital elevation model (DEM) data to extract multi-dimensional terrain features such as altitude, slope, and roughness under the contact point.

[0075] As the foundation for haptic feedback generation, DEM data processing is crucial. With advancements in hardware performance and ongoing theoretical research, the generated DEM data not only includes basic elevation information h(i, j) but also incorporates rich geographic features such as slope s(i, j) and roughness r(i, j). To fully utilize this multi-layered geographic information, it is integrated into a multidimensional matrix, providing more accurate foundational data for haptic feedback.

[0076] When rendering tactile altitude, a logarithmic curve growth and Perlin Noise dynamic modulation are used to better reflect the changes in terrain undulations. This is closely related to human perception mechanisms and the distribution of terrain features. According to the Weber-Fechner law, the intensity of human perception of physical stimuli is proportional to the logarithm of the actual physical quantity. This means that when perceiving altitude changes, a logarithmic curve can better align with the human perception of altitude differences. In this way, larger altitude differences will not lead to excessive exaggeration of tactile amplitude, while smaller altitude differences can be more effectively perceived, thereby improving the recognition of complex terrain details.

[0077] Altitude function:

[0078] A1(i,j)=log(1+h(i,j))

[0079] At the same time, to solve the problem of the logarithmic curve changing too slowly in high-altitude areas, a smooth transition strategy based on linear growth is introduced in high-altitude areas. This enables the system to provide clearer expression when dealing with medium-height hills and towering mountains, and obtains the compensated altitude function A2(i,j):

[0080] A2(i,j)=A1(i,j)+λ[h(i,j)-h th ]

[0081] h(i,j) represents the altitude information, h th Altitude reference value; λ represents the altitude judgment function, when h th >h(i,j) when λ=0, if h th <h(i,j)时λ=1。λ用于调节高低海拔之间的触觉渲染差异,h th Used to distinguish high-altitude areas from low-altitude areas for tactile rendering, and can generally be set to 500m.

[0082] In the final configuration of the haptic system, a fuzzy logic system was used to dynamically adjust the weighting relationships between roughness, slope, and speed, enabling it to flexibly cope with nonlinear changes between parameters and provide a smooth tactile transition. To this end, we adopted a parameter grading method, dividing each input parameter into multiple membership levels, as shown in the following table:

[0083]

[0084]

[0085] In the process of generating the final amplitude, the host computer implements dynamic weight allocation through a fuzzy rule base based on T-norm aggregation operation, performs multi-dimensional reasoning based on roughness r, terrain slope s, and real-time speed v, and uses the center of gravity method (COA) to defuzzify the combined reasoning results to generate the noise modulation factor α.

[0086] α=w r r(i,j)+w s s(i,j)+w v v(i,j)

[0087] w r Represents the weight of roughness, w s Represents the weight of terrain slope, w v Indicates the coordinate real-time speed weight.

[0088] By nonlinearly fusing the multi-scale noise signal output by Perlin Noise with the initial amplitude, the system not only fully preserves the macroscopic structural characteristics of terrain elevation, but also better restores microscopic topographic details through noise modulation. This dual analysis mechanism enables tactile feedback to simultaneously achieve strong recognition of terrain contours and high perception accuracy of surface textures, significantly enhancing the physical realism and cognitive consistency of terrain feedback in virtual interactive scenarios.

[0089] like Figure 5 As shown, in the dynamic simulation of tactile feedback, the present invention adopts Perlin Noise as a modulation method, and introduces an internal noise modulation factor α to quantitatively describe the impact of noise on the final vibration signal. As a gradual noise model, Perlin Noise has the advantage of being able to maintain smoothness of changes locally and continuity globally, which gives it a high degree of realism when simulating natural terrain features. Therefore, Perlin Noise has been widely used in the fields of computer graphics and virtual terrain generation. Introducing it into the tactile feedback system can effectively suppress the sudden changes in tactile perception caused by random noise, ensure the consistency and naturalness of vibration feedback, and thus provide a smoother and more realistic tactile experience. At this time, the target strength of the virtual actuator is as follows:

[0090] A(i,j)=A2(i,j)·[1+αN(x,y)]

[0091] N(x,y) represents the Perlin noise function.

[0092] Utilizing the two-dimensional funnel tactile principle, by precisely controlling the amplitude and phase of four linear resonant actuators (LRAs), multiple virtual tactile points are generated between the actuators to achieve high-density spatial feedback.

[0093] For tactile feedback, the system utilizes vibration modulation technology based on a two-dimensional funnel illusion. This 2D funnel illusion allows the system to precisely locate and modulate each vibrating contact point in the sensor array, adjusting the vibration amplitude to focus the vibration on a highly concentrated virtual vibration point. This not only improves the spatial resolution of tactile feedback but also enables the system to provide a rich tactile experience with minimal hardware. The platform is equipped with four LRAs located at the four corners of the platform, generating sinusoidal vibrations at a frequency of 170Hz, to which humans are most sensitive.

[0094] Regarding the vibrancy rendering of the funnel illusion, there are two rendering methods for the 2D funnel illusion: linear rendering and logarithmic rendering. Research has shown that there is little difference in perceptual accuracy between the two, but logarithmic rendering provides higher spatial resolution and performs better in estimating the illusion's strength. This also meets the requirements for simulating complex terrain structures, which require high spatial perception and strength, so logarithmic rendering is chosen. The specific rendering method is as follows:

[0095]

[0096] like Figure 6 As shown in the formula, A in the formula represents the target strength of the virtual actuator, the value range of k is (1 to 4), and A k (k=1,2,3,4) represents the amplitude that the four actuators need to generate. x and D y is the maximum horizontal and vertical distance between several physical actuators, and Actuator A k The horizontal and vertical distances to the target position A. Using this formula, the amplitudes that the four LRAs need to generate can be accurately calculated to generate the desired tactile feedback.

[0097] The multimodal, high-precision terrain interaction system also includes four linear resonant actuators (LRAs) installed at the four corners of the platform. The LRAs use PWM drive and the operating frequency is set at 170Hz to provide accurate and sensitive tactile feedback.

[0098] Finally, the tactile signal is transmitted to the actuator via PWM modulation, driven at a 170Hz frequency, allowing users to realistically perceive complex terrain changes on the touch interface. The entire system is compact and responsive, significantly improving the accuracy and immersiveness of tactile interaction. It is suitable for a variety of high-precision geographic information interaction scenarios, such as remote sensing data analysis, assisted navigation, and disaster simulation.

[0099] The above are only specific steps of the present invention and do not constitute any limitation to the scope of protection of the present invention; any technical solutions formed by equivalent transformation or equivalent replacement fall within the scope of protection of the present invention; the parts not elaborated in detail in the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic, characterized by: The multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic includes a 16×16 piezoresistive array flexible thin film pressure sensor, a linear resonant actuator and a host computer; The 16×16 piezoresistive array flexible thin film pressure sensor is used to collect pressure distribution and position data when the user touches the sensor in real time; The host computer has a two-dimensional terrain visualization interface, which combines the synchronously loaded digital elevation model data to extract multi-dimensional terrain features such as altitude, slope, and roughness under the contact point; Based on the fuzzy logic algorithm, the multi-dimensional terrain features are judged according to the rules and the feedback amplitude of the linear resonant actuator is calculated. The linear resonant actuators are arranged at the four corners of the system and are used to provide tactile feedback according to the feedback amplitude.

2. The multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic according to claim 1, characterized in that: The 16×16 array sensor captures the pressure distribution on the touch surface, and then uses a super-resolution method combining interpolation and adaptive filtering to reconstruct the original data: Perform linear interpolation on the values ​​on the two horizontal lines along the x direction, and on the y=y1 horizontal line: R1 represents the result of linear interpolation in the direction of y=y1, x2 represents the x-axis coordinate of the known point on the right, x1 represents the x-axis coordinate of the known point on the left, x represents the x-axis coordinate of the target point to be interpolated, Q 11 Represents the sampling value of the coordinate (x1, y1), Q 21 Represents the sample value of coordinate (x2, y1); On the horizontal line y=y2, we have: R2 represents the result of linear interpolation in the y=y2 direction, Q 12 Represents the sampling value of the coordinate (x1, y2), Q 22 Represents the sampling value with coordinates (x2, y2); Perform another linear interpolation on the two intermediate values ​​R1 and R2 along the y direction, and finally obtain the interpolation result W at any m and n. mn : y2 represents the y-axis coordinate of the known point above, y1 represents the y-axis coordinate of the known point below, and y represents the y-axis coordinate of the target point that needs to be interpolated; x m Indicates the x coordinate and y coordinate of the sensor contact point after two interpolations n Indicates the y coordinate of the sensor contact point after two interpolations; The high-resolution pressure field P obtained after reconstruction SR (x,y) is: P(m,n) is a 16×16 array sensor that captures the pressure distribution on the touch surface, where m=1, 2, …, 16 and n=1, 2, …, 16.

3. The multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic according to claim 2, characterized in that: The host computer calculates the pressure center of the contact area: Where C(t)=(x c ,y c ) represents the pressure center of the contact area, position x c and y c They are obtained by the weighted average of each coordinate on the sensor grid; By smoothing the changes in the center of pressure in consecutive frames and calculating its movement speed using adjacent time intervals: v(t) represents the speed of movement, and Δt represents the time interval between adjacent times.

4. The multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic according to claim 1, characterized in that: The host computer can accurately locate and modulate each vibrating contact in the array sensor through the two-dimensional funnel illusion. By adjusting the vibration amplitude, the vibration is concentrated to a highly concentrated virtual vibration point. The output of the linear resonant actuator is: A represents the target strength of the virtual actuator, D x and D y is the maximum horizontal and vertical distance between multiple linear resonant actuators, and Actuator A k The horizontal and vertical distances to the target position A, A k (k=1, 2, 3, 4) represents the feedback of the kth linear resonant actuator.

5. The multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic according to claim 4 is characterized in that: The target strength of the virtual actuator uses Perlin Noise as a modulation method, and an internal noise modulation factor α is introduced to quantitatively describe the impact of noise on the final vibration signal. The entire feedback function is as follows: A(i,j)=A2(i,j)·[1+αN(x,y)] A(i,j) represents the target strength of the virtual actuator, A2(i,j) represents the compensation altitude function, N(x,y) represents the Perlin noise function, and α represents the internal noise modulation factor.

6. The multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic according to claim 5, characterized in that: The host computer implements dynamic weight allocation through a fuzzy rule base based on T-norm aggregation operation, performs multi-dimensional reasoning based on roughness r, terrain slope s, and real-time speed v, and uses the center method to defuzzify the combined reasoning results to generate the noise modulation factor α: α=w r r(i,j)+w s s(i,j)+w v v(i,j) r(i,j) is the roughness of coordinate i,j, s(i,j) is the terrain slope of coordinate i,j, b(i,j) is the real-time speed of coordinate i,j, w r Represents the weight of roughness, w s Represents the weight of terrain slope, w v Indicates the coordinate real-time speed weight.

7. The multimodal high-precision terrain interaction system based on tactile feedback and fuzzy logic according to claim 5, characterized in that: To address the issue of the logarithmic curve changing too slowly in high-altitude areas, a smooth transition strategy based on linear growth is introduced in high-altitude areas. This allows the system to provide clearer expression when dealing with medium-height hills and towering mountains, resulting in the compensated altitude function A2(i,j): A2(i,j)=A1(i,j)+λ[h(i,j)-h th ] A1(i,j)=log(1+h(i,j)) A1(i,j) represents the elevation function, h(i,j) represents the basic altitude information, h th High altitude benchmark value; Let λ denote the altitude judgment function, where λ = 0 when h th > h(i, j), and λ = 1 when h th < h(i, j).

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