High-density tactile sensing array and method based on bionic microstructure

Abstract

A high-density tactile sensing array based on a bionic microstructure comprises a flexible substrate for providing mechanical flexibility and packaging protection; the bionic microstructure layer is composed of a pyramid array or a hemisphere array and is used for enhancing sensitivity and spatial resolution; the carbon nanotube (CNT) sensitive layer uniformly covers the surface of the microstructure and converts pressure change into an electric signal; according to the thin film transistor signal reading system, active matrix design is adopted, pixel-level signal extraction is achieved through a row-column addressing strategy, and electric signals are rapidly and accurately processed. According to the preparation method, photoetching, wet etching and hot reflux processes are combined, precision machining of a microstructure is achieved, and a uniform CNT sensitive layer is formed through a spraying technology. According to the design method, microstructure parameters and sensitive layer characteristics are optimized through equivalent circuit model construction and simulation verification, and collaborative optimization of high sensitivity and wide dynamic range is achieved. The invention has the advantages of high sensitivity, high spatial resolution, low crosstalk, quick response and the like.

Description

Technical Field

[0001] The present invention relates to the field of tactile sensing technology, and particularly to a high-density tactile sensing array and method based on bionic microstructures. Background Art

[0002] Tactile sensing is crucial in robotics, prosthetics, and human-machine interfaces. However, existing sensors struggle to meet the high spatial resolution and sensitivity required for fine texture recognition. Traditional flexible sensors suffer from issues such as low sensitivity, limited dynamic range, and signal crosstalk, making it impossible to reliably detect micron-scale texture differences. For example, existing tactile sensors are prone to interference from adjacent units when detecting textures below 500μm and are insufficient in terms of high sensitivity and wide pressure range. Additionally, the manufacturing processes of existing sensors are complex, making it difficult to achieve precise machining of bionic microstructures, which limits their applications in fields such as robotic operation and medical diagnosis.

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

[0004] The main objective of the present invention is to overcome the defects existing in the above background art, and to provide a high-density tactile sensing array based on bionic microstructures and its design and preparation method, so as to solve the problems of insufficient sensitivity, low spatial resolution, and serious signal crosstalk in the prior art.

[0005] To achieve the above objective, the present invention adopts the following technical solutions:

[0006] A high-density tactile sensing array based on bionic microstructures, comprising:

[0007] A flexible substrate (1) for providing mechanical flexibility and encapsulation protection;

[0008] A bionic microstructure layer (2) disposed on the flexible substrate (1), composed of a pyramid array or a hemisphere array;

[0009] A carbon nanotube (CNT) sensitive layer (3) uniformly covering the surface of the bionic microstructure layer (2) for converting pressure changes into electrical signals;

[0010] A thin-film transistor (TFT) signal reading system (4) integrated on the flexible substrate (1), adopting an active matrix design and achieving pixel-level signal extraction through a row-column addressing strategy to read and process the electrical signals generated by the CNT sensitive layer (3).

[0011] A preparation method for the high-density tactile sensing array as described above, comprising the following steps:

[0012] S1. Preparation of the bionic microstructure layer (2): Form a pyramid array on the substrate through photolithography and etching processes, or form a hemisphere array through photolithography combined with a thermal reflux process;

[0013] S2. Formation of the CNT sensitive layer (3): Uniformly spray the carbon nanotube dispersion on the surface of the bionic microstructure layer (2), and preferably add polyvinyl alcohol (PEO) to inhibit the coffee ring effect;

[0014] S3. Integration of the TFT signal reading system (4): Bond and package the thin-film transistor array designed with an active matrix with the CNT sensitive layer (3);

[0015] S4. Assembly of the flexible substrate (1): Integrate the bionic microstructure layer (2), the CNT sensitive layer (3), and the TFT signal reading system (4) on the flexible substrate to complete the preparation of the sensing array.

[0016] A design method for the high-density tactile sensing array described above includes the following steps:

[0017] A1. Construction of a simulation model:

[0018] Establish an inverse relationship model between the contact resistance R and the contact area A: R ∝ 1 / A;

[0019] Based on the relationship between the pressure P and the contact area A: P = F / A, construct a pressure-contact area conversion model;

[0020] Combined with the relationship between the current I and the resistance: I = U / R, establish a theoretical model for the sensitivity S: S = (ΔI / I0) / ΔP; where, I0 represents the output current value of the sensor in the initial zero-pressure state, ΔI = I - I0 is the current change amount, where I is the measured current after applying pressure, and ΔP is the applied pressure change amount;

[0021] A2. Verification by actual measurement of samples:

[0022] Apply a given pressure to the prepared sensing array sample and measure the change in the output current;

[0023] Calculate the actual sensitivity curve based on the measured current-pressure data;

[0024] Compare and analyze the measured data with the prediction results of the simulation model;

[0025] A3. Evaluation of sensing performance:

[0026] Perform linear fitting on the measured sensitivity curve to determine the sensitivity characteristics of the sensor;

[0027] Evaluate the hysteresis, linearity, and dynamic response characteristics of the sensor;

[0028] Optimize the microstructure parameters and the material properties of the sensitive layer based on the evaluation results.

[0029] The present invention has the following beneficial effects:

[0030] The high-density tactile sensing array of the present invention based on bionic microstructures has a spatial resolution of up to 500 μm for the sensing array pixels, exceeding the human fingertip perception limit, and can accurately reconstruct Braille dot matrices and micron-level surface textures. At the same time, by adopting a TFT active matrix reading system combined with a row-column addressing strategy, the signal crosstalk is significantly reduced, the dynamic response time is short, the cyclic stability is strong, and the signal fidelity is improved. In addition, the manufacturing process of the present invention is innovative. The precise machining of the microstructures is realized through a hybrid process of photolithography-wet etching and photolithography-thermal reflow, and the coffee ring effect is suppressed by using a PEO-modified CNT spraying technology, improving the uniformity of the sensitive layer. The process has strong compatibility and is suitable for mass production. This tactile sensing system can be integrated into robot end effectors, wearable health monitoring devices, medical diagnosis systems, etc., to realize high-end applications such as Braille recognition and minimally invasive surgical tactile navigation. It has the advantages of high precision, fast response, and strong robustness, breaking through the physical limits of traditional flexible sensors and reaching the leading level in low-pressure detection sensitivity and spatial resolution, providing an innovative solution for the intelligent development of artificial tactile systems.

[0031] Furthermore, the design method of the present invention constructs an equivalent circuit model. By using the fact that the resistance change of the sensor under pressure is mainly controlled by the contact resistance, the contact area is inversely proportional to the contact resistance, the pressure is inversely proportional to the contact area, and the current is inversely proportional to the resistance, a theoretical model of the sensitivity is determined. On this basis, through actual measurement verification of samples, a given pressure is applied to measure the change in the output current, the actual sensitivity curve is calculated, and a comparative analysis is carried out with the prediction results of the simulation model to further optimize the microstructure parameters and the material properties of the sensitive layer. This method can not only accurately evaluate the hysteresis, linearity, and dynamic response characteristics of the sensor, but also perform a linear fitting of the sensitivity of the sensor based on the actual measurement data, thereby realizing a precise evaluation of the sensing performance of the pressure signal, providing a scientific basis for the design and optimization of the sensor, and ensuring the high-performance performance of the sensor in practical applications.

[0032] The present invention has the advantages of high spatial resolution, high sensitivity, fast reading speed, low crosstalk, low power consumption, etc., and solves the limitations of existing tactile sensors in micron-level texture detection.

[0033] Optimization of bionic microstructure performance: Through the design of bionic pyramid or hemisphere microstructures, the pyramid array achieves high sensitivity (8.082 kPa-1) in the low-pressure range (0.2 - 0.5 kPa), while the hemisphere array extends the pressure range to 3.6 kPa through adjustable spacing.

[0034] Ultra-high spatial resolution: The pixel density of the sensing array reaches 256×256, the size of a single pixel is 50.8μm×50.8μm, and the spatial resolution is 500μm, exceeding the human fingertip perception limit (1mm), enabling precise reconstruction of Braille dots and micron-level surface textures.

[0035] Low crosstalk and fast response: The TFT active matrix reading system adopts a row-column addressing strategy, combined with the zero-potential method to eliminate parasitic circuit interference. The dynamic response time is as low as 0.125s (loading) and 0.25s (unloading), and the cycle stability exceeds 1000 times, significantly improving signal fidelity.

[0036] Manufacturing process innovation: Through a hybrid process of photolithography-wet etching and photolithography-thermal reflow, precise machining of 10μm-level pyramids and 25μm hemispherical microstructures is achieved; the PEO-modified CNT spraying technology is used to suppress the coffee ring effect, and the uniformity of the sensitive layer is improved by 40%. The process has strong compatibility and is suitable for mass production.

[0037] The present invention can achieve real-time texture reconstruction by connecting to a reading system, and can be integrated into the end effector of a robot, wearable health monitoring devices, and medical diagnostic systems to realize high-end applications such as Braille recognition and haptic navigation in minimally invasive surgery.

[0038] The tactile sensing system constructed by the present invention has the advantages of high precision, fast response, and strong robustness. Its measurement results can accurately and quickly analyze micron-level texture features. Based on bionic design and process optimization, the system breaks through the physical limits of traditional flexible sensors and reaches an advanced level in low-pressure detection sensitivity (0.01Pa level) and spatial resolution (sub-millimeter level).

[0039] Generally speaking, the high-density tactile sensing system and method based on bionic microstructures of the present invention can be directly used in robot fine operations, prosthetic tactile feedback, and wearable medical devices, and has the advantages of fast measurement speed, strong environmental adaptability, and multi-scene compatibility, providing an innovative solution for the intelligent development of artificial tactile systems.

[0040] Other beneficial effects in the embodiments of the present invention will be further described below. Brief Description of the Drawings

[0041] Figure 1 It is a schematic diagram of the sensing array structure of the embodiment of the present invention;

[0042] Figure 2 It is a SEM comparison diagram of the pyramid and hemispherical microstructures of the embodiment of the present invention;

[0043] Figure 3 It is a process flow diagram of the CNT spraying process of the embodiment of the present invention;

[0044] Figure 4Schematic circuit diagram of the TFT signal reading system according to an embodiment of the present invention;

[0045] Figure 5 Experimental results of texture recognition according to an embodiment of the present invention (Braille and 500μm texture reconstruction);

[0046] Figure 6 Sensor sensitivity curve according to an embodiment of the present invention. Detailed implementation manners

[0047] The following provides a detailed description of the implementation manners of the present invention. It should be emphasized that the following description is merely exemplary and is not intended to limit the scope of the present invention and its applications.

[0048] It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element. Additionally, the connection can be for a fixing function or a coupling or communicating function.

[0049] It should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the embodiments of the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention.

[0050] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present invention, "a plurality" means two or more unless otherwise specifically defined.

[0051] Refer to Figure 1 and Figure 2, an embodiment of the present invention provides a high-density tactile sensing array based on a bionic microstructure, including: a flexible substrate 1 for providing mechanical flexibility and encapsulation protection; a bionic microstructure layer 2 disposed on the flexible substrate 1, composed of a pyramid array or a hemisphere array, for enhancing the sensitivity and spatial resolution of the sensor; a carbon nanotube CNT sensitive layer 3 uniformly covering the surface of the bionic microstructure layer 2 for converting pressure changes into electrical signals; a thin-film transistor TFT signal reading system 4 integrated on the flexible substrate 1, adopting an active matrix design, and realizing pixel-level signal extraction through a row-column addressing strategy, for quickly and accurately reading and processing the electrical signals generated by the CNT sensitive layer 3.

[0052] In a preferred embodiment, polyvinyl alcohol PEO is added to the carbon nanotube CNT sensitive layer 3 to inhibit the coffee ring effect.

[0053] In a preferred embodiment, the pyramid microstructure in the bionic microstructure layer 2 is prepared by a silicon-based lithography and wet etching process, with an etching angle of 54.7° ± 0.5° and a height of 10 - 50 μm; the hemisphere microstructure is prepared by a polyimide substrate lithography combined with a thermal reflux process, with a diameter of 25 - 100 μm.

[0054] In a preferred embodiment, the CNT sensitive layer 3 uses a single-walled carbon nanotube SWCNT dispersion, with an SWCNT concentration of 0.15 wt% ± 2% (±2% means the percentage that can float up and down with 0.15 wt% as the central value, the same hereinafter), and the dilution ratio is CNT solution: isopropanol = 1:5 ± 2%.

[0055] In a preferred embodiment, the TFT signal reading system 4 includes a 256×256 pixel array, with a single pixel size of 50.8 μm × 50.8 μm ± 1 μm, a center pitch of 85 μm ± 1 μm, and a response time ≤ 0.25 s.

[0056] In a preferred embodiment, the flexible substrate 1 uses a polydimethylsiloxane PDMS material with a thickness of 25 μm.

[0057] The embodiment of the present invention also provides a preparation method of the high-density tactile sensing array as described above, including the following steps:

[0058] Step S1, preparing the bionic microstructure layer 2: forming a pyramid array on the substrate through a lithography and etching process, or forming a hemisphere array through a lithography combined with a thermal reflux process;

[0059] Step S2, forming the CNT sensitive layer 3: uniformly spraying the carbon nanotube dispersion on the surface of the bionic microstructure layer 2, and preferably adding polyvinyl alcohol PEO to inhibit the coffee ring effect;

[0060] Step S3, integrating the TFT signal reading system 4: Bonding and packaging the thin-film transistor array designed with an active matrix with the CNT sensitive layer 3;

[0061] Step S4, assembling the flexible substrate 1: Integrating the bionic microstructure layer 2, CNT sensitive layer 3, and TFT signal reading system 4 onto the flexible substrate to complete the preparation of the sensing array.

[0062] In a preferred embodiment, in step S1: For the pyramid array, it is prepared by silicon-based lithography and KOH wet etching processes. The etching solution ratio is 70 g KOH, 190 mL H2O, and 40 mL isopropanol. The etching temperature is 80°C ± 2°C, the etching angle is 54.7° ± 1°, and the etching depth is 10 - 50 μm; alternatively, for the hemisphere array, it is prepared by polyimide substrate lithography combined with a thermal reflux process. The thermal reflux temperature is 140°C ± 2°C, the time is 5 ± 0.5 min, and the hemisphere diameter is 25 - 100 μm.

[0063] In a preferred embodiment, in step S2: The carbon nanotube dispersion is a 0.15 wt% ± 2% single-walled carbon nanotube (SWCNT) solution, diluted in isopropanol at a ratio of 1:5 ± 2%. The spraying process parameters include: spraying speed of 1000 rpm ± 2%, spraying times of 1 - 4 times, with a drying interval of 5 ± 0.5 min each time; adding 0.05 wt% ± 2% polyvinyl alcohol (PEO) to inhibit the coffee ring effect.

[0064] In a preferred embodiment, in step S3: Using PDMS soft lithography technology to transfer the CNT sensitive layer to the flexible substrate; Bonding and packaging the TFT chip with silver paste, with a bonding temperature of 120°C ± 2°C and a time of 15 ± 0.5 min; The hemisphere array structure is additionally packaged with a polyurethane heat insulation layer, with a heat insulation layer thickness of 30 mm ± 2% and an area of 50 mm × 50 mm ± 2%.

[0065] The embodiment of the present invention also provides a design method for the high-density tactile sensing array as described above, including the following steps:

[0066] Step A1, constructing a simulation model:

[0067] Establish an inverse relationship model between the contact resistance R and the contact area A: R ∝ 1 / A;

[0068] Based on the relationship between the pressure P and the contact area A: P = F / A, construct a pressure-contact area conversion model;

[0069] Combined with the relationship between current I and resistance: I = U / R, a theoretical model of sensitivity S is established: S = (ΔI / I0) / ΔP; where, I0 represents the output current value of the sensor in the initial zero-pressure state, ΔI = I - I0 is the current change amount, where I is the measured current after applying pressure, and ΔP is the applied pressure change amount;

[0070] Step A2, Sample measurement verification:

[0071] Apply a given pressure to the prepared sensing array sample and measure the output current change;

[0072] Calculate the actual sensitivity curve according to the measured current-pressure data;

[0073] Compare and analyze the measured data with the prediction results of the simulation model;

[0074] Step A3, Sensing performance evaluation:

[0075] Perform linear fitting on the measured sensitivity curve to determine the sensitivity characteristics of the sensor;

[0076] Evaluate the hysteresis, linearity and dynamic response characteristics of the sensor;

[0077] Optimize the microstructure parameters and sensitive layer material characteristics based on the evaluation results.

[0078] The following further describes specific embodiments of the present invention.

[0079] A high-density tactile sensing array based on a bionic microstructure includes a flexible substrate, a bionic microstructure layer, a carbon nanotube (CNT) sensitive layer, and a thin film transistor (TFT) signal reading system. The bionic microstructure layer is composed of a pyramid array or a hemisphere array, with a size of 10 - 50 μm and an adjustable array pitch; the CNT sensitive layer is uniformly covered on the surface of the bionic microstructure by a spraying process, and the coffee ring effect is suppressed by adding polyvinyl alcohol (PEO); the TFT signal reading system adopts an active matrix design and realizes pixel-level signal extraction through a row-column addressing strategy, effectively reducing crosstalk.

[0080] In some specific embodiments, the pyramid microstructures are prepared by photolithography and wet etching processes. The substrate material is silicon, the etching angle is 54.7°, and the height is 10 - 50 μm. The hemispherical microstructures are prepared by photolithography combined with a thermal reflow process. The substrate material is polyimide, and the diameter is 25 - 100 μm. The CNT sensitive layer uses a single-walled carbon nanotube (SWCNT) dispersion liquid, which is uniformly deposited through an automated spraying system. The number of spraying times is 1 - 4 times, and the dilution ratio is 1:5 (CNT solution: isopropyl alcohol). The TFT signal reading system includes a 256×256 pixel array. The size of a single pixel is 50.8 μm × 50.8 μm, the center spacing is 85 μm, and the response time is 0.125 s (loading) and 0.25 s (unloading).

[0081] A design method for the high-density tactile sensing array based on the bionic microstructures is also provided as follows:

[0082] Construct an equivalent circuit model of the sensor, specifically including:

[0083] Regarding the resistance of the circuit when the sensor is under pressure as constant, the change in the resistance of the sensor when under pressure is mainly controlled by the contact resistance, and the contact area is inversely proportional to the contact resistance:

[0084] R ∝ 1 / A

[0085] where R represents the contact resistance and A represents the contact area.

[0086] When a constant force is applied to the sensor, the relationship between the pressure and the contact area is as follows:

[0087]

[0088] where P represents the pressure and A represents the contact area.

[0089] The relationship between the current and the resistance is:

[0090]

[0091] where I represents the current and U represents the voltage.

[0092] The sensitivity of the sensor refers to the ratio of the output change to the input change when the sensor is in a stable working state.

[0093]

[0094] where S represents the sensitivity. It can be deduced from the above formula that the sensitivity can also be expressed by the change rate of the contact area.

[0095] Based on a given (such as randomly given) pressure applied to the object to be measured, calculate the sensitivity of the object to be measured according to the measured change rate of the current.

[0096] Based on the theoretical model of calculation, the simulation sensitivity is fitted to construct a simulation model of the contact area of the microstructure varying with pressure.

[0097] The linear fitting is performed on the actually measured sensor sensitivity, and the sensitivity of the sensor is calculated respectively.

[0098] The sensing performance of the sensor to the pressure signal is evaluated by the actually calculated parameters such as sensitivity and hysteresis.

[0099] As Figure 1 shown, the high-density tactile sensing array includes a flexible substrate 1, a bionic microstructure layer 2, a carbon nanotube (CNT) sensitive layer 3, and a thin-film transistor (TFT) signal reading system 4. The bionic microstructure layer 2 is composed of a pyramid array ( Figure 1 a) or a hemisphere array ( Figure 1 b). The microstructure is precisely processed by photolithography, with a size of 10 - 50 μm and an adjustable array pitch. The CNT sensitive layer 3 is uniformly coated on the surface of the microstructure through an automated spraying system. 0.05 wt% polyvinyl alcohol (PEO) is added during the spraying process to inhibit the coffee ring effect and ensure the uniformity of the conductive layer distribution. The TFT signal reading system 4 adopts an active matrix design, integrating a 256×256 pixel array. The size of a single pixel is 50.8 μm×50.8 μm, with a center pitch of 85 μm. Pixel-level signal extraction is achieved through a row-column addressing strategy. The flexible substrate 1 is made of polydimethylsiloxane (PDMS) material with a thickness of 25 μm, having both mechanical flexibility and encapsulation protection functions.

[0100] Figure 6 This is the comparison curve of the sensitivity and pressure range of the sensing array of the present invention. As shown in the figure, the pyramid microstructure exhibits high sensitivity characteristics (8.082 kPa-1) in the low-pressure range (0.2 - 0.5 kPa), while the hemisphere microstructure extends the pressure detection range to 3.6 kPa by adjusting the pitch (D25 to D150), and at the same time, the sensitivity is increased to 12.113 kPa-1 (D150), covering the application scenarios from micro-force detection to medium-high pressure respectively, and meeting different texture recognition requirements.

[0101] Example 1

[0102] First, a double-sided polished silicon wafer is used as the substrate, and a square window pattern is formed on the surface through a standard photolithography process. The mask plate is designed with four regions of different pitches (10 μm, 20 μm, 30 μm, 40 μm). Subsequently, wet etching with KOH is carried out. The etching solution ratio is 70 g KOH, 190 mL H2O, and 40 mL isopropyl alcohol, and the temperature is controlled at 80 °C. The etching rate is about Etch to a depth of 10 μm to form a pyramid array with an inclination angle of 54.7°. After etching, use a 0.15 wt% single-walled carbon nanotube (SWCNT) dispersion, dilute it with isopropanol at a ratio of 1:5, and uniformly deposit it on the surface of the microstructure through an automated spraying system at a rotation speed of 1000 rpm. The spraying is carried out 3 times, with a 5-minute drying interval between each time. Add 0.05 wt% PEO during the spraying process to inhibit the coffee ring effect, and finally form a uniform CNT sensitive layer. Use PDMS soft lithography technology to transfer the sensitive layer to a flexible substrate and bond and package it with a TFT chip using silver paste. The bonding temperature is 120 °C and the time is 15 minutes.

[0103] Example 2

[0104] Select a polyimide (PI) film as the substrate, spin-coat AZ4620 photoresist with a thickness of 25 μm, and form a cylindrical array pattern (diameter 25 μm, pitch 25 - 150 μm) through photolithography. Subsequently, perform a thermal reflow process at a temperature of 140 °C for 5 minutes. After the photoresist melts under the action of surface tension, a hemispherical structure is formed. Use the same CNT spraying process as in Example 1, and adjust the spraying times to 2 times to avoid overcovering the top of the hemisphere. After the sensitive layer is transferred, integrate the hemisphere array with the TFT chip and encapsulate it with a polyurethane thermal insulation layer. The thickness of the thermal insulation layer is 30 mm, and the area is 50 mm × 50 mm to ensure that the heat is concentrated in the sensing area.

[0105] Example 3

[0106] Attach the pyramid array sensing system prepared in Example 1 to the end effector of the robot, and apply a pre-pressure of 0.2 kPa to the target object (such as a Braille board, a micro-textured metal sheet) to ensure contact stability. Real-time collect the resistance change signals of each pixel point through the TFT system, convert them into grayscale images, and input them into a convolutional neural network (CNN) model for classification. The model structure includes 5 convolutional layers and 3 fully connected layers. The training data set includes 10 types of samples such as 500-μm Braille dots, 800-μm sawtooth textures, and the Tsinghua University logo, and the accuracy rate reaches 99.7%. As Figure 5 shown, the system successfully reconstructs the Braille characters "THU" and 500-μm micro-groove textures. In the spatial resolution verification experiment, scan the 3D-printed 200 - 800-μm texture blocks. The results show that the textures above 500 μm are clearly recognized, and the edge contrast reaches 95%, meeting the requirements of industrial inspection and medical tactile navigation.

[0107] Generally speaking, the high-density tactile sensing system and method based on bionic microstructures of the present invention can achieve precise perception and real-time feedback of micron-level surface textures, and have core advantages such as high sensitivity, wide dynamic range, strong environmental adaptability, and multi-scenario compatibility. Embodiments of the present invention use pyramid and hemisphere microstructures to achieve low-pressure detection (at the 0.01 Pa level) and medium-high pressure ranges (0.2 - 3.6 kPa), while breaking through the spatial resolution limit (500 μm), and solving the industry problems existing in high-precision texture recognition and complex working condition adaptability of the prior art.

[0108] The main advantages of the present invention compared with traditional technologies:

[0109] Making up for the physical limits of existing tactile perception: Traditional flexible sensors (such as capacitive and piezoresistive ones) are limited by manufacturing processes, and the spatial resolution mostly stays at the millimeter level (1 - 2 mm), and the signal crosstalk rate > 30%. Through bionic microstructure design and TFT active matrix reading system, the present invention improves the resolution to 500 μm and reduces the crosstalk rate to < 5%, achieving breakthrough applications in scenarios such as braille recognition and tactile navigation of minimally invasive surgical instruments.

[0110] Model simplification and improvement of calculation efficiency: Traditional tactile signal analysis relies on complex multi-physical field coupling models (such as finite element analysis), which require input of parameters such as material elastic modulus and Poisson's ratio, and the calculation takes up to several hours. Based on the discrete transient mechanics model, the present invention only needs the relationship between contact area and pressure as input to achieve real-time texture reconstruction.

[0111] The solution of the present invention has good stability and is easy to integrate in different environments. The specific application scenarios are as follows:

[0112] Robot grasping and automation: In industrial sorting, by real-time detecting the surface roughness of objects (such as distinguishing polished metal from frosted plastic), the grasping success rate is increased by more than 30%; in agricultural automation, it is used for fruit maturity grading (such as judging by the epidermal texture hardness).

[0113] Tactile reproduction and virtual reality: Integrated into VR gloves, simulating the tactile differences of materials such as silk and sandpaper, with a force feedback delay < 0.2 s, and the immersion experience of users is improved by 50%; in remote surgical training, it provides real-time tactile signal transmission of organ tissues.

[0114] Medical diagnosis and prosthetic control: As a prosthetic fingertip sensor, it realizes adaptive adjustment of grasping force through surface texture recognition (such as cloth and glass); in skin disease detection, combined with AI algorithms to analyze skin micro-protrusion characteristics, assisting in the early screening of melanoma.

[0115] Intelligent Manufacturing and Precision Detection: For on-line detection of surface defects (scratches, bubbles) on chip packages, with an identification accuracy of 20μm; in the aerospace field, detect interlaminar microcracks in composite materials, replacing traditional manual visual inspection.

[0116] This invention has the following market values especially for industries such as intelligent robots and automation control, high-dimensional tactile perception and object feature recognition, virtual reality (VR) and remote tactile reproduction:

[0117] 1) This system provides a high-precision tactile perception module for the end effector of the robot, which can be directly integrated into existing equipment such as industrial robotic arms and grasping units of service robots without modifying the mechanical structure. For example, in the sorting of electronic components, non-destructive grasping is achieved by real-time detecting micro-deformations (accuracy ±5μm) of chip pins, and the failure rate is reduced by 40%; in logistics automation, the sorting path planning is optimized through surface texture recognition (such as the difference between cardboard boxes and plastic films), and the efficiency is increased by 25%. Its modular design (standardized interfaces, installation time < 10 minutes) and low-cost advantage (unit cost < $50) provide an efficient solution for the industrial upgrading of intelligent robots.

[0118] 2) The system breaks through the limitations of traditional single-pressure detection. Through the multi-modal signal coupling (contact area, pressure gradient, dynamic vibration) of bionic microstructures, physical characteristics such as the hardness, roughness, and viscoelasticity of objects can be obtained synchronously. In the food processing industry, the maturity of fruits and vegetables (such as the softness and hardness grading of avocados) is analyzed through tactile features, with an accuracy rate of 98%, which is 30% higher than the traditional optical detection method; in the digitalization of archaeological cultural relics, 3D tactile reconstruction of relief textures (resolution 500μm) is realized, providing a non-destructive recording method for the protection of cultural heritage.

[0119] 3) Based on the contact mechanics model and millisecond-level response characteristics of this system, the tactile differences of materials can be accurately simulated in a virtual environment (such as the friction coefficient of silk is 0.2 ± 0.05, and that of sandpaper is 1.5 ± 0.1). When integrated into a VR glove, the force feedback delay < 0.2s, and the power consumption is reduced to 1.2W (60% less than similar products), and the user experience score is increased by 52%. In the field of remote surgery, real-time tactile signal transmission of organ tissues (bandwidth requirement < 10Mbps) is achieved through the 5G network, enabling doctors to perceive the operating force at the 0.1N level, and significantly reducing the training cost of minimally invasive surgery (the cost of the simulation system drops by 70%).

[0120] The above content is a further detailed description of the present invention in combination with specific / preferred embodiments, and it cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several alternatives or modifications can be made to these described embodiments, and these alternative or modified forms should all be regarded as belonging to the protection scope of the present invention. In the description of this specification, the descriptions with reference to terms such as "an embodiment", "some embodiments", "preferred embodiments", "examples", "specific examples", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. Without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples. Although the embodiments of the present invention and their advantages have been described in detail, it should be understood that various changes, substitutions, and alterations can be made herein without departing from the scope of protection of the patent application.

Claims

1. A high-density tactile sensing array based on bionic microstructures, characterized in that, Comprising: A flexible substrate (1) for providing mechanical flexibility and encapsulation protection; A bionic microstructure layer (2) disposed on the flexible substrate (1), composed of a pyramid array or a hemisphere array; A carbon nanotube (CNT) sensitive layer (3) uniformly covering the surface of the bionic microstructure layer (2) for converting pressure changes into electrical signals; A thin-film transistor (TFT) signal reading system (4) integrated on the flexible substrate (1), using an active matrix design, and realizing pixel-level signal extraction through a row-column addressing strategy to read and process the electrical signals generated by the CNT sensitive layer (3).

2. The sensing array according to claim 1, characterized in that Polyvinyl alcohol (PEO) is added to the carbon nanotube (CNT) sensitive layer (3) to inhibit the coffee ring effect.

3. The sensing array according to claim 1, wherein The etching angle of the pyramid microstructure in the bionic microstructure layer (2) is 54.7° ± 0.5°, and the height is 10 - 50 μm; the diameter of the hemisphere microstructure is 25 - 100 μm.

4. The sensing array according to claim 1, wherein, The CNT sensitive layer (3) is formed from a single-walled carbon nanotube (SWCNT) dispersion, where the SWCNT concentration is 0.15 wt% ± 2%, and the dilution ratio is CNT solution: isopropanol = 1:5 ± 2%.

5. The sensing array according to claim 1, wherein, The TFT signal reading system (4) includes a 256×256 pixel array, and the size of a single pixel is 50.8 μm × 50.8 μm ± 1 μm, and the center pitch is 85 μm ± 1 μm.

6. A method for preparing a high-density tactile sensing array as described in claim 1, characterized in that, Including the following steps: S1. Prepare the bionic microstructure layer (2): form a pyramid array on the substrate through photolithography and etching processes, or form a hemisphere array through photolithography combined with a thermal reflux process; S2. Form the CNT sensitive layer (3): uniformly spray the carbon nanotube dispersion on the surface of the bionic microstructure layer (2), and preferably add polyvinyl alcohol (PEO) to inhibit the coffee ring effect; S3. Integrate the TFT signal reading system (4): bond and package the thin-film transistor array with an active matrix design to the CNT sensitive layer (3); S4. Assemble the flexible substrate (1): integrate the bionic microstructure layer (2), the CNT sensitive layer (3), and the TFT signal reading system (4) on the flexible substrate to complete the preparation of the sensing array.

7. The preparation method according to claim 6, characterized in that, In step S1: The pyramid array is prepared by a silicon-based photolithography and KOH wet etching process, the etching solution ratio is KOH, H2O, and isopropanol, the etching temperature is 80°C ± 2°C, the etching angle is 54.7° ± 1°, and the etching depth is 10 - 50 μm; The hemisphere array is prepared by a polyimide substrate photolithography combined with a thermal reflux process, the thermal reflux temperature is 140°C ± 2°C, the time is 5 ± 0.5 min, and the hemisphere diameter is 25 - 100 μm.

8. The preparation method according to claim 6, characterized in that, In step S2: The carbon nanotube dispersion is a 0.15 wt% ± 2% single-walled carbon nanotube (SWCNT) solution, diluted in isopropanol at a ratio of 1:5 ± 2%; The spraying process parameters include: spraying speed 1000 rpm ± 2%, spraying times 1 - 4 times, and drying for 5 ± 0.5 min at each interval; Add 0.05 wt% ± 2% polyvinyl alcohol (PEO) to inhibit the coffee ring effect.

9. The preparation method according to claim 6, wherein, In step S3: Transfer the CNT sensitive layer to the flexible substrate using PDMS soft lithography technology; Encapsulate the TFT chip by silver paste bonding, with a bonding temperature of 120°C ± 2°C and a time of 15 minutes ± 0.5 min; The hemispherical array structure is additionally encapsulated with a polyurethane thermal insulation layer.

10. A design method of the high-density tactile sensing array as described in claim 1, characterized in that, It includes the following steps: A1. Construct a simulation model: Establish an inverse relationship model between contact resistance R and contact area A: R ∝ 1 / A; Based on the relationship between pressure P and contact area A: P = F / A, construct a pressure-contact area conversion model; Combined with the relationship between current I and resistance: I = U / R, establish a theoretical model of sensitivity S: S = (ΔI / I0) / ΔP; where, I0 represents the output current value of the sensor in the initial zero-pressure state, ΔI = I - I0 is the current change amount, where I is the measured current after applying pressure, and ΔP is the applied pressure change amount; A2. Experimental verification of samples: Apply a given pressure to the prepared sensing array sample and measure the change in output current; Calculate the actual sensitivity curve according to the measured current-pressure data; Compare and analyze the measured data with the prediction results of the simulation model; A3. Evaluation of sensing performance: Perform linear fitting on the measured sensitivity curve to determine the sensitivity characteristics of the sensor; Evaluate the hysteresis, linearity, and dynamic response characteristics of the sensor; Optimize the microstructure parameters and sensitive layer material characteristics based on the evaluation results.

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