Capacitive Tactile Sensor Research Articles

Recent Progress in Advanced Tactile Sensing Technologies for Soft Grippers

AbstractTactile sensing technology is crucial for soft grippers. Soft grippers equipped with intelligent tactile sensing systems based on various sensors can interact safely with the unstructured environments and obtain precise properties of objects (e.g., size and shape). It is essential to develop state‐of‐the‐art sensing technologies for soft grippers to handle different grasping tasks. In this review, the development of tactile sensing techniques for robotic hands is first introduced. Then, the principles and structures of different types of sensors normally adopted in soft grippers, including capacitive tactile sensors, piezoresistive tactile sensors, piezoelectric tactile sensors, fiber Bragg grating (FBG) sensors, vision‐based tactile sensors, triboelectric tactile sensors, and other advanced sensors developed recently are briefly presented. Furthermore, sensing modalities and methodologies for soft grippers are also described in aspects of force measurement, perception of object properties, slip detection, and fusion of perception. The application scenarios of soft grippers are also summarized based on these advanced sensing technologies. Finally, the challenges of tactile sensing technologies for soft grippers that need to be tackled are discussed and perspectives in addressing these challenges are pointed out.

Investigating capacitive flexible tactile sensor with a wide measuring range using PVDF and conductive sponge

Flexible tactile sensors have important application value in the field of artificial intelligence and internet of things. At present, it is a great challenge for tactile sensors to maintain high sensitivity and stability in a large pressure range. This article proposes a flexible capacitive tactile sensor with high sensitivity and large measuring range, which has a sandwich structure. The purpose of this paper is to determine the relationship between the thickness, surface microstructure, sensitivity, and sensing range of poly(vinylidene fluoride) (PVDF) films. The sensor uses conductive sponge with a microstructure surface and an ultra-thin PVDF film as the electrode and dielectric layer, respectively, and provides a comprehensive study in terms of sensor design, theoretical calculation, computer simulation and applications. The minimum detection limit of the sensor are tested by sound vibration, needle blowing, and human physiological signals. It has been shown that the thicker the PVDF film, the lower the sensitivity and the wider the sensing range. The proposed sensor can accurately identify physiological signals such as respiration, pulse and swallowing, and can perceive the softness, hardness and weight of the object as well as identifying the grasping posture. Moreover, the sensor has the characteristics of short response time, good recoverability and stability.

A highly sensitive capacitive flexible tactile sensor based on a composite dielectric layer with a C-type symmetrical structure for wearable electronics

In this work, a capacitive flexible tactile sensor based on the composite dielectric layer with a C-type symmetrical structure is proposed to improve the sensing performance through the introduction of a precise structure. Combined with simulations and experiments, the influence of the structural characteristics of the tactile sensor on its sensitivity is investigated, the correlation between the signal output of the sensor and the loading pressure is shown for different structural parameter designs, and the structure of the sensor is optimized. Data results display that the tactile sensor proposed in this work exhibits a lower detection limit (8.6 Pa) and an ultra-wide linear sensing range (8.6–500 kPa). In addition, from the 55 ms response time of the sensor and 2000 cycles of experiments, it can be concluded that the sensor possesses good repeatability and durability, and can achieve more accurate measurement results in motion detection, soft robots, and electronic skin.

All-printed flexible capacitive array tactile force sensors with tunable sensitivity and low crosstalk for micro motion detection

All-printed flexible capacitive array tactile force sensors with tunable sensitivity and low crosstalk for micro motion detection

A high sensitivity and multi-axis fringing electric field based capacitive tactile force sensor for robot assisted surgery

This paper presents a design of multi-axis tactile force sensor using the fringe effect of an electric field between stationary patterned electrodes. The unique configuration of the electrodes consisting of four separate square-shaped sensing electrodes, with each encircled by excitation electrodes, allows to achieve enhanced fringe field effect and hence sensitivity. The proposed sensor can decouple the normal, shear and angular shear applied forces. The sensor is fabricated using low-cost rapid prototyping techniques with flexible Ecoflex 00–30 and silicone rubber RTV-528 as the elastomers for contact with the environment. An analytical model is developed that correlates the nominal capacitance of the sensor with that of the geometric dimensions of the stationary electrodes and air cavity height between the electrodes and elastomer. The force measurement ranges in the normal, shear, and angular axis are 5 N, 1.5 N, and 1 N respectively. The sensor shows a perfectly linear response, repeatability, and a low hysteresis error, thermal stability and robustness to the environmental interferences that makes it suitable to be used for force feedback in minimally invasive robotic surgery.

Conjugated Polymer-Based Nanocomposites for Pressure Sensors.

Flexible sensors are the essential foundations of pressure sensing, microcomputer sensing systems, and wearable devices. The flexible tactile sensor can sense stimuli by converting external forces into electrical signals. The electrical signals are transmitted to a computer processing system for analysis, realizing real-time health monitoring and human motion detection. According to the working mechanism, tactile sensors are mainly divided into four types-piezoresistive, capacitive, piezoelectric, and triboelectric tactile sensors. Conventional silicon-based tactile sensors are often inadequate for flexible electronics due to their limited mechanical flexibility. In comparison, polymeric nanocomposites are flexible and stretchable, which makes them excellent candidates for flexible and wearable tactile sensors. Among the promising polymers, conjugated polymers (CPs), due to their unique chemical structures and electronic properties that contribute to their high electrical and mechanical conductivity, show great potential for flexible sensors and wearable devices. In this paper, we first introduce the parameters of pressure sensors. Then, we describe the operating principles of resistive, capacitive, piezoelectric, and triboelectric sensors, and review the pressure sensors based on conjugated polymer nanocomposites that were reported in recent years. After that, we introduce the performance characteristics of flexible sensors, regarding their applications in healthcare, human motion monitoring, electronic skin, wearable devices, and artificial intelligence. In addition, we summarize and compare the performances of conjugated polymer nanocomposite-based pressure sensors that were reported in recent years. Finally, we summarize the challenges and future directions of conjugated polymer nanocomposite-based sensors.

Highly Stretchable Additively Manufactured Capacitive Proximity and Tactile Sensors for Soft Robotic Systems

Soft robotics are considered one of the most promising approaches towards fully collaborative robotic devices. Soft robotic systems are intrinsically safe due to their compliant nature. Using additive fabrication for the development of soft capacitive sensors, enables high flexibility and individualization capabilities in terms of design and material properties. In this work, we outline the sensorization of stretchable capacitive sensors for proximity and tactile detection. This sensor will represent an essential component of a soft robotic finger in future work. While the functional principle has already been shown previously, here we explore the design space further and perform more in depth test of the influences of the strain on the tactile measurements. The capacitive pad’s sensitivity is evaluated by applying normal force on each sensor, where the applied force is ranged between 1N and 16N, with resultant capacitive change of the four tactile sensors between 1 pF and 60 pF. The capacitive pad’s proximity sensor is tested using five different materials, with proximity range of 20mm, with change in capacitance between 0.1 pF and 2.4 pF. An essential aspect of soft robotics is that also the sensor may be subject to substantial deformations. We demonstrate that our proposed sensor design can withstand large strains of more than 35% while the sensitivity towards sensing normal forces does not significantly change. This demonstrates that the proposed sensor design will be suitable for various soft robotics applications, where large deformations may occur.

A Novel Sensor for Fruit Ripeness Estimation Using Lithography Free Approach

A flexible tactile sensor has the ability to sense and characterize the firmness and mechanical stiffness of the object. In this work, we demonstrate a low-cost, highly sensitive, flexible capacitive tactile sensor using a nanoneedle-patterned polydimethylsiloxane (PDMS) as a dielectric layer to detect the ripeness of the fruits. The nanoneedle-patterned PDMS was formed using an anodic oxidized porous alumina film as a mold. The developed tactile sensor exhibited high sensitivity due to the high deformity and elasticity of the nanoneedles on the PDMS layer. The higher sensitivity of 1.042–0.67 kPa−1 for a low-pressure regime below 0.2 kPa and the lower sensitivity of 0.35 kPa−1 for a pressure range above 0.6 kPa were demonstrated. This corresponds to a ~12% change in capacitance at 0.1-kPa pressure. Loading unloading tests for over 500 cycles were performed to confirm the absence of hysteresis. The mechanical elastic modulus of different tomato samples was tested using the tactile sensor and a universal test machine. The device could easily discriminate tomatoes of different stiffness. The tomato ripeness detection experiments demonstrate that the sensor can be used in robotic sensors, to estimate the qualitative ripeness of the fruits, during harvesting and transportation. This concept can be utilized in assessing ripeness levels of fruits like mangoes, kiwis, pears, avocados, sapodilla, and so on, after adequate recalibration of the sensor, leading to different sensing ranges.

Braille letter reading: A benchmark for spatio-temporal pattern recognition on neuromorphic hardware.

Spatio-temporal pattern recognition is a fundamental ability of the brain which is required for numerous real-world activities. Recent deep learning approaches have reached outstanding accuracies in such tasks, but their implementation on conventional embedded solutions is still very computationally and energy expensive. Tactile sensing in robotic applications is a representative example where real-time processing and energy efficiency are required. Following a brain-inspired computing approach, we propose a new benchmark for spatio-temporal tactile pattern recognition at the edge through Braille letter reading. We recorded a new Braille letters dataset based on the capacitive tactile sensors of the iCub robot's fingertip. We then investigated the importance of spatial and temporal information as well as the impact of event-based encoding on spike-based computation. Afterward, we trained and compared feedforward and recurrent Spiking Neural Networks (SNNs) offline using Backpropagation Through Time (BPTT) with surrogate gradients, then we deployed them on the Intel Loihi neuromorphic chip for fast and efficient inference. We compared our approach to standard classifiers, in particular to the Long Short-Term Memory (LSTM) deployed on the embedded NVIDIA Jetson GPU, in terms of classification accuracy, power, and energy consumption together with computational delay. Our results show that the LSTM reaches ~97% of accuracy, outperforming the recurrent SNN by ~17% when using continuous frame-based data instead of event-based inputs. However, the recurrent SNN on Loihi with event-based inputs is ~500 times more energy-efficient than the LSTM on Jetson, requiring a total power of only ~30 mW. This work proposes a new benchmark for tactile sensing and highlights the challenges and opportunities of event-based encoding, neuromorphic hardware, and spike-based computing for spatio-temporal pattern recognition at the edge.

High-sensitivity flexible tri-axial capacitive tactile sensor for object grab sensing

In this paper, a high sensitivity, flexible capacitive tri-axial tactile sensor is constructed by pyramid-shaped microarray dielectric layer. The tactile sensor consists of a staggered 2 × 2 capacitive sensor array. Through the measure and analysis of the three-dimensional force, which was applied on the sensor, it could decompose into normal and shear force components. The sensor exhibits high sensitivity due to the pyramidal-shaped microarray and low modulus of the dielectric layer. The sensitivity of the sensor in the x,y and z-axis are 56.47, 53.45 and 90.39 %/N in the ranges of 0 ∼ 0.8, 0 ∼ 0.8 and 0 ∼ 0.6 N, respectively. In addition, the sensor also exhibits fast response and recovery times (60 ms), and longtime cycling stability. The low average test error (about 10.4 %) of the tri-axial tactile sensor provides the technical basis for the application of robotics and wearable devices.

Highly Reliable Sensitive Capacitive Tactile Sensor with Spontaneous Micron‐Pyramid Structures for Electronic Skins

AbstractIn recent years, it is still challenging to develop a capacitive tactile sensor with low cost, high sensitivity, and controllable morphology. Herein, the flexible capacitive pressure sensor (FCPS) with high sensitivity is fabricated via a one‐step template method to produce spontaneous micron‐pyramid structured polydimethylsiloxane (PDMS) by releasing a four‐way stretched PDMS film treated with ultraviolet ozone exposure. The capacitive sensor is composed of two silver nanowire electrodes coated on polyimide substrate and a patterned PDMS dielectric layer sandwiching in the middle, exhibits an ultrahigh sensitivity of 15.66 kPa−1, an ultralow limit of detection of 0.2 Pa, a fast response time of 42.4 ms, and excellent cycling stability. The finite‐elemental analysis suggests that the uniform micro‐pyramid structures are vital to obtain ultrahigh sensitivity, low detection limit, and fast response. In particular, the FCPS can keep the tactile performance unchanged after 4000 repeated tests, reflecting the high robustness. In conclusion, the significant advantages of the sensor enable it to be well applied in the fields of sign language detection, spatial pressure distribution, and physiological signal monitoring, indicating that FCPS has a potential application prospect in the fields of flexible wearable electronic devices and electronic skins.

Ultrasensitive capacitive tactile sensor with heterostructured active layers for tiny signal perception

The development of capacitive tactile sensors with both ultrasensitivity and ultrafast response/relaxation is crucial for the development of intelligent healthcare monitoring technology. Despite the significant improvement in the sensing performance presented by the introduction of microstructures into the dielectric or electrode layers, meeting the demands of intellectualization remains a major challenge. Herein, a strategy to simultaneously introduce microstructures in both the dielectric and electrode layers is developed. The hierarchical sea-urchin TiO2 particle-in-micropore (HSP-MP) structure in the dielectric layer induces stress concentration near the micropore regions, significantly enhancing the sensitivity and toughness of the device. The sparsely spaced large microcone improves the sensitivity of the hierarchical microcone (HM) structure in the electrode layer, while the small microcone reduces the hysteresis caused by interfacial adhesion. With the synergistic effect of the HSP-MP&HM structure, the proposed tactile sensor achieves ultrasensitivity of 10.5 kPa−1, ultrafast response/relaxation time of 5.6/5.6 ms, and ultralow limit of detection of 0.1 Pa. These sensing properties are demonstrated in practical applications, including tiny signal perception of the human fingertip pulse, tiny muscle motion perception for Morse code transmission, and high-resolution flexible perception array with pressure mapping capability.

Full Soft Capacitive Omnidirectional Tactile Sensor Based on Micro-Spines Electrode and Hemispheric Dielectric Structure.

Flourishing in recent years, intelligent electronics is desirably pursued in many fields including bio-symbiotic, human physiology regulatory, robot operation, and human–computer interaction. To support this appealing vision, human-like tactile perception is urgently necessary for dexterous object manipulation. In particular, the real-time force perception with strength and orientation simultaneously is critical for intelligent electronic skin. However, it is still very challenging to achieve directional tactile sensing that has eminent properties, and at the same time, has the feasibility for scale expansion. Here, a fully soft capacitive omnidirectional tactile (ODT) sensor was developed based on the structure of MWCNTs coated stripe electrode and Ecoflex hemisphere array dielectric. The theoretical analysis of this structure was conducted for omnidirectional force detection by finite element simulation. Combined with the micro-spine and the hemispheric hills dielectric structure, this sensing structure could achieve omnidirectional detection with high sensitivity (0.306 ± 0.001 kPa−1 under 10 kPa) and a wide response range (2.55 Pa to 160 kPa). Moreover, to overcome the inherent disunity in flexible sensor units due to nano-materials and polymer, machine learning approaches were introduced as a prospective technical routing to recognize various loading angles and finally performed more than 99% recognition accuracy. The practical validity of the design was demonstrated by the detection of human motion, physiological activities, and gripping of a cup, which was evident to have great potential for tactile e-skin for digital medical and soft robotics.

MOCA-S: A Sensitive Mobile Collaborative Robotic Assistant Exploiting Low-Cost Capacitive Tactile Cover and Whole-Body Control

Safety is one of the most fundamental aspects of robotics, especially when it comes to collaborative robots (cobots) that are expected to physically interact with humans. Although a large body of literature has focused on safety-related aspects for fixed-based cobots, a low effort has been put into developing collaborative mobile manipulators. In response to this need, this work presents MOCA-S, i.e., Sensitive Mobile Collaborative Robotic Assistant, that integrates a low-cost, capacitive tactile cover to measure interaction forces applied to the robot base. The tactile cover comprises a set of 11 capacitive large-area tactile sensors distributed as a 1-D tactile array around the base. Characterization of the tactile sensors with different materials is included. Moreover, two expanded whole-body controllers that exploit the platform’s tactile cover and the loco-manipulation features are proposed. These controllers are tested in two experiments, demonstrating the potential of MOCA-S for safe physical Human-Robot Interaction (pHRI). Finally, an experiment is carried out in which an undesired collision occurs between MOCA-S and a human during a loco-manipulation task. The results demonstrate the intrinsic safety of MOCA-S and the proposed controllers, suggesting a new step towards creating safe mobile manipulators.

Highly linear capacitive tactile sensor with elastic dome-shaped electrodes

Capacitive tactile sensors have been widely used for electronic skins and human-machine interfaces due to their high sensitivity, low power consumption, and fast response. Despite great advances in improving the sensitivity of the sensors through structural design or advanced material selection, achieving linear response over a broad detection range for pressure sensing is still a great challenge. Herein, a capacitive tactile sensor with elastic dome-shaped electrode is reported. We find that the elastic dome-shaped electrode can significantly enhance the linear relationship between the effective electrode area of the capacitor and the applied force over a wide range, which endowed the prepared sensor exhibiting excellent linearity (R 2 = 0.999) up to 120 kPa. In addition, the fabricated sensor sample has good stability, quick response, satisfied sensitivity of 0.115 kPa−1 (0–120 kPa), and can be further expanded with a wider sensing range up to 500 kPa. Based on the proposed model, the sensitivity and linear sensing range of the sensor can be designed flexibly for different application. It can provide a simple but powerful strategy to construct high performance flexible pressure sensors in the future.

A Simple Fabrication, Low Noise, Capacitive Tactile Sensor for Use in Inexpensive and Smart Healthcare Systems

Tactile sensors are among the most important devices used in industrial and biomedical fields. Sensors’ profiles are significantly affected by their structures and material used. This article presents a robust, low-cost, low noise, accurate and simple fabrication capacitive tactile sensor as a single taxel fabricated on foam. This highly scalable design provides excellent noise immunity, accuracy, and due to a unique printable elastic conductor, it is flexible and stretchable with more than 200% strain. Furthermore, the taxel is based on the capacitive Wheatstone bridge. As a result, noise immunity and stability in case of temperature fluctuation is accomplished. Additionally, the sensor’s innovative, simple fabrication, made of Polyurethane foam and printable elastic conductor, allows the system to adapt and achieve relevant results necessary for the purpose of the sensor’s application. Therefore, the proposed sensor has potential applications in industrial and biomedical contexts, such as sleep monitoring, etc.

Fabric Classification Using a Finger-Shaped Tactile Sensor via Robotic Sliding.

Tactile sensing endows the robots to perceive certain physical properties of the object in contact. Robots with tactile perception can classify textures by touching. Interestingly, textures of fine micro-geometry beyond the nominal resolution of the tactile sensors can also be identified through exploratory robotic movements like sliding. To study the problem of fine texture classification, we design a robotic sliding experiment using a finger-shaped multi-channel capacitive tactile sensor. A feature extraction process is presented to encode the acquired tactile signals (in the form of time series) into a low dimensional (≤7D) feature vector. The feature vector captures the frequency signature of a fabric texture such that fabrics can be classified directly. The experiment includes multiple combinations of sliding parameters, i.e., speed and pressure, to investigate the correlation between sliding parameters and the generated feature space. Results show that changing the contact pressure can greatly affect the significance of the extracted feature vectors. Instead, variation of sliding speed shows no apparent effects. In summary, this paper presents a study of texture classification on fabrics by training a simple k-NN classifier, using only one modality and one type of exploratory motion (sliding). The classification accuracy can reach up to 96%. The analysis of the feature space also implies a potential parametric representation of textures for tactile perception, which could be used for the adaption of motion to reach better classification performance.

An improved BP neural network‐based calibration method for the capacitive flexible three‐axis tactile sensor array

Flexible tactile sensing based on capacitive sensing has become a research hotspot in recent years because of its low energy consumption, high performance and wide application prospects. However, the axis error caused by the coupling deformation of the dielectric will seriously affect the accuracy of the sensor. In this paper, a capacitive flexible three-axis tactile sensor array is modelled and simulated, and a neural network-based calibrator for the three-axis sensor array is proposed, which can be used to calibrate the simulated measurement data. The simulation results show that even though the correlation coefficient of linear regression for each axis is very close to 1, the effect of dielectric nonlinear coupling distortion cannot be eliminated. The calibration method based on the neural network can effectively suppress the nonlinear coupling distortion of the dielectric, and reduce the measurement coupling rate of the sensor model from 26% to 1%. At the same time, in order to ensure the measurement accuracy and robustness of different units in the sensor array, the input layer of the calibrator is expanded, and the data set containing capacitance information and two-dimensional location information is used for training. The experimental results show that the proposed calibration method combining two-dimensional position information training accurately calibrates the capacitive flexible three-dimensional tactile sensor array.

Carbon Black/PDMS Based Flexible Capacitive Tactile Sensor for Multi-Directional Force Sensing.

Flexible sensing tends to be widely exploited in the process of human–computer interactions of intelligent robots for its contact compliance and environmental adaptability. A novel flexible capacitive tactile sensor was proposed for multi-directional force sensing, which is based on carbon black/polydimethylsiloxane (PDMS) composite dielectric layer and upper and lower electrodes of carbon nanotubes/polydimethylsiloxane (CNTs/PDMS) composite layer. By changing the ratio of carbon black, the resolution of carbon black/PDMS composite layer increases at 4 wt%, and then decreases, which was explained according to the percolation theory of the conductive particles in the polymer matrix. Mathematical model of force and capacitance variance was established, which can be used to predict the value of the applied force. Then, the prototype with carbon black/PDMS composite dielectric layer was fabricated and characterized. SEM observation was conducted and a ratio was introduced in the composites material design. It was concluded that the resolution of carbon sensor can reach 0.1 N within 50 N in normal direction and 0.2 N in 0–10 N in tangential direction with good stability. Finally, the multi-directional force results were obtained. Compared with the individual directional force results, the output capacitance value of multi-directional force was lower, which indicated the amplitude decrease in capacity change in the normal and tangential direction. This might be caused by the deformation distribution in the normal and tangential direction under multi-directional force.

Fully Printed Flexible Capacitive Array Tactile Force Sensors with Tunable Sensitivity and Low Crosstalk for Monitoring Human Motion and Sound Signals

Fully Printed Flexible Capacitive Array Tactile Force Sensors with Tunable Sensitivity and Low Crosstalk for Monitoring Human Motion and Sound Signals