Large-Area and Low-Cost Force/Tactile Capacitive Sensor for Soft Robotic Applications

Pagoli, Amir; Chapelle, Frédéric; Ramón, Juan Antonio Corrales; Mezouar, Youcef; Lapusta, Yuri

doi:10.3390/s22114083

Cited by 25 publications

(11 citation statements)

References 51 publications

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“…The advent of dielectric elastomer sensors (DESs) and dielectric elastomer actuators (DEAs) has marked a significant milestone in the field of soft electronics, 1 offering promising applications in areas such as soft robotics, 2,3 human motion detection, [4][5][6] haptic interfaces, 7 pressure sensing 8,9 and healthcare monitoring. 10 Usually, DES and DEA have a sandwich structure of two compliant electrode layers and a dielectric elastomer layer between them.…”

Section: Introductionmentioning

confidence: 99%

Influence of stacking on the stability of a multi-layer capacitive dielectric elastomer sensor for strain detection

Prokopchuk,

Ewert,

Menning

et al. 2024

Electroactive Polymer Actuators and Devices (EAPAD) XXVI

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Flexible and stretchable electronics have garnered significant interest for their potential applications in fields like soft robotics, sensor-integrating machine elements, Industry 4.0, biomechanics, and wearable technology. Among these innovations, multi-layer capacitive strain sensors based on dielectric elastomers (DEs) stand out for their sensitivity, large deformation range, and compatibility with complex shapes. In this study, the focus is on advancing the design, fabrication, and evaluation of multi-layer capacitive strain sensors based on DEs. The goal is to explore novel approaches to enhance stability, sensitivity, and manufacturability. The research in this work introduces a comprehensive classification of four-electrode layer dielectric elastomer sensor (4EL-DES) structures, including a new 50 µm-C configuration, to identify designs maximizing capacitance and sensitivity. Additionally, investigation into electrode pin designs is conducted which considers manufacturing feasibility and mechanical stability, utilizing finite element (FE) simulations and experimental validation to assess various options. Novel fabrication techniques, such as upside-down electrode layering and the use of conductive thread paired with conductive carbon grease for electrode connections, aim to streamline manufacturing and enhance reliability. FEM simulations analyze stacked 4EL-DES structures' deformation behavior and the relationship between capacitance change and strain, providing insights into their mechanical and electrical properties under different loading conditions. Experimental results from various sensor configurations, including individual 4EL-DES sensors and stacked and "open" 5EL-DES structures, offer insights into performance capabilities and potential applications. This research contributes to advancing flexible sensor technology, laying the groundwork for high-performance sensors applicable in soft robotics, biomechanics, and beyond.

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Section: Introductionmentioning

confidence: 99%

Influence of stacking on the stability of a multi-layer capacitive dielectric elastomer sensor for strain detection

Prokopchuk,

Ewert,

Menning

et al. 2024

Electroactive Polymer Actuators and Devices (EAPAD) XXVI

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show abstract

“…For a robot to perform tasks based on tactile perception, it is necessary to incorporate a tactile sensor that generates tactile signals. Various types of tactile sensors, such as capacitive [ 4 , 5 ], piezoresistive [ 6 , 7 ], optical [ 8 , 9 ], piezoelectric [ 10 , 11 ], and magnetic sensors [ 12 , 13 ], have been developed for robots to recognize their environments during interactions by generating tactile signals. The signal generated by the aforementioned tactile sensors enables robots to execute sophisticated tasks using robot grippers that were once deemed challenging or unfeasible.…”

Section: Introductionmentioning

confidence: 99%

Effects of Sensing Tactile Arrays, Shear Force, and Proprioception of Robot on Texture Recognition

Yang

Kim

Lim

2023

Sensors

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In robotics, tactile perception is important for fine control using robot grippers and hands. To effectively incorporate tactile perception in robots, it is essential to understand how humans use mechanoreceptors and proprioceptors to perceive texture. Thus, our study aimed to investigate the impact of tactile sensor arrays, shear force, and the positional information of the robot’s end effector on its ability to recognize texture. A deep learning network was employed to classify tactile data from 24 different textures that were explored by a robot. The input values of the deep learning network were modified based on variations in the number of channels of the tactile signal, the arrangement of the tactile sensor, the presence or absence of shear force, and the positional information of the robot. By comparing the accuracy of texture recognition, our analysis revealed that tactile sensor arrays more accurately recognized the texture compared to a single tactile sensor. The utilization of shear force and positional information of the robot resulted in an improved accuracy of texture recognition when using a single tactile sensor. Furthermore, an equal number of sensors placed in a vertical arrangement led to a more accurate distinction of textures during exploration when compared to sensors placed in a horizontal arrangement. The results of this study indicate that the implementation of a tactile sensor array should be prioritized over a single sensor for enhanced accuracy in tactile sensing, and the use of integrated data should be considered for single tactile sensing.

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“…With peripherals, sensor systems can measure, detect, record and even analyze further health conditions of humans, which can also help more accurate diagnoses. Several types of sensors have been developed, including capacitive sensors [ 1 , 2 , 3 , 4 ], piezoresistive sensors [ 5 , 6 ], and piezoelectric sensors [ 7 , 8 ]. The linearity between the input and output, the hysteresis effect of signal feedback, and temperature sensitivity are important specifications regarding the performance of sensors.…”

Section: Introductionmentioning

confidence: 99%

Development of Piezoelectric Silk Sensors Doped with Graphene for Biosensing by Near-Field Electrospinning

Lee

Lin

Hoe

et al. 2022

Sensors

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A novel piezoelectric fiber sensor based on polyvinylidene fluoride piezoelectric (PVDF) doped with graphene is presented. The near-field electrospinning technology was used for developing the sensor. The uniform experimental design method was introduced to determine the ranges of experimental parameters, including the applied voltage, the drum speed range, the graphene doping ratios from 0% to 11 wt% in PVDF solution, and the electrode gap. By experimental results, the conductivities of PVDF solutions with different doping ratios of graphene increased from 19.6 μS/cm to 115.8 μS/cm. Tapping tests were performed to measure the voltages and currents produced by the piezoelectric fibers. The maximum output voltage was 4.56 V at 5 wt% graphene doping ratio in PVDF fibers, which was 11.54 times that of the pure PVDF sensors. Moreover, mechanical properties of the proposed sensor were measured. Motion intention and swallowing test, such as saliva-swallowing and eating, were carried out. When the subject spoke normally, the output voltage of the sensor was between 0.2 and 0.4 V, approximately. Furthermore, when the subject drank water and ate food, the output voltage of the sensor was between 0.5 and 1 V, approximately. The proposed sensor could be used to detect signals of the human body and serve as a wearable device, allowing for more diagnosis and medical treatment.

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Large-Area and Low-Cost Force/Tactile Capacitive Sensor for Soft Robotic Applications

Cited by 25 publications

References 51 publications

Influence of stacking on the stability of a multi-layer capacitive dielectric elastomer sensor for strain detection

Influence of stacking on the stability of a multi-layer capacitive dielectric elastomer sensor for strain detection

Effects of Sensing Tactile Arrays, Shear Force, and Proprioception of Robot on Texture Recognition

Development of Piezoelectric Silk Sensors Doped with Graphene for Biosensing by Near-Field Electrospinning

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