Soft Body Belt-Type Touch Sensor With Impact Resistance: A Study of Dynamic Behavior

Liu, Sophia L.; Cai, Haiyuan; Liu, Chang

doi:10.1109/access.2021.3112391

Cited by 2 publications

(2 citation statements)

References 22 publications

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“…On the other hand, the development of new force sensors with unconventional methods and systems that utilize these sensors is also being actively pursued. Liu et al [34] have developed a unique soft tubeshaped sensor based on the pneumatic conversion principle as a touch sensor for smart furniture. This sensor is superior in that it can be used on soft furniture materials such as beds, but this method also requires physical deformation of the tube, making it difficult to embed or affix the sensor to nearly non-deformable furniture such as tables.…”

Section: Force Sensormentioning

confidence: 99%

“…This is followed by a description of the elements that make up the system. Electrostatic Touch Sensor ✓ ✓ ✓ n/a Parilusyan et al [30] Electrostatic Touch Sensor ✓ ✓ ✓ n/a Wu et al [31] Electrostatic Touch Sensor ✓ ✓ ✓ n/a Lee et al [32] Force sensor ✓ ✓ n/a n/a Cheng et al [33] Force sensor ✓ ✓ n/a n/a Liu et al [34] Force sensor ✓ ✓ n/a n/a Choi et al [35] Force sensor ✓ ✓ n/a n/a Kawakatsu et al [36] Vibration sensor ✓ ✓ n/a ✓ Yasha et al [37] VPU sensor n/a ✓ n/a ✓ Our System Vibration sensor ✓ ✓ ✓ ✓ ✓: it fulfills the requirement. n/a: it does not fulfill the requirement.…”

Section: B Overview Of the Proposed Systemmentioning

confidence: 99%

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Smatable: A Vibration-Based Sensing Method for Making Ordinary Tables Touch-Interfaces

Yoshida,

Matsui,

Ishiyama

et al. 2023

IEEE Access

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In recent years, the equipment that makes up smart homes is required not only to be functional, but also to be integrated with the design and aesthetics of the living space. Among them, interfaces that directly touch the human eye and hands are the key to maintaining design, but there were many issues in terms of integration with design and aesthetics of living spaces. In this paper, we propose an interface system that operates existing furniture by touching it as a new interface that integrates beautifully into the living space. The proposed system detects user operations with four small vibration sensors attached to hidden locations of existing furniture and uses deep learning to learn the vibrations when a person touches the furniture. Using this method, thick materials difficult to achieve with normal capacitive touch sensors can be utilized. In the experiment, a dining table was used as a representative piece of furniture, and the accuracy of detecting the direction in which three participants swiped in four directions on the table was verified. As a result of the experiment, the accuracy was confirmed by Leave-One-Person-Out-Cross-Validation using 3 sessions of swipe data for each individual for 3 participants, and the accuracy was 0.67. Furthermore, we verified the accuracy of a trained model created by adding only one session of evaluation target data to each learning dataset used in the Leave-One-Person-Out-Cross-Validation. As a result, the accuracy reached 0.90, achieving practical precision.

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Section: Force Sensormentioning

confidence: 99%

Section: B Overview Of the Proposed Systemmentioning

confidence: 99%

Smatable: A Vibration-Based Sensing Method for Making Ordinary Tables Touch-Interfaces

Yoshida,

Matsui,

Ishiyama

et al. 2023

IEEE Access

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High‐Load Capable Soft Tactile Sensors: Incorporating Magnetorheological Elastomer for Accurate Contact Detection and Classification of Asymmetric Mechanical Components

Lim,

Yoon

2024

Advanced Intelligent Systems

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Soft tactile sensors are soft and sufficiently flexible for attachment to a robot's gripper to enhance human‐like sensory capabilities. However, existing tactile sensors exhibit large size and a limited force measurement range. This article presents a novel design of a new soft tactile sensor for a robotic gripper, incorporating a sandwich‐like multilayered structure, together with a deep learning (DL) model, which overcomes the limitations of traditional sensors. The structure consists of three distinct layers: a 15 wt% iron magnetorheological elastomer, a flexible printable circuit board layer equipped with three‐dimensional Hall sensors (TLE493D; Infineon), and permanent magnets. Additionally, a multilayer perceptron network that can classify the loading state is adopted for the DL model. This new tactile sensor is capable of performing three distinct functions simultaneously: measurement of normal forces up to 3.73 kgf, identification of the precise location of force occurrence by subdivision into intervals of 2.5 mm, and differentiation between a wide (≈8 mm) and narrow (≈2 mm) contacted surface area. This newly developed soft tactile sensor has considerable potential for improvement in the performance of robotic grippers through its high accuracy, resolution, and large measurement range, as demonstrated by experimentation with the sensor attached to a real gripper.

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Soft Body Belt-Type Touch Sensor With Impact Resistance: A Study of Dynamic Behavior

Cited by 2 publications

References 22 publications

Smatable: A Vibration-Based Sensing Method for Making Ordinary Tables Touch-Interfaces

Smatable: A Vibration-Based Sensing Method for Making Ordinary Tables Touch-Interfaces

High‐Load Capable Soft Tactile Sensors: Incorporating Magnetorheological Elastomer for Accurate Contact Detection and Classification of Asymmetric Mechanical Components

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