Thin Flexible Sheet Handling Using Robotic Hand Equipped with Three-axis Tactile Sensors

Sugiman, Kenji; Jusoh, Mohammad Azzeim Mat; Ohka, Masahiro; Yussof, Hanafiah; Abdullah, Sukarnur Che

doi:10.1016/j.procs.2015.12.332

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Among the identified various tactile sensing principles, capacitive type tactile sensing [1], [8], piezoelectric type sensing [9], piezoresistive type tactile sensing [10], [11], mechanical strain gauges [12] and optical type tactile sensing [13], [14] can be identified as most common types available. They have their own pros and cons based on their applications and scale [2].…”

Section: Introductionmentioning

confidence: 99%

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Design and simulation of MEMS based 5-DOF tactile force sensor

Udayanga

Jayathilaka

Amarasinghe

et al. 2016

2016 Moratuwa Engineering Research Conference (MERCon)

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This paper describes design and simulation of five degrees of freedom (5-DOF) Micro-Electro-Mechanical systems (MEMS) based tactile force sensor. Tactile sensing involves with measuring physical parameters such as force, temperature, etc. with the aid of physical touch. Over the past decades tactile sensors are gaining popularity over non-contact sensors in biomedical and robotic applications. Proposed sensor design with 3mm x 3mm x 300µm dimensions, has the capability to measure not only the magnitude but also the direction of the force applied. A wagon wheel spring structure was proposed, where 8 beams work as springs to relief the force applied. Behavior of these 8 beams are monitored under each loading conditions using defused piezoresistive sensing elements. A finite element analysis of structure was performed to optimize and validate the structure and Multiphysics analysis was performed to validate the working principal of the proposed sensor.

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Section: Introductionmentioning

confidence: 99%

“…Most of the bio-medical and robotics applications, rather than using a single tactile sensor, tactile sensor arrays are being used to acquire the tactile information [14]. Spatial resolution of such tactile sensing array is a critical factor as the performance of the sensor array depends on it [15].…”

Section: Introductionmentioning

confidence: 99%

Design and simulation of MEMS based 5-DOF tactile force sensor

Udayanga

Jayathilaka

Amarasinghe

et al. 2016

2016 Moratuwa Engineering Research Conference (MERCon)

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A Basic Paper Handling Task Experiment Using Tri-axial Tactile Data

Sugiman

Ohka

Jusoh

2017

Procedia Computer Science

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Design and Prototyping Soft Fingers for a Hand Prosthesis with the Aim of Predicting the Gripping Force Using LSTM

Siavashani

Yousefi‐Koma

Vedadi

2021

2021 9th RSI International Conference on Robotics and Mechatronics (ICRoM)

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Hands are used for communicating with the surrounding environment and have a complex structure that enables them to perform various tasks with their multiple degrees of freedom. Hand amputation can prevent a person from performing their daily activities. In that event, finding a suitable, fast, and reliable alternative for the missing limb can affect the lives of people who suffer from such conditions.As the most important use of the hands is to grasp objects, the purpose of this study is to accurately predict gripping force from surface electromyography (sEMG) signals during a pinch-type grip. In that regard, gripping force and sEMG signals are derived from 10 healthy subjects. Results show that for this task, recurrent networks outperform nonrecurrent ones, such as a fully connected multilayer perceptron (MLP) network. Gated recurrent unit (GRU) and long short-term memory (LSTM) networks can predict the gripping force with R-squared values of 0.994 and 0.992, respectively, and a prediction rate of over 1300 predictions per second. The predominant advantage of using such frameworks is that the gripping force can be predicted straight from preprocessed sEMG signals without any form of feature extraction, not to mention the ability to predict future force values using larger prediction horizons adequately. The methods presented in this study can be used in the myoelectric control of prosthetic hands or robotic grippers.

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Thin Flexible Sheet Handling Using Robotic Hand Equipped with Three-axis Tactile Sensors

Cited by 3 publications

References 10 publications

Design and simulation of MEMS based 5-DOF tactile force sensor

Design and simulation of MEMS based 5-DOF tactile force sensor

A Basic Paper Handling Task Experiment Using Tri-axial Tactile Data

Design and Prototyping Soft Fingers for a Hand Prosthesis with the Aim of Predicting the Gripping Force Using LSTM

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