Young Researcher Paper Award 2023
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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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MYU K.K.
Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 35, Number 2(1) (2023)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 365-376
S&M3173 Research Paper of Special Issue https://doi.org/10.18494/SAM4184 Published in advance: December 13, 2022 Published: February 9, 2023 Multilayer-perceptron-based Slip Detection Algorithm Using Normal Force Sensor Arrays [PDF] Hamid Bamshad, Sangwon Lee, Kyungchan Son, Hyemi Jeong, Geonwoo Kwon, and Hyunseok Yang (Received October 25, 2022; Accepted December 5, 2022) Keywords: tactile sensor, robot grasping, slip detection, artificial intelligence
Slip detection is an essential technology for robotic grippers to autonomously grasp unknown objects and can be achieved using a tactile sensor. In this paper, we propose a high-performance multilayer-perceptron-based slip detection algorithm that utilizes only normal force data obtained by frequency selective surface(FSS) sensor arrays. This is achieved in three stages in this study. First, slip and no-slip training data are aggregated such that the data closely resemble those of the real world. Second, the most suitable means of preprocessing the raw sensor output is identified. Third, the classification method with the highest performance is chosen on the basis of a performance comparison among various classification techniques. The online performance of the algorithm is evaluated by conducting two tasks: a simple pick and place task and a task of maintaining a stable grasp of an object whose weight is changing.
Corresponding author: Hyunseok Yang  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Hamid Bamshad, Sangwon Lee, Kyungchan Son, Hyemi Jeong, Geonwoo Kwon, and Hyunseok Yang, Multilayer-perceptron-based Slip Detection Algorithm Using Normal Force Sensor Arrays, Sens. Mater., Vol. 35, No. 2, 2023, p. 365-376. |
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