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Issue title: Special Section: Fuzzy theoretical model analysis for signal processing
Guest editors: Valentina E. Balas, Jer Lang Hong, Jason Gu and Tsung-Chih Lin
Article type: Research Article
Authors: Li, Yua; 1 | Yuan, Kuna; 1 | Cai, Qiana; *; 1 | Yu, Fengyuana; 1 | Cai, Chengfenga; 1 | Li, Xiaoyingb | Liu, Pengfenga | Qian, Meiyua | Yu, Juana | Peng, Xiaomeic | Chen, Hongguana | Qin, Runtiana | Wang, Ziweia | Huang, Nanxia | Liu, Konglinga | Cheng, Zhid
Affiliations: [a] Wuhan Textile University, Wuhan, China | [b] China University of Geosciences, Wuhan, China | [c] The Anqing Technology Transfer Center of Wuhan Textile University, Anqing, China | [d] Wuhan University of Technology, Wuhan, China
Correspondence: [*] Corresponding author. Qian Cai, Wuhan Textile University, Wuhan, China. Tel.: +86 13971355418; E-mail: [email protected].
Note: [1] Co-first author.
Abstract: People can rely on complex tactile systems to perceive the basic physical properties of an object, and take the corresponding action and pressure to grab the object. However, this task is not easy for mechanical manipulator. The feedback of most manipulators is limited to pressure, it is difficult for manipulators to identify the other properties of the object by touch. A new manipulator method is designed in this paper. The tactile images are reflected by flexible tactile sensor in this manipulator system. A large number of tactile images are used to build training set by which the capsule network is trained to evaluate images. When an object is captured by a manipulator, and parameters such as shape, rigidity, weight and density of target objects are analyzed. Pseudo color transformation of tactile images is performed, in this way, the changes of each parameter of tactile signals can be observed visibly. It is innovative to process the tactile image by using capsule network and realize the evolutionary bionic tactile function.
Keywords: Capsule network, image processing, bionic manipulator, pseudo color image
DOI: 10.3233/JIFS-179302
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4677-4685, 2019
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