Socialization of industrial robots: an innovative solution to improve productivity

Mohammad (Behdad)  Jamshidi; Neda  Alibeigi; Bahareh Oryani; Ali Lalbakhsh; Mohammad  Rajabi Soheyli; Nahid  Rabbani

doi:10.1109/IEMCON.2018.8615104

Socialization of industrial robots: an innovative solution to improve productivity

Mohammad (Behdad) Jamshidi, Neda Alibeigi, Bahareh Oryani, Ali Lalbakhsh, Mohammad Rajabi Soheyli, Nahid Rabbani

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

21 Citations (Scopus)

Abstract

Recently, interacting between humans and machines has been considered as an important factor to develop industries. In this paper, a novel intelligent approach to improve productivity in industrial environments involving both workers and industrial robots is presented. The introduced approach contains an integrated combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and the inverse kinematics method named the Socialization of Industrial Robots (SIR). In this approach, staffs can control and justify robots based on environment conditions and their technical experiences. To evaluate and test the proposed method, a famous six-degree of freedom robotic manipulator called the Stanford University Arm is modeled and simulated in MATLAB. The results of simulation have demonstrated that the proposed approach can be counted as a practicable method to develop industrial systems.

Original language	English
Title of host publication	2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON)
Subtitle of host publication	1st-3rd November, 2018
Editors	Satyajit Chakrabarti, Himadri Nath Saha
Place of Publication	Vancouver, Canada
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	832-837
Number of pages	6
ISBN (Print)	9781538672662
DOIs	https://doi.org/10.1109/IEMCON.2018.8615104
Publication status	Published - 2018
Externally published	Yes
Event	IEEE Annual Information Technology, Electronics and Mobile Communication Conference (9th : 2018) - Vancouver, Canada Duration: 1 Nov 2018 → 3 Nov 2018 Conference number: 9th

Conference

Conference	IEEE Annual Information Technology, Electronics and Mobile Communication Conference (9th : 2018)
Abbreviated title	IEMCON
Country/Territory	Canada
City	Vancouver
Period	1/11/18 → 3/11/18

Keywords

the Adaptive Neuro-Fuzzy Inference System
robotic manipulator
socialization of industrial robots
productivity
inverse kinematics

Access to Document

10.1109/IEMCON.2018.8615104

Cite this

Jamshidi, M., Alibeigi, N., Oryani, B., Lalbakhsh, A., Rajabi Soheyli, M., & Rabbani , N. (2018). Socialization of industrial robots: an innovative solution to improve productivity. In S. Chakrabarti, & H. Nath Saha (Eds.), 2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON): 1st-3rd November, 2018 (pp. 832-837). Article 8615104 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IEMCON.2018.8615104

Jamshidi, Mohammad (Behdad) ; Alibeigi, Neda ; Oryani, Bahareh et al. / Socialization of industrial robots : an innovative solution to improve productivity. 2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON): 1st-3rd November, 2018. editor / Satyajit Chakrabarti ; Himadri Nath Saha. Vancouver, Canada : Institute of Electrical and Electronics Engineers (IEEE), 2018. pp. 832-837

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title = "Socialization of industrial robots: an innovative solution to improve productivity",

abstract = "Recently, interacting between humans and machines has been considered as an important factor to develop industries. In this paper, a novel intelligent approach to improve productivity in industrial environments involving both workers and industrial robots is presented. The introduced approach contains an integrated combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and the inverse kinematics method named the Socialization of Industrial Robots (SIR). In this approach, staffs can control and justify robots based on environment conditions and their technical experiences. To evaluate and test the proposed method, a famous six-degree of freedom robotic manipulator called the Stanford University Arm is modeled and simulated in MATLAB. The results of simulation have demonstrated that the proposed approach can be counted as a practicable method to develop industrial systems.",

keywords = "the Adaptive Neuro-Fuzzy Inference System, robotic manipulator, socialization of industrial robots, productivity, inverse kinematics",

author = "Jamshidi, \{Mohammad (Behdad)\} and Neda Alibeigi and Bahareh Oryani and Ali Lalbakhsh and \{Rajabi Soheyli\}, Mohammad and Nahid Rabbani",

year = "2018",

doi = "10.1109/IEMCON.2018.8615104",

language = "English",

isbn = "9781538672662",

pages = "832--837",

editor = "Satyajit Chakrabarti and \{Nath Saha\}, Himadri",

booktitle = "2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "IEEE Annual Information Technology, Electronics and Mobile Communication Conference (9th : 2018), IEMCON ; Conference date: 01-11-2018 Through 03-11-2018",

}

Jamshidi, M, Alibeigi, N, Oryani, B, Lalbakhsh, A, Rajabi Soheyli, M & Rabbani , N 2018, Socialization of industrial robots: an innovative solution to improve productivity. in S Chakrabarti & H Nath Saha (eds), 2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON): 1st-3rd November, 2018., 8615104, Institute of Electrical and Electronics Engineers (IEEE), Vancouver, Canada, pp. 832-837, IEEE Annual Information Technology, Electronics and Mobile Communication Conference (9th : 2018), Vancouver, British Columbia, Canada, 1/11/18. https://doi.org/10.1109/IEMCON.2018.8615104

Socialization of industrial robots: an innovative solution to improve productivity. / Jamshidi, Mohammad (Behdad) ; Alibeigi, Neda ; Oryani, Bahareh et al.
2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON): 1st-3rd November, 2018. ed. / Satyajit Chakrabarti; Himadri Nath Saha. Vancouver, Canada: Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 832-837 8615104.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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T1 - Socialization of industrial robots

T2 - IEEE Annual Information Technology, Electronics and Mobile Communication Conference (9th : 2018)

AU - Jamshidi, Mohammad (Behdad)

AU - Alibeigi, Neda

AU - Oryani, Bahareh

AU - Lalbakhsh, Ali

AU - Rajabi Soheyli, Mohammad

AU - Rabbani , Nahid

N1 - Conference code: 9th

PY - 2018

Y1 - 2018

N2 - Recently, interacting between humans and machines has been considered as an important factor to develop industries. In this paper, a novel intelligent approach to improve productivity in industrial environments involving both workers and industrial robots is presented. The introduced approach contains an integrated combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and the inverse kinematics method named the Socialization of Industrial Robots (SIR). In this approach, staffs can control and justify robots based on environment conditions and their technical experiences. To evaluate and test the proposed method, a famous six-degree of freedom robotic manipulator called the Stanford University Arm is modeled and simulated in MATLAB. The results of simulation have demonstrated that the proposed approach can be counted as a practicable method to develop industrial systems.

AB - Recently, interacting between humans and machines has been considered as an important factor to develop industries. In this paper, a novel intelligent approach to improve productivity in industrial environments involving both workers and industrial robots is presented. The introduced approach contains an integrated combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and the inverse kinematics method named the Socialization of Industrial Robots (SIR). In this approach, staffs can control and justify robots based on environment conditions and their technical experiences. To evaluate and test the proposed method, a famous six-degree of freedom robotic manipulator called the Stanford University Arm is modeled and simulated in MATLAB. The results of simulation have demonstrated that the proposed approach can be counted as a practicable method to develop industrial systems.

KW - the Adaptive Neuro-Fuzzy Inference System

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KW - socialization of industrial robots

KW - productivity

KW - inverse kinematics

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DO - 10.1109/IEMCON.2018.8615104

M3 - Conference proceeding contribution

SN - 9781538672662

SP - 832

EP - 837

BT - 2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON)

A2 - Chakrabarti, Satyajit

A2 - Nath Saha, Himadri

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Vancouver, Canada

Y2 - 1 November 2018 through 3 November 2018

ER -

Jamshidi M, Alibeigi N, Oryani B, Lalbakhsh A, Rajabi Soheyli M, Rabbani N. Socialization of industrial robots: an innovative solution to improve productivity. In Chakrabarti S, Nath Saha H, editors, 2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON): 1st-3rd November, 2018. Vancouver, Canada: Institute of Electrical and Electronics Engineers (IEEE). 2018. p. 832-837. 8615104 doi: 10.1109/IEMCON.2018.8615104

Socialization of industrial robots: an innovative solution to improve productivity

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Keywords

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