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 proceedingConference proceeding contributionpeer-review

11 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 languageEnglish
Title of host publication2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON)
Subtitle of host publication1st-3rd November, 2018
EditorsSatyajit Chakrabarti, Himadri Nath Saha
Place of PublicationVancouver, Canada
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages832-837
Number of pages6
ISBN (Print)9781538672662
DOIs
Publication statusPublished - 2018
Externally publishedYes
EventIEEE Annual Information Technology, Electronics and Mobile Communication Conference (9th : 2018) - Vancouver, Canada
Duration: 1 Nov 20183 Nov 2018
Conference number: 9th

Conference

ConferenceIEEE Annual Information Technology, Electronics and Mobile Communication Conference (9th : 2018)
Abbreviated titleIEMCON
CountryCanada
CityVancouver
Period1/11/183/11/18

Keywords

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

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