An augmented reality framework for robotic tool-path teaching

Sonia Mary Chacko, Armando Granado, Vikram Kapila

Research output: Contribution to journalConference articlepeer-review

Abstract

Robot manipulators are widely used in industries to automate myriad operations. To address the demand shifts in industries, automated systems such as robots must flexibly adapt in response. Such dynamics often necessitate end-users to reprogram robots to meet the changing industry needs. This leads to a demand for experienced programmers, familiar with proprietary robot software. As one alternative, an augmented reality (AR) framework can offer a user-friendly solution that permits end-users to reprogram robots without any domain expertise. This paper presents an AR teaching (ART) methodology that allows end-users to program varied manipulators in an intuitive and effortless manner for tool-path teaching. The ART method is contrasted with an alternative kinesthetic teaching method for its performance and user experience. Results show that the ART method yields a convenient and time-efficient teaching method and it is recommended by users over the kinesthetic teaching method.

Original languageEnglish (US)
Pages (from-to)1218-1223
Number of pages6
JournalProcedia CIRP
Volume93
DOIs
StatePublished - 2020
Event53rd CIRP Conference on Manufacturing Systems, CMS 2020 - Chicago, United States
Duration: Jul 1 2020Jul 3 2020

Keywords

  • Augmented/mixed reality
  • Human-robot interaction
  • Intuitive robot programming
  • User interface design

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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