A Skill-based Robot Co-worker for Industrial Maintenance Tasks

Research output: Research - peer-reviewConference article in Journal

Abstract

This paper investigates the concept of a sensor based robot co-worker working in flexible industrial environments together with and alongside human operators. In this particular work, a realisation of a robot co-worker scenario is developed in order to demonstrate the implementation of a robot co-worker from the starting point of an autonomous industrial mobile manipulator. The cobot is applied on the industrially relevant task of screwing by the use of a skill-based approach. The technical work on the human-robot interface and the screwing skill is described.
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This paper investigates the concept of a sensor based robot co-worker working in flexible industrial environments together with and alongside human operators. In this particular work, a realisation of a robot co-worker scenario is developed in order to demonstrate the implementation of a robot co-worker from the starting point of an autonomous industrial mobile manipulator. The cobot is applied on the industrially relevant task of screwing by the use of a skill-based approach. The technical work on the human-robot interface and the screwing skill is described.
Original languageEnglish
JournalProcedia Manufacturing
Volume11
Pages (from-to)83-90
Number of pages7
ISSN2351-9789
DOI
StatePublished - 19 Sep 2017
Publication categoryResearch
Peer-reviewedYes
EventFAIM 2017 - 27th International Conference on Flexible Automation and Intelligent Manufacturing - Complesso San Geminiano, University of Modena and Reggio Emilia, Modena, Italy
Duration: 27 Jun 201730 Jun 2017
Conference number: 27
http://www.faim2017.org/

Conference

ConferenceFAIM 2017 - 27th International Conference on Flexible Automation and Intelligent Manufacturing
Number27
LocationComplesso San Geminiano, University of Modena and Reggio Emilia
CountryItaly
CityModena
Period27/06/201730/06/2017
Internet address

    Research areas

  • Collaborative Robot, Skill-based Programing, Maintenance task, Screwing operation, Intelligent manufacturing, industry 4.0

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ID: 262736669