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Hand gesture-based on-line programming of industrial robot manipulators

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019
PublisherIEEE
Pages827-834
Number of pages8
ISBN (Electronic)9781728129273
DOIs
Publication statusPublished - 1 Jul 2019
Publication typeA4 Article in a conference publication
EventIEEE International Conference on Industrial Informatics - Helsinki, Helsinki, Finland
Duration: 22 Jul 201925 Jul 2019
https://www.indin2019.org/

Publication series

NameIEEE International Conference on Industrial Informatics (INDIN)
ISSN (Print)1935-4576

Conference

ConferenceIEEE International Conference on Industrial Informatics
Abbreviated titleINDIN '19
CountryFinland
CityHelsinki
Period22/07/1925/07/19
Internet address

Abstract

Robots are widely used in industrial manufacturing processes and play an important role in the enhancement of industrial organizations productivity. One of the major issues that engineers are facing is that, current programming methods are too time-consuming and they lack of intuitiveness use by human users. However, the latest advances in the field of sensors, let manufacturers to develop and produce devices that allow humans to interact with machines in a more intuitive way, reducing the need of additional complex software components, and hence, the required time to establish the aforementioned human-machine interactions. This research work presents an approach for gesture-based on-line programming of industrial robot manipulators. This is achieved by utilizing a combination of devices with a set of integrated, cost-effective visual and bending sensors, in order to precisely track the user's hand position and gestures at system run-time. This continuous tracking allows the robot manipulator to mimic the operator's hand motion. In addition, desired paths performed by a human with expertise on task execution, are translated into robot targets, composing a new robot path, and are stored for later use. Such path can be modified to fit into different robot manufacturers, programming language. Further steps of the presented approach will include the possibility of path optimization by the industrial manipulator itself.

Keywords

  • Gesture recognition, Human-Robot Interaction, Industrial automation, Multi-modal on-line programming, Robotics

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