Intention recognition in manufacturing applications

Craig Schlenoff, Zeid Kootbally, Anthony Pietromartire, Marek Franaszek, Sebti Foufou

Research output: Contribution to journalArticle

Abstract

In this article, we present a novel approach to intention recognition, based on the recognition and representation of state information in a cooperative human-robot environment. States are represented by a combination of spatial relations along with cardinal direction information. The output of the Intention Recognition Algorithms will allow a robot to help a human perform a perceived operation or, minimally, not cause an unsafe situation to occur. We compare the results of the Intention Recognition Algorithms to those of an experiment involving human subjects attempting to recognize the same intentions in a manufacturing kitting domain. In almost every case, results show that the Intention Recognition Algorithms performed as well, if not better, than a human performing the same activity.

Original languageEnglish (US)
Pages (from-to)29-41
Number of pages13
JournalRobotics and Computer-Integrated Manufacturing
Volume33
DOIs
StatePublished - Jan 1 2015

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Recognition Algorithm
Manufacturing
Robots
Robot
Spatial Relations
Human
Output
Experiments
Experiment

Keywords

  • Human-robot collaboration
  • Intention recognition
  • Manufacturing kitting
  • Ontology
  • Robotics
  • State recognition

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Cite this

Intention recognition in manufacturing applications. / Schlenoff, Craig; Kootbally, Zeid; Pietromartire, Anthony; Franaszek, Marek; Foufou, Sebti.

In: Robotics and Computer-Integrated Manufacturing, Vol. 33, 01.01.2015, p. 29-41.

Research output: Contribution to journalArticle

Schlenoff, Craig ; Kootbally, Zeid ; Pietromartire, Anthony ; Franaszek, Marek ; Foufou, Sebti. / Intention recognition in manufacturing applications. In: Robotics and Computer-Integrated Manufacturing. 2015 ; Vol. 33. pp. 29-41.
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