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Evaluating State-Based Intention Recognition Algorithms against Human Performance

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Robot Intelligence Technology and Applications 2

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 274))

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Abstract

In this paper, we describe a novel intention recognition approach based on the representation of state information in a cooperative human-robot environment. We compare the output of the intention recognition algorithms to those of an experiment involving humans attempting to recognize the same intentions in a manufacturing kitting domain. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. Based upon a set of predefined high-level states relationships that must be true for future actions to occur, a robot can use the approaches described in this paper to infer the likelihood of subsequent actions occurring. This would enable the robot to better help the human with the operation or, at a minimum, better stay out of his or her way.

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Author information

Authors and Affiliations

  1. LE2i Lab, University of Burgundy, Dijon, France

    Craig Schlenoff & Sebti Foufou

  2. Computer Science and Engineering Department, Qatar University, Doha, Qatar

    Sebti Foufou

Authors
  1. Craig Schlenoff
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  2. Sebti Foufou
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Corresponding author

Correspondence to Craig Schlenoff .

Editor information

Editors and Affiliations

  1. Electrical Engineering, KAIST, Daejeon, Korea, Republic of (South Korea)

    Jong-Hwan Kim

  2. Computer and Information Technology, Purdue University, West Lafayette, Indiana, USA

    Eric T . Matson

  3. Civil and Environmental Engg., KAIST, Daejeon, Korea, Republic of (South Korea)

    Hyun Myung

  4. Department of Mechanical Engineering, Auckland University, Auckland, New Zealand

    Peter Xu

  5. University of Waterloo, Waterloo, Ontario, Canada

    Fakhri Karray

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© 2014 Springer International Publishing Switzerland

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Schlenoff, C., Foufou, S. (2014). Evaluating State-Based Intention Recognition Algorithms against Human Performance. In: Kim, JH., Matson, E., Myung, H., Xu, P., Karray, F. (eds) Robot Intelligence Technology and Applications 2. Advances in Intelligent Systems and Computing, vol 274. Springer, Cham. https://doi.org/10.1007/978-3-319-05582-4_19

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  • DOI: https://doi.org/10.1007/978-3-319-05582-4_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05581-7

  • Online ISBN: 978-3-319-05582-4

  • eBook Packages: EngineeringEngineering (R0)

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