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Towards a Holistic Framework for Explainable Robot Navigation

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Human-Friendly Robotics 2023 (HFR 2023)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 29))

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Abstract

With the rising tendency to deploy autonomous robots, their navigational decisions will strongly influence humans. Robot navigation should be explainable to mitigate the undesirable effects of navigation faults and unexpectedness on people. To contribute to compliance between humans and autonomous robots, we present HiXRoN (Hierarchical eXplainable Robot Navigation)—a comprehensive hierarchical framework for explaining robot navigational choices. Besides providing explanations of robot navigation, our framework encompasses qualitative, quantitative, and temporal strategies for explanation conveyance. We further discuss its possibilities and limitations.

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Author information

Authors and Affiliations

  1. Ulm University, 89081, Ulm, Germany

    Amar Halilovic

  2. University of Sarajevo, 71000, Sarajevo, Bosnia and Herzegovina

    Senka Krivic

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  1. Amar Halilovic
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Correspondence to Amar Halilovic .

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Editors and Affiliations

  1. Technical University of Munich, Munich, Germany

    Cristina Piazza

  2. Technical University of Munich, Munich, Germany

    Patricia Capsi-Morales

  3. Technical University of Munich, Munich, Germany

    Luis Figueredo

  4. German Aerospace Center, Wessling, Germany

    Manuel Keppler

  5. Ludwig Maximilian University, Munich, Germany

    Hinrich Schütze

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Halilovic, A., Krivic, S. (2024). Towards a Holistic Framework for Explainable Robot Navigation. In: Piazza, C., Capsi-Morales, P., Figueredo, L., Keppler, M., Schütze, H. (eds) Human-Friendly Robotics 2023. HFR 2023. Springer Proceedings in Advanced Robotics, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-031-55000-3_15

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