Planning Human-Robot Interaction Tasks using Graph Models

Luis J. Manso, Pablo Bustos, Rachid Alami, Gregoire Milliezf

    Research output: Chapter in Book/Published conference outputConference publication


    Human-robot interaction is a complex field of robotics inwhich robots are required to deal with different challenging issues. Amongother skills, HRI-capable robots need to generate plans taking humansinto account. To achieve this robots require sufficiently efficient datastructures and rich information about their environment as well as abouthumans and their abilities. An additional requirement when robots aresupposed to actively find and classify objects is the capability of reason-ing about the creation and retyping of the symbols corresponding to theobjects as a result of the actions of their plans. This paper describes howthese requirements can be met using a combination of dynamic graph-like world models and a planning system based on graph-rewriting rules.To demonstrate how the approach can be applied, the paper builds upona robot butler use-case, describing how its world model is structured andits most relevant planning rules. Qualitative and quantitative experimen-tal results are also provided.
    Original languageEnglish
    Title of host publicationInternational Workshop on Recognition and Action for Scene Understanding
    Publication statusPublished - 28 Oct 2015

    Bibliographical note

    © 2015 The Authors


    Dive into the research topics of 'Planning Human-Robot Interaction Tasks using Graph Models'. Together they form a unique fingerprint.

    Cite this