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<http://opendata.unex.es/recurso/ciencia-tecnologia/investigacion/publicaciones/Publicacion/2021-105> ou:urlOrcid <https://research.aston.ac.uk/en/publications/60bff30d-c585-41b0-a1d4-ffebf165588d>;
    dcterms:publisher "Advances in Intelligent Systems and Computing";
    dcterms:creator "Baghel R.";
    bibo:eissn "2194-5365";
    vivo:identifier "2021-105";
    a ou:Publicacion;
    ou:tipoPublicacion "Conference Paper";
    bibo:doi "10.1007/978-3-030-62579-5_13";
    dcterms:title "A Toolkit to Generate Social Navigation Datasets";
    dcterms:contributor "Baghel R., Kapoor A., Bachiller P., Jorvekar R.R., Rodriguez-Criado D., Manso L.J.";
    fabio:hasPublicationYear "2021";
    bibo:issn "2194-5357";
    bibo:volume "1285";
    vcard:url <https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85097425762&origin=inward>;
    ou:urlScopus <https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85097425762&origin=inward>;
    bibo:page_range "180-193";
    ou:vecesCitado "3";
    ou:eid "2-s2.0-85097425762";
    bibo:isbn "9783030625788";
    ou:bibtex "@inproceedings{60bff30dc58541b0a1d4ffebf165588d,\n  title     = 'A Toolkit to Generate Social Navigation Datasets',\n  abstract  = 'Social navigation datasets are necessary to assess social navigation algorithms and train machine learning algorithms. Most of the currently available datasets target pedestrians{\\textquoteright} movements as a pattern to be replicated by robots. It can be argued that one of the main reasons for this to happen is that compiling datasets where real robots are manually controlled, as they would be expected to behave when moving, is a very resource-intensive task. Another aspect that is often missing in datasets is symbolic information that could be relevant, such as human activities, relationships or interactions. Unfortunately, the available datasets targeting robots and supporting symbolic information are restricted to static scenes. This paper argues that simulation can be used to gather social navigation data in an effective and cost-efficient way and presents a toolkit for this purpose. A use case studying the application of graph neural networks to create learned control policies using supervised learning is presented as an example of how it can be used.',\n  keywords  = 'Navigation dataset, Robot simulation, Social navigation, Social robotics',\n  author    = 'Rishabh Baghel and Aditya Kapoor and Pilar Bachiller and Jorvekar, {Ronit R.} and Daniel Rodriguez-Criado and Manso, {Luis J.}',\n  note      = '{\\textcopyright} 2020 The Authors; 21st International Workshop of Physical Agents (WAF2020) ; Conference date: 19-11-2020 Through 20-11-2020',\n  year      = '2020',\n  month     = nov,\n  day       = '3',\n  doi       = '10.1007/978-3-030-62579-5_13',\n  language  = 'English',\n  isbn      = '978-3-030-62578-8',\n  series    = 'Advances in Intelligent Systems and Computing',\n  publisher = 'Springer',\n  pages     = '180--193',\n  editor    = 'Bergasa, {Luis M.} and Manuel Oca{\\~n}a and Rafael Barea and Elena L{\\'o}pez-Guill{\\'e}n and Pedro Revenga',\n  booktitle = 'Advances in Physical Agents II - Proceedings of the 21st International Workshop of Physical Agents WAF 2020',\n  address   = 'Germany',\n}";
    ou:publicadaEnRevista <http://opendata.unex.es/recurso/ciencia-tecnologia/investigacion/revistas/Revista/2021-24376>.
<http://opendata.unex.es/recurso/educacion/universidad/personal/0eabafa30f2481975f11f68ed070d4f7-luis-jesus-manso-fernandez-arguelles> ou:tienePublicacion <http://opendata.unex.es/recurso/ciencia-tecnologia/investigacion/publicaciones/Publicacion/2021-105>.
<http://opendata.unex.es/recurso/educacion/universidad/personal/ae8a4eaf8939a6063f9754ec345f8b9a-pilar-bachiller-burgos> ou:tienePublicacion <http://opendata.unex.es/recurso/ciencia-tecnologia/investigacion/publicaciones/Publicacion/2021-105>.