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Incremental Policy Refinement by Recursive Regression and Kinesthetic Guidance

Bojan Nemec; Mihael Simonč; Tadej Petrič; Aleš Ude


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{
  "description": "<p>Fast deployment of robot tasks requires appropriate<br>\ntools that enable efficient reuse of existing robot control<br>\npolicies. Learning from Demonstration (LfD) is a popular tool<br>\nfor the intuitive generation of robot policies, but the issue of<br>\nhow to address the adaptation of existing policies has not been<br>\nproperly addressed yet. In this work, we propose an incremental<br>\nLfD framework that efficiently solves the above-mentioned<br>\nissue. It has been implemented and tested on a number of<br>\npopular collaborative robots, including Franka Emika Panda,<br>\nUniversal Robot UR10, and KUKA LWR 4.</p>", 
  "creator": [
    {
      "affiliation": "Jo\u017eef Stefan Institute, Ljubljana, Slovenia", 
      "@type": "Person", 
      "name": "Bojan Nemec"
    }, 
    {
      "affiliation": "Jo\u017eef Stefan Institute, Ljubljana, Slovenia", 
      "@type": "Person", 
      "name": "Mihael Simon\u010d"
    }, 
    {
      "affiliation": "Jo\u017eef Stefan Institute, Ljubljana, Slovenia", 
      "@type": "Person", 
      "name": "Tadej Petri\u010d"
    }, 
    {
      "affiliation": "Jo\u017eef Stefan Institute, Ljubljana, Slovenia", 
      "@type": "Person", 
      "name": "Ale\u0161 Ude"
    }
  ], 
  "headline": "Incremental Policy Refinement by Recursive Regression and Kinesthetic Guidance", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2020-01-31", 
  "url": "https://zenodo.org/record/3632342", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3632342", 
  "@id": "https://doi.org/10.5281/zenodo.3632342", 
  "@type": "ScholarlyArticle", 
  "name": "Incremental Policy Refinement by Recursive Regression and Kinesthetic Guidance"
}
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