{
  "abstract": "A method for controlling an embodied agent involves retrieving visual representations of an environment in which the agent engages in an activity. The visual representations or data derived therefrom are processed using one or more high-level control (HLC) machine learning models to generate HLC output. Based on this output, a shortlist of two or more eligible low-level control (LLC) strategies is identified from a superset of candidates. Skill descriptor metadata associated with the eligible LLC strategies is analyzed, and one strategy is selected. The visual representations or data derived therefrom are then processed using one or more LLC machine learning models associated with the selected strategy to generate LLC output. A control signal for the embodied agent is generated based on this LLC output. The activity can include racket sports, locomotion, or object manipulation.",
  "assignees": [
    "GDM HOLDING LLC"
  ],
  "authors": [
    "ABEYRUWAN SAMINDA WISHWAJITH",
    "D'AMBROSIO DAVID B",
    "GRAESSER LAURA HARDING",
    "SANKETI PANNAG R"
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    "name": "Creative Commons Attribution 4.0 International",
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  "source_date": "2026-02-12",
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  "title": "Adaptive robotic control utilizing high-level and low-level strategies",
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