{
  "id": 17355,
  "url": "https://arxiv.org/abs/2608.06221v1",
  "title": "Robot Learning from Human Demonstrations: Handwritten Alphabet Trajectories and Human-Likeness Evaluation",
  "summary": "Learning from demonstration (LfD) provides a developmental framework through which robots can develop motor skills by observing and imitating human dynamics, reducing reliance on explicit programming to teach a skill to a robot. The resulting human-like robot motion is recognised as a key factor in building trust and enabling natural collaboration in human-robot interaction. This paper presents a framework for learning human-like robot motion from demonstration, including data collection, probab",
  "authors": "Alperen Kenan, Paul Bremner, Manuel Giuliani",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": "google",
  "regions": null,
  "published_at": "2026-08-06T16:12:18.000Z",
  "fetched_at": "2026-08-07T05:10:58.501Z",
  "source_slug": "x-arxiv-cs-hc",
  "source_name": "arXiv cs.HC",
  "source_homepage": "https://arxiv.org/list/cs.HC/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/17355",
  "original_url": "https://arxiv.org/abs/2608.06221v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}