{
  "id": 19047,
  "url": "https://arxiv.org/abs/2608.11876v1",
  "title": "D3D-GEN: Robot-Aware Domain-Grounded Interactive 3D World Generation for Social Robotics",
  "summary": "Training and validation of Embodied AI for social navigation critically depends on realistic simulation environments, yet many current approaches fail to find a balance between realism and simulability. We propose D3D-GEN, a novel world generation system that combines a domain agent with a retrieval-augmented generation (RAG) pipeline grounded in that domain. Our system enables users to rapidly generate domain-grounded, fully interactive 3D worlds by automating both the collection of domain know",
  "authors": "Anh Duc Do, Volodymyr Scherbyna, Tai Duc Nguyen, Spaarsh Thakkar, Zhengcheng Shen, Teham Buiyan, Archan Misra, Linh Kästner",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-12T10:03:01.000Z",
  "fetched_at": "2026-08-13T05:10:37.786Z",
  "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/19047",
  "original_url": "https://arxiv.org/abs/2608.11876v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}