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Pack It My Way: Triadic Human-Robot Collaboration for Personalized Autonomous Packing — arXiv:2609.04620

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.04620
License (as archived): CC0-1.0
Archived: 2026-10-16T23:48:55.297Z
SHA-256 of the archived text: e70e88094ec66e62631aa9474e88ca9fd25546d88fe950592ee724822e74952a
Stable URL of this page: https://metraipolis.com/documento/dc_df14c19c7ef9

How to cite

Pack It My Way: Triadic Human-Robot Collaboration for Personalized Autonomous Packing — arXiv:2609.04620 — arXiv (en), https://arxiv.org/abs/2609.04620 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_df14c19c7ef9 (Metraipolis archive dc_df14c19c7ef9, sha256 e70e88094ec66e62631aa9474e88ca9fd25546d88fe950592ee724822e74952a)

BibTeX

@misc{dcdf14c19c7ef9,
  title = {Pack It My Way: Triadic Human-Robot Collaboration for Personalized Autonomous Packing — arXiv:2609.04620},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.04620},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_df14c19c7ef9; sha256 e70e88094ec66e62631aa9474e88ca9fd25546d88fe950592ee724822e74952a},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.04620. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Personalized autonomous packing requires robots to account for resident preferences that cannot be inferred from scene geometry alone. Expert teleoperators can interpret these preferences and translate them into feasible robot actions, but continuous expert involvement limits scalable deployment. In this paper, we investigate triadic human-robot collaboration among a resident, a correction mediator, and a robot by comparing human-expert and voice-agent mediation. We evaluate the two conditions in a user study across Protection, Compactness, andGrouping tasks, using a Show-Correct-Generalize process to assess preference correction and subsequent generalization after the surrounding objects are rearranged. Results show that voice-agent mediation achieves outcomes comparable to human-expert mediation in two of the three preference categories, despite receiving shorter and less detailed instructions. Both mediators are similarly easy to use, although the human expert is perceived as more reliable. These findings demonstrate the potential of voice agents to reduce expert involvement while identifying perceived reliability and preference generalization as remaining challenges.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-07 in cs.RO).
Categorie arXiv: Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2609.04620 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-16T23:21:38.628Z dalla pagina https://arxiv.org/catchup/cs.RO/2026-09-07?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).