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MIRA: Real-Time Full-Duplex Human-Robot Interaction for Embodied Companions — arXiv:2609.24547

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.24547
License (as archived): CC0-1.0
Archived: 2026-10-09T22:24:29.760Z
SHA-256 of the archived text: 905609a20e864c24bff52d36a34d8ef42b2b114d65e6cf510d36f64838a20b47
Stable URL of this page: https://metraipolis.com/documento/dc_42e71bfb7235

How to cite

MIRA: Real-Time Full-Duplex Human-Robot Interaction for Embodied Companions — arXiv:2609.24547 — arXiv (en), https://arxiv.org/abs/2609.24547 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_42e71bfb7235 (Metraipolis archive dc_42e71bfb7235, sha256 905609a20e864c24bff52d36a34d8ef42b2b114d65e6cf510d36f64838a20b47)

BibTeX

@misc{dc42e71bfb7235,
  title = {MIRA: Real-Time Full-Duplex Human-Robot Interaction for Embodied Companions — arXiv:2609.24547},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.24547},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_42e71bfb7235; sha256 905609a20e864c24bff52d36a34d8ef42b2b114d65e6cf510d36f64838a20b47},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.24547. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

% !TEX root = ../main.tex Real-time embodied companion interaction requires a robot to infer user intent from streaming speech, generate timely responses, and execute expressive, interruptible motions. Existing systems typically decouple dialogue orchestration from gesture synthesis, relying on offline motion generation from complete audio. This separation leaves open how a deployed robot can dynamically synchronize response content, prosodic timing, and physical safety under incremental inputs and uncertain turn boundaries. We present MIRA, a unified framework for real-time full-duplex embodied companion interaction. Given streaming user speech, dialogue history, and vocal affect, MIRA predicts both the response text and an explicit embodiment cue that routes the response to the appropriate physical behavior. Discrete social behaviors (\eg listening and greeting) are mapped to validated robot trajectories, while speaking responses are accompanied by streaming, generative co-speech motion. For co-speech motion generation, we propose ROSCO, a prefix-conditioned diffusion model for streaming audio-to-joint motion generation. We further design RHPC, an inference scheme that maintains a sufficiently long temporal context for motion prediction while bounding physical commitment to a short, interruptible prefix. At the interaction level, we design CORTEX, a dual-timescale interaction policy that combines low-latency barge-in preemption and streaming response generation with deliberative turn decisions, backed by a robot-side execution layer that enforces physical safety constraints during execution. MIRA is deployed on an Astribot S1 humanoid robot. Quantitative evaluations demonstrate competitive audio-motion alignment relative to state-of-the-art motion-generation baselines, while real-robot deployment measurements characterize streaming responsiveness and interruption handling.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-22 in cs.RO).
Categorie arXiv: Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2609.24547 — 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 2026-10-09T21:59:59.733Z dalla pagina https://arxiv.org/catchup/cs.RO/2026-09-22?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).