arXiv:2607. 24113v1 Announce Type: cross Abstract: Previous research has shown that a human-like robot's acceptance heavily depends on the setting in which it operates and its ability to perform relevant tasks.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
arXiv:2607. 16428v1 Announce Type: cross Abstract: For a second time, the android robot Andrea was set up at a public museum in Germany for six consecutive days to have conversations with visitors, fully autonomously.
Empathetic social robots should respond not only to what users say, but also to how their emotions dynamically evolve during interaction. However, existing empathetic dialogue systems are often text-c...
arXiv:2607. 24190v1 Announce Type: cross Abstract: Social robots that rely on large language models for conversation are unable to retain information across sessions.
The paper introduces an LLM-based Conversational AI Knowledge Assistant for the Raspberry‑Pi‑powered 13‑Axis MyBuddy humanoid robot. It combines large language model-driven language understanding, real‑time speech recognition, internet‑based knowledge retrieval (e.g., Wikipedia, arXiv), flexible dialogue management, and natural speech synthesis to support intelligent, multi‑turn conversations and emotional‑support interactions. This system aims to overcome the limitations of traditional rule‑based dialogue systems in humanoid robots.
Behaviora is a preliminary conceptual architecture that represents both external and internal behavior of robots and agents in an addressable form. It defines a Behavior Episode composed of components derived from behavior taxonomies, each assigned a persistent Internet of Behaviors (IoB) Address. The architecture also includes a Style Profile to describe how behavior is expressed, an Experience Profile to capture internal state influencing execution, and a Behavior Compiler to translate these representations into platform‑specific actions.
arXiv:2606. 10276v1 Announce Type: cross Abstract: For natural human-robot interaction, a robot must understand human intent expressed not only through language but also through nonverbal signals such as gestures and gaze.