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EDITORIAL article

Front. Robot. AI

Sec. Robot Design

This article is part of the Research TopicInnovative Methods in Social Robot Behavior GenerationView all 6 articles

Editorial: Innovative Methods in Social Robot Behavior Generation

Provisionally accepted
  • 1Honda Research Institute USA Mountain View, Mountain View, United States
  • 2Universitat Augsburg, Augsburg, Germany
  • 3Institut de Robotica i Informatica Industrial, Barcelona, Spain
  • 4Handong Global University, Pohang-si, Republic of Korea
  • 5Sorbonne Universite, Paris, France

The final, formatted version of the article will be published soon.

As social robots become increasingly embedded in our homes, workplaces, and educational settings, 2 the demand for more intuitive, adaptive, and socially aware behavior generation has never been greater. This research topic "Innovative Methods in Social Robot Behavior Generation" was conceived to address 9 this challenge. It brings together contributions that push the boundaries of how social robots perceive, plan, 10 and act in ways that are meaningful, relevant, and "natural". The selected works span technical innovations, 11 empirical field studies, and a systematic analysis towards the shared goal of creating autonomous robotic 12 systems capable of engaging humans through meaningful and contextually appropriate behaviors. The five articles in this collection collectively advance three core themes: As large language models (LLMs) become increasingly integrated into social robots, understanding how

Keywords: Social Robots, behavior generation, Generative models, Multimodal perception, Large language models

Received: 08 Nov 2025; Accepted: 18 Nov 2025.

Copyright: © 2025 Javed, Nasir, Andriella, LEE and Chetouani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Hifza Javed, hifzajaved1@gmail.com

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