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This paper reviews socially appealing design and implementation methods for social robots published between 2020 and 2024, focusing on three critical traits: human-like communication, emotional intelligence, and personality. Analyzing 29 recent empirical studies, we highlight key trends in human-robot interaction (HRI). Recent advancements in natural language processing (NLP) and multimodal interaction, such as Large Language Models (LLMs) and context-aware frameworks, have significantly improved robots’ ability to handle complex conversations and interact effectively in multi-party settings. Generative Adversarial Networks (GANs) have enhanced robots’ expressiveness by generating non-verbal cues like co-speech gestures. Advances in emotion recognition, including multimodal data fusion and physiological sensors, have led to more responsive and emotionally intelligent robots with pleasant personalities. These developments indicate a shift towards robots that not only offer functional assistance but also emotional support, enhancing overall user satisfaction and engagement.

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Am I a Social Buddy? A Literature Review on Socially Appealing Design and Implementation Methods for Social Robots

  • 会议论文

  • 发表日期：

    2025年

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  • Andreea Ioana Niculescu,
  • Kheng Hui Yeo,
  • Jochen Ehnes

摘要

This paper reviews socially appealing design and implementation methods for social robots published between 2020 and 2024, focusing on three critical traits: human-like communication, emotional intelligence, and personality. Analyzing 29 recent empirical studies, we highlight key trends in human-robot interaction (HRI). Recent advancements in natural language processing (NLP) and multimodal interaction, such as Large Language Models (LLMs) and context-aware frameworks, have significantly improved robots’ ability to handle complex conversations and interact effectively in multi-party settings. Generative Adversarial Networks (GANs) have enhanced robots’ expressiveness by generating non-verbal cues like co-speech gestures. Advances in emotion recognition, including multimodal data fusion and physiological sensors, have led to more responsive and emotionally intelligent robots with pleasant personalities. These developments indicate a shift towards robots that not only offer functional assistance but also emotional support, enhancing overall user satisfaction and engagement.