关键词: 人智交互, 社交机器人, 具身智能, 情感计算, 系统性文献综述

Abstract:

[Purpose/Significance] Against the backdrop of a strategic transition from industrial efficiency to embodied intelligence within the "Silver-haired Economy," social robots are evolving from functional tools into social companions. However, the field faces a critical bottleneck: a lack of interaction stickiness and empathetic resonance, which leads to high abandonment rates. Affective computing (AC) serves as the core technology to bridge this gap by enabling machines to detect, interpret, and simulate human emotions. Unlike previous literature that often treats AC as a standalone algorithmic task, this research reconstructs the value of AC from a Human-AI Interaction (HAI) perspective. This approach responds to the national "15th Five-Year Plan" requirements for secure and controllable AI governance by integrating technical pathways with ethical boundaries. By situating social robots within complex social relationships, this study provides a theoretical roadmap for robots to transition from mechanical entities to responsible social agents, thereby supporting the high-quality development of population-centric services. [Method/Process] This study employs a systematic literature review methodology guided by the PRISMA framework to ensure scientific rigor and comprehensiveness. The Web of Science Core Collection served as the primary data source, with a search timeframe spanning from 2015 to 2025 to capture the paradigm shifts triggered by deep learning and large-scale language models. A tripartite search logic-integrating subject entities (social robots), core technologies (affective computing), and interaction contexts (human-robot interaction)-was implemented to filter relevant literature. After a multi-level screening process based on embodiment, technical integrity, and empirical validity, 97 high-quality articles were selected. The study utilizes CiteSpace for keyword clustering and citation burst analysis, mapping the evolution of the field across three distinct stages: from foundational signal processing (2018-2019) to dynamic adaptation models (2020-2022), and finally to generative-driven intelligence and ethical regulation (2023-2025). This systematic approach allows for a deep synthesis of multimodal perception technologies, including robust vision, paralinguistic decoding, and physiological signal sensing. [Results/Conclusions] The findings reveal a significant paradigm shift in affective computing for social robots, evolving from simple signal statistics to deep situational understanding and from static rule-based responses to generative dynamic adaptation. The research proposes a holistic interaction framework comprising three pillars: situational understanding, adaptive action, and ethical constraints. Situational understanding leverages multimodal semantic fusion to decode human intent beyond surface-level data, while adaptive action ensures cross-modal consistency in physical expression through generative AI and long-term memory architectures. Ethical constraints are identified as an internal safety mechanism rather than external regulations, addressing risks such as privacy asymmetry, cultural bias in datasets, and psychological manipulation stemming from high anthropomorphism. The study concludes that the future of social robotics lies in three innovative paradigms: enhancing ecological validity through real-world deployment, constructing lifelong learning mechanisms to sustain long-term relationships, and embedding "human-in-the-loop" ethical fuses directly into algorithmic architectures. Despite these advancements, the research is currently limited by a lack of diverse cultural data and long-term field studies. Future research should prioritize cross-cultural design and the development of explainable affective decision-making modules to ensure the sustainable and benevolent development of embodied intelligence in complex social environments.

Key words: Human-AI interaction, social robots, embodied intelligence, affective computing, systematic literature review