为机器人头像Kim加入个性记忆模块，提升人机互动中的亲和力与信任感。
Not Forgotten: Implementation and Evaluation of a Personalized Episodic Memory for the Humanoid Robot Head Kim
- 用向量语义检索+记忆强度评分，实现对话中个性化历史信息召回。
- 43人实验显示，记忆模块显著提升亲和力（d=0.56）与可信度（d=0.62）。
- 记忆调用不引发不适，适合需建立长期关系的社交机器人场景。
依赖大语言模型的社交机器人无法跨会话保留信息，违背社会预期，阻碍持久关系形成。本文提出一种轻量级情景记忆模块，结合基于向量的语义检索与大语言模型控制的对话系统，部署于人形机器人头像Kim上。该模块采用混合打分函数，融合余弦相似度与记忆强度指标，检索并注入相关历史交互内容至生成提示。在43名参与者参与的视频在线对照研究中，使用人机交互评估量表（HRIES）进行评估。结果显示，情景记忆显著提升感知亲和力（d = 0.60, p < .001），对可信度（d = 0.62）与温暖感（d = 0.56）影响最强；感知干扰无变化（d = 0.00），表明个性化回忆机制未引发隐私担忧或诡异感。结果表明，情景记忆可作为具身人机交互中的社交润滑剂，提升关系质量且不引发负面情绪。
原文摘要 · Abstract (English)
Social robots that rely on large language models for conversation are unable to retain information across sessions. This absence of memory violates social expectations, potentially preventing the formation of persistent relationships. This paper presents a lightweight episodic memory module that integrates vector-based semantic retrieval with an LLM-controlled dialog system, deployed on the humanoid robot head Kim. The module employs a hybrid scoring function combining cosine similarity with a memory strength metric to retrieve contextually relevant past interactions and inject them into the generation prompt. The system was evaluated in a within-subjects video-based online study (N = 43) using the Human-Robot Interaction Evaluation Scale (HRIES). Results show that episodic memory significantly increased perceived sociability (d = 0.60, p < .001), with the strongest effects on perceived trustworthiness (d = 0.62) and warmth (d = 0.56). Perceived disturbance remained unchanged (d = 0.00), indicating that the implemented approach to personalized recall did not trigger privacy-related discomfort or uncanny valley effects. These findings suggest that episodic memory serves as a social lubricant in embodied Human-Robot Interaction, enhancing relational quality without eliciting negative affective responses.
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