Despite the advancement in robotic grasping and dexterity through haptic information, affective social touch, such as handshaking or reassuring stroking, remains a major challenge in Human-Robot-Interaction. This position paper examines current progress and limitations across artificial intelligence, haptics and robotics research, and proposes a novel multi-model architecture to address these gaps. Drawing inspiration from neurobiology, we decompose affective touch into distinct, specialized subtasks models. By treating affective touch as a distributed, closed-loop perceptual task rather than a monolithic motoric movement, we aim to overcome the "haptic uncanny valley" through a peer-to-peer, state-sharing framework. Our approach supports scalable and cumulative development within a Sim-to-Real pipeline, fostering interdisciplinary collaboration. By enabling haptics, AI, and robotics researchers to contribute independently yet coherently, we outline a pathway toward a unified, expressive system for social robotics.

翻译：尽管通过触觉信息在机器人抓取和灵巧操作方面取得了进展，但情感社交触摸（如握手或安慰性抚摸）在人机交互中仍是一项重大挑战。这篇立场论文审视了人工智能、触觉学和机器人学研究领域的当前进展与局限性，并提出了一种新的多模型架构以弥补这些不足。受神经生物学启发，我们将情感触摸分解为独立、专用的子任务模型。通过将情感触摸视为一种分布式、闭环的感知任务，而非单一的运动行为，我们旨在通过一种对等、状态共享的框架克服“触觉恐怖谷”现象。我们的方法支持在从仿真到现实（Sim-to-Real）的流水线中进行可扩展和累积式开发，并促进跨学科合作。通过使触觉学、人工智能和机器人学的研究者能够独立且协同地贡献，我们为构建社交机器人的统一、富有表现力的系统勾勒出一条路径。