让机器人在城市公共空间中智能适应复杂人机交互场景。
Robots in the Wild: Contextually-Adaptive Human-Robot Interactions in Urban Public Environments
- 构建能感知并响应城市环境动态的上下文自适应交互机制
- 聚焦真实公共场景中多变的人机互动挑战
- 适合关注具身智能与人机协同的研究者
人类-机器人交互（HRI）正从受控环境转向动态真实的公共空间，这对机器人系统提出了更高的适应性要求。传统算法导航与结构化场景中的交互策略已不足以应对包含多重动态和复杂社会技术需求的城市公共系统。本研讨会旨在突破可预测、半结构化情境的限制，探索城市公共空间中具身自适应人机交互的设计机遇与挑战，并在澳大利亚计算机人机交互研究社区（OzCHI）内建立合作网络。通过持续对话、经验共享与协作，推动未来研究，使机器人能够应对真实世界公共交互中的固有不确定性与复杂性。
原文摘要 · Abstract (English)
The increasing transition of human-robot interaction (HRI) context from controlled settings to dynamic, real-world public environments calls for enhanced adaptability in robotic systems. This can go beyond algorithmic navigation or traditional HRI strategies in structured settings, requiring the ability to navigate complex public urban systems containing multifaceted dynamics and various socio-technical needs. Therefore, our proposed workshop seeks to extend the boundaries of adaptive HRI research beyond predictable, semi-structured contexts and highlight opportunities for adaptable robot interactions in urban public environments. This half-day workshop aims to explore design opportunities and challenges in creating contextually-adaptive HRI within these spaces and establish a network of interested parties within the OzCHI research community. By fostering ongoing discussions, sharing of insights, and collaborations, we aim to catalyse future research that empowers robots to navigate the inherent uncertainties and complexities of real-world public interactions.
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