野外机器人：城市公共环境中情境自适应的人机交互
Robots in the Wild: Contextually-Adaptive Human-Robot Interactions in Urban Public Environments
AI总结：
本文提出一个为期半天的 OzCHI 研讨会，探讨城市公共环境中情境自适应 HRI 的设计挑战与协作网络。
摘要：
人机交互（HRI）情境正日益从受控环境转向动态的真实世界公共环境，这要求机器人系统具备更强的适应性。这种适应性可以超越算法导航或结构化环境中的传统 HRI 策略，需要机器人有能力在包含多面动态和各种社会技术需求的复杂城市公共系统中导航。因此，我们提议的研讨会寻求将自适应 HRI 研究的边界扩展到可预测的半结构化情境之外，并突显城市公共环境中可适应机器人交互的机遇。这个为期半天的研讨会旨在探索在这些空间中创建情境自适应 HRI 的设计机遇与挑战，并在 OzCHI 研究共同体内建立一个由相关方组成的网络。通过促进持续讨论、洞见分享与合作，我们旨在激发未来研究，使机器人能够应对真实世界公共交互中固有的不确定性和复杂性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
