发表机构
University of Florence; University of Modena and Reggio Emilia; University of Siena（佛罗伦萨大学; 摩德纳和雷焦艾米利亚大学; 锡耶纳大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对机器人间交互缺乏大规模基准的问题，提出R2RI数据集，包含多视角事件与RGB数据，支持感知与交互任务，推动该领域研究。
AI 中文摘要
理解和建模自主智能体之间的交互是机器人学中的一个基本挑战，对协作系统、社交机器人以及人机共存具有广泛影响。尽管机器人交互研究已成为一个引人注目的研究方向，但由于缺乏大规模基准数据集，其进展受到严重阻碍。在本文中，我们介绍了机器人间交互（R2RI），这是第一个专门针对机器人-机器人交互（RRI）任务设计的数据集。R2RI包含不同的人形机器人以及基于真实人类社交行为建模的逼真交互。数据集提供互补的视角，即每个机器人机载传感器提供的自我中心视角和外部固定相机提供的异中心视角，从而能够对交互动态进行丰富的空间和上下文理解。该数据集包含超过650万帧和约5000个视频，帧率为120fps，涵盖事件和RGB域。我们研究了每个域的优缺点，并针对一系列关键的感知和基于交互的任务比较了最先进的方法。我们在此https URL公开发布该数据集及其所有任务和模态的标注。
英文摘要
Understanding and modeling interactions between autonomous agents is a fundamental challenge in robotics, with broad implications for collaborative systems, social robotics, and human-robot coexistence. Although the study of robot interactions has emerged as a compelling research direction, progress has been severely hampered by the absence of large-scale benchmarks. In this paper, we introduce Robot-to-Robot Interaction (R2RI), the first dataset specifically designed to address the Robot-Robot Interaction (RRI) task. R2RI consists of different humanoid robots and realistic interactions modeled on real human social behaviors. Complementary viewpoints are available, \textit{i.e.}, an egocentric perspective from each robot's onboard sensors, and an exocentric perspective from external fixed cameras, thus enabling rich spatial and contextual understanding of the interaction dynamics. The dataset comprises more than $6.5$M frames and $\approx5000$ videos at $120$ fps, including Event and RGB domains. We investigate pros and cons of each domain, comparing state-of-the-art approaches for a number of key sensing and interaction based tasks. We publicly release the dataset and its annotations for all tasks and modalities at https://github.com/MagriniGabriele/R2RI.
