构建48摄像头家庭平台，实时感知人体与物体，提升人机交互质量。
OmniRobotHome: A Multi-Camera Home Platform for Real-Time Human-Robot Interaction
- 部署48个同步摄像头与机械臂，实现全屋实时无标记人体姿态追踪。
- 实验证明感知精度、覆盖率和实时性下降会显著降低交互质量。
- 适合研究人机交互、智能机器人和家庭自动化领域的研究人员。
家用机器人需持续感知周围人员，但以往研究多依赖有限或离线的感知方式。本文认为感知质量是决定家庭交互能力的关键因素，并构建了OmniRobotHome测试平台来验证该观点。该平台在带家具的住宅中部署了48个硬件同步摄像头和3个机械臂，统一于同一世界坐标系，可实时提供无标记全身人体姿态、6D物体位姿、前瞻运动预测，以及一个能与居民对话的社交虚拟代理。通过该平台，我们将感知质量作为实验变量，考察其对安全性、人类辅助和社交互动的影响，发现当实时性、粒度、覆盖范围、准确性、预测能力或记忆功能减弱时，交互质量均出现明显下降。所有代码与数据将公开发布。
原文摘要 · Abstract (English)
Robots in homes must continuously sense the people around them, yet most prior work relies on limited or offline perception. We argue that perception quality is the dominant factor governing what interaction is achievable at home, and build a testbed to test this claim. OmniRobotHome instruments a furnished home with 48 hardware-synchronized cameras and three manipulators in a unified world frame, delivering real-time markerless full-body human pose, 6D object pose, anticipatory motion forecasting, and a social avatar agent that converses with residents. Using the platform, we treat perception quality as an experimental variable across safety, human assistance, and social interaction, and find that interaction quality degrades measurably as real-timeness, granularity, coverage, accuracy, forecasting, or memory is weakened. All code and data will be released.
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