OmniRobotHome: A Multi-Camera Platform for Real-Time Multiadic Human-Robot Interaction
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arXiv
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| Auteurs principaux: | , , , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866917451431673856 |
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| author | Lee, Junyoung Han, Sookwan Kim, Jeonghwan Lee, Inhee Choi, Mingi Kim, Jisoo Woo, Wonjung Joo, Hanbyul |
| author_facet | Lee, Junyoung Han, Sookwan Kim, Jeonghwan Lee, Inhee Choi, Mingi Kim, Jisoo Woo, Wonjung Joo, Hanbyul |
| contents | Human-robot collaboration has been studied primarily in dyadic or sequential settings. However, real homes require multiadic collaboration, where multiple humans and robots share a workspace, acting concurrently on interleaved subtasks with tight spatial and temporal coupling. This regime remains underexplored because close-proximity interaction between humans, robots, and objects creates persistent occlusion and rapid state changes, making reliable real-time 3D tracking the central bottleneck. No existing platform provides the real-time, occlusion-robust, room-scale perception needed to make this regime experimentally tractable. We present OmniRobotHome, the first room-scale residential platform that unifies wide-area real-time 3D human and object perception with coordinated multi-robot actuation in a shared world frame. The system instruments a natural home environment with 48 hardware-synchronized RGB cameras for markerless, occlusion-robust tracking of multiple humans and objects, temporally aligned with two Franka arms that act on live scene state. Continuous capture within this consistent frame further supports long-horizon human behavior modeling from accumulated trajectories. The platform makes the multiadic collaboration regime experimentally tractable. We focus on two central problems: safety in shared human-robot environments and human-anticipatory robotic assistance, and show that real-time perception and accumulated behavior memory each yield measurable gains in both. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_28197 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | OmniRobotHome: A Multi-Camera Platform for Real-Time Multiadic Human-Robot Interaction Lee, Junyoung Han, Sookwan Kim, Jeonghwan Lee, Inhee Choi, Mingi Kim, Jisoo Woo, Wonjung Joo, Hanbyul Robotics Computer Vision and Pattern Recognition Human-robot collaboration has been studied primarily in dyadic or sequential settings. However, real homes require multiadic collaboration, where multiple humans and robots share a workspace, acting concurrently on interleaved subtasks with tight spatial and temporal coupling. This regime remains underexplored because close-proximity interaction between humans, robots, and objects creates persistent occlusion and rapid state changes, making reliable real-time 3D tracking the central bottleneck. No existing platform provides the real-time, occlusion-robust, room-scale perception needed to make this regime experimentally tractable. We present OmniRobotHome, the first room-scale residential platform that unifies wide-area real-time 3D human and object perception with coordinated multi-robot actuation in a shared world frame. The system instruments a natural home environment with 48 hardware-synchronized RGB cameras for markerless, occlusion-robust tracking of multiple humans and objects, temporally aligned with two Franka arms that act on live scene state. Continuous capture within this consistent frame further supports long-horizon human behavior modeling from accumulated trajectories. The platform makes the multiadic collaboration regime experimentally tractable. We focus on two central problems: safety in shared human-robot environments and human-anticipatory robotic assistance, and show that real-time perception and accumulated behavior memory each yield measurable gains in both. |
| title | OmniRobotHome: A Multi-Camera Platform for Real-Time Multiadic Human-Robot Interaction |
| topic | Robotics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2604.28197 |