Vision as Proprioception: Estimating Humanoid Robot Pose from Video
Estimating a humanoid robot's internal state from video has a wide range of real-world applications but remains unexplored. During interactions with a robot, its onboard state information may be unavailable due to privacy, ownership, or communication constraints. Meanwhile, online and AI-generated robot videos provide rich sources of data but typically lack corresponding joint configurations, limiting their direct use in robot learning. To address these issues, we present HumanoidPose, a new framework that treats vision as proprioception to recover full-body joint configurations in world space from video alone. Specifically, we combine pretrained human-pose features with robot kinematics ...
| Authors | Jiaxi Jiang, Matthias Heyrman, René Zurbrügg et al. |
|---|---|
| Primary category | cs.RO |
| Published | 18 October 2026 |
| Last updated at source | 18 October 2026 |
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