iMaC: Translating Actions into Motion and Contact Images for Embodied World Models
Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventional embodied frameworks rely on low-dimensional structured action vectors (e.g., joint angles and end-effector poses), which suffer from limited expressive capacity, poor generalization across diverse embodiments, and unnatural dynamic modeling for complex physical interactions. To address these limitations, this paper proposesiMac (Image as Action Control), a novel unified control paradigm that treats raw visual images as native action representations for embodied world models. Departing from traditional explicit kinematic action encoding, ...
| Authors | Zhenyu Wu, Xiuwei Xu, Yukun Zhou et al. |
|---|---|
| Primary category | cs.RO |
| Published | 8 June 2026 |
| Last updated at source | 8 June 2026 |
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