arXiv Computer Vision October 9, 2026 By Boyao Han, Chen Shi, Jingjing Qian, ZhuoTan Tian, Li Jiang

VersaCamVLA: Camera-Configurable VLA Policies for Robotic Manipulation

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VersaCamVLA introduces a camera‑configurable framework that separates camera‑set representation from action learning in Vision‑Language‑Action models. It learns a unified scene‑token interface that maps any number of posed RGB views into fixed‑size latent tokens using multi‑signal target‑view prediction and Wrist‑Augmented Pose Sampling. At deployment, a lightweight spatial encoder injects these tokens into a pretrained VLA, enabling robust manipulation without explicit 3D sensing or novel‑view rendering, and consistently outperforms prior methods across varying camera counts and unseen poses.

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