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VISTA: Visually Inferred Spatial ConTact Attention for Contact-Rich Manipulation
arXiv:2608.25872v1 Announce Type: new Abstract: Contact-rich manipulation requires precise interaction feedback. While vision-centric imitation learning is prevalent, external visual observations prov
arXiv:2608.25872v1 Announce Type: new Abstract: Contact-rich manipulation requires precise interaction feedback. While vision-centric imitation learning is prevalent, external visual observations provide indirect and ambiguous cues about contact states, particularly under occlusion or subtle object--gripper interactions; dedicated tactile or force sensors can provide rich contact information but introduce additional hardware complexity, calibration requirements, and deployment costs. To bridge this gap, we propose VISTA-Policy, an imitation learning paradigm that utilizes the Visual Deformation Field (VDF), a 3D displacement representation of a compliant gripper, as high-dimensional visuo-physical feedback. The framework integrates: 1) a Physics-Aware Encoding Engine for real-time VDF decoding; 2) an Energy Aggregation Denoising Mechanism to isolate true interaction signals; and 3) a Deformation-Augmented Policy Network with incremental gripper actions for precise closed-loop correction. Extensive evaluations on Cross-Scale Object Grasping, Cap Unscrewing, and Calligraphy Writing demonstrate that VISTA-Policy outperforms the strong pure-vision baseline 3D Diffusion Policy and the tactile baseline. VISTA-Policy further demonstrates substantial out-of-distribution generalization to unseen object scales and robustness against dynamic disturbances, offering a durable and cost-effective route toward general-purpose fine-grained manipulation in unstructured environments. Project videos and supplementary materials are available at: https://sites.google.com/view/vista-policy.
Related
- CAAT: Contact-Aware Attention Scaling and Tactile Masking for Data-Efficient Contact-Rich Manipulation
- Learning When to See and When to Feel: Adaptive Vision-Torque Fusion for Contact-Aware Manipulation
- Spacetime Optimal-Transport Attention for Visuo-Haptic Imitation Learning of Contact-Rich Manipulation
- Force Policy: Learning Hybrid Force-Position Control Policy under Interaction Frame for Contact-Rich Manipulation
Source: arXiv cs.RO | 2026-08-27