Deformable Contact-Aware 3D Object Placement

Songhe Wang; David Miller; Charles A. Kamhoua

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arXiv · 2611.08005

Deformable Contact-Aware 3D Object Placement

Songhe Wang·David Miller·Charles A. Kamhoua

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Abstract

Current language-guided 3D object placement typically predicts a rigid 6-DoF pose, ignoring the physical reality that indoor placements are dictated by contact. Consequently, predicted poses often float, interpenetrate supports, or fail to deform soft surfaces. We propose Deformable Contact-Aware Placement (DCAP), a framework that reframes placement as a drop-to-equilibrium process. Rather than predicting a static pose, DCAP constructs a semantic release state that specifies the drop location, object scale, and deformable components, allowing a coupled rigid-deformable simulator to settle the object under gravity and friction. This explicitly separates semantic intent from physical realization. Evaluated on a benchmark of 2,063 prompt-asset-scene cases, DCAP significantly outperforms static baselines. On standard placements, it improves VLM Physics & Naturalness by 21.2 points and human preference by 26.5 points over the strongest raw rigid baseline, while reducing mean penetration depth by 72.3%. Compared to simulated rollout baselines, DCAP reduces residual speed by 72.1%. Ultimately, our results prove that physically accurate 3D placement requires modeling semantic intent and physical realization as strictly separate processes.

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Songhe Wang, David Miller, Charles A. Kamhoua. 2026-11-05. Deformable Contact-Aware 3D Object Placement. https://arxiv.org/abs/2611.08005

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