Can Explicit Physical Feasibility Benefit VLA Learning? An Empirical Study
Vision-Language-Action (VLA) models map multimodal inputs directly to robot actions and are typically trained through large-scale imitation learning. While this paradigm has shown strong performance, prevailing VLA training procedures do not explicitly supervise hard physical constraints such as obstacle avoidance or kinematic feasibility. As a result, the geometric structure underlying physically feasible behavior must be inferred only implicitly from demonstrations. In this paper, we study whether introducing explicit feasibility supervision can provide effective structured guidance for VLA policies. We formulate a simple geometry-grounded feasibility objective and integrate it into the...
| Authors | Yubai Wei, Chen Wu, Hashem Haghbayan |
|---|---|
| Primary category | cs.LG |
| Published | 20 April 2026 |
| Last updated at source | 5 May 2026 |
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