# ForceDelta-VLA: Distilling Force-Conditioned Action Corrections for Contact-Rich Manipulation

- Source: arXiv cs.RO
- Published: 2026-10-27T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/hwmv5v1to35ahvsww8vux222f
- Original: https://arxiv.org/abs/2609.18242

## Summary

ForceDelta-VLA proposes a correction-distillation framework that constructs an explicit force-correction target from the force-conditioned and force-agnostic predictions of a frozen teacher model, and adds a separate delay-correction target to handle reference-action mismatch. Across nine single-arm and bimanual contact-rich tasks, the system achieves a mean success rate of 82.2%, compared with 54.4% for the ForceVLA baseline and 70.6% for direct execution of the Stage-1 temporal teacher. Compared with ForceVLA, the full system reduces the mean peak contact force of successful trials by about 26% on both platforms.