# From Biological Curves to Modular Soft Robots: Learning-Based Inverse Design with Uncertainty-Guided Refinement

- Source: arXiv cs.RO
- Published: 2026-10-28T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/su8kdb13g3ijkfiabtsao365y
- Original: https://arxiv.org/abs/2610.36681

## Summary

The paper proposes a learning-based real-to-sim-to-real framework that converts biological curves into cable-driven modular soft robot configurations through surrogate-assisted inverse design and uncertainty-guided refinement. The learned forward surrogate reduces deformation prediction time from 1.53×10^5 ms to 0.0008 ms, a speedup of about 1.9×10^8 times; inverse design time drops from 1.99×10^6 ms to 4.18 ms.