# 基于观测参考的工具驱动与残差动力学组织变形预测

> 原文链接：https://robotics.hellobike.com/papers/2026-10-09-2610-14191
> 频道：papers | 更新日期：2026-10-09 | 标签：arxiv, cs.RO
> 核心摘要：该研究用场景特定可微表面模型和观测参考形式，从未来器械运动预测组织变形，并在手术操作片段上回顾验证。

# 基于观测参考的工具驱动与残差动力学组织变形预测

::: v-pre
> 原文链接：[Observation-Referenced Tissue Deformation Forecasting with Tool-Driven and Residual Dynamics](https://arxiv.org/abs/2610.14191)（arXiv 2610.14191 · 发布日期：2026-10-09）

**Observation-Referenced Tissue Deformation Forecasting with Tool-Driven and Residual Dynamics**

该研究用场景特定可微表面模型和观测参考形式，从未来器械运动预测组织变形，并在手术操作片段上回顾验证。

## 核心要点

- 问题面向由未来器械运动预测组织变形，以支持预测性规划和更自主的手术系统。
- 方法将组织点锚定到最后有效观测，仅叠加已知未来工具轨迹诱发的变形。
- 物理模型采用可微、无网格的位置动力学，并包含场景特定刚度、附着、区域尺度和抓取耦合。
- 在12个手术操作片段上，观测参考相对绝对仿真预测取得0.598的中位误差比；周期残差可进一步改善周期结构运动。

**验证范围与局限**：验证为对三个数据集中的12个手术操作片段进行回顾性评估。

## 英文摘要 (Abstract)

Forecasting tissue deformation from future instrument motion could support predictive planning and increasingly autonomous surgical systems. We study this problem using a scene-specific differentiable surface model fitted to an observed tool-tissue interaction window. Rather than forecasting absolute simulated positions, we introduce an \textit{observation-referenced} formulation that anchors each tissue point to its last valid observation and adds only the deformation induced by the known, preplanned future tool trajectory. This reduces sensitivity to reconstruction, initialization, and persistent simulation offsets while preserving the predicted deformation response. The physical model uses differentiable, mesh-free position-based dynamics with scene-specific rigidity, attachment, region scale, and grasp coupling. We further introduce an optional \textit{observation-referenced residual model} combining graph-spectral spatial modes with periodic harmonic dynamics for structured motion not explained by the tool input. We evaluate the framework retrospectively on 12 surgical manipulation clips from three datasets. Observation referencing provides the largest gain, with a median within-clip error ratio of $0.598$ relative to the corresponding absolute simulation forecast. The optional periodic residual further improves forecasting when the remaining motion exhibits periodic structure. These results support observation-referenced deformation prediction as a practical building block for future surgical world models, digital twins, and generative simulators that must predict how tissue evolves under instrument actions.

作者：Tom Olesch, Nan Xiao, Xiongye Xiao, Jonathan C. DeLong, Fei Liu
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## 原始参考来源 (Sources)

- [arXiv 2610.14191：Observation-Referenced Tissue Deformation Forecasting with Tool-Driven and Residual Dynamics](https://arxiv.org/abs/2610.14191)