# SonoWorld：迈向交互式姿态可控超声世界模型

> 原文链接：https://robotics.hellobike.com/papers/2026-10-14-2610-19327
> 频道：papers | 更新日期：2026-10-14 | 标签：arxiv, cs.RO
> 核心摘要：针对机器人超声缺少真实可控仿真环境，SonoWorld用临床视频学习6-DoF可控世界模型，并在留出跟踪扫描和用户研究中验证。

# SonoWorld：迈向交互式姿态可控超声世界模型

::: v-pre
> 原文链接：[SonoWorld: Towards Interactive Pose-Controllable Ultrasound World Models](https://arxiv.org/abs/2610.19327)（arXiv 2610.19327 · 发布日期：2026-10-14）

**SonoWorld: Towards Interactive Pose-Controllable Ultrasound World Models**

针对机器人超声缺少真实可控仿真环境，SonoWorld用临床视频学习6-DoF可控世界模型，并在留出跟踪扫描和用户研究中验证。

## 核心要点

- 机器人超声策略学习受限于缺少真实可控仿真，且探头小位移会引发超声外观大变化。
- SonoWorld从未标注临床视频学习因果视频动力学，并用少量EM跟踪徒手扫描对齐6-DoF控制。
- 训练包括视频扩散预训练、度量探头姿态grounding，以及用于长时自回归生成的分布匹配蒸馏。
- 在留出跟踪扫描上评估姿态跟随、往返一致性和分轴控制；动作判别最高74.8%排对目标运动。

**验证范围与局限**：验证范围为留出跟踪扫描上的合成动作及用户研究，姿态grounding基于小型EM跟踪甲状腺数据集。

## 英文摘要 (Abstract)

Robotic ultrasound can standardize image acquisition and reduce operator workload and variability, but policy learning remains limited by the lack of realistic, controllable simulation environments. While controllable world models have advanced rapidly in natural-image domains, ultrasound world modeling remains challenging because each frame captures only a cross-section of unobserved 3D anatomy, causing small probe motions to induce large appearance changes. Existing approaches rely on robot-tracked poses and latent-space prediction, but do not directly generate the observations required for interactive control. We propose SonoWorld, a causal ultrasound world model that learns video dynamics from unlabeled clinical videos and grounds them to 6-DoF control using a small set of freehand clinical scans tracked with an EM sensor. SonoWorld is trained in three stages: pretraining a latent-action-conditioned video diffusion model on around 6.9 million unlabeled multi-organ ultrasound frames; grounding the learned video dynamics to metric probe poses with a small EM-tracked thyroid dataset; and applying distribution matching distillation to enable causal, long-horizon autoregressive generation with selectively caching eviction tokens at inference time. We evaluate controllability through pose-following fidelity, round-trip consistency, and axis-specific control under synthetic actions on held-out tracked scans, and further validate it with a user study. In model-based action discrimination, SonoWorld correctly ranks the target-directed probe motion over an equal-magnitude opposite motion in up to 74.8% of trials. To our knowledge, SonoWorld is the first causal, pose-controllable ultrasound world model learned primarily from freehand clinical videos, providing a data-driven interactive environment for robotic ultrasound data acquisition and policy evaluation.

作者：Zefan Yang, Zheyuan Zhang, Boris Maihe, Yikang Liu, Hang Yu, Ankush Mukherjee, Xiao Chen, Pingkun Yan, Terrence Chen, Shanhui Sun
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## 原始参考来源 (Sources)

- [arXiv 2610.19327：SonoWorld: Towards Interactive Pose-Controllable Ultrasound World Models](https://arxiv.org/abs/2610.19327)