# 通过物理基础数字孪生降低空间金属连接机器人焊接风险

> 原文链接：https://robotics.hellobike.com/papers/2026-10-15-2610-21939
> 频道：papers | 更新日期：2026-10-15 | 标签：arxiv, cs.RO
> 核心摘要：面向在轨金属连接焊接表征不足，提出物理基础数字孪生原型，并在交叉验证、边界案例和仿真机械臂焊缝中评估。

# 通过物理基础数字孪生降低空间金属连接机器人焊接风险

::: v-pre
> 原文链接：[De-Risking Robotic Welding for In-Space Metal Joining Through Physics-Grounded Digital Twins](https://arxiv.org/abs/2610.21939)（arXiv 2610.21939 · 发布日期：2026-10-15）

**De-Risking Robotic Welding for In-Space Metal Joining Through Physics-Grounded Digital Twins**

面向在轨金属连接焊接表征不足，提出物理基础数字孪生原型，并在交叉验证、边界案例和仿真机械臂焊缝中评估。

## 核心要点

- 在轨服务、制造与装配需要可靠金属连接，但低重力、低压力下机器人焊接特性仍不充分。
- 原型结合有限体积热焊池模型、GP与神经网络代理模型，以及仿真六轴机械臂。
- 五折交叉验证中，GP在八项输出上误差低于神经网络；边界案例74/80落入90%区间。
- 仿真L形焊缝研究支持在实验前筛选焊接条件和控制策略，但仍需进一步硬件相关研究。

**验证范围与局限**：验证范围为模型评估和仿真UR5 L形焊缝研究，仍需热真空、目标化低重力和机器人硬件在环研究。

## 英文摘要 (Abstract)

Growing interest in in-space servicing, manufacturing, and assembly has renewed attention on reliable metal joining for modular construction and on-orbit repair. Robotic welding is promising, but reduced-gravity and low-pressure operation remains poorly characterised and flight-like tests are limited. The UK Space Agency-supported ISPARK project is developing a physics-grounded digital twin for structured process de-risking. This paper evaluates a model-based prototype combining a finite-volume thermal weld-pool model, Gaussian-process (GP) and neural-network surrogates, and a simulated six-axis manipulator. The reduced model includes solid-liquid phase change, effective thermocapillary transport, and a local-pressure parameter. Gravity is assessed separately through a hydrostatic-to-capillary pressure ratio and does not enter the thermal energy equation. Across repeated five-fold cross-validation, the GP has lower normalised mean absolute error than the neural network for all eight outputs. In 10 held-out boundary cases, 74 of 80 solver responses fall within nominal 90% GP predictive intervals. A three-output GP query takes 249 microseconds, including scaling and predictive variance. In a simulated UR5 L-shaped-seam study, a proportional controller adjusts the synergic power-source setting as travel speed falls near the corner. Finite-volume re-evaluation finds all 12 closed-loop operating points and 9 of 12 open-loop points within an illustrative 1.0-3.0 mm root-side-width band. These simulation results support using the framework to screen welding conditions and control strategies before experimental tests. Thermal-vacuum, targeted reduced-gravity, and robotic hardware-in-the-loop studies are needed to assess the model and controller.

作者：Zhou Hao, Umer Masood Chaudry, Robert Shaw, Andrew Cheney, Nick Ludford, Mark Sims, Hongbiao Dong
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## 原始参考来源 (Sources)

- [arXiv 2610.21939：De-Risking Robotic Welding for In-Space Metal Joining Through Physics-Grounded Digital Twins](https://arxiv.org/abs/2610.21939)