Accurate calibration of particle-based simulators is crucial for robotic earthwork simulation, but analytical calibration is challenging due to this task's highly nonlinear particle dynamics and the black-box nature of conventional simulators. Although simulation-based inference (SBI) can estimate posterior distributions over simulation parameters solely from forward simulations, applying SBI directly to high-fidelity (HF) particle simulators is often computationally prohibitive. Low-fidelity (LF) simulators with coarser particles can reduce this cost, but changes in particle size and particle count shift the parameter values needed to reproduce the same observation, producing biased LF posteriors. We propose Bridged SBI, which leverages a biased but informative LF posterior to guide HF inference. This method first uses inexpensive LF simulations to identify a coarse high-density parameter region, and then it learns a local residual bridge to transport LF posterior samples toward HF-consistent regions by correcting the LF--HF discrepancy. We analyze how sequential multi-fidelity SBI (Naive-MF) can suffer from LF-induced posterior miscoverage when it directly relies on the LF posterior without discrepancy correction. We then show that Bridged SBI is designed to alleviate this issue by explicitly modeling the LF--HF discrepancy through residual correction. Experiments on both sim-to-sim particle-parameter calibration and real-to-sim calibration with real soil observation show that Bridged SBI produces more accurate and reliable HF posteriors than HF-only SBI or the Naive-MF baseline, especially under limited HF simulation costs.

翻译：基于粒子的模拟器精确校准对于机器人土方仿真至关重要，但由于该任务中高度非线性的粒子动力学以及传统模拟器的黑箱特性，解析校准极具挑战性。尽管基于模拟的推断（SBI）能够仅通过正向模拟来估计模拟参数的后验分布，但将SBI直接应用于高保真（HF）粒子模拟器往往因计算成本过高而不可行。采用粗粒度粒子的低保真（LF）模拟器可降低计算开销，但粒子尺寸与数量的变化会改变复现相同观测结果所需的参数值，从而产生有偏的LF后验。我们提出桥接式SBI，该方法利用有偏但信息丰富的LF后验来引导HF推断。该方法首先通过低成本的LF模拟确定高密度参数粗区域，随后学习局部残差桥接，通过校正LF-HF差异将LF后验样本迁移至与HF一致的区域。我们分析了序列式多保真SBI（朴素多保真）因直接依赖未校正差异的LF后验而可能导致的LF诱导后验覆盖不足问题，进而证明桥接式SBI通过残差校正显式建模LF-HF差异以缓解该问题的设计原理。在仿真-仿真粒子参数校准及基于真实土壤观测的实际-仿真校准实验中，桥接式SBI生成的高保真后验比仅用HF的SBI或朴素多保真基线更准确可靠，尤其在HF计算资源受限条件下优势显著。