This work establishes a solution to the problem of assessing the robustness of multi-object assemblies to external forces. Our physically-grounded approach handles arbitrary static structures made from rigid objects of any shape and mass distribution without relying on heuristics or approximations. The result is a method that provides a foundation for autonomous robot decision-making when interacting with objects in frictional contact. Our strategy decouples slipping from toppling, enabling independent assessments of these two phenomena, with a shared robustness representation being key to combining the results into an accurate robustness assessment. Our algorithms can be used by motion planners to produce efficient assembly transportation plans, and by object placement planners to select poses that improve the strength of an assembly. Compared to prior work, our approach is more generally applicable than commonly used heuristics and more efficient than dynamics simulations.

翻译：本研究针对多物体组合体对外部作用力的稳健性评估问题提出了一种解决方案。我们的物理基础方法能够处理由任意形状和质量分布的刚性物体构成的静态结构，且不依赖于启发式方法或近似处理。该方法为自主机器人与摩擦接触物体交互时的决策制定提供了基础。我们的策略将滑动与倾倒现象解耦，实现了对这两种现象的独立评估，而共享的稳健性表征是将结果整合为精确稳健性评估的关键。运动规划器可利用本算法生成高效的组合体运输方案，物体摆放规划器则可借助其选择能增强组合体稳定性的位姿。与现有研究相比，本方法比常用启发式策略具有更广泛的适用性，且比动力学仿真更为高效。