非弹性摩擦同时撞击的集值刚体动力学

Mathew Halm, Michael Posa
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摘要

机器人操纵和运动通常需要几乎同时发生碰撞,例如脚步过程中脚跟和脚趾的撞击,其结果对撞击发生的顺序极为敏感。机器人模拟器和状态估计通常缺乏预测这种顺序的保真度和准确性,而是采用启发式方法来选择一种顺序。当把在模拟中学习到的基于模型的控制器和策略应用到真实机器人上时,这种差异会降低性能。我们采用了一个集合值刚体模型来解决这个问题,该模型可对任意冲击顺序的同时摩擦冲击产生一系列广泛的结果。我们首先将 Routh 的撞击模型扩展到多重撞击,将其重新表述为微分包容(DI),并证明任何解决方案都能在有限时间内解决所有撞击。通过将时间视为一种状态,我们将该模型嵌入到另一个 DI 中,从而捕捉到刚体动力学的连续时间演化,并保证解的存在性。最后,我们将同时撞击的模拟视为线性互补问题(LCP),并开发了一种算法,以概率保证对撞击后速度集进行严格逼近。我们在操纵和腿部运动的几个例子中演示了我们的方法,并将预测结果与其他刚性和柔性碰撞模型进行了比较。
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Set-valued rigid-body dynamics for simultaneous, inelastic, frictional impacts
Robotic manipulation and locomotion often entail nearly-simultaneous collisions—such as heel and toe strikes during a foot step—with outcomes that are extremely sensitive to the order in which impacts occur. Robotic simulators and state estimation commonly lack the fidelity and accuracy to predict this ordering, and instead pick one with a heuristic. This discrepancy degrades performance when model-based controllers and policies learned in simulation are placed on a real robot. We reconcile this issue with a set-valued rigid-body model which generates a broad set of outcomes to simultaneous frictional impacts with any impact ordering. We first extend Routh’s impact model to multiple impacts by reformulating it as a differential inclusion (DI), and show that any solution will resolve all impacts in finite time. By considering time as a state, we embed this model into another DI which captures the continuous-time evolution of rigid-body dynamics, and guarantee existence of solutions. We finally cast simulation of simultaneous impacts as a linear complementarity problem (LCP), and develop an algorithm for tight approximation of the post-impact velocity set with probabilistic guarantees. We demonstrate our approach on several examples drawn from manipulation and legged locomotion, and compare the predictions to other models of rigid and compliant collisions.
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