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Understanding the difference between prox and complementarity formulations for simulation of systems with contact

机译:了解PROX和互补配方的差异,用于仿真与联系人

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To plan a robotic task involving intermittent contact, such as an assembly task, it is helpful to be able to simulate the task accurately and efficiently. In the past ten years, the prox formulation of the equations of motion has arisen as a competitive alternative to the well-known linear and nonlinear complementarity problem (LCP and NCP) formulations. In this paper, we compare these two formulations, showing through a set-based argument that the formulations are equivalent. Second, we provide simple examples to compare the most common approaches for solving these formulations. The prox formulation is solved by fixed-point iteration while the complementarity formulation is solved by a pivoting scheme, known as Lemke's algorithm. The well-known paradox of PAINLEVÉ is used in a case where two solutions exist to illustrate that the fixed-point scheme can fail while the pivoting scheme will succeed.
机译:为了规划涉及间歇联系人的机器人任务,例如装配任务,能够准确且有效地模拟任务是有帮助的。在过去的十年中,作为众所周知的线性和非线性互补问题(LCP和NCP)制剂,出现了运动方程的PROx制剂作为竞争替代品(LCP和NCP)制剂。在本文中,我们比较这两种配方,通过基于集的论点来表示配方是等同的。其次,我们提供了简单的例子,以比较解决这些配方的最常见方法。通过定点迭代来解决Prox配方,而通过称为LEMKE算法的枢转方案来解决互补性制剂。在枢转方案成功的同时,存在于存在两个解决方案的情况下使用众所周知的PAILLEVÉ的悖论,而在枢转方案将成功。

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