论文标题

最大坐标中的线性时间变异积分器

Linear-Time Variational Integrators in Maximal Coordinates

论文作者

Brüdigam, Jan, Manchester, Zachary

论文摘要

大多数动态仿真工具使用最小坐标(也称为广义或关节坐标)参数化多体机器人系统的配置。然而,最大坐标方法比最小坐标参数化具有多个优点,包括对封闭运动环和非义学约束的天然处理。本文介绍了在最大坐标中配制的线性变异积分器。由于其变异配方,该算法不会受到约束漂移的影响,并且具有有利的能量和动量保护特性。一种稀疏的矩阵分解技术允许使用$ n $链接的无环铰接机制的动力学,以$ o(n)$(线性)时间计算。引入循环的其他约束也可以通过算法处理而不会产生很多计算开销。实验结果表明,我们的方法提供了速度竞争性的,最小的坐标算法在几种情况下都超过了它们,尤其是在处理闭环和配置奇异性时。

Most dynamic simulation tools parameterize the configuration of multi-body robotic systems using minimal coordinates, also called generalized or joint coordinates. However, maximal-coordinate approaches have several advantages over minimal-coordinate parameterizations, including native handling of closed kinematic loops and nonholonomic constraints. This paper describes a linear-time variational integrator that is formulated in maximal coordinates. Due to its variational formulation, the algorithm does not suffer from constraint drift and has favorable energy and momentum conservation properties. A sparse matrix factorization technique allows the dynamics of a loop-free articulated mechanism with $n$ links to be computed in $O(n)$ (linear) time. Additional constraints that introduce loops can also be handled by the algorithm without incurring much computational overhead. Experimental results show that our approach offers speed competitive with state-of-the-art minimal-coordinate algorithms while outperforming them in several scenarios, especially when dealing with closed loops and configuration singularities.

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