A Linear-Time Variational Integrator for Multibody Systems

TL;DR

This paper introduces a linear-time variational integrator for multibody systems, significantly improving computational efficiency while preserving system properties, suitable for complex articulated robots.

Contribution

The paper develops a recursive $O(n)$ algorithm for variational integrators, leveraging body-wise DEL equations and a quasi-Newton method to enhance scalability and efficiency.

Findings

Achieves $O(n)$ complexity for multibody variational integration.

Demonstrates scalability on complex systems like humanoid robots.

Maintains robustness and energy-momentum conservation in simulations.

Abstract

We present an efficient variational integrator for multibody systems. Variational integrators reformulate the equations of motion for multibody systems as discrete Euler-Lagrange (DEL) equations, transforming forward integration into a root-finding problem for the DEL equations. Variational integrators have been shown to be more robust and accurate in preserving fundamental properties of systems, such as momentum and energy, than many frequently used numerical integrators. However, state-of-the-art algorithms suffer from $O(n^3)$ complexity, which is prohibitive for articulated multibody systems with a large number of degrees of freedom, $n$, in generalized coordinates. Our key contribution is to derive a recursive algorithm that evaluates DEL equations in $O(n)$, which scales up well for complex multibody systems such as humanoid robots. Inspired by recursive Newton-Euler algorithm, our key insight is to formulate DEL equation individually for each body rather than for the entire system. Furthermore, we introduce a new quasi-Newton method that exploits the impulse-based dynamics algorithm, which is also $O(n)$, to avoid the expensive Jacobian inversion in solving DEL equations. We demonstrate scalability and efficiency, as well as extensibility to holonomic constraints through several case studies.