接触を伴う関節剛体のための高速で機能完備な微分可能物理演算
Fast and Feature-Complete Differentiable Physics for Articulated Rigid Bodies with Contact
関節剛体シミュレーション向けに、LCPによる硬接触制約と効率的な解析的勾配を備えた高速な微分可能物理エンジンNimbleを提案し、DART上で有限差分比87倍の高速化を実現した。
著者: Keenon Werling, Dalton Omens, Jeongseok Lee, Ioannis Exarchos, C. Karen Liu
分類: cs.RO, cs.AI, cs.LG, cs.SY, eess.SY
原文アブストラクト
We present a fast and feature-complete differentiable physics engine, Nimble (nimblephysics.org), that supports Lagrangian dynamics and hard contact constraints for articulated rigid body simulation. Our differentiable physics engine offers a complete set of features that are typically only available in non-differentiable physics simulators commonly used by robotics applications. We solve contact constraints precisely using linear complementarity problems (LCPs). We present efficient and novel analytical gradients through the LCP formulation of inelastic contact that exploit the sparsity of the LCP solution. We support complex contact geometry, and gradients approximating continuous-time elastic collision. We also introduce a novel method to compute complementarity-aware gradients that help downstream optimization tasks avoid stalling in saddle points. We show that an implementation of this combination in an existing physics engine (DART) is capable of a 87x single-core speedup over finite-differencing in computing analytical Jacobians for a single timestep, while preserving all the expressiveness of original DART.
