GPU並列実装によるロボット順動力学アルゴリズムの統一的手法と性能解析
A Novel GPU-based Parallel Implementation Scheme and Performance Analysis of Robot Forward Dynamics Algorithms
リー群記法で順動力学アルゴリズムを統一抽象化し、GPU上の並列スキャンと奇数偶数消去で効率的に解く実装スキームを提案、3手法の性能を比較分析した。
著者: Yajue Yang, Yuanqing Wu, Jia Pan
分類: cs.RO
原文アブストラクト
We propose a novel unifying scheme for parallel implementation of articulated robot dynamics algorithms. It is based on a unified Lie group notation for deriving the equations of motion of articulated robots, where various well-known forward algorithms differ only by their joint inertia matrix inversion strategies. This new scheme leads to a unified abstraction of state-of-the-art forward dynamics algorithms into combinations of block bi-diagonal and/or block tri-diagonal systems, which may be efficiently solved by parallel all-prefix-sum operations (scan) and parallel odd-even elimination (OEE) respectively. We implement the proposed scheme on a Nvidia CUDA GPU platform for the comparative study of three algorithms, namely the hybrid articulated-body inertia algorithm (ABIA), the parallel joint space inertia inversion algorithm (JSIIA) and the constrained force algorithm (CFA), and the performances are analyzed.
