A Novel GPU-based Parallel Implementation Scheme and Performance Analysis of Robot Forward Dynamics Algorithms

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 wellknown 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-prefixsum 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.