  We propose a new parallel framework for fast computation of inverse and
forward dynamics of articulated robots based on prefix sums (scans). We
re-investigate the well-known recursive Newton-Euler formulation of robot
dynamics and show that the forward-backward propagation process for robot
inverse dynamics is equivalent to two scan operations on certain semigroups. We
show that the state-of-the-art forward dynamics algorithms may almost
completely be cast into a sequence of scan operations, with unscannable parts
clearly identified. This suggests a serial-parallel hybrid approach for systems
with a moderate number of links. We implement our scan based algorithms on
Nvidia CUDA platform with performance compared with multithreading CPU-based
recursive algorithms; a significant level of acceleration is demonstrated.
