FAST PARALLEL PRECONDITIONED CONJUGATE-GRADIENT ALGORITHMS FOR ROBOT MANIPULATOR DYNAMICS SIMULATION

In this paper fast parallel Preconditioned Conjugate Gradient (PCG) al gorithms for robot manipulator forward dynamics, or dynamic simulation , problem are presented. By exploiting the inherent structure of the f orward dynamics problem, suitable preconditioners are devised to accel erate the iterations. Also, based on the choice of preconditioners, a modified dynamic formulation is used to speedup both serial and parall el computation of each iteration. The implementation of the parallel a lgorithms on two interconnected processor arrays is discussed and thei r computation and communication complexities are analyzed. The simulat ion results for a Puma Arm are presented to illustrate the effectivene ss of the proposed preconditioners. With a faster convergence due to p reconditioning and a faster computation of iterations due to paralleli zation, the developed parallel PCG algorithms represent the fastest al ternative for parallel computation of the problem with O(n) processors .