Fast implementation of robot inverse dynamics with distributed arithmetic via a SIMD architecture

Abstract

Real-time sophisticated robot control schemes require the online evaluation of the inverse robot dynamics model, a computationally intensive task. Research efforts to create efficient implementations of inverse models belong to the domain of computational robot dynamics. The current trends in this domain postulate that major improvements in computational efficiency can be achieved only in the context of customizing the dynamics formulations for specific robots and organizing the numerical computation. In this context, the objective of this paper is to introduce a novel SIMD parallel architecture based upon the distributed arithmetic technique for the efficient implementation of the general-purpose inverse robot dynamic problem. The approach is embedded in the Lagrangian formulation of robot dynamics with all equations expanded symbolically in their scalar form. In the proposed architecture any inherent parallelism of the computations is exploited to partition the inverse dynamics problem into discrete subtasks. The efficiency of the procedure is illustrated via the positioning system of the Puma robot.