Implementation and experimental study of a multiprocessor system for real-time model-based robot motion control

This paper presents the design and implementation of a multiprocessor system for real-time robot motion control. Full inverse dynamics compensation control laws in both joint and Cartesian spaces are used for developing parallel computation algorithms. The algorithms are divided into subtasks which are distributed among a fixed number of processors based on heuristic scheduling algorithms. The control laws are real-time tested on an experimental robot. The results present a feasible way for improving controller performance of current industrial robots.