A contribution to parallelization of symbolic robot models

Abstract

SummaryThis paper is focused on task scheduling in multiprocessor robot controllers. To minimize the input-output time delay our consideration is restricted to parallel architectures that include complete crossbar interconnection networks. In this paper, an efficient scheduling algorithm based on a heuristic function is considered. This function takes into account delays caused by interprocessor communication and minimizes both the execution time and the communication cost. Robot control computation based on a highly efficient customized symbolic method is decomposed into a large number of simple tasks, each involving a single floating-point operation. Starting with an empty partial schedule, each step of the search extends the current partial schedule by adding one of the tasks yet to be scheduled. The heuristic function used in the algorithm actively directs the search for a feasible schedule, i.e. it helps choose the task that extends the current partial schedule. To increase the computational rate we introduced overlapping of computations.