Abstract
A parallel processing scheme is described for robot control computation on the MIMD shared memory multi-processor model. Since the dynamic control law of a robot arm usually contains a large amount of operations compared with the number of available processors, it is important to consider not only the effect of parallel processing but also the efficiency of serial processing in each of the processors. In order to obtain such a desirable solution for the complex scheduling problem, optimization and quasi-optimization algorithms are proposed. The excellent optimization algorithm is based on a branch-and-bound method. On the other hand, the practical quasi-optimization algorithm is based on a partial enumeration method which effectively combines the optimization algorithm and the approximation algorithm (greatest common factor/longest calculation time (GCF/LPT)) that was developed by the authors.
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