Abstract
In this paper parallel computation of manipulator inverse dynamics is investigated. A hierarchical graph-based mapping approach is devised to analyze the inherent parallelism in the Newton-Euler formulation at several computational levels and to derive the features of an abstract architecture for exploitation of parallelism. At each level a parallel algorithm represents the application of a parallel model of computation which transforms the computation into a graph whose structure defines the features of an abstract architecture, i.e., processors and communication structure. Data flow analysis is employed to derive the time lower bound in the computation as well as the sequencing of the abstract architecture. The features of the target architecture are defined by optimization of the abstract architecture to exploit maximum parallelism while minimizing various overheads. A highly parallel MIMD-SIMD architecture is designed and implemented which is capable of efficient exploitation of parallelism at several computational levels. The computation time of the Newton-Euler formulation for a six Degree-Of-Freedom (DOF) general manipulator is measured as 187µs. The increase in the computation time for each additional DOF is 23µs which leads to a computation time of less than 500µs, even for a 12 DOF redundant arm. The architecture also achieves a good performance for other computation problems. For a six DOF general manipulator, the computation time of forward kinematic is measured as 60µs, and forward kinematic and Jacobian as 75µs.
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Fijany, A., Bejczy, A.K. (1989). Parallel Algorithms and Architectures for Manipulator Inverse Dynamics. In: Waldron, K.J. (eds) Advanced Robotics: 1989. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83957-3_15
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DOI: https://doi.org/10.1007/978-3-642-83957-3_15
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