skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Parallel algorithms and architectures for the manipulator inertia matrix

Miscellaneous ·
OSTI ID:5923653

Several parallel algorithms and architectures to compute the manipulator inertia matrix in real time are proposed. An O(N) and an O(log{sub 2}N) parallel algorithm based upon recursive computation of the inertial parameters of sets of composite rigid bodies are formulated. One- and two-dimensional systolic architectures are presented to implement the O(N) parallel algorithm. A cube architecture is employed to implement the diagonal element of the inertia matrix in O(log{sub 2}N) time and the upper off-diagonal elements in O(N) time. The resulting K{sub 1}O(N) + K{sub 2}O(log{sub 2}N) parallel algorithm is more efficient for a cube network implementation. All the architectural configurations are based upon a VLSI Robotics Processor exploiting fine-grain parallelism. In evaluation all the architectural configurations, significant performance parameters such as I/O time and idle time due to processor synchronization as well as CPU utilization and on-chip memory size are fully included. The O(N) and O(log{sub 2}N) parallel algorithms adhere to the precedence relationships among the processors. In order to achieve a higher speedup factor; however, parallel algorithms in conjunction with Non-Strict Computational Models are devised to relax interprocess precedence, and as a result, to decrease the effective computational delays. The effectiveness of the Non-strict Computational Algorithms is verified by computer simulations, based on a PUMA 560 robot manipulator. It is demonstrated that a combination of parallel algorithms and architectures results in a very effective approach to achieve real-time response for computing the manipulator inertia matrix.

Research Organization:
Ohio State Univ., Columbus, OH (USA)
OSTI ID:
5923653
Resource Relation:
Other Information: Thesis (Ph. D.)
Country of Publication:
United States
Language:
English