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Automatic Scheduling for Parallel Forward Dynamics Computation of Open Kinematic Chains

Abstract

Recent progress in the algorithm as well as the processor power have made the dynamics simulation of complex kinematic chains more realistic in various fields such as human motion simulation and molecular dynamics. The computation can be further accelerated by employing parallel processing on multiple processors. In fact, parallel processing enviroment is becoming more affordable thanks to recent release of multiple-core processors. Although several parallel algorithms for the forward dynamics computation have been proposed in literature, there still remains the problem of automatic scheduling, or load distribution, for handling arbitrary kinematic chains on a given parallel processing environment. In this paper, we propose a method for finding the schedule that minimizes the computation time. We test the method using three human character models with different complexities and show that parallel processing on two processors reduces the computation time by 35--36%. Download: Bibtex: @INPROCEEDINGS{ Yamane-RSS-07, AUTHOR = {K. Yamane and Y. Nakamura}, TITLE = {Automatic Scheduling for Parallel Forward Dynamics Computation of Open Kinematic Chains}, BOOKTITLE = {Proceedings of Robotics: Science and Systems}, YEAR = {2007}, ADDRESS = {Atlanta, GA, USA}, MONTH = {June}, DOI = {10.15607/RSS.2007.III.025} }

🌉 Interdisciplinary Bridge — Machine Learning and Mathematics & Optimization
📈 Trend Setter — Efficient Computing
🧭 Keyword Pioneer — kinematic chain
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics