Abstract
This paper investigates a new approach for solving the forward kinematics of cable-driven parallel robots. This approach combines an interval algorithm with neural networks to provide a fast but accurate initial guess. The neural networks increase the computation speed by a factor of 200 or more, while the interval algorithm provides guaranteed convergence and a definite solution to any chosen degree of accuracy. Iterative techniques are faster still, but the proposed algorithm is considered real-time feasible.
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Acknowledgments
This work was partially supported by the Fraunhofer-Gesellschaft Internal Programs under Grant No. WISA 823 244. Furthermore, the research leading to these results received founding for the European Community’s Seventh Framework Program under Grant agreement number NMP2-SL-2011-285404-CableBot.
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Schmidt, V., Müller, B., Pott, A. (2014). Solving the Forward Kinematics of Cable-Driven Parallel Robots with Neural Networks and Interval Arithmetic. In: Thomas, F., Perez Gracia, A. (eds) Computational Kinematics. Mechanisms and Machine Science, vol 15. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7214-4_12
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DOI: https://doi.org/10.1007/978-94-007-7214-4_12
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