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Pose Calibration Method of 6-D.O.F. Cable Driven Parallel Robot Using Hybrid Recurrent Neural Network

[+] Author Affiliations
Sung-Hyun Choi, Kyoung-Su Park, Jun-Mu Heo, Hue Ha

Gachon University, Seongnam, South Korea

Paper No. ISPS-MIPE2018-8520, pp. V001T09A002; 3 pages
doi:10.1115/ISPS-MIPE2018-8520
From:
  • ASME-JSME 2018 Joint International Conference on Information Storage and Processing Systems and Micromechatronics for Information and Precision Equipment
  • ASME-JSME 2018 Joint International Conference on Information Storage and Processing Systems and Micromechatronics for Information and Precision Equipment
  • San Francisco, California, USA, August 29–30, 2018
  • Conference Sponsors: Information Storage and Processing Systems Division
  • ISBN: 978-0-7918-5193-7
  • Copyright © 2018 by ASME

abstract

Cable driven parallel robots (CDPRs) have been widely used in precision Industries. However, an error occurs in repetitive motion of the CDPR because of the elongation and recovery of cable. Also, it is difficult to apply the numerical cable model because of its complexity. In this paper, we use the frequency based H-RNN method for accurate kinematics. H-RNN predicted more accurately compared with LSTM and RNN algorithms.

Copyright © 2018 by ASME

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