Trajectory tracking of a one-DOF manipulator using multiple fishing line actuators by iterative learning control

Shu Ono, Ken Masuya, Kentaro Takagi, Kenji Tahara

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

3 被引用数 (Scopus)

抄録

In this paper, an iterative learning control scheme for a trajectory tracking task using a one-DOF joint manipulator which is driven by multiple antagonistic fishing line artificial muscle actuators is proposed. The fishing line actuator is one of the soft actuators made by coiling and heating a twisted polymer fiber. It has attracted attention from those who would develop soft robotic devices because it is soft, light, and low-cost. It, however, has several drawbacks, e.g. output force limitation, strong nonlinearity, or energy efficiency, etc. To cope with these drawbacks, firstly a one-DOF manipulator driven by multiple antagonistic actuators is proposed to enhance its output force, and the energy efficiency is analyzed to investigate the relationship between the energy consumption and a number of activated fishing line actuator. Next, an iterative learning control scheme to accomplish a trajectory tracking task by the one-DOF manipulator is proposed to improve its control performance even though under the existence of unknown nonlinearities. The effectiveness of the proposed control scheme is demonstrated through several experiments.

本文言語英語
ホスト出版物のタイトル2018 IEEE International Conference on Soft Robotics, RoboSoft 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ467-472
ページ数6
ISBN(電子版)9781538645161
DOI
出版ステータス出版済み - 7月 5 2018
イベント1st IEEE International Conference on Soft Robotics, RoboSoft 2018 - Livorno, イタリア
継続期間: 4月 24 20184月 28 2018

出版物シリーズ

名前2018 IEEE International Conference on Soft Robotics, RoboSoft 2018

会議

会議1st IEEE International Conference on Soft Robotics, RoboSoft 2018
国/地域イタリア
CityLivorno
Period4/24/184/28/18

!!!All Science Journal Classification (ASJC) codes

  • 人工知能
  • 制御と最適化
  • モデリングとシミュレーション
  • 機械工学

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