TY - GEN
T1 - Trajectory tracking of a one-DOF manipulator using multiple fishing line actuators by iterative learning control
AU - Ono, Shu
AU - Masuya, Ken
AU - Takagi, Kentaro
AU - Tahara, Kenji
N1 - Funding Information:
*This work was supported by JSPS KAKENHI Grant Number JP16H02882, 17H03204 1S. Ono, K. Masuya, and K. Tahara are with Department of Mechanical Engineering, Faculty of Engineering, Kyushu University, 744 Moto’oka, Nishi-ku, Fukuoka 819-0395, Japan tahara@ieee.org 2K. Takagi is with the Department of Mechanical Systems Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan kentaro.takagi@nagoya-u.jp
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/5
Y1 - 2018/7/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85050702018&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050702018&partnerID=8YFLogxK
U2 - 10.1109/ROBOSOFT.2018.8405370
DO - 10.1109/ROBOSOFT.2018.8405370
M3 - Conference contribution
AN - SCOPUS:85050702018
T3 - 2018 IEEE International Conference on Soft Robotics, RoboSoft 2018
SP - 467
EP - 472
BT - 2018 IEEE International Conference on Soft Robotics, RoboSoft 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st IEEE International Conference on Soft Robotics, RoboSoft 2018
Y2 - 24 April 2018 through 28 April 2018
ER -
