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http://dx.doi.org/10.7746/jkros.2021.16.1.035

Iterative Learning Control of Trajectory Generation for the Soft Actuator  

Song, Eunjeong (Department of Mechanical Engineering, Sungkyunkwan University)
Koo, Jachoon (Department of Mechanical Engineering, Sungkyunkwan University)
Publication Information
The Journal of Korea Robotics Society / v.16, no.1, 2021 , pp. 35-40 More about this Journal
Abstract
As the robot industry develops, industrial automation uses industrial robots in many parts of the manufacturing industry. However, rigidity-based conventional robots have a disadvantage in that they are challenging to use in environments where they grab fragile objects or interact with people because of their high rigidity. Therefore, researches on soft robot have been actively conducted. The soft robot can hold or manipulate fragile objects by using its compliance and has high safety even in an atypical environment with human interaction. However, these advantages are difficult to use in dynamic situations and control by the material's nonlinear behavior. However, for the soft robot to be used in the industry, control is essential. Therefore, in this paper, real-time PD control is applied, and the behavior of the soft actuator is analyzed by providing various waveforms as inputs. Also, Iterative learning control (ILC) is applied to reduce errors and select an ILC type suitable for soft actuators.
Keywords
Soft Actuator; Soft Robotics; Control; Real Time Control; Iterative Learning Control;
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