@inproceedings{3eeaf0a5ee824352ba5d2f2734379561,
title = "Direct Demonstration-Based Imitation Learning and Control for Writing Task of Robot Manipulator",
abstract = "In this paper, we propose an imitation learning method based on a direct demonstration of robot manipulators. To track the desired position and force, we designed an impedance controller. As a result of imitation learning, the robot can be acted as intended even if the initial position is different, and be able to perform a writing task well even if a different contact force is applied to the changing environment. We propose Long Short-Term Memory (LSTM)-based imitation learning method through the demonstration data. Finally, the proposed method was verified by applying the writing task with the actual industrial robot manipulator that acts as the expert's intention for the direct demonstration.",
keywords = "Direct Demonstration, Imitation Learning, Impedance Controller, LSTM, Robot Manipulator, Writing Task",
author = "Sejun Park and Park, {Ju Hyun} and Sangmoon Lee",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Consumer Electronics, ICCE 2023 ; Conference date: 06-01-2023 Through 08-01-2023",
year = "2023",
doi = "10.1109/ICCE56470.2023.10043386",
language = "English",
series = "Digest of Technical Papers - IEEE International Conference on Consumer Electronics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 IEEE International Conference on Consumer Electronics, ICCE 2023",
address = "United States",
}