EEG-controlled tele-grasping for undefined objects

This paper presents a teleoperation system of robot grasping for undefined objects based on a real-time EEG (Electroencephalography) measurement and shared autonomy. When grasping an undefined object in an unstructured environment, real-time human decision is necessary since fully autonomous graspin...

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Main Authors: Minki Kim, Myoung-Su Choi, Ga-Ram Jang, Ji-Hun Bae, Hyung-Soon Park
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-12-01
Series:Frontiers in Neurorobotics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fnbot.2023.1293878/full
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author Minki Kim
Myoung-Su Choi
Ga-Ram Jang
Ji-Hun Bae
Hyung-Soon Park
author_facet Minki Kim
Myoung-Su Choi
Ga-Ram Jang
Ji-Hun Bae
Hyung-Soon Park
author_sort Minki Kim
collection DOAJ
description This paper presents a teleoperation system of robot grasping for undefined objects based on a real-time EEG (Electroencephalography) measurement and shared autonomy. When grasping an undefined object in an unstructured environment, real-time human decision is necessary since fully autonomous grasping may not handle uncertain situations. The proposed system allows involvement of a wide range of human decisions throughout the entire grasping procedure, including 3D movement of the gripper, selecting proper grasping posture, and adjusting the amount of grip force. These multiple decision-making procedures of the human operator have been implemented with six flickering blocks for steady-state visually evoked potentials (SSVEP) by dividing the grasping task into predefined substeps. Each substep consists of approaching the object, selecting posture and grip force, grasping, transporting to the desired position, and releasing. The graphical user interface (GUI) displays the current substep and simple symbols beside each flickering block for quick understanding. The tele-grasping of various objects by using real-time human decisions of selecting among four possible postures and three levels of grip force has been demonstrated. This system can be adapted to other sequential EEG-controlled teleoperation tasks that require complex human decisions.
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spelling doaj.art-9d8b3d12e62c4460be5dd065242662ba2023-12-19T10:57:48ZengFrontiers Media S.A.Frontiers in Neurorobotics1662-52182023-12-011710.3389/fnbot.2023.12938781293878EEG-controlled tele-grasping for undefined objectsMinki Kim0Myoung-Su Choi1Ga-Ram Jang2Ji-Hun Bae3Hyung-Soon Park4Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of KoreaApplied Robot R&D Department, Korea Institute of Industrial Technology, Ansan, Republic of KoreaApplied Robot R&D Department, Korea Institute of Industrial Technology, Ansan, Republic of KoreaApplied Robot R&D Department, Korea Institute of Industrial Technology, Ansan, Republic of KoreaDepartment of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of KoreaThis paper presents a teleoperation system of robot grasping for undefined objects based on a real-time EEG (Electroencephalography) measurement and shared autonomy. When grasping an undefined object in an unstructured environment, real-time human decision is necessary since fully autonomous grasping may not handle uncertain situations. The proposed system allows involvement of a wide range of human decisions throughout the entire grasping procedure, including 3D movement of the gripper, selecting proper grasping posture, and adjusting the amount of grip force. These multiple decision-making procedures of the human operator have been implemented with six flickering blocks for steady-state visually evoked potentials (SSVEP) by dividing the grasping task into predefined substeps. Each substep consists of approaching the object, selecting posture and grip force, grasping, transporting to the desired position, and releasing. The graphical user interface (GUI) displays the current substep and simple symbols beside each flickering block for quick understanding. The tele-grasping of various objects by using real-time human decisions of selecting among four possible postures and three levels of grip force has been demonstrated. This system can be adapted to other sequential EEG-controlled teleoperation tasks that require complex human decisions.https://www.frontiersin.org/articles/10.3389/fnbot.2023.1293878/fullbrain-machine (computer) interfacetelerobotics and teleoperationhuman-robot collaborationsteady-state visual evoked potential (SSVEP)electroencephalogram (EEG)
spellingShingle Minki Kim
Myoung-Su Choi
Ga-Ram Jang
Ji-Hun Bae
Hyung-Soon Park
EEG-controlled tele-grasping for undefined objects
Frontiers in Neurorobotics
brain-machine (computer) interface
telerobotics and teleoperation
human-robot collaboration
steady-state visual evoked potential (SSVEP)
electroencephalogram (EEG)
title EEG-controlled tele-grasping for undefined objects
title_full EEG-controlled tele-grasping for undefined objects
title_fullStr EEG-controlled tele-grasping for undefined objects
title_full_unstemmed EEG-controlled tele-grasping for undefined objects
title_short EEG-controlled tele-grasping for undefined objects
title_sort eeg controlled tele grasping for undefined objects
topic brain-machine (computer) interface
telerobotics and teleoperation
human-robot collaboration
steady-state visual evoked potential (SSVEP)
electroencephalogram (EEG)
url https://www.frontiersin.org/articles/10.3389/fnbot.2023.1293878/full
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