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It is being tried to control robot arm using brain signal in the field of brain-machine interface (BMI). Thisstudy is focused on applying guidance laws for efficient robot arm control using 3D coordinates obtained from Magnetoencephalography(MEG) signal which represents movement of upper limb. The 3D coordinates obtained frombrain signal is inappropriate to be used directly because of the spatial difference between human upper limb and robotarm’s end-effector. The spatial difference makes the robot arm to be controlled from a third-person point of view withassist of visual feedback. To resolve this inconvenience, guidance laws which are frequently used for tactical ballisticmissile are applied. It could be applied for the users to control robot arm from a first-person point of view whichis expected to be more comfortable. The algorithm which enables robot arm to trace MEG signal is provided in thisstudy. The algorithm is simulated and applied to 6-DOF robot arm for verification. The result was satisfactory anddemonstrated a possibility in decreasing the training period and increasing the rate of success for certain tasks suchas gripping object.

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