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This paper presents a positioning control of the arm of the humanoid robot by linear visual servoing. Linear visual servoing is based on the linear approximation between binocular visual space and joint space of the arm of the humanoid robot. It is very robust to calibration error, especially to camera angle errors and joint angle errors, because it uses neither camera angles nor joint angles to calculate feedback command. In this paper, we propose a method to expand work space of linear visual servoing by using neck joint. We obtain the linear approximation matrix in wide space and express it as a function of the neck angle by using the neural network. Some experimental results are presented to demonstrate the effectiveness of the proposed method.