## 1 Introduction  
Advanced robotic technologies add convenience to human life, not only in industrial applications, but also in the fields of education and entertainment. Researchers have developed numerous types of robots to meet different demands, so that the human-robot interactions are simplified and robots can carry out more complex functions. There are many kinds of robotic systems, but the robot arm is the one most used [1]. For many factories in the industrial field, such as car assembly plants, the use of robot arms is an important tool in the manufacturing process. In order for the movement of robot arms to be controlled according to the target positions, the robot arm movement needs to be designed with respect to stability and precision. As the recognition technology has improved in a variety of ways, robots have become more human-like; hence, these robots are called humanoid robots, as they resemble humans in appearance and imitate their behavior. Robots now offer valuable assistance for humans in their everyday life. There are now many smartphones on the market, which means that thousands of touch panels must be tested by quality assurance engineers, which can be a dull job. Therefore, we have designed a smartphone automatic test system that uses a robot arm to reduce human operating time and human resources. The mechanical arm of the traditional design generally uses fixed path planning and strategies to control the entire procedure, so that the robot can reach a specific target position and complete the task, as with industrial robot arms. Although the robot arm can finish tasks accurately, if the target position is changed, the robot arm cannot reach the new point until the whole control process has been redesigned. In this study, we applied a two-camera vision system to recognize the characters and locate the position of the targets. A video camera was utilized to capture the commands on the screen of the control panel and another camera was used to read characters and recognize the screen image of the smart phone. The proposed system identifies an object position and the control scheme calculates the relative position of the moving path through image processing and fuzzy control, and then drives the robot arm to reach the desired position. The effectiveness of the proposed control design was verified by the combination of hardware and software tests. A number of researchers have studied the motion control of robot arms over the past decades. [PERSON] [2] considered the dynamic equation of a robot arm. Based on sensor signal feedback, a PID control was designed for the arm to achieve the desired position. [PERSON] [3] established a simulation system of the robot arm so that the coordinates of each joint could be computed by the simulation system; thus, the arm could be controlled to track an assigned trajectory. [PERSON] [4] calculated the magnitude of the torque for each joint of the robot arm when it grabs an object. Using the PA-10 robot arm made by Mitsubishi Company as a platform, the paper [5] proposed the concept of a harmonic drive model to investigate the gravity and material influence on the robot arm. Moreover, the robot arm was controlled so as to track a desired trajectory and the motion error analyzed. In [6], a two-link robot arm was controlled by a fuzzy sliding mode controller, in which the parameters were adjusted by fuzzy-neural techniques. In general, the kinematics for robot arms includes two basic problems: the forward kinematics problem and the inverse kinematics problem. Usually, forward kinematics is solved by building a D-H model [1, 7], deriving the kinematics and differential kinematics formula of the robot to control the robot arm and change its position. Based on the D-H model, it is evident that the kinematics of robotmanipulators are nonlinear functions and, actually, the combination of trigonometric functions.