# A Robotic Automatic Assembly System Based on Vision
## 1 Introduction
In [22], a multi-workpiece recognition algorithm was proposed to locate the three-dimensional workpiece of monocular vision in a complex industrial environment, which was based on adaptive sub-pattern manifold learning. [PERSON] et al. [23] taught robots to perform object assembly using multi-modal 3D vision. Compared to 3-D vision, the monocular vision is low cost and easy to implement. For incomplete information workpiece detection, such as exceeding-field of view, [PERSON] et al. designed a super-field component image measuring instrument by using image stitching technology [12]. The adaptive image stitching algorithm was proposed in [24] for panoramic image acquisition of super-field components. In [13], [PERSON] et al. realized the effective recognition of the exceeding-field workpiece by extracting the feature points on the workpiece and conducting shape matching. In addition, the force control or hybrid position/force control method is commonly used for assembly tasks. In previous studies, there were three classes of control methods: position control, force control, and hybrid position/force control [10; 25]. Position control is used to complete the assembly task and vision sensors are widely used to get the positions and orientations of assembly objects [26; 27]. The electronic circuit assembly was completed using vision based on OpenCV for an industry robot [26]. The peg-hole assembly was completed through a vision system estimation [27]. The interaction force was obtained by force sensors to guide the robot to complete the assembly [28; 29]. Most of the assembly strategies are based on the idea of modeling. A three-point contact model is built, and the pose misalignment between the peg and hole is estimated by force and geometric analysis [30]. A novel modeling method of geometric errors was proposed by [PERSON] et al. for precision assembly [31]. A control scheme was used to teach the contact states during operation [10]. A robotic assembly parameter optimization method [23; 32] was proposed to enable industrial robots to assemble a workpiece. Compared with the previous work, this paper is aimed at a mobile phone production line process using a robot. A comparative overview Table 1 is listed, which shows the key differences between the different previous systems and the proposed system. The automatic system has also been extensively used in the food industry [33]. There are few references for applying this system to a mobile phone assembly line. In this work, the robot system is proposed to realize the mobile phone assembly process's automation. At first, a minimum rectangle fitting algorithm is proposed to solve pose estimation problem of moving workpieces with incomplete information. The camera-belt-robot multi-hybrid modular calibration is used to calibrate the assembly system, which could obtain the pose relationship \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Contents** & **System of [5]** & **System of [6]** & **Proposed System** \\ \hline Products types & Single species & Single species & Multiple species \\ Robots numbers & Multiple robots & Multiple robots & One robot \\ Calibration method & Multiple calibration & Multiple calibration & Model calibration \\ Detection and grabbing & Targets within the field of view & Targets within the field of view & Targets with over field of view \\ Function & Assembly in the same position & Positioning and handling & Assembly in the different position \\ \hline \hline \end{tabular}
\end{table} 
Table 1: A comparative overview between the previous systems and the proposed system. among the robot, the conveyor belt, and the two cameras. Then a posture estimation algorithm on a moving conveyor belt is proposed to track the objects with different speeds. At last, the effectiveness of the method verified that back shell and screen components were assembled with a six-degree-of-freedom LINKHOU. The rest of this paper is laid out as follows. Section 2 introduces the assembly system description of phone screen components and housing cover.