# Dynamic Synthesis of Three -- Point Circle Peripheral Docking Technology Pose
## 1 Introduction
The region segmentation method was applied to compress the number of point clouds and reconstruct the image butt flange for the application of the ship shafting automatic butt joint system to improve the assembly efficiency by [PERSON] of Huazhong University of Science and Technology [21]. A visual automatic docking method based on heterogeneous equipment was proposed by [PERSON] of Nanchang Aviation University. Using a laser tracker and industrial camera for data fusion, the docking method was able to monitor the docking process and improve the docking quality [22]. A fast positioning method based on deep learning and binocular vision was proposed for docking mechanisms. Simulation results showed that the average error of the docking process was less than the capture radius and met the docking requirements [23]. [PERSON] of Harbin University of Technology proposed both a monocular vision navigation method based on the shortest path to describe the calculation model of capture point parameters, as well as an including the segmentation, selection, and combination of contours in images to solve the contour extraction problem of docking rings in complex images. Simulation results showed that the proposed method was accurate and stable to the acquisition point [24]. A high\(-\)precision line\(-\)of\(-\)sight angle measuring system was developed by [PERSON] of the Chinese Academy of Sciences to realize intersection and docking of vehicles [25]. The overall coordinate system model of the double optical path based on laser transmission was established by [PERSON] of the Chinese Academy of Sciences. In the experiment, fast and accurate docking with an error value less than 2 was achieved [26]. A vision system was designed by [PERSON] of Northwestern Polytechnical University for the capture process. The system used four charge\(-\)coupled device (CCD) cameras, among which two had a \(20^{\circ}\) field of view to detect distant targets, and the other two had a \(40^{\circ}\) field of view for detecting close range targets [27]. The relative posture was determined between the artificial landmark and the camera according to the perspective three\(-\)point (P3P) visual positioning method. The guidance signs of the docking target were collected by the vehicle monocular vision system [28]. An autonomous rendezvous and docking mechanism combining electromagnetic technology and a \"pen cap\" docking mechanism was designed by [PERSON] of Shanghai Jiao Tong University, and it can serve as a reference for the calibration of far\(-\)field models [29]. The matching degree was evaluated by [PERSON] of the Harbin Institute of Technology based on contour direction features, and the target pose parameters were solved from the optimal matching results to achieve the target navigation requirements of space docking [30]. The studies mentioned above focused on the accuracy and energy loss analysis of the docking process. However, there is great demand to expand the reconstruction space of the docking mechanism while ensuring a lightweight structure and low cost. Furthermore, the maximum diameter of the docking body channel is only about 800 mm, which limits space expansion and interworking; thus, the channel diameter, structure weight, and cost need to be optimized. In this study, the \"three\(-\)point circle peripheral cone\" car body reconstruction technology is proposed to realize large space reconstruction and driving mode switching between the twin mini car and the single car based on cost control, aiming at the demand for space reconstruction of intelligent automobiles. The process of double mini car integration is studied with a large tolerance and a weak collision in a short distance during its dynamic deceleration. The visual positioning capture control algorithm is focused upon in the space docking process. Dynamic and static research and experiments are conducted on the docking mechanism. The reconstructed vehicle model is shown in Figure 1.