# Research of Flexible Assembly of Miniature Circuit Breakers Based on Robot Trajectory Optimization
## 7 Conclusions  
This paper proposes a flexible automatic assembly technique to solve the high rigidity issue in current MCB manufacturing, and realizes the flexible automatic assembly of multiple MCB parts with a single robot. A time-optimal trajectory PSO method with a multi-optimization mechanism is proposed. A fitness switch function that judges, compares, and optimizes the results is employed to improve the calculation efficiency. Simulation  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Part** & **Section** & \
\begin{tabular}{c} **No** \\ **Optimization** \\ \end{tabular} &
\begin{tabular}{c} **Standard** \\ **PSO** \\ \end{tabular} & **Improved PSO** \\ \hline \multirow{4}{*}{Arc} & AB & 9.34 & 16.43 & 9.08 \\  & BC & 15.36 & 14.54 & 12.85 \\ \cline{1-1}  & CD & 11.06 & 4.64 & 5.85 \\ \cline{1-1}  & DE & 12.52 & 8.03 & 12.75 \\ \cline{1-1}  & Total & 48.28 & 43.63 & 40.53 \\ \hline \multirow{4}{*}{Big-U rod} & AB & 12.76 & 13.88 & 12.68 \\  & BC & 11.84 & 9.00 & 9.05 \\ \cline{1-1}  & CD & 15.04 & 14.63 & 11.23 \\ \cline{1-1}  & DE & 11.06 & 11.39 & 14.45 \\ \cline{1-1}  & Total & 50.70 & 48.89 & 47.40 \\ \hline \multirow{4}{*}{Yoke} & AB & 10.22 & 13.50 & 7.43 \\ \cline{1-1}  & BC & 14.64 & 11.90 & 15.33 \\ \cline{1-1}  & CD & 12.18 & 12.62 & 10.30 \\ \cline{1-1}  & DE & 12.10 & 9.65 & 8.33 \\ \cline{1-1}  & Total & 49.14 & 47.68 & 41.38 \\ \hline \multirow{4}{*}{Handle} & AB & 12.48 & 12.65 & 9.90 \\ \cline{1-1}  & BC & 13.90 & 9.29 & 10.45 \\ \cline{1-1}  & CD & 12.86 & 9.36 & 9.75 \\ \cline{1-1}  & DE & 8.34 & 11.68 & 9.68 \\ \cline{1-1}  & Total & 47.58 & 42.98 & 39.78 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Comparison of operating times of different parts on the experimental platform (unit: s).  
Figure 16: Flexible assembly experiment.  
and experimental results show that compared with other methods, the proposed improved PSO significantly raise the accuracy and efficiency of the robot trajectory planning.  
However, the proposed trajectory planning method is developed for the purpose of MCB assembly and is proven on our specifically designed experimental platform. The practicability cannot be fully proven by the experimental results since the conditions of manufacturing are more severe and complicated. Therefore, there are several issues to be improved in the future work: Firstly, the proposed method is expected to be applied to other robotic applications, as well as to different types of industrial robots, e.g., parallel robots, SCARA robots, for a validation of generality; Secondly, it is expected that the proposed method works under the condition that the robot operating with its maximum power, i.e., the fastest motion, and so that to inspect the performance of the proposed method; Thirdly, the cooperating system of the robot and a machine vision device is expected to be established in the next step, to automatically identify and adjust randomly postured parts.  
Conceptualization, L.S. and Z.W.; methodology, Y.H.; software, G.Z.; validation, Z.C.; formal analysis, Y.H.; investigation, Z.W.; resources, L.S.; data curation, X.C.; writing--original draft preparation, Y.H.; writing--review and editing, Z.W.; visualization, X.C.; supervision, Z.W. and L.S.; project administration, L.S.; funding acquisition, Z.W. and L.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Science Technology Department of Zhejiang Province, grant number 2021C01046, and by Wenzhou Science & Technology Bureau, grant numbers ZG2020049 and G20210020.  
Not applicable.  
We are grateful for the support provided by Technology Institute of Wenzhou University in Yueqing.  
The authors declare no conflict of interest.