# Path Planning of Rail-Mounted Logistics Robots Based on the Improved Dijkstra Algorithm
## 4 Conclusions  
This paper presents an enhanced version of the Dijkstra algorithm for the purpose of path planning in rail-hung logistics robots. The proposed algorithm incorporates a real-time node occupancy and time window conflict judgment model to facilitate global path planning and conflict coordination in multi-robot systems. One of the key contributions is the incorporation of real-time node occupancy, which enables the identification of all the shortest feasible routes across various tasks. Additionally, the introduction of a time  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Adjusting Policies** & **Path** & **Travel Time (s)** & **Distance (m)** \\ \hline Initial planning & 12-11-76-168 & 155.7 & 140 \\ Delay waiting & 12-11-76-168 & 231.4 & 140 \\ Replanning & 168-143-141-12-13-78 & 197.1 & 160 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Comparison of different dynamic adjustment strategies.  
Figure 10: (**a**) Robot route planned before the dynamic adjustment. (**b**) Robot route planned after the dynamic adjustment. The two lines with different colors stand for the planned paths of the two robots, respectively.  
window conflict judgment model effectively mitigates route conflicts that may arise when executing multiple tasks. This model, in conjunction with system priority setting and conflict coordination strategies, facilitates the achievement of optimal path planning for the system. A Chan algorithm utilizing the Time Difference of Arrival (TDOA) was presented as a means to achieve Ultra-Wideband (UBW) placement, with the objective of accurately locating rail-mounted logistics robots.  
Compared with the traditional Dijkstra algorithm, the algorithm proposed herein can not only plan the shortest path when executing multiple tasks but also determine whether the path of each task is in conflict and the type of conflict. According to the priority of the task and the conflict coordination strategy, the task path is either replanned or delayed. The results show that although the travel distance after replanning is 14.28% more than that after delay waiting, the travel time of the former is reduced by 17.82%. Therefore, choosing to replan when encountering path conflicts can improve the efficiency of executing multi-tasks. In the section on the UWB positioning algorithm, we compared the Chan algorithm based on TDOA with the Taylor algorithm based on TDOA. When the number of positioning base stations was four, the performance of the former was significantly better than that of the latter. In the accuracy test, the error in the former was within the allowable range. Therefore, the Chan algorithm based on TDOA was selected, which can provide accurate positioning information for the robot.  
Based on the above-mentioned experimental results, our proposed algorithm can plan a conflict-free optimal path and dynamically adjust the on-orbit conflicts in real time to avoid track congestion when multiple robots execute the job.  
[PERSON] and [PERSON] proposed the idea. [PERSON], [PERSON] and [PERSON] designed the research. [PERSON], [PERSON] and [PERSON] derived the theory and conducted the simulation. [PERSON] and [PERSON] drew and created the figures. [PERSON], [PERSON] and [PERSON] wrote the paper. All authors have read and agreed to the published version of the manuscript.  
We sincerely acknowledge the financial support from the Key Research and Development Program of Shaanxi Province (no. 2022 GY-308, 2022 GY-208), and the National Natural Science Foundation of China (no. 12172064).  
Not applicable.  
The data that support the findings of this study are available from the corresponding author upon reasonable request.  
The authors declare no conflict of interest.