## 6 Conclusions  
In this study, the problem of UAV path planning in mountainous post-disaster rescue scenarios is addressed by considering surrounding obstacles, weather conditions, and real-time sensor-perceived terrain features. To tackle this problem, this paper makes the following three contributions:  
1. A comparative analysis of existing commonly used path planning algorithms was conducted, and the GWO algorithm and the APF algorithm were selected as the foundational algorithms for UAV path planning in post-disaster mountain rescue scenarios. A simulation environment was constructed using elevation maps, and a third-order B-spline curve was employed to achieve smooth trajectory generation for the UAV paths.
2. The traditional GWO algorithm was improved by employing a nonlinear adjustment strategy for control parameters to balance the global and local search capabilities. Additionally, the update strategy for individual positions in the GWO algorithm was optimized to enhance the coordination of search capabilities and reduce the likelihood of falling into local optima. The traditional APF algorithm was also enhanced by introducing attractive forces along the planned flight paths to address the issue of becoming trapped in local optima when the attractive and repulsive forces are equal. These improvements overcome the limitations of the APF algorithm in three-dimensional path planning tasks.
3. In this paper, a fusion algorithm that combines the IGWO algorithm with the IAPF method is proposed. The initial paths generated by the IGWO algorithm provide the basis for the IAPF algorithm to incorporate both the attractive forces along the flight paths and the planning directions.  
The simulation results demonstrate that compared to the traditional GWO algorithm, the IGWO-APF algorithm achieves faster convergence to optimal paths. The planned paths effectively avoid obstacles, resulting in lower path planning costs and higher path quality. Compared to the PSO, GA, and WPA algorithms, the fusion algorithm also exhibits higher planning efficiency and superior planning effectiveness. The effectiveness and superiority of the IGWO-APF algorithm in solving the three-dimensional UAV path planning problem in post-disaster rescue missions are confirmed by the experiments.  
However, this study still has some limitations in the simulation experiments. For instance, it did not consider the real-time obstacle avoidance problem posed by dynamic obstacles such as birds in mountainous environments. Further improvements are necessary to make the UAV path planning more practical and realistic. Additionally, this study only conducted simulation-based experiments without deploying the algorithms on actual UAVsfor real-flight experiments. Therefore, in future work, the algorithms should be deployed and tested in real-world scenarios to further validate their performance.  
Conceptualization, D.H. and Q.Y.; methodology, D.H.; software, D.H. and Q.Y.; validation, Q.Y., H.J. and Y.C.; formal analysis, H.J. and X.Z.; investigation, D.H. and Q.Y.; resources, Q.Y. and D.H.; data curation, H.J., Y.C. and X.Z.; writing--original draft preparation, D.H. and Q.Y.; writing--review and editing, D.H., Q.Y. and L.W.; visualization, D.H.; supervision, Q.Y., H.J., Y.C. and L.W.; project administration, D.H. and Q.Y.; funding acquisition, H.J. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Research Center for Scientific Development of Higher Education Institutions, Ministry of Education, grant number 2022 IT 177; Independent research project of the Key Laboratory of Flight Techniques and Flight Safety, grant number FZ2021 ZZ04.  
Data are contained within the article.  
The authors declare no conflicts of interest.