## 5 Discussion
### Analysis of Path Planning Effectiveness  
From Figure 11, it can be observed that the IGWO algorithm successfully completes the path planning task from three different starting points. However, in Figure 11a, it should be noted that the paths generated by the IGWO algorithm are too close to the mountainous obstacles from (12, 14, 19) to (12, 21, 25). This proximity increases the risk of the UAV colliding with the mountains, potentially leading to a crash. Additionally, the path planned at (15, 23, 40) exhibits considerable twists and turns, indicating lower path smoothness. Therefore, the use of the APF algorithm is necessary for secondary path planning to address these challenges in proximity to obstacles and path smoothness. According to Table 5, it can be observed that the IGWO-IAPF algorithm consistently achieves superior optimal fitness values and average optimal fitness values compared to the GWO, PSO, GA, and WPA algorithms. This indicates that the IGWO-IAPF algorithm consistently finds the optimal path compared to other algorithms. The standard deviation of the IGWO algorithm is significantly lower than that of other algorithms, indicating lower curve dispersion and improved stability in path optimization. The planning time of the IGWO-IAPF algorithm is relatively good compared to several other algorithms, being only around 6% slower than the PSO algorithm. However, due to the adoption of a quadratic programming mode during the planning process, the IGWO-IAPF algorithm has a higher computational complexity compared to the PSO algorithm. Nevertheless, the IGWO-IAPF algorithm demonstrates a relatively better planning performance. Therefore, this study believes that the improved IGWO-IAPF algorithm is capable of rapidly conducting effective path planning and improving planning efficiency. From Figure 12, it can be observed that the IGWO-IAPF algorithm achieves favorable results in UAV path planning. The legend and textual labels in the figure provide corresponding parameter descriptions. The algorithmic steps of the IGWO-IAPF algorithm proposed in this paper are shown in the box in the figure. The fusion algorithm consists of three stages during the path planning process: the first and third stages involve fast path planning using the IAPF algorithm, while the second stage represents the path planning phase of the IGWO-IAPF algorithm. In the first and third stages, when the distance between \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Algorithm** & **Optimal Fitness Value** & **Average Optimal Fitness Value** & **Standard Deviation** & **Algorithm Planning Time/s** \\ \hline IGWO-IAPF & 1583.68 & 1607.39 & 23.52 & 53.06 \\ GWO & 1827.69 & 1890.71 & 158.98 & 126.37 \\ PSO & 1683.29 & 1694.52 & 103.41 & 46.58 \\ GA & 1709.16 & 1733.23 & 53.62 & 62.14 \\ WPA & 1699.04 & 1723.41 & 89.27 & 55.42 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison results of algorithm multiple runs. the UAV and obstacles is greater than \(p_{0}\), the algorithm directly utilizes the IAPF algorithm for fast planning. However, when the distance between the UAV and obstacles is less than \(p_{0}\), the fusion algorithm is employed for planning. From the figure, it can be observed that although the planned flight path comes close to the peaks of obstacles, it consistently maintains a safe distance. From Figure 13, it can be observed that both the IGWO-IAPF algorithm and the other four algorithms successfully plan paths that avoid obstacle areas, allowing the UAV to reach the target point smoothly. However, the paths planned by the traditional GWO algorithm are too far from the obstacle at (80, 35, 62), resulting in significantly reduced flight efficiency. On the other hand, the WPA algorithm plans a path that is too close to the obstacle at (80, 35, 62), which increases the risk of collision during actual operation. Additionally, the paths planned by the four comparative algorithms exhibit significant turning angles, which have a considerable impact on the flight range and path smoothness.