Research on Path Planning Model of UAV for Emergency Rescue in Plateau Regions

In response to the limitations of traditional rescue methods in plateau regions due to complex terrain and harsh weather, this paper proposes a dynamic path planning model of unmanned aerial vehicle (UAV) and solves it using an improved NSGA-II algorithm. A multi-objective optimization model is constructed by integrating simulated Digital Elevation Models (DEM) and threat factors. Simulation cases are employed to validate the improved NSGA-II algorithm with comparisons to the traditional NSGA-II and PSO algorithms. Experimental results demonstrate that in scenarios at altitudes of 5000–10000 meters, the improved NSGA-II algorithm achieves 39% higher overall operational efficiency than the traditional NSGA-II and 22% higher than the PSO algorithm. It significantly reduces the runtime and iteration counts, lowers the mean optimal fitness value, and exhibits superior capability in avoiding environmental threat zones. The enhanced NSGA-II algorithm demonstrates advanced path planning performance, providing technical support for drone-based emergency rescue operations in plateau regions. These advancements will not only promote breakthroughs in multi-objective optimization algorithms but also significantly enhance emergency response capabilities and safeguard life and property security in plateau regions.