MRFO-based 3D path planning for UAV rescue missions in complex mountainous environments

Abstract

To address the limitations of traditional path planning methods in complex terrains, such as poor safety, low efficiency, and insufficient adaptability, this paper proposes a three-dimensional UAV path planning method based on the Manta Ray Foraging Optimization (MRFO) algorithm for rescue missions in complex mountainous environments. First, a three-dimensional safe map model is constructed by integrating terrain information and no-fly zone constraints. On this basis, multiple flight constraints including flight altitude, no-fly zone avoidance, climbing gradient, turning slope, and overload are comprehensively considered. A multi-objective weighted cost function is designed to evaluate path length, altitude stability, and path smoothness. Furthermore, the MRFO algorithm simulates three foraging behaviors of manta rays: chain foraging, spiral foraging, and somersault foraging. Combined with adaptive weight adjustment and boundary handling strategies, efficient path optimization is achieved. Simulation results demonstrate that the proposed method can rapidly generate safe, smooth, and energy-efficient rescue paths that satisfy UAV dynamic constraints. The approach significantly improves mission execution efficiency and safety in complex mountainous environments.