Energy-Aware UAV Coverage Planning in Mountainous Terrain via Contour-Aligned Path Generation

Coverage path planning in mountainous terrain is energy-intensive for multirotor UAVs due to frequent altitude changes. This letter proposes a Contour-Aligned Path Generation (CAPG) framework that leverages terrain structure to minimize energy use while ensuring full coverage. CAPG reduces the 3D problem to efficient 2D planning by extracting elevation contour primitives from digital elevation models and sequencing them via an asymmetric Traveling Salesperson Problem (ATSP) that accounts for the higher cost of climbs versus descents. Key ideas include constraining UAVs to discrete altitude bands and modeling gravity-induced energy asymmetry in path costs. In simulations based on the DJI Matrice 300 RTK model over 20 mountainous terrains, CAPG lowered energy consumption by about 35.4% compared with grid-based methods, while maintaining 98.3% coverage and above-ground-level (AGL) deviations within <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>1.1 m. Ablation studies show ATSP optimization saves 52.5% energy and altitude quantization adds 28.1%. CAPG consistently achieved robust savings across terrain types, highlighting its potential for energy-critical missions in environmental monitoring and precision agriculture.