Multi-UAV coverage planning in complex mountainous environments is often constrained by idealized energy modeling, the “wood barrel effect” of traditional global energy minimization paradigms, and a lack of dynamic fault tolerance. To address these limitations, this study proposes a survivability-oriented Min–Max optimization architecture driven by the novel Lévy–Flight Terrain-Following Constrained Planning Optimization (LF-TF-CPO) algorithm. Coupling a high-fidelity 3D topographical matrix with a nonlinear aerodynamic energy model, the framework prioritizes individual UAV safety. Monte Carlo simulations demonstrate that LF-TF-CPO compresses the average maximum individual energy consumption to 665.64 kJ, preserving an adequate operational margin below the 950 kJ physical redline to absorb unmodeled aerodynamic perturbations while ensuring a 31.30 min mission duration. Ablation studies verify the Min–Max objective mitigates localized overloads with a marginal 0.4% energy trade-off. Furthermore, an emergency recovery protocol validates dynamic resilience across simultaneous and cascading failures by consistently stabilizing post-failure peak loads within safe margins. Notably, statistical evaluations establish a robust empirical sweet spot (
Li et al. (Thu,) studied this question.