Terrain-Following Path Planning for UAV Swarms with Collision Avoidance

To address the problem of multi-UAV path planning in the complex terrain environment with obstacle threat, this paper proposes an improved A* algorithm combined with B-spline curve optimization. Firstly, unlike fixed-weight approaches, the terrain following of UAV is achieved by incorporating ground altitude s(n) with a weighted parameter w₁ in the heuristic function, while maintaining a minimum safety clearance. Then, the weight coefficient of the estimated cost in the heuristic function is set according to the obstacle rate Q, significantly improving search efficiency in cluttered environments. Finally, cubic B-spline smoothing is applied to eliminate redundant waypoints and ensure kinematic feasibility of the planned paths. Simulation results demonstrate that compared to traditional A*, the proposed algorithm reduces path search time by 76% and decreases waypoints by up to 52.24%, while generating smoother, more navigable trajectories suitable for real-world UAV operations.