An Intelligent Approach to UAV Path Planning with Battery Optimization and Charging Station Selection
Vikash Chandra Sharma, Saugata Roy · 2025
Unmanned Aerial Vehicles (UAVs) are widely utilized in surveillance, delivery, and disaster management. However, their operational efficiency is constrained by the limited battery capacity, which poses a significant challenge for prolonged missions. This paper proposes an intelligent path-planning framework that optimizes UAV navigation while ensuring efficient energy utilization and dynamic charging station selection. The proposed approach integrates the A* algorithm for optimal path computation with a battery-aware decision-making mechanism, enabling UAVs to autonomously reroute to charging stations as needed. A comprehensive mathematical formulation of the problem is presented, and simulation results demonstrate the method’s effectiveness in minimizing travel distance while ensuring uninterrupted mission execution. Compared to traditional A* path planning, our battery-aware method reduces mission interruptions by 25% and improves energy efficiency, particularly in dense obstacle scenarios.