Low-complexity UAV path planning for distributed data collection

This paper presents an energy-efficient flight path planning scheme for rechargeable uncrewed aerial vehicles (UAVs) that sequentially harvest data from distributed ground nodes (GNs). The UAV has a limited battery and must return to a charging station to recharge when needed. We propose a novel low-complexity path planning method that iteratively updates the visiting sequence of GNs and their corresponding hovering locations. The path always ends at a charging station, and a new GN is added only if the charging station can still be reached. Our analysis shows that the proposed algorithm has a quadratic computational complexity with respect to the number of GNs, compared to the exponential complexity of the optimal design. Numerical results demonstrate that our scheme achieves near-optimal performance in terms of energy consumption.