Work

Optimum Path Planning for Large Scale Distributed IoT Data Collection Using a Rechargeable UAV

Year: 2025

Type: article

Abstract: This paper designs energy-efficient flight trajectories for a rechargeable unmanned aerial vehicle (UAV) with battery capacity limitations, performing data collection from widely distributed internet-of-things (IoT) ground nodes. We propose a novel optimization framework using dynamic programming, incorporating battery recharging as needed. We develop an optimal backward-forward algorithm that jointly determines the service locations for each ground node, the visiting sequence of these locations, and the optimal times to return to a docking station for battery recharging. Our algorithm optimally minimizes the UAV’s total energy consumption, establishing fundamental performance bounds for airborne data harvesting from widely distributed ground nodes.

Source: IEEE Open Journal of the Communications Society

DOI: 10.1109/ojcoms.2025.3578412

Authors: Dhanushka Kudathanthirige, Hazer Inaltekin, Stephen V. Hanly, Iain B. Collings

Institution: Macquarie University

Language: English

Topic: UAV Applications and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: gold

Estimated APC paid: $2,075