RT Conference Proceedings
T1 Ruta óptima para vehículos aéreos no tripulados para la recolección de datos en entornos IoT.
A1 Martín Izquierdo, Adrián
A1 De la Bandera Cascales, Isabel
A1 Barco-Moreno, Raquel
K1 Aviones sin piloto
K1 Optimización de las trayectorias
K1 Telecomunicaciones
AB In this article, a novel approach is presented for dynamic route planning of unmanned aerial vehicles (UAVs) forefficient data collection in industrial environments using UAVs connected to 5G and ultra-low power device networks.The proposed approach is based on bio-inspired algorithms, which draw inspiration from the behavior of animals andplants. The algorithm uses a combination of genetic algorithm (GA) and rapid exploration random tree (RRT) tooptimize the UAV’s route and reduce energy consumption, while complying with the UAV’s flight limitations,considering the energy consumed by the UAV. This solution focuses on achieving higher energy efficiency and betterdata collection capability in industrial environments. The combination of GA and RRT is capable of finding optimalroutes for data collection, reducing the UAV’s energy consumption while ensuring that all flight constraints are met.
YR 2023
FD 2023
LK https://hdl.handle.net/10630/27576
UL https://hdl.handle.net/10630/27576
LA spa
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 6 mar 2026