Novel 3D UAV Path Planning for IoT Services Based on Interactive Cylindrical Vector Teaching–Learning Optimization Algorithm DOI Creative Commons
Xinghe Jiang, Xuanyu Wu,

Zhifeng Zhang

и другие.

Sensors, Год журнала: 2025, Номер 25(8), С. 2407 - 2407

Опубликована: Апрель 10, 2025

In the 6G-IoT convergence ecosystem, UAV path planning for static environments is systematically investigated as a resource coordination problem where communication demands and terrain constraints are balanced through intelligent trajectory optimization. The innovation of this paper lies in proposal an interactive cylinder vector teaching–learning-based optimization (ICVTLBO) algorithm, points represented cylindrical coordinates, targeted strategies proposed during teacher learner phases to address uncertainty challenges, such elevation fluctuations link instability caused by obstacles environments. ICVTLBO compared with other classical novel algorithms on CEC2022 benchmark function suite, demonstrating its effectiveness reliability solving complex problems. Subsequently, real digital model (DEM) maps utilized establish nine diverse scenarios simulation 3D experimental results show that outperforms methods, providing high-quality paths UAVs

Язык: Английский

Novel 3D UAV Path Planning for IoT Services Based on Interactive Cylindrical Vector Teaching–Learning Optimization Algorithm DOI Creative Commons
Xinghe Jiang, Xuanyu Wu,

Zhifeng Zhang

и другие.

Sensors, Год журнала: 2025, Номер 25(8), С. 2407 - 2407

Опубликована: Апрель 10, 2025

In the 6G-IoT convergence ecosystem, UAV path planning for static environments is systematically investigated as a resource coordination problem where communication demands and terrain constraints are balanced through intelligent trajectory optimization. The innovation of this paper lies in proposal an interactive cylinder vector teaching–learning-based optimization (ICVTLBO) algorithm, points represented cylindrical coordinates, targeted strategies proposed during teacher learner phases to address uncertainty challenges, such elevation fluctuations link instability caused by obstacles environments. ICVTLBO compared with other classical novel algorithms on CEC2022 benchmark function suite, demonstrating its effectiveness reliability solving complex problems. Subsequently, real digital model (DEM) maps utilized establish nine diverse scenarios simulation 3D experimental results show that outperforms methods, providing high-quality paths UAVs

Язык: Английский

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