Home // IARIA Congress 2025, The 2025 IARIA Annual Congress on Frontiers in Science, Technology, Services, and Applications // View article
Authors:
Judit Salvans Baucells
Elham Fakhraian
Ivana Semanjski
Keywords: Unmanned Aerial Vehicles (UAV); Unmanned Aerial System (UAS); path planning; Rapidly-Exploring Random Tree Star (RRT*); geozones; optimization; jellyfish Swarm algorithm; Urban Air Mobility (UAM).
Abstract:
The growing demand for autonomous aerial operations highlights the need for efficient and regulation-compliant trajectory planning, particularly in Urban Air Mobility (UAM) applications. This paper presents a UAV path planning framework that combines a geozone-aware Rapidly Exploring Random Tree Star (RRT*) algorithm with a jellyfish-inspired optimization technique to navigate complex airspaces while adhering to safety and regulatory constraints. The method accounts for obstacles, no-fly zones, and altitude limits, and has been tested using real-world geospatial data from Piombino, Italy. Results demonstrate the generation of smooth, efficient trajectories. By enabling scalable and adaptive drone operations, this work supports reliable urban delivery services and integration into future U-space traffic management systems.
Pages: 155 to 161
Copyright: Copyright (c) IARIA, 2025
Publication date: July 6, 2025
Published in: conference
ISBN: 978-1-68558-284-5
Location: Venice, Italy
Dates: from July 6, 2025 to July 10, 2025