A Multi-constrained Trajectory Representation Framework for Predictable and Low Error UAV Missions

The rapid growth of Unmanned Aerial Vehicle (UAV) applications across various sectors has underscored the need for advanced trajectory planning methods that ensure safe and predictable UAV operations in increasingly regulated airspace, such as the European U-space. This paper presents a novel approa...

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Detalles Bibliográficos
Autores: Casado González, Rafael, Bermúdez Marín, Aurelio, Hernández Orallo, Enrique, Tavares Calafate, Carlos
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Fundación Dialnet. Universidad de La Rioja
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/47943
Acceso en línea:https://doi.org/10.1007/s10846-026-02384-y
https://hdl.handle.net/10578/47943
Access Level:acceso abierto
Palabra clave:Trajectory planning
Unmanned Aerial Vehicle
Unmanned Aircraft System Traffic Management
U-space
Descripción
Sumario:The rapid growth of Unmanned Aerial Vehicle (UAV) applications across various sectors has underscored the need for advanced trajectory planning methods that ensure safe and predictable UAV operations in increasingly regulated airspace, such as the European U-space. This paper presents a novel approach to UAV trajectory planning that incorporates multiple constraints on the flight path, allowing desired speed and acceleration parameters to be defined for specific waypoint positions and times. By enabling precise control over dynamic parameters at each waypoint, our solution ensures smoother and more reliable UAV trajectories, minimizing the risks of abrupt or unpredictable manoeuvres that typically result from waypoint sequences with sudden changes. Experimental results based on use cases with varying requirements demonstrate that our constrained trajectory planning approach indeed provides more predictable and efficient UAV navigation, thereby meeting U-space mandates for safe and coordinated air traffic management. Depending on the experiment, the proposal reduces the error in following the planned mission by 20% to 90%. In addition, a moderate reduction in flight time has been observed in all experiments, reaching up to 40%.