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Română · beta. Traducerea a fost făcută automat și este încă în curs de revizuire. Citește pagina în engleză

În afara temei aiqbench

În afara temei aiqbench

Această știre a fost preluată de la o sursă pe care o urmărim, dar nu ține de domeniul AI sau cuantic, așa că nu există o perspectivă aiqbench pentru ea.

An Optimal Algorithm for Changing from Longitudinal to Latitudinal Formation of Autonomous Aircraft Squadrons

arXiv1 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2610.17511v1 Announce Type: new Abstract: This work presents an algorithm for changing from longitudinal to latitudinal formation of autonomous aircraft squadrons. The maneuvers are defined dynamically by using a predefined set of 3D basic maneuvers. This formation change is necessary when the squadron has to perform tasks demanding both formations, such as landing, lift-off, obstacle avoidance and georeferencing. The time complexity analysis of the transformation algorithm reveals that its efficiency is optimal. Simulations show that the formation change is done without collision, and the proof of correctness ensures its latitudinal formation features.

Abstract:This work presents an algorithm for changing from longitudinal to latitudinal formation of autonomous aircraft squadrons. The maneuvers are defined dynamically by using a predefined set of 3D basic maneuvers. This formation change is necessary when the squadron has to perform tasks demanding both formations, such as landing, lift-off, obstacle avoidance and georeferencing. The time complexity analysis of the transformation algorithm reveals that its efficiency is optimal. Simulations show that the formation change is done without collision, and the proof of correctness ensures its latitudinal formation features.

Robotics (cs.RO)

arXiv:2610.17511 [cs.RO]

(or arXiv:2610.17511v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.17511 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

Proceeding Series of the Brazilian Society of Applied and Computational Mathematics, Vol. 1, N. 1, 2013

https://doi.org/10.5281/zenodo.21473681 Focus to learn more DOI(s) linking to related resources

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