UAV trajectory optimisation in smart cities using modified A* algorithm combined with Haversine and Vincenty formulas

Andreou, A, Mavromoustakis, CX, Batalla, JM, Markakis, EK, Mastorakis, G and Mumtaz, S ORCID: https://orcid.org/0000-0001-6364-6149, 2023. UAV trajectory optimisation in smart cities using modified A* algorithm combined with Haversine and Vincenty formulas. IEEE Transactions on Vehicular Technology. ISSN 0018-9545

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Abstract

It is anticipated that the backbone of Smart Cities concerning automation and networking will be formed by Unmanned Aerial Vehicles in the imminent future. Therefore, our research focuses on developing advanced microcontrollers embedded with Artificial Intelligence techniques for self-governing Unmanned Aerial Vehicles. The main objective of this research was to enable full automation for the execution of flight paths with non-trivial sequences that will be performed with centimetre-level accuracy. Also, by utilising dynamic flight plans and trajectories, we aim to secure autonomous aviation based on norms, with control loops and fundamental constraints. More specifically, we evolved a novel algorithmic technique for trajectory optimisation, which deploys a modification to the A* search algorithm, implemented by the Haversine formula and enhances accuracy using Vincenty’s formula. Furthermore, realistic values for trajectory optimisation and obstacle avoidance were found through the implementation of a simulative investigation. The outcomes of our methodology indicate that the safety constraints associated with the integration of Unmanned Aerial Vehicles in the urban environment can be significantly mitigated. Consequently, their effectiveness will be increased in realising their diverse operations and capabilities.

Item Type:	Journal article
Publication Title:	IEEE Transactions on Vehicular Technology
Creators:	Andreou, A., Mavromoustakis, C.X., Batalla, J.M., Markakis, E.K., Mastorakis, G. and Mumtaz, S.
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Date:	10 March 2023
ISSN:	0018-9545
Identifiers:	Number Type 10.1109/tvt.2023.3254604 DOI 1741516 Other
Rights:	© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Ward
Date Added:	04 Apr 2023 08:00
Last Modified:	04 Apr 2023 08:00
URI:	https://irep.ntu.ac.uk/id/eprint/48693

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