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Authors: Rina Azoulay 1 and Shulamit Reches 2

Affiliations: 1 Department of Computer Science, Jerusalem College of Technology, Havaad Haleumi Street, Jerusalem and Israel ; 2 Department of Mathematics, Jerusalem College of Technology, Havaad Haleumi Street, Jerusalem and Israel

ISBN: 978-989-758-350-6

Keyword(s): Systems and Applications, Transportation Systems, UAVs, Agents, Distributed AI.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Bioinformatics ; Biomedical Engineering ; Cooperation and Coordination ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Formal Methods ; Industrial Applications of AI ; Informatics in Control, Automation and Robotics ; Information Systems Analysis and Specification ; Intelligent Control Systems and Optimization ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Methodologies and Technologies ; Mobile Agents ; Multi-Agent Systems ; Operational Research ; Planning and Scheduling ; Simulation ; Simulation and Modeling ; Soft Computing ; Software Engineering ; Symbolic Systems ; Uncertainty in AI

Abstract: In this study, we consider a situation where several privately owned unmanned aerial vehicles (UAVs) are supposed to travel on several routes. We develop a model for grouping them into UAV flocks that are supposed to travel on similar routes within the same time window. Our proposed flocking protocol enables each UAV to optimize its own preferences concerning its flights. Using this protocol enables all UAVs to enjoy freer routes and fewer encounters with other UAVs, thus saving time and energy during their flights. The protocol allows each UAV to create a flock or to join an existing flock to save its resources. Joining flocks in a crowded environment can reduce the overhead caused by encountering additional UAVs in the environment. We developed a flocking protocol that allows each UAV to design its optimal route. The protocol is based on a public on-line communication blackboard, which enables each UAV to receive information about existing flocks, join an existing flock or build a n ew flock and publish it on the blackboard. In addition, we defined a strategy for each UAV to assist in deciding which flock to join or whether to create a new flock to optimize its expected utility. Finally, the effectiveness of the proposed algorithm is verified by means of simulations. (More)

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Paper citation in several formats:
Azoulay, R. and Reches, S. (2019). UAV Flocks Forming for Crowded Flight Environments.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 154-163. DOI: 10.5220/0007369401540163

@conference{icaart19,
author={Rina Azoulay. and Shulamit Reches.},
title={UAV Flocks Forming for Crowded Flight Environments},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={154-163},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007369401540163},
isbn={978-989-758-350-6},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - UAV Flocks Forming for Crowded Flight Environments
SN - 978-989-758-350-6
AU - Azoulay, R.
AU - Reches, S.
PY - 2019
SP - 154
EP - 163
DO - 10.5220/0007369401540163

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