Machine Learning Methods for Management UAV Flocks -- a Survey
- URL: http://arxiv.org/abs/2108.13448v1
- Date: Mon, 30 Aug 2021 18:03:34 GMT
- Title: Machine Learning Methods for Management UAV Flocks -- a Survey
- Authors: Rina Azoulay and Yoram Haddad and Shulamit Reches
- Abstract summary: UAV technology can be used in a wide range of domains, including communication, agriculture, security, and transportation.
It may be useful to group the UAVs into clusters/flocks in certain domains, and various challenges associated with UAV usage can be alleviated by clustering.
Several computational challenges arise in UAV flock management, which can be solved by using machine learning (ML) methods.
- Score: 3.190574537106449
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: The development of unmanned aerial vehicles (UAVs) has been gaining momentum
in recent years owing to technological advances and a significant reduction in
their cost. UAV technology can be used in a wide range of domains, including
communication, agriculture, security, and transportation. It may be useful to
group the UAVs into clusters/flocks in certain domains, and various challenges
associated with UAV usage can be alleviated by clustering. Several
computational challenges arise in UAV flock management, which can be solved by
using machine learning (ML) methods. In this survey, we describe the basic
terms relating to UAVS and modern ML methods, and we provide an overview of
related tutorials and surveys. We subsequently consider the different
challenges that appear in UAV flocks. For each issue, we survey several machine
learning-based methods that have been suggested in the literature to handle the
associated challenges. Thereafter, we describe various open issues in which ML
can be applied to solve the different challenges of flocks, and we suggest
means of using ML methods for this purpose. This comprehensive review may be
useful for both researchers and developers in providing a wide view of various
aspects of state-of-the-art ML technologies that are applicable to flock
management.
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