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Learning Vision-based Cohesive Flight in Drone Swarms [article]

Fabian Schilling, Julien Lecoeur, Fabrizio Schiano, Dario Floreano
2018 arXiv   pre-print
This paper presents a data-driven approach to learning vision-based collective behavior from a simple flocking algorithm.  ...  We simulate a swarm of quadrotor drones and formulate the controller as a regression problem in which we generate 3D velocity commands directly from raw camera images.  ...  Acknowledgements We thank Enrica Soria for the feedback and helpful discussions, as well as Olexandr Gudozhnik and Przemyslaw Kornatowski for their contributions to the drone hardware.  ... 
arXiv:1809.00543v1 fatcat:lkizzqursnejndc3muovz6riri

A Review of Counter-UAS Technologies for Cooperative Defensive Teams of Drones

Vittorio Ugo Castrillo, Angelo Manco, Domenico Pascarella, Gabriella Gigante
2022 Drones  
on their applicability and suitability in the case of mini drones.  ...  For this purpose, the paper evaluates the concept of a multiplatform counter-UAS system (CUS), based mainly on a team of mini drones acting as a cooperative defensive system.  ...  Drones 2022, 6, 65  ... 
doi:10.3390/drones6030065 fatcat:bpnk3izp5vf3zcvvoeg3kf5n34

Mathematical modeling for flocking flight of autonomous multi-UAV system, including environmental factors

2020 KSII Transactions on Internet and Information Systems  
We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.  ...  In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones.  ...  Many studies have considered using sensors for the autonomous flight of drones. Global Positioning System (GPS) based autonomous drone swarm models are proposed [12, 17, 23, 24] .  ... 
doi:10.3837/tiis.2020.02.007 fatcat:pkwvafv5nzahzi3dkppwsv47jy

Aerial and Under-water Dronal Communication: Potentials, Issues and Vulnerabilities

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
With the advent of Deep Learning and Machine Learning the autonomous navigation functionalities have been improved but it still poses a challenge as navigating a drone involves the integration of its software  ...  Topics in navigation such as Control, Hardware, Algorithms, Path-Planning, and communication are touched upon in this paper.  ...  by all the drones in cohesion.  ... 
doi:10.35940/ijitee.a4958.119119 fatcat:p2xwhx7tybd5vp37ivs6tzapdq

UAV Swarm Intelligence: Recent Advances and Future Trends

Yong-Kun Zhou, Bin Rao, Wei Wang
2020 IEEE Access  
Through this in-depth literature review, we intend to provide novel insights into the latest technologies in UAV swarm intelligence.  ...  In this paper, we present a comprehensive survey of UAV swarm intelligence from the hierarchical framework perspective. Firstly, we review the basics and advances of UAV swarm intelligent technology.  ...  To be able to fully synchronize all the drones in the group during the entire flight, the mission-based UAV swarm coordination protocol (MUSCOP) can effectively maintain the group cohesion of different  ... 
doi:10.1109/access.2020.3028865 fatcat:bvru22a2jregnmzbpehefg7irm

A General Auxiliary Controller for Multi-agent Flocking [article]

Jinfan Zhou, Jiyu Cheng, Lin Zhang, Wei Zhang
2021 arXiv   pre-print
We demonstrate the efficacy of the auxiliary controller by applying it to several existing algorithms including learning-based and non-learning-based methods.  ...  “Learning vision-based flight in IEEE Transactions on Robotics 22.2 (2006), pp. 402– drone swarms by imitation”.  ...  of Vision-Based Decentralized Controllers for Robot “Stable flocking of mobile agents part I: dynamic Swarms”. In: arXiv preprint arXiv:2002.02308 (2020). topology”.  ... 
arXiv:2112.06023v1 fatcat:o7s4b6evc5ggnbfh4j2737kdzy

Machine Learning Methods for Management UAV Flocks - a Survey

Rina Azoulay, Yoram Haddad, Shulamit Reches
2021 IEEE Access  
For each issue, we survey several machine learning-based methods that have been suggested in the literature to handle the associated challenges.  ...  Several computational challenges arise in UAV flock management, which can be solved by using machine learning (ML) methods.  ...  and drone swarms.  ... 
doi:10.1109/access.2021.3117451 fatcat:f6xli6srencw3ezqg5fyzwmuie

Science, technology and the future of small autonomous drones

Dario Floreano, Robert J. Wood
2015 Nature  
We are witnessing the advent of a new era of robots -drones -that can autonomously fly in natural and man-made environments.  ...  Autonomous flight in confined spaces presents great scientific and technical challenges owing to the energetic cost of staying airborne and to the perceptual intelligence required to negotiate complex  ...  D.F. also thanks the Swiss National Science Foundation through the National Centre of Competence in Research Robotics.  ... 
doi:10.1038/nature14542 pmid:26017445 fatcat:jiz2myqb3fh57fys352ydg4zm4

Online Flocking Control of UAVs with Mean-Field Approximation [article]

Malintha Fernando
2021 arXiv   pre-print
Our algorithm builds on the Mean-Field Approximation and incorporates the collective behavioral rules: cohesion, separation, and velocity alignment.  ...  We present a novel approach to the formation controlling of aerial robot swarms that demonstrates the flocking behavior.  ...  Further, [20] and [21] propose data-driven approaches for the vision-based flocking of quadrotors.  ... 
arXiv:2103.15241v1 fatcat:t4tty4ca25ftzbr7pgmvb6mm7a

Final Program

2020 2020 International Conference on Unmanned Aircraft Systems (ICUAS)  
We are certain that all of us will take pleasure in visiting Athens and in travelling through the city's incredible history. We look forward to seeing all of you in Athens.  ...  and future directions in unmanned aircraft systems.  ...  due to their short flight time.  ... 
doi:10.1109/icuas48674.2020.9214039 fatcat:7jr6chhfija47kgtwoxqmfmmoe

Blockchain-Based Federated Learning in UAVs Beyond 5G Networks: A Solution Taxonomy and Future Directions

Deepti Saraswat, Ashwin Verma, Pronaya Bhattacharya, Sudeep Tanwar, Gulshan Sharma, Pitshou N. Bokoro, Ravi Sharma
2022 IEEE Access  
UAVs mainly communicate with mobile base stations, ground stations (GS), or networked peer UAVs, known as UAV swarms.  ...  Thus, blockchain (BC)-based FL schemes for UAVs allow trusted exchange of FL updates among UAV swarms and GS.  ...  A timely response mechanism should be designed to prevent UAV-based calamities during in-flight swarm operations.  ... 
doi:10.1109/access.2022.3161132 fatcat:4h6ormfvjfd45n25vvzkynvyg4

Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System Perspective [article]

Haijun Wang, Haitao Zhao, Jiao Zhang, Dongtang Ma, Jiaxun Li, Jibo Wei
2018 arXiv   pre-print
in recent years.  ...  In this paper, we present a comprehensive survey on the UAV networks from a CPS perspective.  ...  In [233] , two back propagation networks are used in the control system to achieve the model identification and control. • Reinforcement learning-based flight control algorithms: Reinforcement learning  ... 
arXiv:1812.06821v1 fatcat:5b65dzzsunepnl5fzfvxsf442y

A Decade of UAV Docking Stations: A Brief Overview of Mobile and Fixed Landing Platforms

Carlo Giorgio Grlj, Nino Krznar, Marko Pranjić
2022 Drones  
Rapid advances in computer vision systems gave birth to precise landing systems. These algorithms are the main reason that docking stations became a viable solution.  ...  Even though batteries have been improved and are constantly being improved, they provide fairly low energy density, which limits multirotors' UAV flight endurance.  ...  Other designs found for this review are systems for multiple smaller UAV landings and docking, like in [84] . These can be used for drone swarms which are used for the same operation.  ... 
doi:10.3390/drones6010017 fatcat:3kwnfg6ynfaj5jqceyqcl3hci4

Recent Advances in Formations of Multiple Robots

Saar Cohen, Noa Agmon
2021 Current Robotics Reports  
Furthermore, machine learning (ML)-based methods for navigating a robot team through unknown complex environments can be incorporated, where the robot team aims to reach a goal position while avoiding  ...  For instance, consensus-based control and collision avoidance are usually intertwined together for the sake of reaching a consensus in a manner which is collision-free.  ...  , and formation flights.  ... 
doi:10.1007/s43154-021-00049-2 fatcat:xu4xzhaqpvduljk6pvf34z6fva

A swarm behaviour for jellyfish bloom detection

Fidel Aznar, Mar Pujol, Ramón Rizo
2017 Ocean Engineering  
In this paper we will deal with the issue of swarm behaviour for jellyfish detection using UAVs (Unmanned Aerial Vehicles). Swarm behaviour is inspired by the functioning of biological swarms.  ...  Finally, a macroscopic model will be provided to predict the probability that an individual is placed in a position at a given moment.  ...  Acknowledgement This work has been carried out by the project "Intelligent Swarm Systems of Unmanned Aerial Vehicles for Security and Surveillance" TIN2013-40982-R.  ... 
doi:10.1016/j.oceaneng.2017.02.009 fatcat:q632kuh5eff6fammkecobtjt6e
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