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A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

This work presents a review and discussion of the challenges that must be solved in order to successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From the discussion, we extract constraints and links that relate the local level MAV capabilities to the global operations...

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Autores principales: Coppola, Mario, McGuire, Kimberly N., De Wagter, Christophe, de Croon, Guido C. H. E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806031/
https://www.ncbi.nlm.nih.gov/pubmed/33501187
http://dx.doi.org/10.3389/frobt.2020.00018
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author Coppola, Mario
McGuire, Kimberly N.
De Wagter, Christophe
de Croon, Guido C. H. E.
author_facet Coppola, Mario
McGuire, Kimberly N.
De Wagter, Christophe
de Croon, Guido C. H. E.
author_sort Coppola, Mario
collection PubMed
description This work presents a review and discussion of the challenges that must be solved in order to successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From the discussion, we extract constraints and links that relate the local level MAV capabilities to the global operations of the swarm. These should be taken into account when designing swarm behaviors in order to maximize the utility of the group. At the lowest level, each MAV should operate safely. Robustness is often hailed as a pillar of swarm robotics, and a minimum level of local reliability is needed for it to propagate to the global level. An MAV must be capable of autonomous navigation within an environment with sufficient trustworthiness before the system can be scaled up. Once the operations of the single MAV are sufficiently secured for a task, the subsequent challenge is to allow the MAVs to sense one another within a neighborhood of interest. Relative localization of neighbors is a fundamental part of self-organizing robotic systems, enabling behaviors ranging from basic relative collision avoidance to higher level coordination. This ability, at times taken for granted, also must be sufficiently reliable. Moreover, herein lies a constraint: the design choice of the relative localization sensor has a direct link to the behaviors that the swarm can (and should) perform. Vision-based systems, for instance, force MAVs to fly within the field of view of their camera. Range or communication-based solutions, alternatively, provide omni-directional relative localization, yet can be victim to unobservable conditions under certain flight behaviors, such as parallel flight, and require constant relative excitation. At the swarm level, the final outcome is thus intrinsically influenced by the on-board abilities and sensors of the individual. The real-world behavior and operations of an MAV swarm intrinsically follow in a bottom-up fashion as a result of the local level limitations in cognition, relative knowledge, communication, power, and safety. Taking these local limitations into account when designing a global swarm behavior is key in order to take full advantage of the system, enabling local limitations to become true strengths of the swarm.
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spelling pubmed-78060312021-01-25 A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints Coppola, Mario McGuire, Kimberly N. De Wagter, Christophe de Croon, Guido C. H. E. Front Robot AI Robotics and AI This work presents a review and discussion of the challenges that must be solved in order to successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From the discussion, we extract constraints and links that relate the local level MAV capabilities to the global operations of the swarm. These should be taken into account when designing swarm behaviors in order to maximize the utility of the group. At the lowest level, each MAV should operate safely. Robustness is often hailed as a pillar of swarm robotics, and a minimum level of local reliability is needed for it to propagate to the global level. An MAV must be capable of autonomous navigation within an environment with sufficient trustworthiness before the system can be scaled up. Once the operations of the single MAV are sufficiently secured for a task, the subsequent challenge is to allow the MAVs to sense one another within a neighborhood of interest. Relative localization of neighbors is a fundamental part of self-organizing robotic systems, enabling behaviors ranging from basic relative collision avoidance to higher level coordination. This ability, at times taken for granted, also must be sufficiently reliable. Moreover, herein lies a constraint: the design choice of the relative localization sensor has a direct link to the behaviors that the swarm can (and should) perform. Vision-based systems, for instance, force MAVs to fly within the field of view of their camera. Range or communication-based solutions, alternatively, provide omni-directional relative localization, yet can be victim to unobservable conditions under certain flight behaviors, such as parallel flight, and require constant relative excitation. At the swarm level, the final outcome is thus intrinsically influenced by the on-board abilities and sensors of the individual. The real-world behavior and operations of an MAV swarm intrinsically follow in a bottom-up fashion as a result of the local level limitations in cognition, relative knowledge, communication, power, and safety. Taking these local limitations into account when designing a global swarm behavior is key in order to take full advantage of the system, enabling local limitations to become true strengths of the swarm. Frontiers Media S.A. 2020-02-25 /pmc/articles/PMC7806031/ /pubmed/33501187 http://dx.doi.org/10.3389/frobt.2020.00018 Text en Copyright © 2020 Coppola, McGuire, De Wagter and de Croon. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Robotics and AI
Coppola, Mario
McGuire, Kimberly N.
De Wagter, Christophe
de Croon, Guido C. H. E.
A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints
title A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints
title_full A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints
title_fullStr A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints
title_full_unstemmed A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints
title_short A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints
title_sort survey on swarming with micro air vehicles: fundamental challenges and constraints
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806031/
https://www.ncbi.nlm.nih.gov/pubmed/33501187
http://dx.doi.org/10.3389/frobt.2020.00018
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