Swarm Robotics: Past, Present, and Future [Point of View]

Swarm robotics deals with the design, construction, and deployment of large groups of robots that coordinate and cooperatively solve a problem or perform a task. It takes inspiration from natural self-organizing systems, such as social insects, fish schools, or bird flocks, characterized by emergent...

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Vydáno v:Proceedings of the IEEE Ročník 109; číslo 7; s. 1152 - 1165
Hlavní autoři: Dorigo, Marco, Theraulaz, Guy, Trianni, Vito
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.07.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
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ISSN:0018-9219, 1558-2256
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Abstract Swarm robotics deals with the design, construction, and deployment of large groups of robots that coordinate and cooperatively solve a problem or perform a task. It takes inspiration from natural self-organizing systems, such as social insects, fish schools, or bird flocks, characterized by emergent collective behavior based on simple local interaction rules <xref ref-type="bibr" rid="ref1">[1] , <xref ref-type="bibr" rid="ref2">[2] . Typically, swarm robotics extracts engineering principles from the study of those natural systems in order to provide multirobot systems with comparable abilities. This way, it aims to build systems that are more robust, fault-tolerant, and flexible than single robots and that can better adapt their behavior to changes in the environment.
AbstractList Swarm robotics deals with the design, construction, and deployment of large groups of robots that coordinate and cooperatively solve a problem or perform a task. It takes inspiration from natural self-organizing systems, such as social insects, fish schools, or bird flocks, characterized by emergent collective behavior based on simple local interaction rules <xref ref-type="bibr" rid="ref1">[1] , <xref ref-type="bibr" rid="ref2">[2] . Typically, swarm robotics extracts engineering principles from the study of those natural systems in order to provide multirobot systems with comparable abilities. This way, it aims to build systems that are more robust, fault-tolerant, and flexible than single robots and that can better adapt their behavior to changes in the environment.
Swarm robotics takes inspiration from natural selforganizing systems such as social insects, fish schools or bird flocks, deriving rules to build robotic systems that are more robust, fault-tolerant and flexible than single robots. Over the last two decades, swarm robotics has made significant progress, providing concrete demonstrations on how robot swarms could address complex problems, and also contributing to a better understanding of how complex behaviors emerge in nature. However, as of today, only few published experiments have been able to demonstrate collective behavior in a number of robots that can effectively be compared to the size of biological swarms, and further research is needed before swarm robotics is mature enough to be employed in real world applications. Here we summarize the main lessons learned during the first two decades of research in the field and the main open problems still to be solved, such as the lack of dedicated hardware and software platforms, the need for reliable methodologies for swarm design, or how to make the best out of biological inspiration. We then present what we expect to be the main avenues of research in the future, and discuss how application demands may drive swarm robotics research, transitioning from abstract studies towards an engineering practice. Specifically, we identify precision agriculture, infrastructure inspection and maintenance, defense, space missions, entertainment and precision medicine as the application fields that will most likely drive the science and technology of robot swarms in the next three decades.
Swarm robotics deals with the design, construction, and deployment of large groups of robots that coordinate and cooperatively solve a problem or perform a task. It takes inspiration from natural self-organizing systems, such as social insects, fish schools, or bird flocks, characterized by emergent collective behavior based on simple local interaction rules [1] , [2] . Typically, swarm robotics extracts engineering principles from the study of those natural systems in order to provide multirobot systems with comparable abilities. This way, it aims to build systems that are more robust, fault-tolerant, and flexible than single robots and that can better adapt their behavior to changes in the environment.
Author Theraulaz, Guy
Dorigo, Marco
Trianni, Vito
Author_xml – sequence: 1
  givenname: Marco
  orcidid: 0000-0002-3971-0507
  surname: Dorigo
  fullname: Dorigo, Marco
  organization: Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle (IRIDIA), Université Libre de Bruxelles (ULB), Brussels, Belgium
– sequence: 2
  givenname: Guy
  orcidid: 0000-0002-3062-4215
  surname: Theraulaz
  fullname: Theraulaz, Guy
  organization: Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse-Paul Sabatier, Toulouse, France
– sequence: 3
  givenname: Vito
  orcidid: 0000-0002-9114-8486
  surname: Trianni
  fullname: Trianni, Vito
  organization: Institute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Rome, Italy
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Snippet Swarm robotics deals with the design, construction, and deployment of large groups of robots that coordinate and cooperatively solve a problem or perform a...
Swarm robotics takes inspiration from natural selforganizing systems such as social insects, fish schools or bird flocks, deriving rules to build robotic...
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SubjectTerms Adaptation and Self-Organizing Systems
Artificial Intelligence
Computational Complexity
Computer Science
Design methodology
Fault tolerance
Insects
Life Sciences
Multiagent Systems
Multiple robots
Neurons and Cognition
Nonlinear Sciences
Performance evaluation
Psychology and behavior
Robotics
Robots
Robustness
Self organizing systems
Self-organizing networks
Swarm particle optimization
Title Swarm Robotics: Past, Present, and Future [Point of View]
URI https://ieeexplore.ieee.org/document/9460560
https://www.proquest.com/docview/2542502478
https://hal.science/hal-03362874
Volume 109
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