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Swarm robotics

About: Swarm robotics is a research topic. Over the lifetime, 3001 publications have been published within this topic receiving 60746 citations.


Papers
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BookDOI
01 Jan 1999
TL;DR: This chapter discusses Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks, and its application to Data Analysis and Graph Partitioning.
Abstract: 1. Introduction 2. Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks 3. Division of Labor and Task Allocation 4. Cemetery Organization, Brood Sorting, Data Analysis, and Graph Partitioning 5. Self-Organization and Templates: Application to Data Analysis and Graph Partitioning 6. Nest Building and Self-Assembling 7. Cooperative Transport by Insects and Robots 8. Epilogue

5,822 citations

Journal ArticleDOI
TL;DR: This book provides fairly comprehensive coverage of recent research developments and constitutes an excellent resource for researchers in the swarm intelligence area or for those wishing to familiarize themselves with current approaches e.g. it would be an ideal introduction for a doctoral student wanting to enter this area.
Abstract: (2002). Swarm Intelligence: From Natural to Artificial Systems. Connection Science: Vol. 14, No. 2, pp. 163-164.

1,777 citations

Proceedings ArticleDOI
13 Apr 1997
TL;DR: The paper introduces the algorithm, begins to develop a social science context for it, and explores some aspects of its functioning.
Abstract: Particle swarm adaptation is an optimization paradigm that simulates the ability of human societies to process knowledge The algorithm models the exploration of a problem space by a population of individuals; individuals' successes influence their searches and those of their peers The algorithm is relevant to cognition, in particular the representation of schematic knowledge in neural networks Particle swarm optimization successfully optimizes network weights, simulating the adaptive sharing of representations among social collaborators The paper introduces the algorithm, begins to develop a social science context for it, and explores some aspects of its functioning

1,630 citations

Journal ArticleDOI
TL;DR: This paper analyzes the literature from the point of view of swarm engineering and proposes two taxonomies: in the first taxonomy, works that deal with design and analysis methods are classified; in the second, works according to the collective behavior studied are classified.
Abstract: Swarm robotics is an approach to collective robotics that takes inspiration from the self-organized behaviors of social animals. Through simple rules and local interactions, swarm robotics aims at designing robust, scalable, and flexible collective behaviors for the coordination of large numbers of robots. In this paper, we analyze the literature from the point of view of swarm engineering: we focus mainly on ideas and concepts that contribute to the advancement of swarm robotics as an engineering field and that could be relevant to tackle real-world applications. Swarm engineering is an emerging discipline that aims at defining systematic and well founded procedures for modeling, designing, realizing, verifying, validating, operating, and maintaining a swarm robotics system. We propose two taxonomies: in the first taxonomy, we classify works that deal with design and analysis methods; in the second taxonomy, we classify works according to the collective behavior studied. We conclude with a discussion of the current limits of swarm robotics as an engineering discipline and with suggestions for future research directions.

1,405 citations

Book ChapterDOI
01 Jan 1993
TL;DR: It is argued that the latter two type of unpredictability, when exhibited by systems capable of producing order, can result in a non-trivial, different form of intelligent behavior (Swarm Intelligence).
Abstract: Cellular Robotic Systems are capable of ’intelligent* behavior. The meaning of this intelligence is analyzed in the paper. We define robot intelligence and robot system intelligence in terms of unpredictability of improbable behavior. The concept of unpredictability is analyzed in relation to (1) statistical unpredictability, (2) inaccessibility, (3) undecidability, (4) intractability, and (5) non-representability. We argue that the latter two type of unpredictability, when exhibited by systems capable of producing order, can result in a non-trivial, different form of intelligent behavior (Swarm Intelligence). Engineering problems related to Swarm Intelligence are mentioned in relation to Cellular Robotic Systems which consist of collections of autonomous, non-synchronized, non-intelligent robots cooperating to achieve global tasks.

942 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023115
2022305
2021167
2020224
2019217
2018224