Literature DB >> 33141726

Autonomous task sequencing in a robot swarm.

Lorenzo Garattoni1, Mauro Birattari2.   

Abstract

Robot swarms mimic natural systems in which collective abilities emerge from the interaction of individuals. So far, the swarm robotics literature has focused on the emergence of mechanical abilities (e.g., push a heavy object) and simple cognitive abilities (e.g., select a path between two alternatives). In this article, we present a robot swarm in which a complex cognitive ability emerged. This swarm was able to collectively sequence tasks whose order of execution was a priori unknown. Because sequencing tasks is an albeit simple form of planning, the robot swarm that we present provides a different perspective on a pivotal debate in the history of artificial intelligence: the debate on planning in robotics. In the proposed swarm, the two robotics paradigms-deliberative (sense-model-plan-act) and reactive (sense-act)-that are traditionally considered antithetical coexist in a particular way: The ability to plan emerges at the collective level from the interaction of reactive individuals.
Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Entities:  

Year:  2018        PMID: 33141726     DOI: 10.1126/scirobotics.aat0430

Source DB:  PubMed          Journal:  Sci Robot        ISSN: 2470-9476


  8 in total

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Authors:  Yasemin Ozkan-Aydin; Daniel I Goldman; M Saad Bhamla
Journal:  Proc Natl Acad Sci U S A       Date:  2021-02-09       Impact factor: 11.205

2.  Phenotypic Plasticity Provides a Bioinspiration Framework for Minimal Field Swarm Robotics.

Authors:  Edmund R Hunt
Journal:  Front Robot AI       Date:  2020-03-16

3.  Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms.

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Journal:  Front Robot AI       Date:  2019-11-26

4.  Automatic Off-Line Design of Robot Swarms: A Manifesto.

Authors:  Mauro Birattari; Antoine Ligot; Darko Bozhinoski; Manuele Brambilla; Gianpiero Francesca; Lorenzo Garattoni; David Garzón Ramos; Ken Hasselmann; Miquel Kegeleirs; Jonas Kuckling; Federico Pagnozzi; Andrea Roli; Muhammad Salman; Thomas Stützle
Journal:  Front Robot AI       Date:  2019-07-19

5.  Sparse Robot Swarms: Moving Swarms to Real-World Applications.

Authors:  Danesh Tarapore; Roderich Groß; Klaus-Peter Zauner
Journal:  Front Robot AI       Date:  2020-07-02

6.  An Empirical Study on Drivers' Willingness to Use Automatic Features of Intelligent Vehicles: A Psychological Empowerment Perspective.

Authors:  Ting Li; Sumeet Gupta; Hong Zhou
Journal:  Front Psychol       Date:  2021-12-16

7.  Empirical assessment and comparison of neuro-evolutionary methods for the automatic off-line design of robot swarms.

Authors:  Ken Hasselmann; Antoine Ligot; Julian Ruddick; Mauro Birattari
Journal:  Nat Commun       Date:  2021-07-16       Impact factor: 14.919

8.  Interaction between a robot and Bunimovich stadium billiards.

Authors:  J V A Vasconcelos; L H Miranda-Filho; A J F de Souza; A R de C Romaguera; A L R Barbosa
Journal:  Sci Rep       Date:  2022-03-23       Impact factor: 4.379

  8 in total

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