Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Group-level patterns emerge from individual speed as revealed by an extremely social robotic fish

View ORCID ProfileJolle W. Jolles, Nils Weimar, View ORCID ProfileTim Landgraf, View ORCID ProfilePawel Romanczuk, Jens Krause, View ORCID ProfileDavid Bierbach
doi: https://doi.org/10.1101/2020.06.10.143883
Jolle W. Jolles
1Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz
2Zukunftskolleg, University of Konstanz, Konstanz
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jolle W. Jolles
  • For correspondence: j.w.jolles@gmail.com david.bierbach@gmx.de
Nils Weimar
3Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tim Landgraf
4Department of Mathematics and Computer Science, Institute for Computer Science, Freie Universität Berlin, Berlin
5Excellence Cluster ‘Science of Intelligence’, Technische Universität Berlin, Berlin
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Tim Landgraf
Pawel Romanczuk
5Excellence Cluster ‘Science of Intelligence’, Technische Universität Berlin, Berlin
6Faculty of Life Sciences, Thaer-Institute, Humboldt-Universität zu Berlin, Berlin
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Pawel Romanczuk
Jens Krause
3Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin
5Excellence Cluster ‘Science of Intelligence’, Technische Universität Berlin, Berlin
6Faculty of Life Sciences, Thaer-Institute, Humboldt-Universität zu Berlin, Berlin
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David Bierbach
3Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin
5Excellence Cluster ‘Science of Intelligence’, Technische Universität Berlin, Berlin
6Faculty of Life Sciences, Thaer-Institute, Humboldt-Universität zu Berlin, Berlin
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for David Bierbach
  • For correspondence: j.w.jolles@gmail.com david.bierbach@gmx.de
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Understanding the emergence of collective behaviour has long been a key research focus in the natural sciences. Besides the fundamental role of social interaction rules, a combination of theoretical and empirical work indicates individual speed may be a key process that drives the collective behaviour of animal groups. Socially-induced changes in speed by interacting animals make it difficult to isolate the effects of individual speed on group-level behaviours. Here we tackled this issue by pairing guppies with a biomimetic robot. We used a closed-loop tracking and feedback system to let a robotic fish naturally interact with a live partner in real time, and programmed it to strongly copy and follow its partner’s movements while lacking any preferred movement speed or directionality of its own. We show that individual differences in guppies’ movement speed were highly repeatable and shaped key collective patterns: higher individual speeds resulted in stronger leadership, lower cohesion, higher alignment, and better temporal coordination in the pairs. By combining the strengths of individual-based models and observational work with state-of-the-art robotics, we provide novel evidence that individual speed is a key, fundamental process in the emergence of collective behaviour.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted June 12, 2020.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Group-level patterns emerge from individual speed as revealed by an extremely social robotic fish
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Group-level patterns emerge from individual speed as revealed by an extremely social robotic fish
Jolle W. Jolles, Nils Weimar, Tim Landgraf, Pawel Romanczuk, Jens Krause, David Bierbach
bioRxiv 2020.06.10.143883; doi: https://doi.org/10.1101/2020.06.10.143883
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Group-level patterns emerge from individual speed as revealed by an extremely social robotic fish
Jolle W. Jolles, Nils Weimar, Tim Landgraf, Pawel Romanczuk, Jens Krause, David Bierbach
bioRxiv 2020.06.10.143883; doi: https://doi.org/10.1101/2020.06.10.143883

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Animal Behavior and Cognition
Subject Areas
All Articles
  • Animal Behavior and Cognition (4838)
  • Biochemistry (10734)
  • Bioengineering (8013)
  • Bioinformatics (27174)
  • Biophysics (13935)
  • Cancer Biology (11080)
  • Cell Biology (15984)
  • Clinical Trials (138)
  • Developmental Biology (8757)
  • Ecology (13232)
  • Epidemiology (2067)
  • Evolutionary Biology (17309)
  • Genetics (11665)
  • Genomics (15882)
  • Immunology (10989)
  • Microbiology (25989)
  • Molecular Biology (10608)
  • Neuroscience (56326)
  • Paleontology (417)
  • Pathology (1727)
  • Pharmacology and Toxicology (2998)
  • Physiology (4529)
  • Plant Biology (9588)
  • Scientific Communication and Education (1610)
  • Synthetic Biology (2671)
  • Systems Biology (6959)
  • Zoology (1507)