Abstract

In this work, teams of small mobile robots are used to test hypotheses about cooperative transport by ants. This study attempts to explain a decrease in steady-state transport speed with increasing team size that was previously observed in the ant Novomessor cockerelli. Two models of one-dimensional collective towing are compared: one in which transporters with different maximum speeds pull the payload with continuous, variable forces and another in which transporters with identical speeds pull with intermittent, unsynchronized forces. A statistical analysis of ant data supports the hypothesis that ants behave according to the first model, in which the steady-state transport speed is the maximum speed of the slowest teammate. By contrast, the ant data are not consistent with the second model, which predicts constant speed regardless of team size. To verify these predictions, the ant behaviours in each model are translated into decentralized controllers and implemented on teams of two to four robots. The controller for the first model incorporates a real-time reinforcement learning algorithm that successfully reproduces the observed relationship between ant team size and transport speed. The controller for the second model yields the predicted invariance of transport speed with team size. These results show the value of robotic swarms for testing mechanistic hypotheses about biological collectives.

Original languageEnglish (US)
Article number180409
JournalRoyal Society Open Science
Volume5
Issue number10
DOIs
StatePublished - Oct 1 2018

Fingerprint

Robots
Controllers
Reinforcement learning
Invariance
Mobile robots
Learning algorithms
Statistical methods
Robotics
Testing

Keywords

  • Ants
  • Decentralized coordination
  • Heterogeneous teams
  • Reinforcement learning
  • Self-organization
  • Swarm robotics

ASJC Scopus subject areas

  • General

Cite this

Multi-robot replication of ant collective towing behaviours. / Wilson, Sean; Buffin, Aurélie; Pratt, Stephen C.; Berman, Spring.

In: Royal Society Open Science, Vol. 5, No. 10, 180409, 01.10.2018.

Research output: Contribution to journalArticle

Wilson, Sean ; Buffin, Aurélie ; Pratt, Stephen C. ; Berman, Spring. / Multi-robot replication of ant collective towing behaviours. In: Royal Society Open Science. 2018 ; Vol. 5, No. 10.
@article{0a9542c8790944cf86781caf053326f9,
title = "Multi-robot replication of ant collective towing behaviours",
abstract = "In this work, teams of small mobile robots are used to test hypotheses about cooperative transport by ants. This study attempts to explain a decrease in steady-state transport speed with increasing team size that was previously observed in the ant Novomessor cockerelli. Two models of one-dimensional collective towing are compared: one in which transporters with different maximum speeds pull the payload with continuous, variable forces and another in which transporters with identical speeds pull with intermittent, unsynchronized forces. A statistical analysis of ant data supports the hypothesis that ants behave according to the first model, in which the steady-state transport speed is the maximum speed of the slowest teammate. By contrast, the ant data are not consistent with the second model, which predicts constant speed regardless of team size. To verify these predictions, the ant behaviours in each model are translated into decentralized controllers and implemented on teams of two to four robots. The controller for the first model incorporates a real-time reinforcement learning algorithm that successfully reproduces the observed relationship between ant team size and transport speed. The controller for the second model yields the predicted invariance of transport speed with team size. These results show the value of robotic swarms for testing mechanistic hypotheses about biological collectives.",
keywords = "Ants, Decentralized coordination, Heterogeneous teams, Reinforcement learning, Self-organization, Swarm robotics",
author = "Sean Wilson and Aur{\'e}lie Buffin and Pratt, {Stephen C.} and Spring Berman",
year = "2018",
month = "10",
day = "1",
doi = "10.1098/rsos.180409",
language = "English (US)",
volume = "5",
journal = "Royal Society Open Science",
issn = "2054-5703",
publisher = "The Royal Society",
number = "10",

}

TY - JOUR

T1 - Multi-robot replication of ant collective towing behaviours

AU - Wilson, Sean

AU - Buffin, Aurélie

AU - Pratt, Stephen C.

AU - Berman, Spring

PY - 2018/10/1

Y1 - 2018/10/1

N2 - In this work, teams of small mobile robots are used to test hypotheses about cooperative transport by ants. This study attempts to explain a decrease in steady-state transport speed with increasing team size that was previously observed in the ant Novomessor cockerelli. Two models of one-dimensional collective towing are compared: one in which transporters with different maximum speeds pull the payload with continuous, variable forces and another in which transporters with identical speeds pull with intermittent, unsynchronized forces. A statistical analysis of ant data supports the hypothesis that ants behave according to the first model, in which the steady-state transport speed is the maximum speed of the slowest teammate. By contrast, the ant data are not consistent with the second model, which predicts constant speed regardless of team size. To verify these predictions, the ant behaviours in each model are translated into decentralized controllers and implemented on teams of two to four robots. The controller for the first model incorporates a real-time reinforcement learning algorithm that successfully reproduces the observed relationship between ant team size and transport speed. The controller for the second model yields the predicted invariance of transport speed with team size. These results show the value of robotic swarms for testing mechanistic hypotheses about biological collectives.

AB - In this work, teams of small mobile robots are used to test hypotheses about cooperative transport by ants. This study attempts to explain a decrease in steady-state transport speed with increasing team size that was previously observed in the ant Novomessor cockerelli. Two models of one-dimensional collective towing are compared: one in which transporters with different maximum speeds pull the payload with continuous, variable forces and another in which transporters with identical speeds pull with intermittent, unsynchronized forces. A statistical analysis of ant data supports the hypothesis that ants behave according to the first model, in which the steady-state transport speed is the maximum speed of the slowest teammate. By contrast, the ant data are not consistent with the second model, which predicts constant speed regardless of team size. To verify these predictions, the ant behaviours in each model are translated into decentralized controllers and implemented on teams of two to four robots. The controller for the first model incorporates a real-time reinforcement learning algorithm that successfully reproduces the observed relationship between ant team size and transport speed. The controller for the second model yields the predicted invariance of transport speed with team size. These results show the value of robotic swarms for testing mechanistic hypotheses about biological collectives.

KW - Ants

KW - Decentralized coordination

KW - Heterogeneous teams

KW - Reinforcement learning

KW - Self-organization

KW - Swarm robotics

UR - http://www.scopus.com/inward/record.url?scp=85056797652&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056797652&partnerID=8YFLogxK

U2 - 10.1098/rsos.180409

DO - 10.1098/rsos.180409

M3 - Article

VL - 5

JO - Royal Society Open Science

JF - Royal Society Open Science

SN - 2054-5703

IS - 10

M1 - 180409

ER -