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  1. Swarm Intelligence
  2. Swarm Intelligence : Volume 6
  3. Swarm Intelligence : Volume 6, Issue 4, December 2012
  4. ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems
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Swarm Intelligence : Volume 11
Swarm Intelligence : Volume 10
Swarm Intelligence : Volume 9
Swarm Intelligence : Volume 8
Swarm Intelligence : Volume 7
Swarm Intelligence : Volume 6
Swarm Intelligence : Volume 6, Issue 4, December 2012
ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems
Set-based particle swarm optimization applied to the multidimensional knapsack problem
The dynamics of ant colony optimization algorithms applied to binary chains
Swarm Intelligence : Volume 6, Issue 3, September 2012
Swarm Intelligence : Volume 6, Issue 2, June 2012
Swarm Intelligence : Volume 6, Issue 1, March 2012
Swarm Intelligence : Volume 5
Swarm Intelligence : Volume 4
Swarm Intelligence : Volume 3
Swarm Intelligence : Volume 2
Swarm Intelligence : Volume 1

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ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems

Content Provider SpringerLink
Author Pinciroli, Carlo Trianni, Vito O’Grady, Rehan Pini, Giovanni Brutschy, Arne Brambilla, Manuele Mathews, Nithin Ferrante, Eliseo Caro, Gianni Ducatelle, Frederick Birattari, Mauro Gambardella, Luca Maria Dorigo, Marco
Copyright Year 2012
Abstract We present a novel multi-robot simulator named ARGoS. ARGoS is designed to simulate complex experiments involving large swarms of robots of different types. ARGoS is the first multi-robot simulator that is at the same time both efficient (fast performance with many robots) and flexible (highly customizable for specific experiments). Novel design choices in ARGoS have enabled this breakthrough. First, in ARGoS, it is possible to partition the simulated space into multiple sub-spaces, managed by different physics engines running in parallel. Second, ARGoS’ architecture is multi-threaded, thus designed to optimize the usage of modern multi-core CPUs. Finally, the architecture of ARGoS is highly modular, enabling easy addition of custom features and appropriate allocation of computational resources. We assess the efficiency of ARGoS and showcase its flexibility with targeted experiments. Experimental results demonstrate that simulation run-time increases linearly with the number of robots. A 2D-dynamics simulation of 10,000 e-puck robots can be performed in 60 % of the time taken by the corresponding real-world experiment. We show how ARGoS can be extended to suit the needs of an experiment in which custom functionality is necessary to achieve sufficient simulation accuracy. ARGoS is open source software licensed under GPL3 and is downloadable free of charge.
Starting Page 271
Ending Page 295
Page Count 25
File Format PDF
ISSN 19353812
Journal Swarm Intelligence
Volume Number 6
Issue Number 4
e-ISSN 19353820
Language English
Publisher Springer US
Publisher Date 2012-11-16
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Simulation Swarm robotics Multi-robot systems High-performance ARGoS Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks ApplicationMathematics/Computational Methods of Engineering Communications Engineering, Networks Computer Communication Networks
Content Type Text
Resource Type Article
Subject Artificial Intelligence
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