ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems
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- 作者：Carlo Pinciroli (1)
Vito Trianni (2)
Rehan O鈥橤rady (1)
Giovanni Pini (1)
Arne Brutschy (1)
Manuele Brambilla (1)
Nithin Mathews (1)
Eliseo Ferrante (1)
Gianni Di Caro (3)
Frederick Ducatelle (3)
Mauro Birattari (1)
Luca Maria Gambardella (3)
Marco Dorigo (1) - 关键词：Simulation ; Swarm robotics ; Multi ; robot systems ; High ; performance ; ARGoS
- 刊名：Swarm Intelligence
- 出版年：2012
- 出版时间：December 2012
- 年：2012
- 卷：6
- 期：4
- 页码：271-295
- 全文大小：1135KB
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Vito Trianni (2)
Rehan O鈥橤rady (1)
Giovanni Pini (1)
Arne Brutschy (1)
Manuele Brambilla (1)
Nithin Mathews (1)
Eliseo Ferrante (1)
Gianni Di Caro (3)
Frederick Ducatelle (3)
Mauro Birattari (1)
Luca Maria Gambardella (3)
Marco Dorigo (1)
1. IRIDIA, CoDE, Universit茅 Libre de Bruxelles, 50 Avenue F. Roosevelt, CP 194/6, 1050, Bruxelles, Belgium
2. ISTC, Consiglio Nazionale delle Ricerche, via San Martino della Battaglia 44, 00185, Roma, Italy
3. IDSIA, USI-SUPSI, Galleria 2, 6928, Manno-Lugano, Switzerland - ISSN：1935-3820
文摘
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鈥?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聽% 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.