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Collective decision-making based on social odometry

  • Swarm Robotics
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Abstract

In this paper, we propose a swarm intelligence localization strategy in which robots have to locate different resource areas in a bounded arena and forage between them. The robots have no knowledge of the arena dimensions and of the number of resource areas. The strategy is based on peer-to-peer local communication without the need for any central unit. Social Odometry leads to a self-organized path selection. We show how collective decisions lead the robots to choose the closest resource site from a central place. Results are presented with simulated and real robots.

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Notes

  1. This time initialization is used only for evaluation purposes.

  2. Further details on the robot platform can be found at http://www.e-puck.org.

  3. For an exhaustive description of the board see http://www.rbz.es/randb/.

  4. Note that when a robot spins in place we consider the distance traveled as the arc made by one of the wheels. Therefore, \(\Delta{d^{i}_{k+1}}=\xi^{i}_{k+1}\cdot\rho/2\), where ρ is the distance between the wheels (53 mm for the e-puck) and \(\xi^{i}_{k+1}\) is the angular displacement made in the time step duration.

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Acknowledgments

A. Campo and M. Dorigo acknowledge support from the Belgian F.R.S.-FNRS, of which they are a Research Fellow and a Research Director, respectively. This work was partially supported by the Gestión de la Demanda Eléctrica Doméstica con Energía Solar Fotovoltaica project, funded by the Plan Nacional de I+D+i 2007-2010 (ENE2007-66135) of the Spanish Ministerio de Educación y Ciencia and the N4C—Networking for Challenged Communications Citizens: Innovative Alliances and Test beds project, funded by the Seventh Framework Program (FP7-ICT-223994-N4C) of the European Commission. The information provided is the sole responsibility of the authors and does not reflect the European Commission’s opinion. The Spanish Ministry and the European Commission are not responsible for any use that might be made of data appearing in this publication.

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Authors and Affiliations

  1. ETSIT, Universidad Politécnica de Madrid, Avd. Complutense 30, 28040, Madrid, Spain

    Álvaro Gutiérrez & Félix Monasterio-Huelin

  2. IRIDIA, CoDE, Université Libre de Bruxelles, 50 Av. Franklin Roosevelt, CP 194/6, 1050, Brussels, Belgium

    Alexandre Campo & Marco Dorigo

  3. European Centre for Soft Computing, C. Gonzalo Gutiérrez Quirós S/N, 33600, Asturias, Spain

    Luis Magdalena

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  1. Álvaro Gutiérrez
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  2. Alexandre Campo
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Correspondence to Álvaro Gutiérrez.

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Gutiérrez, Á., Campo, A., Monasterio-Huelin, F. et al. Collective decision-making based on social odometry. Neural Comput & Applic 19, 807–823 (2010). https://doi.org/10.1007/s00521-010-0380-x

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