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Distributed Autonomous Robotic Systems pp 373–385Cite as

Evo-Bots: A Simple, Stochastic Approach to Self-assembling Artificial Organisms

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Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 6))

Abstract

This paper describes an alternative path towards artificial life—one by which simple modular robots with novel hybrid motion control are used to represent artificial organisms. We outline conceptually how such a system would work, and present a partial hardware implementation. The hardware, a set of self-reconfigurable modules called the evo-bots, operates on an air table. The modules use a stop-start anchor mechanism to either rest or move. In the latter case, they undergo semi-random motion. The modules can search for, harvest and exchange energy. In addition, they can self-assemble, and thereby form compound structures. Six prototypes of the evo-bot modules were built. We experimentally demonstrate their key functions, namely hybrid motion control, energy harvesting and sharing, and simple structure formation.

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Notes

  1. 1.

    The conceptual foundation is based on preliminary work presented in [13]. This work also presents simulation results and a preliminary module implementation (described further in [7]).

  2. 2.

    In [11] the authors presented preliminary work about the energy management system.

  3. 3.

    Maximum Power Point Tracking. Weak sources may collapse if they have to supply power that exceeds their limit. MPPT algorithms reach the maximum power point of a source and stay at this level. Therefore, the source supplies its maximum power in a safe way.

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Acknowledgements

This research was supported by a Marie Curie European Reintegration Grant within the 7th European Community Framework Programme (grant no. PERG07-GA-2010-268354). It was also funded by the Engineering and Physical Sciences Research Council (EPSRC) through scholarship support (M. Doyle) and grant no. EP/K033948/1. In addition the authors would like to thank Paul Eastwood and Michael Port for their invaluable assistance in preparing the experimental environment.

Author information

Authors and Affiliations

  1. Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK

    Juan A. Escalera, Matthew J. Doyle & Roderich Groß

  2. Department of Automatics and Systems Engineering, University Carlos III of Madrid, Leganés, Spain

    Juan A. Escalera

  3. Laboratoire de Systèmes Robotiques, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Francesco Mondada

Authors
  1. Juan A. Escalera
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  2. Matthew J. Doyle
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  3. Francesco Mondada
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  4. Roderich Groß
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Corresponding author

Correspondence to Juan A. Escalera .

Editor information

Editors and Affiliations

  1. Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK

    Roderich Groß

  2. Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK

    Andreas Kolling

  3. School for Engineering of Matter, Transport and Energy (SEMTE), Arizona State University, Tempe, AZ, USA

    Spring Berman

  4. Massachusetts Institute of Technology, Cambridge, MA, USA

    Emilio Frazzoli

  5. ENAC, IIE, DIAL, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

    Alcherio Martinoli

  6. Department of Mechanical Engineering and Science, Kyoto University, Kyoto, Japan

    Fumitoshi Matsuno

  7. Wyss Institute for Biologically Inspired Engineering, Harvard University Wyss Institute for Biologically Inspired, Cambridge, MA, USA

    Melvin Gauci

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Escalera, J.A., Doyle, M.J., Mondada, F., Groß, R. (2018). Evo-Bots: A Simple, Stochastic Approach to Self-assembling Artificial Organisms. In: Groß, R., et al. Distributed Autonomous Robotic Systems. Springer Proceedings in Advanced Robotics, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-73008-0_26

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  • DOI: https://doi.org/10.1007/978-3-319-73008-0_26

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  • Print ISBN: 978-3-319-73006-6

  • Online ISBN: 978-3-319-73008-0

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