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A Rule Synthesis Algorithm for Programmable Stochastic Self-assembly of Robotic Modules

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Distributed Autonomous Robotic Systems

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

Abstract

Programmable self-assembly of modular robots offers promising means for structure formation at different scales. Rule-based approaches have been previously employed for distributed control of stochastic self-assembly processes. The assembly rate in the process directly depends on the concurrency level induced by the employed ruleset, i.e. the number of concurrent steps necessary to build one instance of the target structure. Our aim here is to design a formal synthesis algorithm to automatically derive rulesets of high concurrency for a given target structure composed of robotic modules. In the literature, self-assembly of (simulated or real) robotic modules has been realized through manually designed rulesets or manually adjusted rulesets generated by employing graph-grammar formalisms or metaheuristic methods. In this work, we employ an extended graph-grammar formalism, adapted for self-assembly of robotic modules, and propose a novel formal synthesis algorithm capable of generating rulesets for robotic modules by natively considering the morphology of their connectors. The synthesized rulesets induce a high level of concurrency in the self-assembly scheme by exploiting controlled information propagation, using solely local communication. Simulation results of microscopic (non-spatial) and submicroscopic (spatial) models of our robotic platform confirm higher performance of rulesets synthesized by our algorithm compared to related work in the literature.

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Acknowledgements

We gratefully acknowledge the contributions of Loic Waegeli and Brice Platerrier to the microscopic simulation framework. This work has been sponsored by the Swiss National Science Foundation under the grant numbers 200021_137838/1 and 200020_157191/1.

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Authors and Affiliations

  1. École Polytechnique Fédérale de Lausanne (EPFL), Distributed Intelligent Systems and Algorithms Laboratory (DISAL), Lausanne, Switzerland

    Bahar Haghighat & Alcherio Martinoli

Authors
  1. Bahar Haghighat
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  2. Alcherio Martinoli
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Corresponding author

Correspondence to Bahar Haghighat .

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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Haghighat, B., Martinoli, A. (2018). A Rule Synthesis Algorithm for Programmable Stochastic Self-assembly of Robotic Modules. 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_23

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  • DOI: https://doi.org/10.1007/978-3-319-73008-0_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73006-6

  • Online ISBN: 978-3-319-73008-0

  • eBook Packages: EngineeringEngineering (R0)

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