Synthesizing rulesets for programmable robotic self-assembly: A case study using floating miniaturized robots

Bahar Haghighat*, Brice Platerrier, Loic Waegeli, Alcherio Martinoli

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

9 Citations (Scopus)

Abstract

Programmable stochastic self-assembly of modular robots provides promising means to formation of structures at different scales. Formalisms based on graph grammars and rule-based approaches have been previously published for controlling the self-assembly process. While several rule-synthesis algorithms have been proposed, formal synthesis of rulesets has only been shown for self-assembly of abstract graphs. Rules deployed on robotic modules are typically tuned starting from their abstract graph counterparts or designed manually. In this work, we extend the graph grammar formalism and propose a new encoding of the internal states of the robots. This allows formulating formal methods capable of automatically deriving the rules based on the morphology of the robots, in particular the number of connectors. The derived rules are directly applicable to robotic modules with no further tuning. In addition, our method allows for a reduced complexity in the rulesets. In order to illustrate the application of our method, we extend two synthesis algorithms from the literature, namely Singleton and Linchpin, to synthesize rules applicable to our floating robots. A microscopic simulation framework is developed to study the performance and transient behavior of the two algorithms. Finally, employing the generated rulesets, we conduct experiments with our robotic platform to demonstrate several assemblies.

Original languageEnglish
Title of host publicationSwarm Intelligence - 10th International Conference, ANTS 2016, Proceedings
EditorsXiaodong Li, Manuel López-Ibáñez, Carlo Pinciroli, Marco Dorigo, Mauro Birattari, Thomas Stützle, Kazuhiro Ohkura
PublisherSpringer Verlag
Pages197-209
Number of pages13
ISBN (Electronic)978-3-319-44427-7
ISBN (Print)9783319444260
DOIs
Publication statusPublished - 28-Aug-2016
Externally publishedYes
Event10th International Conference on Swarm Intelligence, ANTS 2016 - Brussels, Belgium
Duration: 7-Sep-20169-Sep-2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9882 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Swarm Intelligence, ANTS 2016
Country/TerritoryBelgium
CityBrussels
Period07/09/201609/09/2016

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