## Robot self-assembly as adaptive growth process : Collective selection of seed position and self-organizing tree-structures

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2016
##### Publication type
Contribution to a conference collection
Published
##### Published in
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - Piscataway, NJ : IEEE, 2016. - pp. 5745-5750. - eISSN 2153-0866. - ISBN 978-1-5090-3762-9
##### Abstract
Autonomous self-assembly allows to create structures and scaffolds on demand and automatically. The desired structure may be predetermined or alternatively it is the result of an artificial growth process that adapts to environmental features and to the intermediate structure itself. In a self-organizing and decentralized control approach the robots interact only locally and form the structure collectively. Designing a complete approach that allows the robot group to collectively decide on where to start the self-assembly, that adapts at runtime to environmental conditions, and that guarantees the structural stability, is challenging and does not yet exist. We present an approach to self-assembly inspired by diffusion-limited aggregation that generates an adaptive structure reacting to environmental conditions in an artificial growth process. During a preparatory stage the robots collectively decide where to start the self-assembly also depending on environmental conditions. In the actual self-assembly stage, the robots create tree-like structures that grow towards light. We report the results of robot self-assembly experiments with 50 Kilobots. Our results demonstrate how an adaptive growth process can be implemented in robots. We briefly describe our future work of how to extend the approach to a 3-d growth process and how robot self-assembly as an open-ended adaptive growth process opens up a multiplicity of future opportunities.
##### Subject (DDC)
004 Computer Science
##### Conference
IROS 2016 : IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 9, 2016 - Oct 14, 2016, Daejeon, South Korea
##### Cite This
ISO 690SOORATI, Mohammad Divband, Heiko HAMANN, 2016. Robot self-assembly as adaptive growth process : Collective selection of seed position and self-organizing tree-structures. IROS 2016 : IEEE/RSJ International Conference on Intelligent Robots and Systems. Daejeon, South Korea, Oct 9, 2016 - Oct 14, 2016. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway, NJ:IEEE, pp. 5745-5750. eISSN 2153-0866. ISBN 978-1-5090-3762-9. Available under: doi: 10.1109/IROS.2016.7759845
BibTex
@inproceedings{Soorati2016Robot-59873,
year={2016},
doi={10.1109/IROS.2016.7759845},
title={Robot self-assembly as adaptive growth process : Collective selection of seed position and self-organizing tree-structures},
isbn={978-1-5090-3762-9},
publisher={IEEE},
booktitle={2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages={5745--5750},
author={Soorati, Mohammad Divband and Hamann, Heiko}
}

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<dcterms:abstract xml:lang="eng">Autonomous self-assembly allows to create structures and scaffolds on demand and automatically. The desired structure may be predetermined or alternatively it is the result of an artificial growth process that adapts to environmental features and to the intermediate structure itself. In a self-organizing and decentralized control approach the robots interact only locally and form the structure collectively. Designing a complete approach that allows the robot group to collectively decide on where to start the self-assembly, that adapts at runtime to environmental conditions, and that guarantees the structural stability, is challenging and does not yet exist. We present an approach to self-assembly inspired by diffusion-limited aggregation that generates an adaptive structure reacting to environmental conditions in an artificial growth process. During a preparatory stage the robots collectively decide where to start the self-assembly also depending on environmental conditions. In the actual self-assembly stage, the robots create tree-like structures that grow towards light. We report the results of robot self-assembly experiments with 50 Kilobots. Our results demonstrate how an adaptive growth process can be implemented in robots. We briefly describe our future work of how to extend the approach to a 3-d growth process and how robot self-assembly as an open-ended adaptive growth process opens up a multiplicity of future opportunities.</dcterms:abstract>
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