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  4. Evo-Bots: A Simple, Stochastic Approach to Self-assembling Artificial Organisms
 
conference paper

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

Escalera, Juan A.
•
Doyle, Matthew J.
•
Mondada, Francesco  
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January 1, 2019
Distributed Autonomous Robotic Systems
13th International Symposium on Distributed Autonomous Robotic Systems (DARS)

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 ormove. 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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Type
conference paper
DOI
10.1007/978-3-319-73008-0_26
Web of Science ID

WOS:000552327000026

Author(s)
Escalera, Juan A.
Doyle, Matthew J.
Mondada, Francesco  
Gross, Roderich
Date Issued

2019-01-01

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG

Publisher place

Cham

Published in
Distributed Autonomous Robotic Systems
ISBN of the book

978-3-319-73008-0

978-3-319-73006-6

Series title/Series vol.

Springer Proceedings in Advanced Robotics

Volume

6

Start page

373

End page

385

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
SCI-STI-FMO1  
Event nameEvent placeEvent date
13th International Symposium on Distributed Autonomous Robotic Systems (DARS)

London, ENGLAND

Nov 07-09, 2016

Available on Infoscience
August 8, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/170682
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