Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. An Optimal Planning Framework to Deploy Self-Reconfigurable Modular Robots
 
research article

An Optimal Planning Framework to Deploy Self-Reconfigurable Modular Robots

Khodr, Hala  
•
Mutlu, Mehmet  
•
Hauser, Simon  
Show more
July 25, 2019
IEEE Robotics and Automation Letters

Self-reconfiguration is a hard problem due to the high dimensionality of self-reconfigurable modular systems. Searchbased approaches offer complete and optimal solutions. However, naive search algorithms cannot directly solve self-reconfiguration tasks in reasonable time. In this letter, a transition model, a search heuristic, pruning strategies, and offline computations are proposed to advance performance of search-based self-reconfiguration methods. The targeted reconfiguration tasks include the reconfiguration of any distribution of modules, whether it is a complex structures or disconnected modules distributed in space. Hypothesized strategies are tested with conventional search methods to understand their contributions on complexity, optimality (minimum number of steps), completeness, and time efficiency. The whole framework is designed keeping hardware restrictions in mind and deployed on real Roombots hardware.

  • Details
  • Metrics
Type
research article
DOI
10.1109/LRA.2019.2931216
Author(s)
Khodr, Hala  
Mutlu, Mehmet  
Hauser, Simon  
Bernardino, Alexandre
Ijspeert, Auke  
Date Issued

2019-07-25

Published in
IEEE Robotics and Automation Letters
Volume

4

Issue

4

Start page

4278

End page

4285

Subjects

roombots

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
BIOROB  
Available on Infoscience
April 21, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/168287
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés