Automatic scalable size selection for the shape of a distributed robotic collective

Michael Rubenstein*, Wei Min Shen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Scopus citations

Abstract

A collective of robots can together complete a task that is beyond the capabilities of any of its individual robots. One property of a robotic collective that allows it to complete such a task is the shape of the collective. One method to form that shape is to form it at a size proportional to the number of robots in that collective, i.e. scalably. In our previous work, scalably forming the shape of the collective required that each robot know the total number of robots in the collective. In this work we present a method called S-DASH, which now allows a collective to scalably form a shape without knowing how many robots are in the collective. Furthermore, S-DASH will change the size of the shape to reflect the addition or removal of robots from the collective. This paper also provides demonstrations of SDASH running on a simulated collective of robots.

Original languageEnglish (US)
Title of host publicationIEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings
Pages508-513
Number of pages6
DOIs
StatePublished - 2010
Event23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Taipei, Taiwan, Province of China
Duration: Oct 18 2010Oct 22 2010

Publication series

NameIEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings

Other

Other23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010
Country/TerritoryTaiwan, Province of China
CityTaipei
Period10/18/1010/22/10

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Automatic scalable size selection for the shape of a distributed robotic collective'. Together they form a unique fingerprint.

Cite this