Bio-inspired group behaviors for the deployment of a swarm of robots to multiple destinations

Spring Berman, Ádám Halász, Vijay Kumar, Stephen Pratt

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

42 Scopus citations

Abstract

We present a methodology for characterizing and synthesizing swarm behaviors using both a macroscopic model that represents a swarm as a continuum and a microscopic model that represents individual robots. We develop a systematic approach for synthesizing behaviors at the macroscopic level that can be realized on individual robots at the microscopic level. Our methodology is inspired by a dynamical model of ant house hunting [1], a decentralized process in which a colony attempts to emigrate to the best site among several alternatives. The model is hybrid because the colony switches between different sets of behaviors, or modes, during this process. At the macroscopic level, we are able to synthesize controllers that result in the deployment of a robotic swarm in a predefined ratio between distinct sites. We then derive hybrid controllers for individual robots using only local interactions and no communication that respect the specifications of the global continuous behavior. Our simulations demonstrate that our synthesis procedure yields a correct microscopic model from the macroscopic description with guarantees on performance at both levels.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Robotics and Automation, ICRA'07
Pages2318-2323
Number of pages6
DOIs
StatePublished - 2007
Event2007 IEEE International Conference on Robotics and Automation, ICRA'07 - Rome, Italy
Duration: Apr 10 2007Apr 14 2007

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Other

Other2007 IEEE International Conference on Robotics and Automation, ICRA'07
CountryItaly
CityRome
Period4/10/074/14/07

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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