Coalition coordination for tightly coupled multirobot tasks with sensor constraints

Yu Zhang, Lynne E. Parker, Subbarao Kambhampati

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

5 Scopus citations

Abstract

Although many approaches have been developed to form robot coalitions that can achieve a multirobot task, no general methods exist to execute these coalitions, especially when the coordination among the robots is tightly coupled. In this paper, we propose a coordination mechanism as the first step to address coalition execution; it provides a flexible method to reason about synergies with overlapping coalitions (thus enabling multi-tasking robots in multi-robot tasks), which not only improves efficiency, but also reduces resource requirements in task execution. This means that our approach enables tasks that cannot be easily handled before, especially when critical resources are rare but commonly required. Our approach is based on the concept of sensor constraint, which is introduced by the tight coupling (e.g., information sharing) between the robots. We show that our algorithm is sound and complete in finding a coordination solution given a few assumptions, and discuss a distributed implementation. Simulation results are provided to demonstrate the capabilities of this new approach.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1090-1097
Number of pages8
ISBN (Electronic)9781479936854, 9781479936854
DOIs
StatePublished - Sep 22 2014
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: May 31 2014Jun 7 2014

Publication series

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

Other

Other2014 IEEE International Conference on Robotics and Automation, ICRA 2014
Country/TerritoryChina
CityHong Kong
Period5/31/146/7/14

ASJC Scopus subject areas

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

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