Applying DCOP-MST to a team of mobile robots with directional sensing abilities

Harel Yedidsion, Roie Zivan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

DCOP-MST is an extension of the DCOP framework for representing and solving dynamic multi-agent applications that include teams of mobile sensing agents. Local search algorithms, enhanced with exploration methods were recently found to produce high quality solutions for DCOP-MST in software simulations. Applying DCOP-MST to robots with directed sensors (e.g., cameras) requires addressing limitations, which were not part of the original design of the DCOP-MST model, e.g., limited angle of the field of vision, collisions between robots etc. In this paper we contribute to the ongoing effort of applying DCOPs to real world applications by addressing the challenges one faces when applying the DCOP-MST model to a team of mobile sensing robots with directed sensors. We integrate the required adjustments into a new model, DCOP-MSTR, which is the modified version of DCOP-MST for such a real world robot application with directed sensors. The proposed revised model was implemented and evaluated both in software simulations and on a team of robots carrying cameras. Our evaluation of existing algorithms revealed the need to combine actions that change the location of a robot with actions that change its sensing direction in order to achieve effective exploration when solving DCOP-MSTR.

Original languageEnglish
Title of host publicationAAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1357-1358
Number of pages2
ISBN (Electronic)9781450342391
StatePublished - 1 Jan 2016
Event15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore
Duration: 9 May 201613 May 2016

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016
Country/TerritorySingapore
CitySingapore
Period9/05/1613/05/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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