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Carnegie Mellon Robotics Institute

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Abstract

Multirobot coordination, if made efficient and robust, promises high impact on automation. The challenge is to enable robots to work together in an intelligent manner to execute a global task. The market approach has had considerable success in the multirobot coordination domain. This paper investigates the effects of introducing opportunistic optimization with leaders to enhance market-based multirobot coordination. Leaders are able to optimize within subgroups of robots by collecting information about their tasks and status, and re-allocating the tasks within the subgroup in a more profitable manner. The presented work considers the effects of a leader optimizing a single subgroup, and some effects of multiple leaders optimizing overlapping subgroups. The implementations were tested on a variation of the distributed traveling salesman problem. Presented results show that global costs can be reduced, and hence task allocation can be improved, utilizing leaders.

Keywords

Market Based, mult-agent, multirobot, optimization

Notes

Associated Center(s) / Consortia: Field Robotics Center

Associated Project(s): Cognitive Colonies

Number of pages: 7

Text Reference

M Bernardine Dias and Anthony (Tony) Stentz, "Opportunistic Optimization for Market-Based Multirobot Control," Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '02), September, 2002, pp. 2714 - 2720.

BibTeX Reference

@inproceedings{Dias_2002_4037,
   author = "M Bernardine Dias and Anthony (Tony) Stentz",
   title = "Opportunistic Optimization for Market-Based Multirobot Control",
   booktitle = "Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '02)",
   pages = "2714 - 2720",
   month = "September",
   year = "2002",
   volume = "3",
}

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