Opportunistic Optimization for Market-Based Multirobot Control - Robotics Institute Carnegie Mellon University

Opportunistic Optimization for Market-Based Multirobot Control

Conference Paper, Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 3, pp. 2714 - 2720, September, 2002

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.

BibTeX

@conference{Dias-2002-8533,
author = {M. Bernardine Dias and Anthony (Tony) Stentz},
title = {Opportunistic Optimization for Market-Based Multirobot Control},
booktitle = {Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2002},
month = {September},
volume = {3},
pages = {2714 - 2720},
keywords = {Market Based, mult-agent, multirobot, optimization},
}