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Publication Details

Task Inference and Distributed Task Management in the Centibots Robotic System

by Ortiz, C. and Vincent, R. and Morisset, B.

in The Fourth International Joint Conference on Autonomous Agents and Multi Agent Systems

Published by ACM
Jul 2005.

Abstract

We describe the Centibots system, a very large scale distributed robotic system, consisting of more than 100 robots, that has been successfully deployed in large, unknown indoor environments, over extended periods of time (i.e., durations corresponding to several power cycles). Unlike most multiagent systems, the set of tasks about which teams must collaborate is not given {\it a priori}. We first describe a task inference algorithm that identifies potential team commitments that collectively balance constraints such as reachability, sensor coverage, and communication access. We then describe a dispatch algorithm for task distribution and management that assigns resources depending on either task density or replacement requirements stemming from failures or power shortages. The targeted deployment environments are expected to lack a supporting communication infrastructure; robots manage their own network and reason about the concomitant localization constraints necessary to maintain team communication. Finally, we present quantitative results in terms of a ``search and rescue problemÂ’Â’ and discuss the team-oriented aspects of the system in the context of prevailing theories of multiagent collaboration.

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Associated Projects

Centibots

Centibots very large-scale robot teams

This is a joint project with Stanford, University of Washington, and ActiveMedia Robotics, to design, implement and demonstrate a computational framework for the coordination of very large robot teams, consisting of at least 100 small, resource limited robots, on an indoor reconnaissance task.

AIC Personnel

Name Title E-mail
Morisset, Benoit Alumnus
Ortiz, Charles L Program Director
Vincent, Regis Program Manager

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