Reconfiguration control in adaptive networks

(cont.) In the second setting, we propose a novel total field collision avoidance algorithm of magnetic nature which permits a set of vehicles to reconfigure successively without knowing each other's positions; strategic sensor positioning makes sure that the vehicles do not sense their own fields. Contributions of our research are a multiagent learning algorithm, a unified game theoretic framework for addressing reconfiguration problems, the identification of reconfiguration control as a problem common to several different fields but previously addressed with field-specific methods, the proposal of a definition of robustness in this context and, for the two trajectory planning settings in which our algorithm was implemented, two algorithms for distributed coordination and collision avoidance, respectively.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2003

Author dc:creator

• Sigurd, Karin.

Advisor dc:contributor.advisor

• Sanjoy K. Mitter and Jonathan P. How.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/16948

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/16948