Controlling a formation of unmanned autonomous vehicles is a daunting prospect even when the formation operates under ideal conditions. When communication between vehicles is limited, maintaining a formation becomes difficult. In some cases the formation may become unstable. While a control law may stabilize a formation of vehicles with good communication, it may not be able to do so with poor communication. The resulting lack of formation stability affects the level of ï¬ delity the formation has to the original control law. Formation ï¬ delity is the degree to which the vehicles in a formation follow the trajectories prescribed by a control law. Many formation control laws assume certain conditions. Perfect formation ï¬ delity is not guaranteed when the vehicles in a formation are no longer operated under those conditions. We seek to mitigate the detrimental effects of poor communication and other real-world phenomena on formation ï¬ delity. Through simulation we test the effectiveness of a new way to implement an existing formation control law. Real-world conditions such as rigid-body motion, swarm dynamics, poor communication, and other phenomena are assessed and discussed. It is concluded through testing in simulation that it is possible to control a formation of boats by directing each boat with a unique set of waypoints in simulation. While these waypoints do not lead to perfect formation behavior, testing shows that implementing this control law using these waypoints allows the formation to be more robust to reduced communication. / Master of Science

I present a system for robust leaderless organization of an amorphous network into hierarchical clusters. This system, which assumes that nodes are spatially embedded and can only talk to neighbors within a given radius, scales to networks of arbitrary size and converges rapidly. The amount of data stored at each node is logarithmic in the diameter of the network, and the hierarchical structure produces an addressing scheme such that there is an invertible relation between distance and address for any pair of nodes. The system adapts automatically to stopping failures, network partition, and reorganization.

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Thesis (Ph. D.)--Miami University, Dept. of Microbiology, 2006. / Title from second page of PDF document. Includes bibliographical references (p. 160-176).

Thesis (Ph. D.)--Miami University, Dept. of Microbiology, 2004. / Title from second page of PDF document. Includes bibliographical references (p. 139-145).

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