Thesis (M. Sc.)Computer Science)--University of Pretoria, 2005. / Includes summary. Includes bibliographical references. Available on the Internet via the World Wide Web.

No description available.

In this thesis, we investigate the problem of path formation and prey retrieval in a swarm of robots. We present two swarm intelligence control mechanisms used for distributed robot path formation. In the first, the robots form linear chains. We study three variants of robot chains, which vary in the degree of motion allowed to the chain structure. The second mechanism is called vectorfield. In this case, the robots form a pattern that globally indicates the direction towards a goal or home location. Both algorithms were designed following the swarm robotics control principles: simplicity of control, locality of sensing and communication, homogeneity and distributedness. We test each controller on a task that consists in forming a path between two objects—the prey and the nest—and to retrieve the prey to the nest. The difficulty of the task is given by four constraints. First, the prey requires concurrent, physical handling by multiple robots to be moved. Second, each robot’s perceptual range is small when compared to the distance between the nest and the prey; moreover, perception is unreliable. Third, no robot has any explicit knowledge about the environment beyond its perceptual range. Fourth, communication among robots is unreliable and limited to a small set of simple signals that are locally broadcast. In simulation experiments we test our controllers under a wide range of conditions, changing the distance between nest and prey, varying the number of robots used, and introducing different obstacle configurations in the environment. Furthermore, we tested the controllers for robustness by adding noise to the different sensors, and for fault tolerance by completely removing a sensor or actuator. We validate the chain controller in experiments with up to twelve physical robots. We believe that these experiments are among the most sophisticated examples of self-organisation in robotics to date.

Thesis (Ph.D.)--University of Wyoming, 2008. / Title from PDF title page (viewed on August 5, 2009). Includes bibliographical references (p. 261-271).

Thesis (Ph.D.)--University of Louisville, 2007. / Adviser: Adel S. Elmaghraby. Includes bibliographical references.

Thesis (Ph.D.)--University of Wyoming, 2007. / Title from PDF title page (viewed on June 22, 2009). Includes bibliographical references (p. 179-183).

Thesis (Ph.D.)--Drexel University, 2010. / Includes abstract and vita. Includes bibliographical references (leaves XXX-XXX).

Thesis (M.S.)--Boise State University, 2009. / Includes abstract. Includes bibliographical references (leaves 58-60).

Thesis (M.S.)--Boise State University, 2009. / Title from t.p. of PDF file (viewed May 6, 2010). Includes abstract. Includes bibliographical references (leaves 58-60).

No description available.