Techniques for Controlling Swarms of Robots

Detalhes bibliográficos
Ano de defesa: 2009
Autor(a) principal: Luciano Cunha de Araujo Pimenta
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/GASP-7Y5F4W
Resumo: This thesis addresses the problem of controlling very large groups of robots, refereed as swarms. Scalable solutions in which there is no need for labelling the robots are proposed. All the robots run the same software and the success of the task execution does not depend on specific members of the group. Robustness to dynamic addition and deletion of agents is also an advantage of our approaches. In the first methodology, we model the swarm as a fluid immersed in a region where a field of external forces, which is free of local minima, is defined. In this case, the Smoothed Particle Hydrodynamics (SPH) method is applied to model the robotic fluid', more specifically, to model the interactions among the robots of the group. The Finite Element Method (FEM) is also used in this work to compute the fields that determine external forces. This approach is instantiated in a pattern generation task and also in a coverage task. In the second methodology, a problem of optimal environment coverage using robots equipped with sensors is addressed by means of tools from the Locational Optimization theory. Three important extensions of well-known results in the literature are presented: (i) sensors with different footprints, (ii) disk-shaped robots, and (iii) nonconvex polygonal environments. Both approaches are verified in simulations. The first technique is also implemented and tested in actual robots.