In many robotics tasks, it is advantageous for robots to assemble into formations. In
many of these applications, it is useful for the robots to have differing capabilities
(i.e., be heterogeneous). These differences are task specific, but the most obvious
differences lie in sensing and locomotion capabilities. Groups of robots may also have
only imperfect or partially-known information about one another as well. One key
piece of information that robots lack is how many other robots are in the environment.
This thesis describes a method for formation control that allows heterogeneous robots
with limited information to dynamically assemble into formations, merge smaller
formations together, and correct errors that may arise in the formation. The approach
is shown to be scalable and robust against robot failure, and is evaluated in multiple
simulated environments.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:MWU.1993/18331 |
| Date | 03 April 2013 |
| Creators | de Denus, Michael Andrew Rolland |
| Contributors | Anderson, John ( Computer Science ), Scuse, David ( Computer Science ) McNeill, Dean ( Electrical and Computer Engineering ) |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Detected Language | English |
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