Fault Detection in Robotic Swarm, M.Sc. Thesis Sharif University of Technology ; Alasti, Aria (Supervisor) ; Salarieh, Hassan (Co-Supervisor)
Abstract
Fault detection in swarm robots is one of the most important issues that has drawn a lot of scientists’ attention. Previous studies have shown a lot of problems regarding this issue, such as dependency of data-based methods to mission and high complexity of model-based methods on the condition that nonlinear models are used. Extended information filter is an applicable method for fault detection because it could turn the inverse of a big matrix to a simple summation of information that is so desired in terms of calculations. The goal of this study is to identify the agents with fault in swarm robots online by modifying the extended information filter. In this study, it has been attempted to...
Cataloging briefFault Detection in Robotic Swarm, M.Sc. Thesis Sharif University of Technology ; Alasti, Aria (Supervisor) ; Salarieh, Hassan (Co-Supervisor)
Abstract
Fault detection in swarm robots is one of the most important issues that has drawn a lot of scientists’ attention. Previous studies have shown a lot of problems regarding this issue, such as dependency of data-based methods to mission and high complexity of model-based methods on the condition that nonlinear models are used. Extended information filter is an applicable method for fault detection because it could turn the inverse of a big matrix to a simple summation of information that is so desired in terms of calculations. The goal of this study is to identify the agents with fault in swarm robots online by modifying the extended information filter. In this study, it has been attempted to...
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