@phdthesis{Gross2020,
  type      = {Master Thesis},
  author    = {Daniel Thomas Gro{\"s}},
  title     = {An implementation approach of the gap navigation tree using the TurtleBot 3 Burger and ROS Kinetic},
  journal    = {Ein Implementierungsansatz des Differenz Navigation Baum mit dem TurtleBot 3 Burger und ROS Kinetic},
  doi       = {10.25924/opus-3888},
  pages     = {IX, 73},
  year      = {2020},
  abstract  = {The creation of a spatial model of the environment is an important task to allow the planning of routes through the environment. Depending on the number of sensor inputs different ways of creating a spatial environment model are possible. This thesis introduces an implementation approach of the Gap Navigation Tree which is aimed for usage with robots that have a limited amount of sensors. The Gap Navigation Tree is a tree structure based on depth discontinuities constructed from the data of a laser scanner. Using the simulated TurtleBot 3 Burger and ROS kinetic a framework is created that implements the theory of the Gap Navigation Tree. The framework is structured in a way that allows using different robots with different sensor types by separating the detection of depth discontinuities from the building and updating of the Gap Navigation Tree.},
  language  = {en}
}