2018 International Conference on Control, Artificial Intelligence, Robotics &Amp; Optimization (ICCAIRO) 2018
DOI: 10.1109/iccairo.2018.00038
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Qualitative Geometrical Uncertainty in a Topological Robot Localization System

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Cited by 5 publications
(3 citation statements)
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“…Small penalization was applied if expected and real orientations belong to adjacent quadrants, large penalization was applied for opposite quadrants and none for same quadrants. Further details of this variation can be found in [69]. This heading penalization, w h , was then included in the state transition probability:…”
Section: Localization In the Object-based Pose Graphmentioning
confidence: 99%
“…Small penalization was applied if expected and real orientations belong to adjacent quadrants, large penalization was applied for opposite quadrants and none for same quadrants. Further details of this variation can be found in [69]. This heading penalization, w h , was then included in the state transition probability:…”
Section: Localization In the Object-based Pose Graphmentioning
confidence: 99%
“…Early work in robot localization was done in a topological map [1], as was early work on localization in a pipe network [2]. Recent work on topological localization incorporates some geometric information [3], and recent work on localization in pipes also uses both metric and topological information [4].…”
Section: Introductionmentioning
confidence: 99%
“…Recent work on topological localization adds the challenges of erroneous repeated observations of the environment at a topological map node, inclusion of information assigned to nearby nodes, and failing to make an observation at a node [11], the last of which is especially applicable where a robot has limited sensing ability as is the case in a pipe environment. Use of geometric information on the robot's orientation has been applied using prior knowledge of the orientation between two topological map nodes [12]. Recent work on localization in pipe networks also incorporates both metric and topological information [13], and similar methods have been applied to autonomous road vehicles [14] [15] [16] [17].…”
Section: Introductionmentioning
confidence: 99%