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Vectorized Point Clouds for Mobile Robotics
Jelínek, Aleš ; Mazal, Jan (oponent) ; Duchoň,, František (oponent) ; Žalud, Luděk (vedoucí práce)
This doctoral thesis deals with processing of point clouds produced by laser scanners and subsequent searching for correspondences between the approximations obtained in this way for the purpose of simultaneous localization and mapping in mobile robotics. The first method performs filtration and segmentation of the data and is able to do both operations at the same time in one algorithm. For vectorization, an optimized total least squares algorithm is introduced. It is probably the fastest algorithm in its category, comparable even to the eliminating methods, which, however, provide significantly worse approximations. For similarity evaluation, optimal registration and correspondence search between two sets of vectorized scans, new analytical methods are presented as well. All of the algorithms introduced were thoroughly tested and their features investigated in many experiments.
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Vectorized Point Clouds for Mobile Robotics
Jelínek, Aleš ; Mazal, Jan (oponent) ; Duchoň,, František (oponent) ; Žalud, Luděk (vedoucí práce)
This doctoral thesis deals with processing of point clouds produced by laser scanners and subsequent searching for correspondences between the approximations obtained in this way for the purpose of simultaneous localization and mapping in mobile robotics. The first method performs filtration and segmentation of the data and is able to do both operations at the same time in one algorithm. For vectorization, an optimized total least squares algorithm is introduced. It is probably the fastest algorithm in its category, comparable even to the eliminating methods, which, however, provide significantly worse approximations. For similarity evaluation, optimal registration and correspondence search between two sets of vectorized scans, new analytical methods are presented as well. All of the algorithms introduced were thoroughly tested and their features investigated in many experiments.
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