Focuses on acquiring spatial models of physical environments through mobile robots. The robotic mapping problem is commonly referred to as SLAM (simultaneous localization and mapping). 3D maps are necessary to avoid collisions with complex obstacles and to self-localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle). New solutions to the 6D SLAM problem for 3D laser scans are proposed and a wide variety of applications are presented. Complete treatment of 3 dimensional robotic mapping Presents the Simultaneous Localization and Mapping Problem with Six Degrees of Freedom Presents the algorithms needed for automatic semantic 3D map building using a 3D laser range finder and the mobile robot Kurt3D
INDICE: Introduction.- Perceiving 3D Range Data.- State of the Art.- 3D Range Image Registration.- Globally Consistent Range Image Registration.- Experiments and Results.- 3D Maps with Semantics.- Conclusions and Outlook.
Automation and Robotics; Control Engineering; Artificial Intelligence (incl. Robotics) Researchers, graduate students, and professionals in robotics, computer vision, and multimedia
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