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3D Robotic Mapping de Andreas Nüchter

3D Robotic Mapping: Springer Tracts in Advanced Robotics, cartea 52

Autor Andreas Nüchter
en Limba Engleză Hardback – 17 ian 2009
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
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Specificații

ISBN-13: 9783540898832
ISBN-10: 3540898832
Pagini: 228
Ilustrații: XIX, 204 p.
Dimensiuni: 160 x 241 x 18 mm
Greutate: 0.51 kg
Ediția:2009
Editura: Springer
Colecția Springer Tracts in Advanced Robotics
Seria Springer Tracts in Advanced Robotics

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

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.

Recenzii

From the reviews:
“The book 3D Robotic Mapping by Andreas Nüchter represents an excellent reference for any roboticist working in the area of Simultaneous Localization and Mapping, especially those interested in 3D map building. … The book’s intended target audience is large, ranging from undergraduate students to postdoctoral researchers keen on learning or working on this topic. … I strongly recommend this book as a good introduction and reference material for 3D perception and mapping with mobile robots.”­­­ (Radu Bogdan Rusu, Künstliche Intelligenz, Vol. 24, June, 2010)

Textul de pe ultima copertă

The monograph written by Andreas Nüchter is focused 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.

Caracteristici

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 Includes supplementary material: sn.pub/extras