3D Robotic Mapping

3D Robotic Mapping
Author: Andreas Nüchter
Publisher: Springer Science & Business Media
Total Pages: 214
Release: 2009-01-17
Genre: Technology & Engineering
ISBN: 3540898832


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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


3D Robotic Mapping
Language: en
Pages: 214
Authors: Andreas Nüchter
Categories: Technology & Engineering
Type: BOOK - Published: 2009-01-17 - Publisher: Springer Science & Business Media

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Focuses on acquiring spatial models of physical environments through mobile robots The robotic mapping problem is commonly referred to as SLAM (simultaneous loc
Semantic 3D Object Maps for Everyday Robot Manipulation
Language: en
Pages: 235
Authors: Radu Bogdan Rusu
Categories: Technology & Engineering
Type: BOOK - Published: 2013-01-13 - Publisher: Springer

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The book written by Dr. Radu B. Rusu presents a detailed description of 3D Semantic Mapping in the context of mobile robot manipulation. As autonomous robotic p
Robotic Mapping and Exploration
Language: en
Pages: 206
Authors: Cyrill Stachniss
Categories: Technology & Engineering
Type: BOOK - Published: 2009-05-06 - Publisher: Springer

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"Robotic Mapping and Exploration" is an important contribution in the area of simultaneous localization and mapping (SLAM) for autonomous robots, which has been
3D Robotic Mapping and Place Recognition
Language: en
Pages:
Authors: Muhammad Sheraz Khan
Categories:
Type: BOOK - Published: 2017 - Publisher:

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Multi-Robot Mapping Based on 3D Maps Integration
Language: en
Pages: 0
Authors: Elzbieta Roszkowska
Categories: Technology & Engineering
Type: BOOK - Published: 2022 - Publisher:

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An unknown environment could be mapped more efficiently by a group of robots than a single robot. The time reduction due to parallelization is crucial in comple