Fr. 158.00

Mapping, Planning and Exploration with Pose SLAM

Inglese · Tascabile

Spedizione di solito entro 6 a 7 settimane

Descrizione

Ulteriori informazioni

This monograph introduces a unifying framework for mapping, planning and exploration with mobile robots considering uncertainty, linking such problems with a common SLAM approach, adopting Pose SLAM as the basic state estimation machinery. Pose SLAM is the variant of SLAM where only the robot trajectory is estimated and where landmarks are used to produce relative motion measurements between robot poses. With regards to extending the original Pose SLAM formulation, this monograph covers the study of such measurements when they are obtained with stereo cameras, develops the appropriate noise propagation models for such case, extends the Pose SLAM formulation to SE(3), introduces information-theoretic loop closure tests, and presents a technique to compute traversability maps from the 3D volumetric maps obtained with Pose SLAM. A relevant topic covered in this monograph is the introduction of a novel path planning approach that exploits the modeled uncertainties in Pose SLAM to searchfor the path in the pose graph that allows the robot to navigate to a given goal with the least probability of becoming lost. Another relevant topic is the introduction of an autonomous exploration method that selects the appropriate actions to drive the robot so as to maximize coverage, while minimizing localization and map uncertainties. This monograph is appropriate for readers interested in an information-theoretic unified perspective to the SLAM, path planning and exploration problems, and is a reference book for people who work in mobile robotics research in general.

Sommario

Introduction.- SLAM Front-end.- SLAM Back-end.- Path planning in belief space with Pose SLAM.- Active Pose SLAM.- Conclusions.

Riassunto

This monograph introduces a unifying framework for mapping, planning and exploration with mobile robots considering uncertainty, linking such problems with a common SLAM approach, adopting Pose SLAM as the basic state estimation machinery. Pose SLAM is the variant of SLAM where only the robot trajectory is estimated and where landmarks are used to produce relative motion measurements between robot poses. With regards to extending the original Pose SLAM formulation, this monograph covers the study of such measurements when they are obtained with stereo cameras, develops the appropriate noise propagation models for such case, extends the Pose SLAM formulation to SE(3), introduces information-theoretic loop closure tests, and presents a technique to compute traversability maps from the 3D volumetric maps obtained with Pose SLAM. A relevant topic covered in this monograph is the introduction of a novel path planning approach that exploits the modeled uncertainties in Pose SLAM to searchfor the path in the pose graph that allows the robot to navigate to a given goal with the least probability of becoming lost. Another relevant topic is the introduction of an autonomous exploration method that selects the appropriate actions to drive the robot so as to maximize coverage, while minimizing localization and map uncertainties. This monograph is appropriate for readers interested in an information-theoretic unified perspective to the SLAM, path planning and exploration problems, and is a reference book for people who work in mobile robotics research in general.

Dettagli sul prodotto

Autori Juan Andrade-Cetto, Rafae Valencia, Rafael Valencia
Editore Springer, Berlin
 
Lingue Inglese
Formato Tascabile
Pubblicazione 01.01.2018
 
EAN 9783319868974
ISBN 978-3-31-986897-4
Pagine 114
Dimensioni 155 mm x 7 mm x 235 mm
Peso 209 g
Illustrazioni XII, 114 p. 40 illus., 38 illus. in color.
Serie Springer Tracts in Advanced Robotics
Categorie Scienze naturali, medicina, informatica, tecnica > Tecnica > Elettronica, elettrotecnica, telecomunicazioni

B, Künstliche Intelligenz, Robotics, Artificial Intelligence, Automation, engineering, Control, Robotics, Automation, Robotics and Automation

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