FastSLAM A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics /

This monograph describes a new family of algorithms for the simultaneous localization and mapping problem in robotics (SLAM). SLAM addresses the problem of acquiring an environment map with a roving robot, while simultaneously localizing the robot relative to this map. This problem has received enor...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Montemerlo, Michael (Autor), Thrun, Sebastian (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Colección:Springer Tracts in Advanced Robotics, 27
Temas:
Control engineering.
Robotics.
Automation.
Mathematical optimization.
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Image processing-Digital techniques.
Computer vision.
Control, Robotics, Automation.
Optimization.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 1 Introduction
  • Applications of SLAM, Joint Estimation, Posterior Estimation, The Extended Kalman Filter, Structure and Sparsity in SLAM, FastSLAM, Outline
  • 2 The SLAM Problem
  • Problem Definition, SLAM Posterior, SLAM as a Markov Chain, Extended Kalman Filtering, Scaling SLAM Algorithms, Robust Data Association, Comparison of FastSLAM to Existing Techniques
  • 3 FastSLAM 1.0
  • Particle Filtering, Factored Posterior Representation, The FastSLAM 1.0 Algorithm, FastSLAM with Unknown Data Association, Summary of the FastSLAM Algorithm, FastSLAM Extensions, Log(N) FastSLAM, Experimental Results, Summary
  • 4 FastSLAM 2.0
  • Sample Impoverishment, FastSLAM 2.0, FastSLAM 2.0 Convergence, Experimental Results, Grid-based FastSLAM, Summary
  • 5 Dynamic Environments
  • SLAM With Dynamic Landmarks, Simultaneous Localization and People Tracking, FastSLAP Implementation,Experimental Results, Summary
  • 6 Conclusions
  • Conclusions, Future Work
  • References, Index.

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