Random Finite Sets for Robot Mapping and SLAM New Concepts in Autonomous Robotic Map Representations /

Random Finite Sets for Robot Mapping and SLAM New Concepts in Autonomous Robotic Map Representations /

Simultaneous Localisation and Map (SLAM) building algorithms, which rely on random vectors to represent sensor measurements and feature maps are known to be extremely fragile in the presence of feature detection and data association uncertainty. Therefore new concepts for autonomous map representati...

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Bibliographic Details
Main Authors: Mullane, John (Author), Vo, Ba-Ngu (Author), Adams, Martin (Author), Vo, Ba-Tuong (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
Series:Springer Tracts in Advanced Robotics, 72
Subjects:
Engineering.
Artificial intelligence.
Robotics.
Automation.
Robotics and Automation.
Artificial Intelligence (incl. Robotics).
Online Access:Full Text via HEAL-Link
Table of Contents:
  • Part I Random Finite Sets
  • Why Random Finite Sets?
  • Estimation with Random Finite Sets
  • Part II Random Finite Set Based Robotic Mapping
  • An RFS Theoretic for Bayesian Feature-Based Robotic Mapping
  • An RFS ‘Brute Force’ Formulation for Bayesian SLAM
  • Rao-Blackwellised RFS Bayesian SLAM
  • Extensions with RFSs in SLAM.

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