Approaches to Mobile Robot Localization in Indoor Environments

Abstract:

This thesis deals with all aspects of mobile robot localization for indoor applications. The problems span from tracking the position given an initial estimate, over finding it without any prior position knowledge, to automatically building a representation of the environment while performing localization. The theme is the use of minimalistic models which capture the large scale structures of the environment, such as the dominant walls, to provide scalable and low-complexity solutions. In many cases it is enough to only maintain an estimate of the robot position. For such situation an extensively tested low-complexity, robust and accurate pose tracking method is presented which utilizes the minimalistic model in combination with a laser sensor. When the initial position is unknown the robot must perform global localization. Two different methods are investigated. The first one is a novel localization scheme, based on the ideas of Multiple Hypothesis Tracking. The second is an, experimentally verified, significant improvement of the standard Monte Carlo Localization technique. To automatically generate an environmental representation an hierarchical approach to simultaneous localization and mapping (SLAM) is presented. The map scaling issue is here addressed by dividing the environment into submaps, each representing a small area.

BibTeX Entry:

@PhdThesis{Jensfelt01PhD,
  author =       {P. Jensfelt},
  title =        {Approaches to Mobile Robot Localization in Indoor Environments},
  address =      {Royal Institute of Technology, SE-100 44 Stockholm, Sweden},
  year =         2001,
  ISSN_ISBN =    {ISBN 91-7283-135-9, ISSN 1404-2150},
  school =       {Signal, Sensors and Systems (S3)}
}

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