Pose Tracking Using Laser Scanning and Minimalistic Environmental
Models
Patric
Jensfelt and Henrik I. Christensen
Abstract
Keeping track of the position and orientation over time using sensor
data, i.e. \emph{pose tracking}, is a central component in many mobile
robot systems. In this paper we present a Kalman filter based approach
utilizing a minimalistic environmental model. By continuously updating
the pose, matching the sensor data to the model is straightforward and
outliers can be filtered out effectively by validation gates. The
minimalistic model paves the way for a low-complexity algorithm with a
high degree of robustness and accuracy. Robustness here refers both to
being able to track the pose for a long time, but also handling
changes and clutter in the environment. This robustness is gained by
the minimalistic model only capturing the stable and large scale
features of the environment. The effectiveness of the pose tracker
will be demonstrated through a number of experiments, including a run
of 90 minutes which clearly establishes the robustness of the method.
BibTeX Entry:
@Article{Jensfelt01a,
author = {Patric Jensfelt and Henrik I. Christensen},
title = {Pose Tracking Using Laser Scanning and Minimalistic Environmental Models},
journal = {IEEE Transactions on Robotics and Automation},
year = 2001,
volume = 17,
number = 2,
pages = {138--147},
month = apr
}
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