An experimental comparison of localization methods

@inproceedings{Gutmann1998AnEC,
  title={An experimental comparison of localization methods},
  author={Jens-Steffen Gutmann and Wolfram Burgard and Dieter Fox and Kurt Konolige},
  booktitle={IROS},
  year={1998}
}
Localization is the process of updating the pose of a robot in an environment, based on sensor readings. In this experimental study, we compare two recent methods for localization of indoor mobile robots: Markov localization, which uses a probability distribution across a grid of robot poses; and scan matching, which uses Kalman filtering techniques based on matching sensor scans. Both these techniques are dense matching methods , that is, they match dense sets of environment features to an a… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 32 references

Bayesian landmark learning for mobile robot

S. Thrun
localization.Machine Learning, • 1998

Thrun . Theinteractivemuseum tourguiderobot

D. Fox, D. Hennig
1998

Milios . Globally consistentrangescanalignmentfor environmentmapping

H.
AutonomousRobots • 1997

Thrun . Active mobilerobotlocalization

J. Connell.
1997

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