Probabilistic Localization by Appearance Models and Active Vision

  title={Probabilistic Localization by Appearance Models and Active Vision},
  author={Ben J. A. Kr{\"o}se and Roland Bunschoten},
In order to do useful things a mobile robot needs some sort of global information about the environment it is operating in. In this paper an approach is described where the global information is not cast in a model of the geometry of the environment but in a model of all sensory data of the robot. As a primary sensing system we used computer vision. The model gives a probability distribution over the learned locations given an observation. We developed an active vision strategy to increase the… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 18 references

\Continuity properties of the appearance manifold for mobile robot estimation

F Pourraz, J L Crowley
SIRS'98 • 1998

James Crowley, \Appearance based processes for visual navigation

C S Andersen, Stephan Jones
Proc. SIRS'97 • 1997

\A direct interpretation of dynamic images and camera motion for vision guided robotics

Koichiro Deguchi
Proc. IEEE/SICE/RSJ Int. Conf. on Multisensor Fusion • 1996

Kuipers: \Learning to explore and build maps

A Pierce
Proc. AAAI-94 • 1994

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