(Enter summary)
Abstract: We consider the problem of locating a robot in
an initially-unfamiliar environment from visual input.
The robot is not given a map of the environment, but
it does have access to a collection of training examples,
each of which specifies the video image observed when
the robot is at a particular location and orientation. (Update)
Context of citations to this paper: More
...applying geometric transformations to fit the data extracted from the most recent image to the models assigned to the reference images. [4, 17] apply a neural network to learn the position of the robot given a reference image. One advantage of this approach lies in the...
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BibTeX entry: (Update)
Dudek, G., and Zhang, C. 1996. Vision-based robot localization without explicit object models. In Proc. International Conference of Robotics and Automation. Minneapolis, MN: IEEE Press. http://citeseer.ist.psu.edu/750293.html More
@misc{ dudek96visionbased,
author = "G. Dudek and C. Zhang",
title = "Vision-based robot localization without explicit object models",
text = "Dudek, G., and Zhang, C. 1996. Vision-based robot localization without
explicit object models. In Proc. International Conference of Robotics and
Automation. Minneapolis, MN: IEEE Press.",
year = "1996",
url = "citeseer.ist.psu.edu/750293.html" }
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