Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9654555 | Robotics and Autonomous Systems | 2005 | 16 Pages |
Abstract
We propose a novelty filter that can operate on-line, so that each new input is evaluated for novelty with respect to the data seen so far. The novelty filter learns to ignore inputs that have been sensed previously, or where similar inputs have been perceived. We demonstrate the use of the novelty filter on a series of simple inspection tasks using a mobile robot. The robot highlights those parts of an environment that are novel in some way, that is they are not part of the model acquired during exploration of a different environment. We show the effectiveness of the method using inputs from both sonar sensors and a monochrome camera.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Stephen Marsland, Ulrich Nehmzow, Jonathan Shapiro,