Dayoub, Feras, Duckett, Tom and Cielniak, Grzegorz
(2009)
An adaptive spherical view representation for navigation in changing environments.
In: 4th European Conference on Mobile Robots ECMR-09, 22 - 25 September 2009, Mlini / Dubrovnik.
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Item Type: | Conference or Workshop contribution (Paper) |
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Item Status: | Live Archive |
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Abstract
Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In previous work we introduced a method to update the reference views in a topological map so that a mobile robot could continue to localize itself in a changing environment using omni-directional vision. In this work we extend this longterm updating mechanism to incorporate a spherical metric representation of the observed visual features for each node in the topological map. Using multi-view geometry we are then able to estimate the heading of the robot, in order to enable navigation between the nodes of the map, and to simultaneously adapt the spherical view representation in response to environmental changes. The results demonstrate the persistent performance of the proposed system in a long-term experiment.
Additional Information: | Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In previous work we introduced a method to update the reference views in a topological map so that a mobile robot could continue to localize itself in a changing environment using omni-directional vision. In this work we extend this longterm updating mechanism to incorporate a spherical metric representation of the observed visual features for each node in the topological map. Using multi-view geometry we are then able to estimate the heading of the robot, in order to enable navigation between the nodes of the map, and to simultaneously adapt the spherical view representation in response to environmental changes. The results demonstrate the persistent performance of the proposed system in a long-term experiment. |
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Keywords: | SLAM, Persistent Mapping, Omnidirectional Vision, Mobile Robot Navigation. |
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Subjects: | H Engineering > H671 Robotics G Mathematical and Computer Sciences > G740 Computer Vision |
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Divisions: | College of Science > School of Computer Science |
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ID Code: | 1960 |
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Deposited On: | 17 Sep 2009 12:19 |
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