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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/3388

Title: Vision-based topological map building and localisation using persistent features
Authors: Sabatta, DG
Keywords: Topological map technique
Localisation algorithm
Robotics
Scale invariant feature transform (SIFT)
SIFT features
Datasets
Maps
Vision-based topological map building
Mechatronics symposium
Issue Date: Nov-2008
Citation: Sabatta, DG. 2008. Vision-based topological map building and localisation using persistent features. Robotics and Mechatronics Symposium, Bloemfontein, South Africa, 11 November 2008, pp 1-6
Abstract: This paper proposes a topological mapping technique that utilises persistent SIFT features to reduce the amount of data storage required. It delivers, as an output, a topological map that lends itself well to conventional path planning techniques. The approach assimilates features into a statistical model which promises improved data association. Experiments were performed using omnidirectional camera images from the Cogniron dataset. A map was constructed from one of the supplied routes and the performance of the localisation algorithm evaluated using another route within the same environment. Thereafter the map was updated using the comparison route and the results discussed. The statistical feature association approach is shown to be more robust than conventional methods
Description: Robotics and Mechatronics Symposium, Bloemfontein, South Africa, 11 November 2008
URI: http://hdl.handle.net/10204/3388
ISBN: 9780620424639
Appears in Collections:Mobile intelligent autonomous systems
General science, engineering & technology

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