dc.contributor.author |
Sabatta, DG
|
|
dc.date.accessioned |
2009-05-18T14:09:07Z |
|
dc.date.available |
2009-05-18T14:09:07Z |
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dc.date.issued |
2008-11 |
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dc.identifier.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 |
en |
dc.identifier.isbn |
9780620424639 |
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dc.identifier.uri |
http://hdl.handle.net/10204/3388
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dc.description |
Robotics and Mechatronics Symposium, Bloemfontein, South Africa, 11 November 2008 |
en |
dc.description.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 |
en |
dc.language.iso |
en |
en |
dc.subject |
Topological map technique |
en |
dc.subject |
Localisation algorithm |
en |
dc.subject |
Robotics |
en |
dc.subject |
Scale invariant feature transform (SIFT) |
en |
dc.subject |
SIFT features |
en |
dc.subject |
Datasets |
en |
dc.subject |
Maps |
en |
dc.subject |
Vision-based topological map building |
en |
dc.subject |
Mechatronics symposium |
en |
dc.title |
Vision-based topological map building and localisation using persistent features |
en |
dc.type |
Conference Presentation |
en |
dc.identifier.apacitation |
Sabatta, D. (2008). Vision-based topological map building and localisation using persistent features. http://hdl.handle.net/10204/3388 |
en_ZA |
dc.identifier.chicagocitation |
Sabatta, DG. "Vision-based topological map building and localisation using persistent features." (2008): http://hdl.handle.net/10204/3388 |
en_ZA |
dc.identifier.vancouvercitation |
Sabatta D, Vision-based topological map building and localisation using persistent features; 2008. http://hdl.handle.net/10204/3388 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Sabatta, DG
AB - 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
DA - 2008-11
DB - ResearchSpace
DP - CSIR
KW - Topological map technique
KW - Localisation algorithm
KW - Robotics
KW - Scale invariant feature transform (SIFT)
KW - SIFT features
KW - Datasets
KW - Maps
KW - Vision-based topological map building
KW - Mechatronics symposium
LK - https://researchspace.csir.co.za
PY - 2008
SM - 9780620424639
T1 - Vision-based topological map building and localisation using persistent features
TI - Vision-based topological map building and localisation using persistent features
UR - http://hdl.handle.net/10204/3388
ER -
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en_ZA |