SLAM - Loop closing with visually salient features
Within the context of Simultaneous Localisation and Mapping (SLAM), "loop closing" is the task of deciding whether or not a vehicle has, after an excursion of arbitrary length, returned to a previously visited area. Reliable loop closing is both essential and hard. It is without doubt one...
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| Format: | Conference item |
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2005
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| _version_ | 1797056977320280064 |
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| author | Newman, P Ho, K IEEE |
| author_facet | Newman, P Ho, K IEEE |
| author_sort | Newman, P |
| collection | OXFORD |
| description | Within the context of Simultaneous Localisation and Mapping (SLAM), "loop closing" is the task of deciding whether or not a vehicle has, after an excursion of arbitrary length, returned to a previously visited area. Reliable loop closing is both essential and hard. It is without doubt one of the greatest impediments to long term, robust SLAM. This paper illustrates how visual features, used in conjunction with scanning laser data, can be used to a great advantage. We use the notion of visual saliency to focus the selection of suitable (affine invariant) image-feature descriptors for storage in a database. When queried with a recently taken image the database returns the capture time of matching images. This time information is used to discover loop closing events. Crucially this is achieved independently of estimated map and vehicle location. We integrate the above technique into a SLAM algorithm using delayed vehicle states and scan matching to form interpose geometric constraints. We present initial results using this system to close loops (around 100m) in an indoor environment. © 2005 IEEE. |
| first_indexed | 2024-03-06T19:29:59Z |
| format | Conference item |
| id | oxford-uuid:1d1efe84-5807-42d5-b9ca-d6cda18c3c3d |
| institution | University of Oxford |
| last_indexed | 2024-03-06T19:29:59Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | oxford-uuid:1d1efe84-5807-42d5-b9ca-d6cda18c3c3d2022-03-26T11:09:06ZSLAM - Loop closing with visually salient featuresConference itemhttp://purl.org/coar/resource_type/c_5794uuid:1d1efe84-5807-42d5-b9ca-d6cda18c3c3dSymplectic Elements at Oxford2005Newman, PHo, KIEEEWithin the context of Simultaneous Localisation and Mapping (SLAM), "loop closing" is the task of deciding whether or not a vehicle has, after an excursion of arbitrary length, returned to a previously visited area. Reliable loop closing is both essential and hard. It is without doubt one of the greatest impediments to long term, robust SLAM. This paper illustrates how visual features, used in conjunction with scanning laser data, can be used to a great advantage. We use the notion of visual saliency to focus the selection of suitable (affine invariant) image-feature descriptors for storage in a database. When queried with a recently taken image the database returns the capture time of matching images. This time information is used to discover loop closing events. Crucially this is achieved independently of estimated map and vehicle location. We integrate the above technique into a SLAM algorithm using delayed vehicle states and scan matching to form interpose geometric constraints. We present initial results using this system to close loops (around 100m) in an indoor environment. © 2005 IEEE. |
| spellingShingle | Newman, P Ho, K IEEE SLAM - Loop closing with visually salient features |
| title | SLAM - Loop closing with visually salient features |
| title_full | SLAM - Loop closing with visually salient features |
| title_fullStr | SLAM - Loop closing with visually salient features |
| title_full_unstemmed | SLAM - Loop closing with visually salient features |
| title_short | SLAM - Loop closing with visually salient features |
| title_sort | slam loop closing with visually salient features |
| work_keys_str_mv | AT newmanp slamloopclosingwithvisuallysalientfeatures AT hok slamloopclosingwithvisuallysalientfeatures AT ieee slamloopclosingwithvisuallysalientfeatures |