DMCA
SLAM — Loop Closing with Visually Salient Features (2005)
| Citations: | 65 - 7 self |
BibTeX
@MISC{Newman05slam—,
author = {Paul Newman and Kin Ho},
title = {SLAM — Loop Closing with Visually Salient Features },
year = {2005}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
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.
Keyphrases
slam loop closing visually salient feature loop closing slam algorithm interpose geometric constraint visual feature long term visual saliency image-feature descriptor present initial result robust slam simultaneous localisation scan matching arbitrary length affine invariant reliable loop closing capture time great advantage laser data loop closing event vehicle location delayed vehicle state indoor environment time information
