Name
Abstract | ||
|---|---|---|
The task of Simultaneous Localization and Mapping (SLAM) is regularly performed in network spaces consisting of a set of corridors connecting locations in the space. Empirical research has demonstrated that such spaces generally exhibit common structural properties relating to aspects such as corridor length. Consequently there exists potential to improve performance through the placement of priors over these properties. In this work we propose an appearance-based SLAM method which explicitly models the space as a network and in turn uses this model as a platform to place priors over its structure. Relative to existing works, which implicitly assume a network space and place priors over its structure, this approach allows a more formal placement of priors. In order to achieve robustness, the proposed method is implemented within a multi-hypothesis tracking framework. Results achieved on two publicly available datasets demonstrate the proposed method outperforms a current state-of-the-art appearance-based SLAM method. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICRA.2015.7140010 | IEEE International Conference on Robotics and Automation |
Keywords | Field | DocType |
SLAM (robots),robust control,appearance-based SLAM,corridor length,corridors connecting location,formal placement,multihypothesis tracking framework,network space,robustness,simultaneous localization and mapping,structural property | Existential quantification,Appearance based,Robustness (computer science),Probability distribution,Artificial intelligence,Simultaneous localization and mapping,Prior probability,Mathematics,Machine learning,Empirical research | Conference |
Volume | Issue | ISSN |
2015 | 1 | 1050-4729 |
Citations | PageRank | References |
0 | 0.34 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Padraig Corcoran | 1 | 191 | 23.08 |
| Ted J. Steiner | 2 | 1 | 1.38 |
| Michela Bertolotto | 3 | 863 | 91.77 |
| John J. Leonard | 4 | 4696 | 431.59 |