Rao-Blackwellised RFS Bayesian SLAM
This chapter proposes an alternative Bayesian framework for feature-based SLAM, again in the general case of uncertain feature number and data association. As in Chapter 5, a first order solution, coined the probability hypothesis density (PHD) SLAM filter, is used, which jointly propagates the post...
| Main Authors: | , , , |
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| Format: | Book Chapter |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/60486 |
| _version_ | 1848760609694285824 |
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| author | Mullane, J. Vo, Ba-Ngu Adams, M. Vo, Ba Tuong |
| author_facet | Mullane, J. Vo, Ba-Ngu Adams, M. Vo, Ba Tuong |
| author_sort | Mullane, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This chapter proposes an alternative Bayesian framework for feature-based SLAM, again in the general case of uncertain feature number and data association. As in Chapter 5, a first order solution, coined the probability hypothesis density (PHD) SLAM filter, is used, which jointly propagates the posterior PHD of the map and the posterior distribution of the vehicle trajectory. In this chapter however, a Rao-Blackwellised (RB) implementation of the PHD-SLAM filter is proposed based on the GM PHD filter for the map and a particle filter for the vehicle trajectory, with initial results presented in [56] and further refinements in [57] . |
| first_indexed | 2025-11-14T10:18:30Z |
| format | Book Chapter |
| id | curtin-20.500.11937-60486 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:18:30Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-604862018-06-18T01:13:46Z Rao-Blackwellised RFS Bayesian SLAM Mullane, J. Vo, Ba-Ngu Adams, M. Vo, Ba Tuong This chapter proposes an alternative Bayesian framework for feature-based SLAM, again in the general case of uncertain feature number and data association. As in Chapter 5, a first order solution, coined the probability hypothesis density (PHD) SLAM filter, is used, which jointly propagates the posterior PHD of the map and the posterior distribution of the vehicle trajectory. In this chapter however, a Rao-Blackwellised (RB) implementation of the PHD-SLAM filter is proposed based on the GM PHD filter for the map and a particle filter for the vehicle trajectory, with initial results presented in [56] and further refinements in [57] . 2011 Book Chapter http://hdl.handle.net/20.500.11937/60486 10.1007/978-3-642-21390-8_6 restricted |
| spellingShingle | Mullane, J. Vo, Ba-Ngu Adams, M. Vo, Ba Tuong Rao-Blackwellised RFS Bayesian SLAM |
| title | Rao-Blackwellised RFS Bayesian SLAM |
| title_full | Rao-Blackwellised RFS Bayesian SLAM |
| title_fullStr | Rao-Blackwellised RFS Bayesian SLAM |
| title_full_unstemmed | Rao-Blackwellised RFS Bayesian SLAM |
| title_short | Rao-Blackwellised RFS Bayesian SLAM |
| title_sort | rao-blackwellised rfs bayesian slam |
| url | http://hdl.handle.net/20.500.11937/60486 |