Rao-Blackwellised RFS Bayesian SLAM
| dc.contributor.author | Mullane, J. | |
| dc.contributor.author | Vo, Ba-Ngu | |
| dc.contributor.author | Adams, M. | |
| dc.contributor.author | Vo, Ba Tuong | |
| dc.date.accessioned | 2018-01-30T08:00:44Z | |
| dc.date.available | 2018-01-30T08:00:44Z | |
| dc.date.created | 2018-01-30T05:59:14Z | |
| dc.date.issued | 2011 | |
| dc.identifier.citation | Mullane J. and Vo B.N. and Adams M., Vo B.T. 2011. Rao-Blackwellised RFS Bayesian SLAM, in Random Finite Sets for Robot Mapping and SLAM. Springer Tracts in Advanced Robotics, vol 72, pp. 97-126. Berlin: Springer. | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/60486 | |
| dc.identifier.doi | 10.1007/978-3-642-21390-8_6 | |
| dc.description.abstract |
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] . | |
| dc.title | Rao-Blackwellised RFS Bayesian SLAM | |
| dc.type | Book Chapter | |
| dcterms.source.volume | 72 | |
| dcterms.source.startPage | 97 | |
| dcterms.source.endPage | 126 | |
| dcterms.source.title | Springer Tracts in Advanced Robotics | |
| curtin.department | School of Electrical Engineering and Computing | |
| curtin.accessStatus | Fulltext not available |
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