Title :
The Labeled Multi-Bernoulli SLAM Filter
Author :
Deusch, Hendrik ; Reuter, Stephan ; Dietmayer, Klaus
Author_Institution :
Inst. of Meas., Control & Microtechnol., Ulm Univ., Ulm, Germany
Abstract :
In this contribution, a new algorithm addressing the simultaneous localization and mapping (SLAM) problem is proposed: a Rao-Blackwellized implementation of the Labeled Multi-Bernoulli SLAM (LMB-SLAM) filter. Further, we establish that the LMB-SLAM does not require the approximations used in Probability Hypothesis Density SLAM (PHD-SLAM). The LMB-SLAM is shown to outperform PHD-SLAM in simulations by providing a more accurate map as well as an improved estimate of the vehicle´s trajectory which is an expected result due to the superior performance of the LMB filter in tracking applications.
Keywords :
Kalman filters; SLAM (robots); pose estimation; set theory; LMB-SLAM filter; Rao-Blackwellized implementation; labeled multiBernoulli SLAM filter; simultaneous localization and mapping problem; tracking applications; vehicle trajectory estimation; Approximation methods; Distribution functions; Graphical models; Simultaneous localization and mapping; Trajectory; Vectors; Vehicles; Labeled multi-bernoulli; SLAM; localization; mapping; random finite sets;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2015.2414274
