Rbpf-slam algorithms (c + + library Mrpt-slam)

Rbpf-slam Solutions in Mrpt

1. pfStandardProposal : Sequential importance resampling algorithm based on standard proposal distributions & any type of metric map

Description:the pfStandardProposal algorithm can be used with any metric map or combination of several of them simultaneously, provide D, the observation likelihood function is implemented for the sensor observations in each map. This algorithm however are not recommendable since the ' standard ' proposal distribution is the motion model (the "actions") , and most of the particles would end up in areas incompatible with the observations, and thus, resampling would occur quite Often. Only with this algorithm if the motion model was known to be very precise. Example Config files:

2. pfAuxiliaryPFOptimal : Approximate optimal proposed distribution algorithm based on any type of metric map

Description:the pfAuxiliaryPFOptimal algorithm (introduced in this and this papers) can is used with any metric map or combination of SE Veral of them simultaneously, provided that an observation likelihood function are implemented for the sensor observations In each map. The algorithm would automatically approximate the optimal proposal distribution disregarding the quality of the motion mode L. However, the worse, the motion model, the longer it'll take-to-run each iteration. Example Config files:

• $MRPT/share/mrpt/config_files/rbpf-slam/gridmapping_optimal_sampling.ini: Grid Mapping example with one SICK laser scanner and one mid-sized (~100m long) loop closure.
• $MRPT/share/mrpt/config_files/rbpf-slam/example_3_gridmaps.ini: Three grid maps for three horizontal laser scanners at different heights.

Example of Gridmapping with a RBPF (Rbpf-slam app).

3. pfOptimalProposal : Optimal proposed distribution algorithm based on grid map

Description:the pfOptimalProposal algorithm for grid maps corresponds to the heuristic approximation of the optimal proposal Introduc Ed by G. Grisetti et al. In: "Improved techniques for Grid Mapping with rao-blackwellized particle Filters", Grisetti, G. Stachniss, C. Burgard, W. IEEE Transactions on Robotics (2007) –pdf the implementation in MRPT relies on a version of ICP For Gridmaps. An alternative implementation (independent of MRPT) is the popular gmapping. Note: pfOptimalProposal Requires setting the parameter pfOptimalProposal_mapSelection (see example config files for details). Example Config files:

• $MRPT/share/mrpt/config_files/rbpf-slam/gridmapping_RBPF_grid_ICPbased_malaga.ini: Grid mapping with a mid-sized loop closure.

4. pfOptimalProposal : Optimal proposed distribution algorithm based on point graph

Description:the pfOptimalProposal Algorithm for point maps is a version of the Grisetti et al. 's idea, but applied to point clouds (f Aster to update than grid maps). AFAIK, this method hasn ' t been published on the literature, but works quite fine. Note: pfOptimalProposal Requires setting the parameter pfOptimalProposal_mapSelection (see example config files for details). Example Config files:

• $MRPT/share/mrpt/config_files/rbpf-slam/gridmapping_RBPF_ICPbased_malaga.ini: Point cloud Mapping with a mid-sized loop closure.

Rbpf-slam algorithms (c + + library Mrpt-slam)