Unscented FastSLAM

Unscented fastslam is a Rao-Backwellized unscented particle filter that uses the unscented filter for both the localization and mapping.

Authors
Chanki Kim;

Get the Source Code via SVN
svn co https://svn.openslam.org/data/svn/ufastslam

Long Description
Fastslam is one of the robust incremental mapping algorithm that can deal with multimodal distribution. However it suffers from two important limitations which are the derivation of the Jacobian matrices and the linear approximations of nonlinear functions. The latter makes the filter inconsistent. Another challenge in the particle filtering slam is to reduce the number of particles while maintaining the estimation accuracy. This code provides a modified algorithm based on the scaled unscented transformation. It overcomes the limitations of the Fastslam algorithm by directly using linear relations. This approach improves the filter consistency and state estimation accuracy, in other words it requires smaller number of particles than the Fastslam to satisfy the similar performance.


Input Data
This code imports the Victoria park dataset which includes laser range and odometry information. The perception range of the laser is restricted from 80 meters to 30 meters. This code is not optimized and uses a linear search in the data association.

Logfile Format
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Type of Map
feature maps

Hardware/Software Requirements
Windows OS, matlab 20xx

Papers Describing the Approach
Chanki Kim, Rathinasamy Sakthivel, and Wan Kyun Chung: Unscented FastSLAM: A Robust and Efficient Solution to the SLAM Problem, IEEE Transactions on Robotics, Volume 24, Issue 4, pages 808-820, Aug. 2008 (link)

Chanki Kim, Hyoungkyun Kim, and Wan Kyun Chung: Exactly Rao-Blackwellized Unscented Particle Filters for SLAM, In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Sahnghai, China, pages 3589-3594, May 2011

License Information
This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
The authors allow the users of OpenSLAM.org to use and modify the source code for their own research. Any commercial application, redistribution, etc has to be arranged between users and authors individually and is not covered by OpenSLAM.org.

Unscented fastslam is licensed under the Creative Commons (Attribution-NonCommercial-ShareAlike).


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