|
I-SLSJF is a local submap joining algorithm using sparse information filter and least squares optimization. The input of I-SLSJF is a sequence of local maps and
the output of I-SLSJF is a global map. The preprocessed Victoria Park data set and the corrected DLR-Spatial-Cognition data set are provided to demonstrate the algorithm.
Further information | |
|
Authors Shoudong Huang; Zhan Wang; | |
|
Get the Source Code! | |
|
Long Description I-SLSJF is a new local submap joining algorithm for building large-scale feature based maps. The algorithm is based on the recently developed Sparse Local Submap Joining Filter (SLSJF) and uses multiple iterations to improve the estimate and hence is called Iterated SLSJF (I-SLSJF). The input to the I-SLSJF algorithm is a sequence of local submaps. The output of the algorithm is a global map containing the global positions of all the features as well as all the robot start/end poses of the local submaps. A number of simuation and experimental data sets are provided together with the MATLAB source code. The user can easily use the code to fuse their own local maps. | |
|
Input Data A sequence of small loal maps, each local map contain a state vector estimate and the corresponding covariance matrix. | |
|
Type of Map point feature maps | |
|
Hardware/Software Requirements MATLAB | |
|
Documentation Document for 2D I-SLSJF MATLAB code | |
|
Papers Describing the Approach Shoudong Huang, Zhan Wang, Gamini Dissanayake, and Udo Frese: Iterated SLSJF: A sparse local submap joining algorithm with improved consistency , 2008 Australiasan Conference on Robotics and Automation. Canberra, December 2008. , 2008 (link) Shoudong Huang, Zhan Wang, and Gamini Dissanayake: Sparse local submap joining filter for building large-scale maps, IEEE Transactions on Robotics, 2008 (link) | |
|
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. | |
|
*** OpenSLAM.org is not responsible for the content of this webpage *** *** Copyright and V.i.S.d.P.: Shoudong Huang; Zhan Wang; *** |