An Approach to Reduce Computational Cost for Localization Problem
One of the biggest factors that contribute to the computational cost of extended Kalman filter-based SLAM is the covariance update. This is due to the multiplications of the covariance matrix with other parameters and the increment of its dimension, which is twice the number of landmarks. Therefore...
Saved in:
Main Authors: | , |
---|---|
Format: | Conference or Workshop Item |
Language: | English English |
Published: |
2014
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/9786/1/An%20Approach%20to%20Reduce%20Computational%20Cost%20for%20Localization%20Problem.pdf http://umpir.ump.edu.my/id/eprint/9786/7/An%20Approach%20to%20Reduce%20Computational%20Cost%20for%20Localization%20Problem%20-%20Abstract.pdf http://umpir.ump.edu.my/id/eprint/9786/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Internet
http://umpir.ump.edu.my/id/eprint/9786/1/An%20Approach%20to%20Reduce%20Computational%20Cost%20for%20Localization%20Problem.pdfhttp://umpir.ump.edu.my/id/eprint/9786/7/An%20Approach%20to%20Reduce%20Computational%20Cost%20for%20Localization%20Problem%20-%20Abstract.pdf
http://umpir.ump.edu.my/id/eprint/9786/