Exploiting Locality in SLAM by Nested Dissection
Abstract
In this paper we investigate how a nested dissection ordering method can improve the performance of smoothing SLAM. The computational complexity of SLAM is dominated by the cost of factorizing a matrix of all measurements into a square root form, which has cubic complexity in the worst case. We show that the computational complexity for the factorization of typical measurement matrices occurring in the SLAM problem can be bound tighter under reasonable assumptions. Download: Bibtex: @INPROCEEDINGS{ Krauthausen-RSS-06, AUTHOR = {P. Krauthausen and A. Kipp and F. Dellaert}, TITLE = {Exploiting Locality in SLAM by Nested Dissection}, BOOKTITLE = {Proceedings of Robotics: Science and Systems}, YEAR = {2006}, ADDRESS = {Philadelphia, USA}, MONTH = {August}, DOI = {10.15607/RSS.2006.II.010} }