Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

CiteULike is a free service for managing and discovering scholarly references - click here to get started.

Sign In to gain access to subscriptions and/or personal tools.
The International Journal of Robotics Research
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Wang, Z.
Right arrow Articles by Dissanayake, G.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

D-SLAM: A Decoupled Solution to Simultaneous Localization and Mapping

Zhan Wang

ARC Centre of Excellence for Autonomous Systems (CAS) Faculty of Engineering University of Technology Sydney, Australia; zwang{at}eng.uts.edu.au

Shoudong Huang

ARC Centre of Excellence for Autonomous Systems (CAS) Faculty of Engineering University of Technology Sydney, Australia; sdhuang{at}eng.uts.edu.au

Gamini Dissanayake

ARC Centre of Excellence for Autonomous Systems (CAS) Faculty of Engineering University of Technology Sydney, Australia; gdissa{at}eng.uts.edu.au

The main contribution of this paper is the reformulation of the simultaneous localization and mapping (SLAM) problem for mobile robots such that the mapping and localization can be treated as two concurrent yet separated processes: D-SLAM (decoupled SLAM). It is shown that SLAM with a range and bearing sensor in an environment populated with point features can be decoupled into solving a nonlinear static estimation problem for mapping and a low-dimensional dynamic estimation problem for localization. This is achieved by transforming the measurement vector into two parts: one containing information relating features in the map and another with information relating the map and robot. It is shown that the new formulation results in an exactly sparse information matrix for mapping when it is solved using an Extended Information Filter (EIF).Thus a significant saving in the computational effort can be achieved for large-scale problems by exploiting the special properties of sparse matrices. An important feature of D-SLAM is that the correlation among features in the map are still kept and it is demonstrated that the uncertainty of the feature estimates monotonically decreases. The algorithm is illustrated and evaluated through computer simulations and experiments.

Key Words: decoupled SLAM • extended information filter • sparse matrix • computational complexity

The International Journal of Robotics Research, Vol. 26, No. 2, 187-204 (2007)
DOI: 10.1177/0278364906075173


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?