Skip navigation
Skip navigation

Fast covariance recovery in incremental nonlinear least square solvers

Ila, Viorela; Polok, Lucas; Solony, Marek; Smrz, Pavel; Zemcik, Pavel


Many estimation problems in robotics rely on efficiently solving nonlinear least squares (NLS). For example, it is well known that the simultaneous localisation and mapping (SLAM) problem can be formulated as a maximum likelihood estimation (MLE) and solved using NLS, yielding a mean state vector. However, for many applications recovering only the mean vector is not enough. Data association, active decisions, next best view, are only few of the applications that require fast state covariance...[Show more]

CollectionsANU Research Publications
Date published: 2015
Type: Conference paper
Source: Proceedings - IEEE International Conference on Robotics and Automation
DOI: 10.1109/ICRA.2015.7139841


File Description SizeFormat Image
01_Ila_Fast_covariance_recovery_in_2015.pdf1.59 MBAdobe PDF    Request a copy

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator