— Smoothing and optimization approaches are an effective means for solving the simultaneous localization and mapping (SLAM) problem. Most of the existing techniques focus mainly ...
Gian Diego Tipaldi, Giorgio Grisetti, Wolfram Burg...
— This paper presents a vision-based approach to SLAM in large-scale environments with minimal sensing and computational requirements. The approach is based on a graphical repres...
Henrik Andreasson, Tom Duckett, Achim J. Lilientha...
— In this paper, we present an Extended Kalman Filter (EKF)-based estimator for simultaneous localization and mapping (SLAM) with processing requirements that are linear in the n...
This paper aims at a discussion of the structure of the SLAM problem. The analysis is not strictly formal but based both on informal studies and mathematical derivation. The first ...
— This paper provides a novel state vector and covariance sub-matrix recovery algorithm for a recently developed submap based exactly sparse Extended Information Filter (EIF) SLA...