Exactly Sparse Delayed State Filter based robust SLAM with Stereo Vision (CROSBI ID 561107)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Kitanov, Andrej ; Petrović, Ivan
engleski
Exactly Sparse Delayed State Filter based robust SLAM with Stereo Vision
This paper presents a new SLAM solution based on Exactly Sparse Delayed State Filter and data association by a novel robust stereo vision image registration constrained geometrically with odometry inputs. The proposed constrained image registration algorithm is robust to high uncertainty of odometry inputs and high percentage of data association outliers and achieves fast convergence. Extended Information Filter (i.e. the dual of the Extended Kalman Filter) is used to estimate the mobile robot’s pose history, because information matrix then exhibits exactly sparse structure with Markov process model which yields efficient filtering. Computationally most demanding operations - mean and covariance recovery that are needed in data association and filter motion update - can be recovered in linear time by solving system of sparse equations. Although our solution is tested on 2D stereo vision based SLAM benchmarking problem taken from Rawseeds database, it can solve general 3D SLAM problem.
SLAM; mobile robot; stereo vision; localization
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Podaci o prilogu
136-142.
2010.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of ISR / ROBOTIK 2010
München:
Podaci o skupu
The joint conference of the 41st International Symposium on Robotics (ISR 2010) and the 6th German Conference on Robotics (ROBOTIK 2010)
predavanje
07.07.2010-09.07.2010
München, Njemačka