Implementation of monocular 2D EKF-vSLAM algorithm

Yuanzi He

doi:10.1117/12.3009523

16 October 2023 Implementation of monocular 2D EKF-vSLAM algorithm

Yuanzi He

Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 128030Z (2023) https://doi.org/10.1117/12.3009523
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

Aiming at the localization and composition of mobile robots in unknown environments, this paper briefly summarizes the connotation of SLAM, analyzes the principle of extended Kalman filter theory, which is an algorithm process of gradually approaching the real state of the system through recursive estimation of the state of nonlinear random dynamic system, and finally verifies the relevant theories and algorithms through two-dimensional EKF vSLAM simulation experiments. The experimental results show that the EKF-vSLAM algorithm can effectively improve the accuracy of robot positioning and landmark positioning in two-dimensional environments, reduce the uncertainty of mobile robot positioning and composition in unknown environments, and to some extent improve the autonomy of mobile robots.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuanzi He "Implementation of monocular 2D EKF-vSLAM algorithm", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 128030Z (16 October 2023); https://doi.org/10.1117/12.3009523

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available