MATEC Web of Conferences
Volume 42, 20162015 The 3rd International Conference on Control, Mechatronics and Automation (ICCMA 2015)
|Number of page(s)||5|
|Section||Robot design and development|
|Published online||17 February 2016|
Comparison of the SLAM algorithms: Hangar experiments
Selcuk University in Konya, TURKEY
a Corresponding author: email@example.com
This study purposes to compare two known algorithms in an application scenario of simultaneous localization and mapping (SLAM) and to present issues related with them as well. Mostly used SLAM algorithms Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are compared with respect to the point of accuracy of the robot states, localization and mapping. Because of considering the most implementations in the previous studies, the simulation environments are chosen as big as possible to provide reliable results. In this study, two different hangar regions are tried to be simulated. According to the outcomes of the applications, UKF-based SLAM algorithm has superior performance over the EKF-based one, apart from elapsed time.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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