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Dieter Fox, Wolfram Burgard, Frank Dellaert, and Sebastian Thrun, 1999, “Monte Carlo Localization: Efficient Position Estimation for Mobile Robot,” Proc. of the sixteenth National Conference on Artificial Intelligence John Wiley & Sons Ltd.

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Article

Experimental comparison of the Simultaneous Localization and Mapping Schemes in the Practical Environments Using the Robot Operating System

1Department of Mechanical Engineering, Chonnam National University, Gwanju, Korea


Journal of Automation and Control. 2018, Vol. 6 No. 1, 15-18
DOI: 10.12691/automation-6-1-2
Copyright © 2018 Science and Education Publishing

Cite this paper:
Ju-Min Kim, Ha Jeong Seok, Chang-bae Moon. Experimental comparison of the Simultaneous Localization and Mapping Schemes in the Practical Environments Using the Robot Operating System. Journal of Automation and Control. 2018; 6(1):15-18. doi: 10.12691/automation-6-1-2.

Correspondence to: Chang-bae  Moon, Department of Mechanical Engineering, Chonnam National University, Gwanju, Korea. Email: cbmoon@jnu.ac.kr

Abstract

In recent days, mobile service robots have been widely developed for security, cleaning and guidance purpose. The use of open source code based on Robot Operating System (ROS) supports rapid testing and comparison of the previous developed schemes. Especially, the SLAM (Simultaneous Localization and Mapping) schemes are most useful because the SLAM schemes are requiring the previous recorded logging data from sensors, e.g., odometry and laser scanners. In this paper, we represent the simulation method using ROS and being supported SLAM schemes by ROS. The simulations carried out by using the previous recorded odometry and laser scanning data. The experimental results are presented by using the Cartographer and KARTO SLAM schemes.

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