Abstract
The reference map for a given environment is one of the most essential elements for a mobile robot to automatically control itself and find a path. Simultaneous localization and mapping (SLAM) is a technology that aids the autonomous movement of a mobile robot in a given environment by simultaneously creating a map and performing localization. Graph-based SLAM is the state-of-the-art solution. However, graph-based SLAM faces certain problems when constructing graphs because of the front-end processing failure that occurs when using Iterative Closest Points (ICP). When the robot is in motion, a deviation between the scan images of the environment appears in every scan. Therefore, it is necessary to perform matching of the two images by using an outlier rejection algorithm for a robust ICP algorithm. In this paper, we propose an ICP outlier rejection scheme to compare to scan images and select matching points and reject mismatched parts. The experimental results show that the proposed scheme is reliable and robust in practical environments.
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Acknowledgements
This work was carried out with the support of “Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ01386005)” Rural Development Administration, Republic of Korea.
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Jo, J.H., Moon, Cb. Development of a Practical ICP Outlier Rejection Scheme for Graph-based SLAM Using a Laser Range Finder. Int. J. Precis. Eng. Manuf. 20, 1735–1745 (2019). https://doi.org/10.1007/s12541-019-00175-0
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DOI: https://doi.org/10.1007/s12541-019-00175-0