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Open AccessArticle

Large-Scale Outdoor SLAM Based on 2D Lidar

College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Author to whom correspondence should be addressed.
Electronics 2019, 8(6), 613;
Received: 8 May 2019 / Revised: 23 May 2019 / Accepted: 28 May 2019 / Published: 31 May 2019
(This article belongs to the Special Issue Autonomous Vehicles Technology)
For autonomous driving, it is important to navigate in an unknown environment. In this paper, we propose a fully automated 2D simultaneous localization and mapping (SLAM) system based on lidar working in large-scale outdoor environments. To improve the accuracy and robustness of the scan matching module, an improved Correlative Scan Matching (CSM) algorithm is proposed. For efficient place recognition, we design an AdaBoost based loop closure detection algorithm which can efficiently reject false loop closures. For the SLAM back-end, we propose a light-weight graph optimization algorithm based on incremental smoothing and mapping (iSAM). The performance of our system is verified on various large-scale datasets including our real-world datasets and the KITTI odometry benchmark. Further comparisons to the state-of-the-art approaches indicate that our system is competitive with established techniques.
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Keywords: 2D-SLAM; lidar; scan matching; loop closure; graph optimization 2D-SLAM; lidar; scan matching; loop closure; graph optimization
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Ren, R.; Fu, H.; Wu, M. Large-Scale Outdoor SLAM Based on 2D Lidar. Electronics 2019, 8, 613.

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