Semantically Assisted Loop Closure in SLAM Using NDT Histograms

Zaganidis, Anestis and Zerntev, Alexandros and Duckett, Tom and Cielniak, Grzegorz (2019) Semantically Assisted Loop Closure in SLAM Using NDT Histograms. In: International Conference on Intelligent Robots and Systems (IROS), 4-8, November, 2019, Macao, China.

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Semantically Assisted Loop Closure in SLAM Using NDT Histograms
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Abstract

Precise knowledge of pose is of great importance for reliable operation of mobile robots in outdoor environments. Simultaneous localization and mapping (SLAM) is the online construction of a map during exploration of an environment. One of the components of SLAM is loop closure detection, identifying that the same location has been visited and is present on the existing map, and localizing against it. We have shown in previous work that using semantics from a deep segmentation network in conjunction with the Normal Distributions Transform point cloud registration improves the robustness, speed and accuracy of lidar odometry. In this work we extend the method for loop closure detection, using the labels already available from local registration into NDT Histograms, and we present a SLAM pipeline based on Semantic assisted NDT and PointNet++. We experimentally demonstrate on sequences from the KITTI benchmark that the map descriptor we propose outperforms NDT Histograms without semantics, and we validate its use on a SLAM task.

Keywords:localization, SLAM, semantic mapping
Subjects:H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G760 Machine Learning
G Mathematical and Computer Sciences > G740 Computer Vision
H Engineering > H670 Robotics and Cybernetics
Divisions:College of Science > School of Computer Science
ID Code:37750
Deposited On:10 Oct 2019 13:36

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