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Computer Science > Robotics

arXiv:2108.01383 (cs)
[Submitted on 3 Aug 2021]

Title:On the descriptive power of LiDAR intensity images for segment-based loop closing in 3-D SLAM

Authors:Jan Wietrzykowski, Piotr Skrzypczyński
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Abstract:We propose an extension to the segment-based global localization method for LiDAR SLAM using descriptors learned considering the visual context of the segments. A new architecture of the deep neural network is presented that learns the visual context acquired from synthetic LiDAR intensity images. This approach allows a single multi-beam LiDAR to produce rich and highly descriptive location signatures. The method is tested on two public datasets, demonstrating an improved descriptiveness of the new descriptors, and more reliable loop closure detection in SLAM. Attention analysis of the network is used to show the importance of focusing on the broader context rather than only on the 3-D segment.
Comments: Accepted for publication at IROS 2021
Subjects: Robotics (cs.RO); Artificial Intelligence (cs.AI)
Cite as: arXiv:2108.01383 [cs.RO]
  (or arXiv:2108.01383v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2108.01383

Submission history

From: Jan Wietrzykowski [view email]
[v1] Tue, 3 Aug 2021 09:44:23 UTC (3,108 KB)
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