Recurrent-OctoMap: Learning state-based map refinement for long-term semantic mapping with 3-D-Lidar data

Sun, L. orcid.org/0000-0002-0393-8665, Yan, Z., Zaganidis, A. et al. (2 more authors) (2018) Recurrent-OctoMap: Learning state-based map refinement for long-term semantic mapping with 3-D-Lidar data. IEEE Robotics and Automation Letters, 3 (4). pp. 3749-3756. ISSN 2377-3766

Abstract

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Keywords: Mapping; simultaneous localization and mapping (SLAM); deep learning in robotics and automation; object detection; segmentation and categorization
Dates:
  • Accepted: 19 June 2018
  • Published (online): 16 July 2018
  • Published: October 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 13 Jan 2020 16:59
Last Modified: 13 Jan 2020 17:03
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: https://doi.org/10.1109/lra.2018.2856268
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