TNDF-Fusion: Implicit Truncated Neural Distance Field for LiDAR Dense Mapping and Localization in Large Urban Environments-Reference-Cited by-同舟云学术

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TNDF-Fusion: Implicit Truncated Neural Distance Field for LiDAR Dense Mapping and Localization in Large Urban Environments

Published:2024-09 Issue:9 Volume:9 Page:7445-7452
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Chen Zhiming¹^ORCID,Zhang Kun¹^ORCID,Chen Hua²^ORCID,Wang Michael Yu³^ORCID,Zhang Wei²^ORCID,Yu Hongyu⁴^ORCID

Affiliation:

1. Cheng Kar-Shun Robotics Institute, The Hong Kong University of Science and Technology, Hong Kong, SAR, China

2. School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen, China

3. School of Engineering, Great Bay University, Dongguan, China

4. Robotics Institute, The Hong Kong University of Science and Technology, Hong Kong, SAR, China

Funder

Innovation and Technology Commission

Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7083369/10601335/10598317.pdf?arnumber=10598317

Reference43 articles.

1. Faster-LIO: Lightweight Tightly Coupled Lidar-Inertial Odometry Using Parallel Sparse Incremental Voxels

2. Efficient and Probabilistic Adaptive Voxel Mapping for Accurate Online LiDAR Odometry

3. OctoMap: an efficient probabilistic 3D mapping framework based on octrees

4. VDBFusion: Flexible and Efficient TSDF Integration of Range Sensor Data

5. Vision meets robotics: The KITTI dataset

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