Pseudo-Anchors: Robust Semantic Features for Lidar Mapping in Highly Dynamic Scenarios-Reference-Cited by-同舟云学术

Pseudo-Anchors: Robust Semantic Features for Lidar Mapping in Highly Dynamic Scenarios

Published:2022 Issue: Volume: Page:1-12
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Yang Chenxi¹^ORCID,He Lei¹^ORCID,Zhuang Hanyang²^ORCID,Wang Chunxiang¹^ORCID,Yang Ming¹^ORCID

Affiliation:

1. Department of Automation, Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai Jiao Tong University, Shanghai, China

2. University of Michigan—Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

Guangxi key Laboratory of Automobile Components and Vehicle Technology Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/4358928/09963776.pdf?arnumber=9963776

Reference27 articles.

1. Sensor Fusion-Based Low-Cost Vehicle Localization System for Complex Urban Environments

2. Road marking detection using LIDAR reflective intensity data and its application to vehicle localization

3. iSAM: Incremental Smoothing and Mapping

4. G²o: A general framework for graph optimization

5. Precise Localization in High-Definition Road Maps for Urban Regions

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