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Monte Carlo Localization on Gaussian Process Occupancy Maps for Urban Environments

  • Published:2018-09 Issue:9 Volume:19 Page:2893-2902
  • ISSN:1524-9050
  • Container-title:IEEE Transactions on Intelligent Transportation Systems
  • language:
  • Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Hata Alberto Y.ORCID,Ramos Fabio T.ORCID,Wolf Denis F.ORCID

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

School of Information Technologies members

Mobile Robots Laboratory members

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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2. A Real-Time Detection Algorithm for Semi-structured Boundaries in the Park Based on 3D LiDAR;Lecture Notes in Electrical Engineering;2024

3. Magnetic Field-Aided Global Localization in Repetitive Environments;2023 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM);2023-06-09

4. LiDAR localization at 100 FPS: A map-aided and template descriptor-based global method;International Journal of Applied Earth Observation and Geoinformation;2023-06

5. Robust Localization for Intelligent Vehicles Based on Compressed Road Scene Map in Urban Environments;IEEE Transactions on Intelligent Vehicles;2023-01
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