Ground Encoding: Learned Factor Graph-based Models for Localizing Ground Penetrating Radar-Reference-Cited by-同舟云学术

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Ground Encoding: Learned Factor Graph-based Models for Localizing Ground Penetrating Radar

Published:2021-09-27 Issue: Volume: Page:
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Container-title:2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Baikovitz Alexander,Sodhi Paloma,Dille Michael,Kaess Michael

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9635848/9635849/09636764.pdf?arnumber=9636764

Cited by 10 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

1. Subsurface Feature-based Ground Robot/Vehicle Localization Using a Ground Penetrating Radar;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. Learning Covariances for Estimation with Constrained Bilevel Optimization;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Looking Beneath More: A Sequence-based Localizing Ground Penetrating Radar Framework;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. Indoor Environment Reconstruction for Unmanned System Using Multiple Low-Cost Sensors;Remote Sensing;2024-03-03

5. GROUNDED: A localizing ground penetrating radar evaluation dataset for learning to localize in inclement weather;The International Journal of Robotics Research;2023-07-25

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