Fu Zhang
Aerospace Engineering · IEEE Robotics and Automation Letters · 2019–2021
A researcher in the Science corpus: 5 papers; trusts 43 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Aerospace Engineering — 57 citations into it; #2,721 of 6,421 by trust here, #4,570 by citations
- Computer Vision and Pattern Recognition — 49 citations into it
- Geology — 16 citations into it; #367 of 687 by trust here, #604 by citations
- Electrical and Electronic Engineering — 12 citations into it; #13,943 of 16,539 by trust here, #14,827 by citations
- Instrumentation — 9 citations into it
- Artificial Intelligence — 7 citations into it
- Automotive Engineering — 6 citations into it
- Environmental Engineering — 6 citations into it; #3,420 of 5,479 by trust here, #4,337 by citations
Whom Fu Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tixiao Shan
- Jiarong Lin
- Christian Forster
- Aleksandr V. Segal
- Ji Zhang
- Davide Scaramuzza
- Adam Bry
- Zichao Zhang
- Andreas Fabri
- Christoph Hertzberg
Who trusts Fu Zhang overall
Papers from Fu Zhang's perspective
Ordered by how strongly the researchers Fu Zhang trusts endorse each paper. Same corpus, a different order for every researcher.
- SVO: Fast semi-direct monocular visual odometry
- iSAM2: Incremental smoothing and mapping using the Bayes tree
- LOAM: Lidar Odometry and Mapping in Real-time (Robotics: Science and Systems Conference)
- Tightly Coupled 3D Lidar Inertial Odometry and Mapping (IEEE International Conference on Robotics and Automation)
- 3D is here: Point Cloud Library (PCL)
- Stanley: The robot that won the DARPA Grand Challenge
- Generalized-ICP (Robotics: Science and Systems Conference)
- LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain (IEEE/RJS International Conference on Intelligent RObots and Systems)
- On-Manifold Preintegration for Real-Time Visual--Inertial Odometry (IEEE Transactions on robotics)
- Autonomous driving in urban environments: Boss and the Urban Challenge
Their papers
- FAST-LIO2: Fast Direct LiDAR-Inertial Odometry (2021) — 1,661 citations
- FAST-LIO: A Fast, Robust LiDAR-Inertial Odometry Package by Tightly-Coupled Iterated Kalman Filter (2020) — 1,065 citations
- Pixel-Level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments (2021) — 324 citations
- R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package (2021) — 386 citations
- Loam livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV (2019) — 362 citations