Jiarong Lin
Aerospace Engineering · 2019–2021
A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Aerospace Engineering — 43 citations into it; #3,477 of 6,421 by trust here, #5,385 by citations
- Computer Vision and Pattern Recognition — 35 citations into it
- Geology — 15 citations into it; #452 of 687 by trust here, #652 by citations
- Electrical and Electronic Engineering — 9 citations into it
- Instrumentation — 7 citations into it
- Automotive Engineering — 6 citations into it
- Robotics & Control — 6 citations into it
- Environmental Engineering — 5 citations into it; #2,771 of 5,479 by trust here, #4,524 by citations
Whom Jiarong Lin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tixiao Shan
- Zichao Zhang
- Andreas Fabri
- Aleksandr V. Segal
- Adam Bry
- Patrick Labatut
- Shital Shah
- Sergio Garrido-Jurado
- Brendan Englot
- Wei Xu
Who trusts Jiarong Lin overall
Papers from Jiarong Lin's perspective
Ordered by how strongly the researchers Jiarong Lin trusts endorse each paper. Same corpus, a different order for every researcher.
- iSAM2: Incremental smoothing and mapping using the Bayes tree
- SVO: Fast semi-direct monocular visual odometry
- Tightly Coupled 3D Lidar Inertial Odometry and Mapping (IEEE International Conference on Robotics and Automation)
- 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)
- Autonomous driving in urban environments: Boss and the Urban Challenge
- 3D is here: Point Cloud Library (PCL)
- Stanley: The robot that won the DARPA Grand Challenge
- LINS: A Lidar-Inertial State Estimator for Robust and Efficient Navigation (IEEE International Conference on Robotics and Automation)
- LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping (IEEE/RJS International Conference on Intelligent RObots and Systems)
Their papers
- FAST-LIO2: Fast Direct LiDAR-Inertial Odometry (2021) — 1,661 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