46 citations · 131 across the 7 of their papers we have counts for
9 papers
MARSIM: A light-weight point-realistic simulator for LiDAR-based UAVs
Fanze Kong, Xiyuan Liu, Benxu Tang +6
The emergence of low-cost, small form factor and light-weight solid-state LiDAR sensors have brought new opportunities for autonomous unmanned aerial vehicles (UAVs) by advancing n…
RLIVE++: A Robust, Real-time, Radiance reconstruction package with a tightly-coupled LiDAR-Inertial-Visual state Estimator
Jiarong Lin, Fu Zhang
Simultaneous localization and mapping (SLAM) are crucial for autonomous robots (e.g., self-driving cars, autonomous drones), 3D mapping systems, and AR/VR applications. This work p…
R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
Jiarong Lin, Fu Zhang
In this letter, we propose a novel LiDAR-Inertial-Visual sensor fusion framework termed R3LIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to achie…
FAST-LIO2: Fast Direct LiDAR-inertial Odometry
Wei Xu, Yixi Cai, Dongjiao He +2
This paper presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry framework. Building on a highly efficient tightly-coupled iterated Kalman filter, FAST-LIO2 has…
R2LIVE: A Robust, Real-time, LiDAR-Inertial-Visual tightly-coupled state Estimator and mapping
Jiarong Lin, Chunran Zheng, Wei Xu +1
In this letter, we propose a robust, real-time tightly-coupled multi-sensor fusion framework, which fuses measurement from LiDAR, inertial sensor, and visual camera to achieve robu…
A decentralized framework for simultaneous calibration, localization and mapping with multiple LiDARs
Jiarong Lin, Xiyuan Liu, Fu Zhang
LiDAR is playing a more and more essential role in autonomous driving vehicles for objection detection, self localization and mapping. A single LiDAR frequently suffers from hardwa…