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20182022
most citedLIC-Fusion: LiDAR-Inertial-Camera Odometry

10 citations · 25 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.RO20226 cited

Online Self-Calibration for Visual-Inertial Navigation Systems: Models, Analysis and Degeneracy

Yulin Yang, Patrick Geneva, Xingxing Zuo +1

In this paper, we study in-depth the problem of online self-calibration for robust and accurate visual-inertial state estimation. In particular, we first perform a complete observa…

cs.RO2021

Distributed Visual-Inertial Cooperative Localization

Pengxiang Zhu, Patrick Geneva, Wei Ren +1

In this paper we present a consistent and distributed state estimator for multi-robot cooperative localization (CL) which efficiently fuses environmental features and loop-closure…

cs.RO20205 cited

LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking

Xingxing Zuo, Yulin Yang, Patrick Geneva +4

Multi-sensor fusion of multi-modal measurements from commodity inertial, visual and LiDAR sensors to provide robust and accurate 6DOF pose estimation holds great potential in robot…

cs.RO20201 cited

MIMC-VINS: A Versatile and Resilient Multi-IMU Multi-Camera Visual-Inertial Navigation System

Kevin Eckenhoff, Patrick Geneva, Guoquan Huang

As cameras and inertial sensors are becoming ubiquitous in mobile devices and robots, it holds great potential to design visual-inertial navigation systems (VINS) for efficient ver…

cs.RO201910 cited

LIC-Fusion: LiDAR-Inertial-Camera Odometry

Xingxing Zuo, Patrick Geneva, Woosik Lee +2

This paper presents a tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual featur…

cs.RO2018

Closed-form Preintegration Methods for Graph-based Visual-Inertial Navigation

Kevin Eckenhoff, Patrick Geneva, Guoquan Huang

In this paper we propose a new analytical preintegration theory for graph-based sensor fusion with an inertial measurement unit (IMU) and a camera (or other aiding sensors).Rather…