FAST-LIVO: Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry

03/02/2022
by   Chunran Zheng, et al.
0

To achieve accurate and robust pose estimation in Simultaneous Localization and Mapping (SLAM) task, multi-sensor fusion is proven to be an effective solution and thus provides great potential in robotic applications. This paper proposes FAST-LIVO, a fast LiDAR-Inertial-Visual Odometry system, which builds on two tightly-coupled and direct odometry subsystems: a VIO subsystem and a LIO subsystem. The LIO subsystem registers raw points (instead of feature points on e.g., edges or planes) of a new scan to an incrementally-built point cloud map. The map points are additionally attached with image patches, which are then used in the VIO subsystem to align a new image by minimizing the direct photometric errors without extracting any visual features (e.g., ORB or FAST corner features). To further improve the VIO robustness and accuracy, a novel outlier rejection method is proposed to reject unstable map points that lie on edges or are occluded in the image view. Experiments on both open data sequences and our customized device data are conducted. The results show our proposed system outperforms other counterparts and can handle challenging environments at reduced computation cost. The system supports both multi-line spinning LiDARs and emerging solid-state LiDARs with completely different scanning patterns, and can run in real-time on both Intel and ARM processors. We open source our code and dataset of this work on Github to benefit the robotics community.

READ FULL TEXT

page 5

page 6

research
07/14/2021

FAST-LIO2: Fast Direct LiDAR-inertial Odometry

This paper presents FAST-LIO2: a fast, robust, and versatile LiDAR-inert...
research
09/10/2021

R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

In this letter, we propose a novel LiDAR-Inertial-Visual sensor fusion f...
research
03/07/2022

Direct LiDAR-Inertial Odometry

This paper proposes a new LiDAR-inertial odometry framework that generat...
research
10/25/2020

Towards High-Performance Solid-State-LiDAR-Inertial Odometry and Mapping

We present a novel tightly-coupled LiDAR-inertial odometry and mapping s...
research
04/22/2021

LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping

We propose a framework for tightly-coupled lidar-visual-inertial odometr...
research
06/17/2022

Effective Solid State LiDAR Odometry Using Continuous-time Filter Registration

Solid-state LiDARs are more compact and cheaper than the conventional me...
research
06/30/2023

LIO-GVM: an Accurate, Tightly-Coupled Lidar-Inertial Odometry with Gaussian Voxel Map

This letter presents an accurate and robust Lidar Inertial Odometry fram...

Please sign up or login with your details

Forgot password? Click here to reset