DMLO: Deep Matching LiDAR Odometry

04/08/2020
by   Naiyan Wang, et al.
0

LiDAR odometry is a fundamental task for various areas such as robotics, autonomous driving. This problem is difficult since it requires the systems to be highly robust running in noisy real-world data. Existing methods are mostly local iterative methods. Feature-based global registration methods are not preferred since extracting accurate matching pairs in the nonuniform and sparse LiDAR data remains challenging. In this paper, we present Deep Matching LiDAR Odometry (DMLO), a novel learning-based framework which makes the feature matching method applicable to LiDAR odometry task. Unlike many recent learning-based methods, DMLO explicitly enforces geometry constraints in the framework. Specifically, DMLO decomposes the 6-DoF pose estimation into two parts, a learning-based matching network which provides accurate correspondences between two scans and rigid transformation estimation with a close-formed solution by Singular Value Decomposition (SVD). Comprehensive experimental results on real-world datasets KITTI and Argoverse demonstrate that our DMLO dramatically outperforms existing learning-based methods and comparable with the state-of-the-art geometry based approaches.

READ FULL TEXT

Authors

page 1

04/17/2019

LO-Net: Deep Real-time Lidar Odometry

We present a novel deep convolutional network pipeline, LO-Net, for real...
03/05/2021

Fail-Aware LIDAR-Based Odometry for Autonomous Vehicles

Autonomous driving systems are set to become a reality in transport syst...
09/13/2021

LiDAR Odometry Methodologies for Autonomous Driving: A Survey

Vehicle odometry is an essential component of an automated driving syste...
06/01/2021

Markov Localisation using Heatmap Regression and Deep Convolutional Odometry

In the context of self-driving vehicles there is strong competition betw...
09/01/2020

LodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation

Deep learning based LiDAR odometry (LO) estimation attracts increasing r...
09/30/2019

ViLiVO: Virtual LiDAR-Visual Odometry for an Autonomous Vehicle with a Multi-Camera System

In this paper, we present a multi-camera visual odometry (VO) system for...
01/06/2020

CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description

As an important technology in 3D mapping, autonomous driving, and robot ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.