Paper Info
Title
SeqPolar: Sequence Matching of Polarized LiDAR Map With HMM for Intelligent Vehicle Localization
Abstract
3D LiDAR maps are playing a more and more important role in intelligent vehicle localization. In this paper, the proposed SeqPolar localization method consists of two parts. The first part is a novel node-based LiDAR map representation method, termed polarized LiDAR map (PLM), and the second is a map matching algorithm based on a second-order hidden Markov model (HMM2) for vehicle localization. Unlike existing 3D LiDAR map, which is usually constructed by accumulating 3D LiDAR clouds collected at different times, the proposed polarized LiDAR map is generated from a set of nodes. Each node consists of three elements: a polarized LiDAR image, scene features extracted from the polarized LiDAR image, and sensor pose. The polarized LiDAR image encodes 3D coordinates and reflectivities of the 3D LiDAR cloud using a multi-channel image format, a more concise, straightforward, and structured representation of the 3D LiDAR cloud. In the localization step, we propose an HMM2-based method to match a sequence of input polarized images within the map nodes and find the nearest node from the PLM. Afterward, the vehicle is readily localized from the matched map node with 3D registration. The proposed SeqPolar localization method has been validated with the actual field dataset and the public KITTI database. Experimental results demonstrate that the proposed HMM2-based matching method can achieve up to 98% accuracy to find the nearest node from PLM. Moreover, the SeqPolar localization method based on the pre-built PLM can achieve 30-centimeter localization accuracy in average on both test datasets.
Year
DOI
Venue
2022
10.1109/TVT.2022.3170627
IEEE Transactions on Vehicular Technology
Keywords
DocType
Volume
Hidden Markov model,intelligent vehicle,polarized LiDAR map,LiDAR cloud representation,vehicle localization
Journal
71
Issue
ISSN
Citations 
7
0018-9545
0
PageRank 
References 
Authors
0.34
21
5
Name
Order
Citations
PageRank
Qianwen Tao100.34
Zhaozheng Hu2144.31
Zhe Zhou300.34
Hanbiao Xiao411.03
Jianan Zhang500.34