A study on localization methods for autonomous vehicle based on particle filter using 2D laser sensor measurements and road features

被引：1

作者：

Ahn K.-J. ^{[1
]}

Lee T. ^{[2
]}

Kang Y. ^{[3
]}

机构：

[1] The Department of Secured Smart Electric Vehicle Engineering, Kookmin University

[2] The Graduate School of Automotive Engineering, Kookmin University

[3] Department of Automotive Engineering, Kookmin University

来源：

Journal of Institute of Control, Robotics and Systems | 2016年 / 22卷 / 10期

关键词：

2D laser sensor; Autonomous vehicle; Grid map; Localization; Particle filter; Road feature information;

D O I：

10.5302/J.ICROS.2016.16.0141

中图分类号：

学科分类号：

摘要：

This paper presents a study of localization methods based on particle filter using 2D laser sensor measurements and road feature map information, for autonomous vehicles. In order to navigate in an urban environment, an autonomous vehicle should be able to estimate the location of the ego-vehicle with reasonable accuracy. In this study, road features such as curbs and road markings are detected to construct a grid-based feature map using 2D laser range finder measurements. Then, we describe a particle filter-based method for accurate positional estimation of the autonomous vehicle in real-time. Finally, the performance of the proposed method is verified through real road driving experiments, in comparison with accurate DGPS data as a reference. © ICROS 2016.

引用

页码：803 / 810

页数：7

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