Lidar-based Localization Algorithm of Vehicle in Parking Lot

被引：0
|
作者：
Zhou S. [1 ,2 ]
Li W. [2 ]
Guo J. [1 ]
机构：
[1] School of Automotive Studies, Tongji University, Shanghai
[2] Chinesisch-Deutsche Hochschule, Tongji University, Shanghai
来源：
Tongji Daxue Xuebao/Journal of Tongji University | 2021年 / 49卷 / 07期
关键词：
Autopilot; High-precision positioning; Lidar; Particle filter; ROS(robot operating system);
D O I：
10.11908/j.issn.0253-374x.20464
中图分类号：
学科分类号：
摘要：
Under the limit of car localization sensors such as GPS and Wi-Fi in parking lots and tunnels, an autonomous self-localization method of vehicle based on lidar is proposed. The lidar simultaneous localization and mapping (SLAM) algorithm is used to obtain the estimated pose of vehicle through three-dimensional lidar point cloud matching, and all poses are adjusted according to the graph optimization method and the nonlinear optimization method. Then, a planar grid map of environmental information with controllable resolution is obtained. Based on the Monte Carlo method, a particle filter is adopted for real-time vehicle localization, and an improved method of particle sampling is proposed to achieve real-time high-precision autonomous localization of vehicle. Experimental results show that the particle filter can effectively realize the localization of vehicles in parking lot and other non-GPS environments, and the localization accuracy is within 10 cm. © 2021, Editorial Department of Journal of Tongji University. All right reserved.
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页码：1029 / 1038
页数：9
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