LIDAR-based Parking Spot Search Algorithm

被引：0
|
作者：
Imameev, Dinir [1 ]
Zakiev, Aufar [1 ]
Tsoy, Tatyana [1 ]
Bai, Yang [2 ]
Svinin, Mikhail [2 ]
Magid, Evgeni [1 ]
机构：
[1] Kazan Fed Univ, Higher Inst Informat Technol & Intelligent Syst I, Intelligent Robot Dept, Lab Intelligent Robot Syst LIRS, Kazan, Russia
[2] Ritsumeikan Univ, Coll Informat Sci & Engn, Kyoto, Japan
来源：
THIRTEENTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2020) | 2021年 / 11605卷
基金：
俄罗斯基础研究基金会;
关键词：
Clustering algorithms; LIDAR; laser range finder; LRF; parking; autonomous vehicle; robot operating system; ROS;
D O I：
10.1117/12.2587070
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Autonomous driving considers issues related to a car driving in different real world situations. This work addresses a parking task and describes a new LIDAR-based parking spot search algorithm. The proposed approach was successfully validated in virtual experiments within the Gazebo simulator in a parking area with a perpendicular parking setup. HDBScan, OPTICS, and Gaussian Mixture clustering methods were compared for LIDAR data clustering in the parking spot search task, and the HDBScan clustering demonstrated best prediction and performance results.
引用
收藏
页数：7
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