Paper Info
Title
Vehicle detection and car park mapping using laser scanner
Abstract
In this project, we took on the task of localizing an automatic vehicle and building a map of the car park in real time. This takes place within the car park of INRIA Rhone-Alpes on the CyCab vehicle with a Sick laser range scanner. Our method uses only laser scanners to retrieve the position and orientations of vehicles in the car park. With the detected vehicles as landmarks, CyCab performs a localization of itself and builds a map of the car park at the same time. Classical clustering and segmentation techniques to extract line segments from the laser scan data are applied. The key contribution of the paper is the extraction of vehicle poses from the line segments using Bayesian programming. The method of FastSLAM is used in localizing CyCab and estimating the pose of vehicles in the car park. A set of hypotheses is obtained as a result. The second contribution is a method of combining the set of hypotheses together to form a final map of the car park.
Year
DOI
Venue
2005
10.1109/IROS.2005.1545233
Intelligent Robots and Systems, 2005.
Keywords
Field
DocType
Bayes methods,automatic guided vehicles,feature extraction,image segmentation,laser ranging,mobile robots,object detection,optical scanners,path planning,pattern clustering,road vehicles,Bayesian programming,CyCab vehicle,FastSLAM,automatic vehicle localization,car park mapping,clustering technique,laser scanner,line segment extraction,map building,segmentation technique,vehicle detection,vehicle pose extraction,Bayesian Programming,SLAM,Vehicle Detection
Motion planning,Object detection,Computer vision,Laser scanning,Segmentation,Computer science,Feature extraction,Image segmentation,Artificial intelligence,Cluster analysis,Mobile robot
Conference
ISBN
Citations 
PageRank 
0-7803-8912-3
12
1.39
References 
Authors
4
3
Name
Order
Citations
PageRank
Christopher Tay Meng Keat1121.39
Cédric Pradalier233938.22
Christian Laugier318428.66