Please use this identifier to cite or link to this item:
Title: Curb-intersection feature based Monte Carlo Localization on urban roads
Authors: Qin, B.
Chong, Z.J.
Bandyopadhyay, T.
Ang Jr., M.H. 
Frazzoli, E.
Rus, D.
Issue Date: 2012
Citation: Qin, B.,Chong, Z.J.,Bandyopadhyay, T.,Ang Jr., M.H.,Frazzoli, E.,Rus, D. (2012). Curb-intersection feature based Monte Carlo Localization on urban roads. Proceedings - IEEE International Conference on Robotics and Automation : 2640-2646. ScholarBank@NUS Repository.
Abstract: One of the most prominent features on an urban road is the curb, which defines the boundary of a road surface. An intersection is a junction of two or more roads, appearing where no curb exists. The combination of curb and intersection features and their idiosyncrasies carry significant information about the urban road network that can be exploited to improve a vehicle's localization. This paper introduces a Monte Carlo Localization (MCL) method using the curb-intersection features on urban roads. We propose a novel idea of "Virtual LIDAR" to get the measurement models for these features. Under the MCL framework, above road observation is fused with odometry information, which is able to yield precise localization. We implement the system using a single tilted 2D LIDAR on our autonomous test bed and show robust performance in the presence of occlusion from other vehicles and pedestrians. © 2012 IEEE.
Source Title: Proceedings - IEEE International Conference on Robotics and Automation
ISBN: 9781467314039
ISSN: 10504729
DOI: 10.1109/ICRA.2012.6224913
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Oct 23, 2021

Page view(s)

checked on Oct 14, 2021

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.