Title :
Curb-intersection feature based Monte Carlo Localization on urban roads
Author :
Qin, B. ; Chong, Z.J. ; Bandyopadhyay, T. ; Ang, M.H., Jr. ; Frazzoli, E. ; Rus, D.
Author_Institution :
Nat. Univ. of Singapore, Singapore, Singapore
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.
Keywords :
Monte Carlo methods; automated highways; distance measurement; optical radar; Monte Carlo localization; curb features; curb-intersection features; odometry information; single tilted 2D LIDAR; urban road network; virtual LIDAR; Feature extraction; Laser beams; Laser radar; Measurement by laser beam; Roads; Robustness; Vehicles;
Conference_Titel :
Robotics and Automation (ICRA), 2012 IEEE International Conference on
Conference_Location :
Saint Paul, MN
Print_ISBN :
978-1-4673-1403-9
Electronic_ISBN :
1050-4729
DOI :
10.1109/ICRA.2012.6224913