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Paper WeB09.5

Qin, Baoxing (NUS), Chong, Zhuang Jie (NUS), Bandyopadhyay, Tirthankar (Singapore MIT Alliance for R & T), Ang Jr, Marcelo H (National University of Singapore), Frazzoli, Emilio (Massachusetts Institute of Technology), Rus, Daniela (MIT)

Curb-Intersection Feature Based Monte Carlo Localization on Urban Roads

Scheduled for presentation during the Regular Session "Localization II" (WeB09), Wednesday, May 16, 2012, 11:30−11:45, Meeting Room 9 (Sa)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on November 18, 2017

Keywords Localization, Field Robots, Autonomous Navigation

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.

 

 

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