Paper Info
Title
Sub-meter vehicle navigation using efficient pre-mapped visual landmarks
Abstract
This paper presents a vehicle navigation system that is capable of achieving sub-meter GPS-denied navigation accuracy in large-scale urban environments, using pre-mapped visual landmarks. Our navigation system tightly couples IMU data with local feature track measurements, and fuses each observation of a pre-mapped visual landmark as a single global measurement. This approach propagates precise 3D global pose estimates for longer periods. Our mapping pipeline leverages a dual-layer architecture to construct high-quality pre-mapped visual landmarks in real time. Experimental results demonstrate that our approach provides sub-meter GPS-denied navigation solutions in large-scale urban scenarios.
Year
DOI
Venue
2016
10.1109/ITSC.2016.7795602
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)
Keywords
Field
DocType
submeter vehicle navigation system,efficient pre-mapped visual landmark,submeter GPS-denied navigation accuracy,large-scale urban environment,IMU data,local feature track measurement,single global measurement,3D global pose estimation,pipeline leverage mapping,dual-layer architecture
Computer vision,Visualization,Simulation,Navigation system,Feature extraction,Inertial measurement unit,Artificial intelligence,Global Positioning System,Engineering,Mobile robot navigation,Landmark,Fuse (electrical)
Conference
ISBN
Citations 
PageRank 
978-1-5090-1890-1
0
0.34
References 
Authors
10
6
Name
Order
Citations
PageRank
Han-Pang Chiu19410.83
Mikhail Sizintsev21498.87
Xun S. Zhou380.83
Phillip Miller410.70
Supun Samarasekera579285.72
Rakesh Kumar 00016162.52