Assessment of modern smartphone sensors performance on vehicle localization in urban environments

2017 ◽  
Author(s):  
Chris Danezis ◽  
Theodoros Lazarou
Keyword(s):  
Urban Environments ◽  
Vehicle Localization ◽  
Smartphone Sensors

scholarly journals GPS and Stereovision-Based Visual Odometry: Application to Urban Scene Mapping and Intelligent Vehicle Localization

2011 ◽  
Vol 2011 ◽  
pp. 1-17 ◽  
Author(s):  
Lijun Wei ◽  
Cindy Cappelle ◽  
Yassine Ruichek ◽  
Frédérick Zann
Keyword(s):  
Feature Detection ◽  
Reference Frames ◽  
Estimation Method ◽  
Ground Truth ◽  
Urban Environments ◽  
Relative Depth ◽  
Gps Receiver ◽  
Minimization Method ◽  
Vehicle Localization ◽  
Stereoscopic System

We propose an approach for vehicle localization in dense urban environments using a stereoscopic system and a GPS sensor. Stereoscopic system is used to capture the stereo video flow, to recover the environments, and to estimate the vehicle motion based on feature detection, matching, and triangulation from every image pair. A relative depth constraint is applied to eliminate the tracking couples which are inconsistent with the vehicle ego-motion. Then the optimal rotation and translation between the current and the reference frames are computed using an RANSAC based minimization method. Meanwhile, GPS positions are obtained by an on-board GPS receiver and periodically used to adjust the vehicle orientations and positions estimated by stereovision. The proposed method is tested with two real sequences obtained by a GEM vehicle equipped with a stereoscopic system and a RTK-GPS receiver. The results show that the vision/GPS integrated trajectory can fit the ground truth better than the vision-only method, especially for the vehicle orientation. And vice-versa, the stereovision-based motion estimation method can correct the GPS signal failures (e.g., GPS jumps) due to multipath problem or other noises.

Long-term vehicle localization in urban environments based on pole landmarks extracted from 3-D lidar scans

2021 ◽  
Vol 136 ◽  
pp. 103709
Author(s):  
Alexander Schaefer ◽  
Daniel Büscher ◽  
Johan Vertens ◽  
Lukas Luft ◽  
Wolfram Burgard
Keyword(s):  
Urban Environments ◽  
Vehicle Localization
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