Title :
Position estimation by registration to planetary terrain
Author :
Sheshadri, Aashish ; Peterson, Kevin M. ; Jones, Heather L. ; Whittaker, William L Red
Author_Institution :
Robot. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
LIDAR-only and camera-only approaches to global localization in planetary environments have relied heavily on availability of elevation data. The low-resolution nature of available DEMs limits the accuracy of these methods. Availability of new high-resolution planetary imagery motivates the rover localization method presented here. The method correlates terrain appearance with orthographic imagery. A rover generates a colorized 3D model of the local terrain using a panorama of camera and LIDAR data. This model is orthographically projected onto the ground plane to create a template image. The template is then correlated with available satellite imagery to determine rover location. No prior elevation data is necessary. Experiments in simulation demonstrate 2m accuracy. This method is robust to 30° differences in lighting angle between satellite and rover imagery.
Keywords :
artificial satellites; correlation theory; data analysis; digital elevation models; geophysical image processing; image colour analysis; image sensors; optical radar; planetary rovers; terrain mapping; DEM; LIDAR; camera-only approach; colorized 3D model; correlation method; elevation data availability; global localization; orthographic imagery; orthographic projection; planetary environment; planetary imagery; planetary terrain; position estimation; rover imagery; rover localization method; satellite imagery; template image; terrain appearance; Accuracy; Cameras; Head; Image resolution; Laser radar; Lighting; Satellites;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems (MFI), 2012 IEEE Conference on
Conference_Location :
Hamburg
Print_ISBN :
978-1-4673-2510-3
Electronic_ISBN :
978-1-4673-2511-0
DOI :
10.1109/MFI.2012.6343004