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Carnegie Mellon Robotics Institute

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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.

Notes

Sponsor: NASA

Associated Center(s) / Consortia: Field Robotics Center

Associated Project(s): Google Lunar X Prize

Text Reference

Aashish Sheshadri, Kevin Peterson, Heather Jones, and William (Red) L. Whittaker, "Position Estimation by Registration to Planetary Terrain," International Conference on Multisensor Fusion and Information Integration (MFI), September, 2012.

BibTeX Reference

@inproceedings{Sheshadri_2012_7335,
   author = "Aashish Sheshadri and Kevin Peterson and Heather Jones and William (Red) L. Whittaker",
   title = "Position Estimation by Registration to Planetary Terrain",
   booktitle = "International Conference on Multisensor Fusion and Information Integration (MFI)",
   publisher = "IEEE",
   month = "September",
   year = "2012",
}

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