The 7th IFAC Symposium on Intelligent Autonomous Vehicles 2010

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A crater detection and identification algorithm for autonomous lunar landing

Marc Spigai
Thales Alenia Space
France

S├ębastien Clerc
Thales Alenia Space
France

Vincent Simard-Bilodeau
U. Sherbrooke and NGC Aerospace
Canada

Abstract:
Future space exploration missions and in particular robotic lunar landing missions will require a high-precision autonomous navigation. A key element of the navigation chain is the direct determination of the camera pose in the terrain reference frame by detecting and identifying visual features. For space applications and lunar landing in particular, craters can serve as useful features. A segmentation-based method is introduced to automatically detect craters in an image. Finally, a method to identify the detected craters in a reference database is presented.

 

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