CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Image matching with scale adjustment
Computer Vision and Image Understanding
Diffusion Distance for Histogram Comparison
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Global Positioning Systems, Inertial Navigation, and Integration
Global Positioning Systems, Inertial Navigation, and Integration
Journal of Field Robotics - Special Issue on Space Robotics, Part III
A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Vision-aided inertial navigation for spacecraft entry, descent, and landing
IEEE Transactions on Robotics
Vision-based unmanned aerial vehicle navigation using geo-referenced information
EURASIP Journal on Advances in Signal Processing - Special issue on signal processing advances in robots and autonomy
Hi-index | 0.00 |
Future space exploration missions such as Mars sample return or the lunar lander mission require precise information about the lander position during the descent and landing steps. This article presents a solution, Landstel, that exploits on-board vision to localize the lander with respect to orbital imagery. The algorithm is based on the geometric repartition of surface landmarks to match descent images with orbital images. It is designed to be robust to illumination variations, to be independent of the presence of specific features on the surface, and to have low memory and processing power requirements. Overall absolute localization is achieved by the integration of Landstel with inertial navigation or with visual odometry, according to a loose fusion scheme. Extensive results with simulated and real data validate the proposed approach, and show that it works well even under difficult conditions where the landmark repeatability rate drops to 10%. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.