Rover Localization through 3D Terrain Registration in Natural Environments

The registration of 3D points clouds is an important and challenging task in computer vision. In this paper we consider the problem of localizing a rover through 3D terrain registration in a natural environment. Two different local feature-based 3D terrain registration approaches are investigated: s...

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Bibliographic Details
Published in2006 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 4121 - 4126
Main Authors Bakambu, J.N., Gemme, S., Dupuis, E.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2006
Subjects
3-D Localization
Autonomous Navigation
Clouds
Computer vision
fingerprint
Fingerprint recognition
Geometry
Image reconstruction
Intelligent robots
Laser radar
Mars
Navigation
Space technology
Spin-image
Terrain Registration
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Summary:The registration of 3D points clouds is an important and challenging task in computer vision. In this paper we consider the problem of localizing a rover through 3D terrain registration in a natural environment. Two different local feature-based 3D terrain registration approaches are investigated: spin-image matching and point fingerprint matching. To overcome the huge memory storage problem of local features-based registration algorithms and improve the accuracy of the matching results, while reducing the computing time of the matching process, we developed an enhanced matching algorithm. The rover global localization scenario was conducted in the Mars Yard located at the Canadian Space Agency. The experimental results using natural environment data sensed by a high resolution and accurate 3D range sensor (LIDAR), demonstrate the effectiveness our enhanced matching algorithm
ISBN:9781424402588
1424402581
ISSN:2153-0858
2153-0866
DOI:10.1109/IROS.2006.281899