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Evaluation and Comparison of Terrain Classification Techniques from LADAR Data for Autonomous Navigation
M. Hebert, N. Vandapel, S. Keller, and R.R. Donamukkala
23rd Army Science Conference, December, 2002.

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Abstract

Autonomous navigation remains a considerable challenge, primarily because of the difficulty in describing the environment of the robot in a way that captures the variability of natural environments. In this paper, we focus on the problem of extracting the ground terrain surface from sparse 3-D data from LADAR mobility sensors, including the segmentation of the terrain from obscuring vegetation. We summarize three approaches to LADAR processing and discuss their limitations. Experimental evaluation was conducted with a GDRS LADAR sensor and with a Z+F laser range finder.

Notes

Associated centers: VASC and FRC
Associated labs/groups: 3D Computer Vision Group and NavLab
Associated project: CTA Robotics

Text Reference

M. Hebert, N. Vandapel, S. Keller, and R.R. Donamukkala, "Evaluation and Comparison of Terrain Classification Techniques from LADAR Data for Autonomous Navigation," 23rd Army Science Conference, December, 2002.

BibTeX Reference

@inproceedings{Hebert_2002_4108,
   author = "Martial Hebert and Nicolas Vandapel and Stefan Keller and Raghavendra Rao Donamukkala",
   title = "Evaluation and Comparison of Terrain Classification Techniques from LADAR Data for Autonomous Navigation",
   booktitle = "23rd Army Science Conference",
   month = "December",
   year = "2002"
}