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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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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.

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

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.

@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"
}