The Robotics Institute

Carnegie Mellon Robotics Institute

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.

Keywords

vegetation, mobile robot, autonomous navigation

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Field Robotics Center

Associated Lab(s) / Group(s): 3D Computer Vision Group

Associated Project(s): CTA Robotics

Text Reference

Martial Hebert, Nicolas Vandapel, Stefan Keller, and Raghavendra Rao 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",
}

The Robotics Institute

Menu