The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

The authors propose a method to estimate terrain roughness directly from the depth information. They estimate the fractal dimension of terrain using the fractal Brownian function approach. For experiments with real data, they extend the approach to accommodate irreguarly sampled elevation data supplied by a scanning laser rangefinder. Applying this extended method to noisy range imagery of natural terrain (sand and rocks), the authors find that the resulting estimates of fractal dimension correlate closely to human perception of the roughness of the terrain, showing that the fractal dimension of the sensed point set is a practical and effective measure of the roughness of natural terrain.

Notes

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

Text Reference

K. Arakawa and Eric Krotkov, "Estimating Fractal Dimenions of Natural Terrain from Irregularly Spaced Data," Proceedings of International Conference on Intelligent Robots and Systems (IROS 93), July, 1993, pp. 1364 - 1370.

BibTeX Reference

@inproceedings{Krotkov_1993_1379,
   author = "K. Arakawa and Eric Krotkov",
   title = "Estimating Fractal Dimenions of Natural Terrain from Irregularly Spaced Data",
   booktitle = "Proceedings of International Conference on Intelligent Robots and Systems (IROS 93)",
   pages = "1364 - 1370",
   month = "July",
   year = "1993",
   volume = "2",
}

The Robotics Institute

Menu