Share Email Print

Proceedings Paper

Stereo-vision-based terrain mapping for off-road autonomous navigation
Author(s): Arturo L. Rankin; Andres Huertas; Larry H. Matthies
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as nogo regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Paper Details

Date Published: 30 April 2009
PDF: 17 pages
Proc. SPIE 7332, Unmanned Systems Technology XI, 733210 (30 April 2009); doi: 10.1117/12.819099
Show Author Affiliations
Arturo L. Rankin, Jet Propulsion Lab. (United States)
Andres Huertas, Jet Propulsion Lab. (United States)
Larry H. Matthies, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 7332:
Unmanned Systems Technology XI
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?