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Proceedings Paper

Vision-based obstacle detection and path planning for planetary rovers
Author(s): Magnus Snorrason; Jeff Norris; Paul G. Backes
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Paper Abstract

NASA's next-generation Mars rovers are capable of capturing panoramic stereo imagery of their surroundings. Three- dimensional terrain maps can be derived from such imagery through stereo image correlation. While 3-D data is inherently valuable for planning a path through local terrain, obstacle detection is not fully reliable due to anomalies and noise in the range data. We present an obstacle-detection approach that first identifies potential obstacles based on color-contrast in the monocular imagery and then uses the 3-D data to project all detected obstacles into a 2-D overhead-view obstacle map where noise originating from the 3-D data is easily removed. We also developed a specialized version of the A* search algorithm that produces optimally efficient paths through the obstacle map. These paths are of similar quality as those generated by the traditional A* , at a fraction of the computational cost. Performance gains by an order of magnitude are accomplished by a two-stage approach that leverages the specificity of obstacle shape on Mars. The first stage uses depth-first A* to quickly generate a somewhat sub-optimal path through the obstacle map. The following refinement stage efficiently eliminates all extraneous way-points. Our implementation of these algorithms is being integrated into NASA's award-winning Web-Interface for Telescience.

Paper Details

Date Published: 22 July 1999
PDF: 11 pages
Proc. SPIE 3693, Unmanned Ground Vehicle Technology, (22 July 1999); doi: 10.1117/12.354460
Show Author Affiliations
Magnus Snorrason, Charles River Analytics Inc. (United States)
Jeff Norris, Charles River Analytics Inc. (United States)
Paul G. Backes, Jet Propulsion Lab. (United States)


Published in SPIE Proceedings Vol. 3693:
Unmanned Ground Vehicle Technology
Grant R. Gerhart; Robert W. Gunderson; Chuck M. Shoemaker, Editor(s)

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